Write a position paper of 2-3 page in APA format with high order thinking

7.1 Evaluating Information

7.2 Neo-Luddite Views of Computers, Technology, and Quality of Life 7.3 Digital Divides y

7.4 Control of Our Devices and Data

7.5 Making Decisions About Technology A Exercises a

A

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In this chapter, we consider such questions as these: Does the openness and "democracy" of the Web increase distribution of useful information or of inac curate, foohsh, and biased information? How should we handle the latter? How can we evaluate complex computer models of physical and social phenomena? Is computing technology evil? Why do some people think it is? How does access to digital technology ditfer among dilferent populations? How should we control technology to ensure positive uses and consequences? How soon will robots and digital devices be more intelligent than people? What will happen after that?

Whole books focus on these topics. The presentations here are necessarily brief. They introduce issues, arguments, and many questions.

7.1 Evaluating Information

A little learning is a dang 'rous thing; Drink deep, or taste not the Pierian spring; There shallow draughts intoxicate the brain, And drinking largely sobers us again.

—Alexander Pope, 1709'

7.1.1 The Need for Responsible Judgment

What is real? What is fake? Why does it matter?

We can get the wrong answer to a question quicker than our fathers and mothers could find a pencil.

—Robert McHenry^

There is a daunting amount of information on the Web—^and much of it is wrong. Quack medical cures abound. Distorted history, errors, outdated information, bad financial advice—it is all there. Marketers and pubUc relations firms spread unlabeled advertisements through blogs, social media, and video sites. Search engines have largely replaced librarians for finding information, but search engines rank informa tion sources at least partially by popularity and give prominent display to content providers who pay; librarians do not. Wikipedia, the biggest online encyclopedia, is immensely popular, but can we rely on its accuracy and objectivity when anyone can edit any article at any time? On social journalism sites, readers submit and vote on news stories. Is this a good way to get news? The nature of the Intemet encourages people to post their immediate thoughts and reactions without taking time for con templation or for checking facts. How do we know what is worth reading in contexts where there are no editors selecting well-written and well-researched articles?

Faking photos is not new; photographers have long staged scenes and altered photos in dark rooms. When we see a video of a currently popular performer sing ing with Elvis Presley (who died in 1977), we know we are watching creative

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entertainment—digital magic at work. But the same technologies can deceive, and circulation of a fake photo on the Internet can start a riot or bring death threats to an innocent person. Here is an example of the latter: A young man in Canada posted a selfie he took in his bathroom mirror while holding his iPad. After a series of terror ist attacks in Paris that killed 130 people, someone modified the photo to make the iPad look like a copy of the Quran and made the man appear to be wearing a sui cide vest of explosives. The person who modified the image (or someone else) then posted the fake picture with the claim that the man was one of the Paris terrorists. Two news companies republished the false photo and claim without checking them.^

Video-manipulation tools (and increased bandwidth) provide the opportunity for more sophisticated "forging" of people. A company developed an animation system that modifies video images of a real person to produce a new video in which the person is speaking whatever words the user of the system provides. Another system analyzes recordings of a person's voice and synthesizes speech with the voice, inflections, and tones of that person. Combined, these systems have many uses, including entertainment and advertising, but clearly people can use them to mislead in highly unethical ways.'*

We have probably all heard of hoaxes that circulate on the Internet. In Chapter 5, we saw that governments hack into email accounts and infrastructure systems. They may also generate disruptive hoaxes. After false reports of an explosion and toxic leak from a chemical factory in Louisiana spread on social media, supported by fake videos and fake screenshots of respected news sources, a joumahst traced this very sophisticated hoax and several others to a group in Russia that already had a reputa tion for spreading pro-Russian-govemment propaganda in social media in Russia.^

How do we know when someone is manipulating us? How carefully must we (and news organizations!) check authenticity before circulating provocative images, videos, and stories?

Example: Wikipedia

To explore some issues of information quality, we consider Wikipedia. Wikipedia is a collaborative project among large numbers of strangers worldwide. It is huge, free, participatory, noncommercial, ad-free, and written by volunteers. The English edition has more than five million articles, well more than the hundreds of thou sands in the long-respected Encyclopaedia Britannica, first published in 1768 and online since 1994.^*^ Wikipedia is one of the Internet's most-used reference sites. But are its entries true, honest, and reliable?

We expect encyclopedias to be accurate and objective. Traditionally, expert scholars selected by editorial boards write encyclopedia entries. Volunteers, not carefully selected scholars, write and continually edit and update Wikipedia articles.

^Both Britannica and World Book Encyclopedia provide free articles, but full access requires a paid subscription.

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Anyone who chooses to participate can do so. People worry that the lack of edito rial control means no accountability, no standards of quality, and no way for the ordinary person to judge the value of the information. They argue that because hundreds of milhons of people—anyone at all—can write or edit articles, accuracy and quality are impossible. Truth does not come from populist free-for-alls. Mem bers of the staffs of political candidates have distorted the Wikipedia biographies of their candidates to make their bosses look better. Opponents and enemies regularly vandalize profiles of prominent people. The staff of a federal agency removed criti cisms of the agency from its Wikipedia article. Discredited theories about historic events such as the terrorist attacks on September 11, 2001, and the assassination of John F. Kennedy reappear regularly. A lawyer reported that one party in a legal case edited Wikipedia entries to make information appear more favorable to that party. (Jurors are not supposed to consult online sources about a trial, but some do.)

Removing false information, hoaxes, and the like requires constant effort by volunteer administrators and the Wikipedia staff. The Encyclopaedia Britannica has errors and oddities, but the nature of Wikipedia makes it prone to more. Anonym ity of writers can encourage dishonesty. Open, volunteer, instant-pubhshing sys tems cannot prevent errors and vandalism as easily as pubhshers of printed books or closed, proprietary online information sources. Several potential Wikipedia competitors, Veropedia, Citizendium, and Google's Knol project, tried to address weaknesses of Wikipedia, but none survived.

Despite the errors, sloppiness, bad writing, and intentional distortions, most of Wikipedia is, perhaps surprisingly, of high quality and extraordinary value. Why? What protects quality in large, open, volunteer projects? First, although anyone can write and edit Wikipedia articles, most people do not. Many who do are edu cated and have expertise in the subjects they write about, and they correct articles promptly. After well-publicized incidents of manipulation of articles, Wikipedia's managers developed procedures and policies to reduce the likelihood of such inci dents. For example, they lock articles on some controversial topics or people; the public cannot directly edit them. We, as users, can (and must) learn to deal appro priately with side effects or weaknesses of new paradigms. Even though much of Wikipedia is excellent and useful, many articles are not up to date, and someone may have wrecked the accuracy and objectivity of any individual article at any hour. Articles on technology, basic science, history, and literature are more likely to be reliable than those on politics, controversial topics and people, and current events. We learn to use Wikipedia for background, but to check facts and seek alternative points of view. Should we judge Wikipedia (and, by extension, the mass of information on the Web) by the excellent material it provides or by the poor- quality material it includes?

Written by fools for the reading of imbeciles. —An evaluation of newspapers, not websites, by a character in

Joseph Conrad's novel The Secret Agent (1907)

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The "wisdom of the crowd"

People ask all sorts of questions of their digital assistants, apps, and websites such as answers.com. These queries can be about diverse personal topics such as dating, travel, food, and college ("Are online college classes as good as classroom classes?"), or wide-ranging technical, social, economic, and politi cal issues ("If we can produce enough food to feed everyone in the world, why don't we?"). Of course, a lot of answers are ill informed. On some sites, the questioner designates the posted answer he or she deems the best. What quali fies the questioner, presumably a person who does not know the answer, to judge the worthiness of the replies? To what extent does the ease of posting a question reduce the likelihood that a person seeks out well-researched or expert information on the subject? There are obviously questions for which this kind of forum might not provide the best results. (An example might be: Is it safe to drink alcohol while using an acne medicine?) However, other questions, such as the first two sample questions quoted above, are likely to generate many varied ideas and perspectives. Sometimes, that is exactly what the questioner wants. If someone asked questions like those of only a few friends, the answers might be less varied and less useful.

Some health sites on the Web encourage the public to rate doctors, hospitals, and medical treatments. Are such ratings valuable or dangerous? Do these sites motivate doctors and hospitals to change their practices to achieve higher ratings at the expense of good medical care? Websites have sprung up to buy and sell votes to get prominent display for articles on social media sites. What are the implica tions of such practices for sites where the public rates medical care? Can respon sible operators of sites that display material based on rankings or votes anticipate manipulation and protect against it?

Let's pause briefly to put the problems of incorrect, distorted, and manipulated information in perspective. Quack medical cures and manipulative marketing are hardly new. Product promotions not labeled as advertising date back hundreds of years. Eighteenth-century opera stars paid people to attend performances and cheer for them or boo their rivals. "Hatchet jobs" in the form of news articles, books, ads, and campaign flyers have dishonestly attacked politicians long before digital tech nology existed. There are plenty of poorly written and inaccurate books. Historical movies merge truth and fiction, some for dramatic purposes, some for ideological purposes, leaving us with a distorted idea of what really happened. Two hundred years ago, cities had more newspapers than they do today; most of them were opinionated and partisan. At supermarket counters, we can buy newspapers with stories as outlandish as any online. The New York Times is a prime example of a respected newspaper, staffed by trained journalists, with an editorial board in charge. Yet, one of its reporters fabricated many stories. Numerous other incidents of plagiarism, fabrication, and insufficient fact-checking have embarrassed news papers and television networks.

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So, the problems of unreliable information are not new, but they are problems, and the Web magnifies them. We consider two questions: How good is the wis dom of the crowd? And how can we distinguish good sources of information on the Web?

Researchers find that crowds do, in fact, generate good answers to certain kinds of questions. When a large number of people respond, they produce a lot of answers, but the average, or median, or most common answer is often a good one. This works well when the people are isolated from each other and express indepen dent opinions. Some researchers think a large (independent) group is likely to be more accurate than a committee of experts for a variety of questions such as esti mating economic growth or how well a new product or movie will do. A Canadian mining company, perhaps hoping for such a phenomenon, posted a large set of geological data on the Web and held a contest to choose areas to look for gold. The U.S. Patent Office is experimenting with online crowdsourcing to help determine if the inventions described in patent applications are truly new; people with expertise in particular technologies can alert the Patent Office to existing products that are similar.

However, the wisdom of crowds requires some independence and diversity. When people see responses provided by others, some undesirable things happen. People modify their responses so that the set of responses becomes less diverse, and the best answer may no longer stand out. People become more confident from reinforcement even though accuracy does not improve. In social networks (as well as in-person teams working on projects in businesses, organizations, and govern ment agencies), peer pressure and dominant personalities can reduce the wisdom of the group.^ Group settings are still useful for soliciting ideas and feedback; governments and businesses have long used open forums, town hall meetings, and focus groups for such purposes.

How can we distinguish good sources of information on the Web? Search engines and other services at first ranked sites by the number of people who visited them. Some developed more sophisticated algorithms to consider the quality of informa tion on sites where users provide content. A variety of people and services review and rate sites and blogs. Critics of the quality of information on the Web and the lack of editorial control disdain such ratings as merely popularity contests, contending, for example, that the Internet gratifies the "mediocrity of the masses."® For blogs, as for Wikipedia or health care sites, they argue that popularity, voting, and consensus do not determine truth. That is correct, but there is no magic formula that tells us what is true and reliable either on the Web or off the Web. The fact that a large num ber of people visit a website does not guarantee quality, but it provides some infor mation. (Why have newspapers long published "best seller" lists for books?) We can choose to read only blogs written by Nobel Prize winners and college professors, if we wish, or only those recommended by friends and others we trust. We can choose to read only product reviews written by professionals, or we can read reviews posted by the public and get an overview of different points of view.

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Over time, the distinction between the online equivalents of responsible jour nalism and supermarket tabloids becomes clear. Good reputations develop, just as they have for centuries offline. Many university libraries provide guides for evalu ating websites and the information on them.^ One good step is to determine who sponsors the site. If you cannot determine the sponsor of a site, you can choose to consider its information as reliable as the information on a flyer you might find under your car's windshield wiper when you park in a busy parking lot. Ultimately, we must find sites, reviewers, ratings, editors, experts, and other sources we trust. Good judgment and skepticism are always valuable.

The only way to preserve the wisdom of the crowd is to protect the independence of the individual

—^Jonah Lehrer'"

Vulnerable viewers

Since you are reading this book, you probably are a student, a reasonably well- educated person who is learning how to analyze arguments and make good judg ments. You can develop skills to evaluate material you read on the Web. But what about people who have less education or ability? For example, what risks does bad information pose to children who find it on the Web? Some critics of the Web worry most about the impact of inaccurate information on such vulnerable people. These fears sometimes edge toward a belief that we (or experts, or the govern ment) should somehow prevent such information from appearing. The many strong arguments for freedom of speech in general are arguments against any centralized or legally mandated way of accomplishing this. What can we do to improve the quality of information? Basic social and legal forces help (to a degree): freedom of speech (to provide responses, corrections, alternative viewpoints, and so on), teachers and parents, competition, fraud and libel laws—and people who care, who volunteer to write, review, and correct online information. What else can we do to reduce access to dangerously wrong information by vulnerable people?

Narrowing the information stream

All the problems of junk and nonsense on the Web notwithstanding, the Web now gives us access to more high-quality, up-to-date information than libraries did in the past—and much more conveniently. Consider current events, politics, and con troversial issues. With the Web, we can:

• read and listen to thousands of news sources from our own and other countries, getting different cultural and political perspectives on events

• read the full text of government documents—^bills, budgets, investigative reports, and congressional testimony and debate—instead of relying on a few sentences quoted from an official news release or a sound bite from a biased spokesperson

Chapter 7 Evaluating and Controlling Technology

• search archives of millions of news articles from the past 200 years

• follow websites, blogs, tweets, and social media news of conservatives, liberals, libertarians, tea party activists, environmentalists, evangelical Christians, animal rights activists, and so on, far more easily and cheaply than when we had to seek out and subscribe to their print newsletters and magazines

But what do people actually do? Some get all their news and interpretation of events from a small number of apps or sites that reflect a specific political point of view. Online tools make it easy: You just set up your bookmarks and feeds and never look anywhere else, except perhaps at other sources recommended by the ones you frequent. Some critics see the Web as significantly encouraging political narrowness and political extremes by making it easy for people to avoid seeing alternative opinions.

How else do our digital tools narrow information streams? In Chapter 2, we saw that search engines personalize results for users based on their location, past searches, profile information, and other criteria. Given the huge amount of infor mation on the Web, this fine tuning helps us find what we want quickly and can be valuable. However, it means that when we are searching for something outside our usual context, including perhaps information on controversial subjects, we might have to make an elfort to look a little harder.

Sometimes, it is not that we are looking for an easy way to get information; rather, we are unaware that the information we get is filtered or biased. Facebook recognized that if we receive loo much information that does not interest us, we stop reading it. To counter this problem, it set its news feed algorithms to filter updates from friends based on how recently a member communicated with them.

ir;ttnEinn;f;[iTiT.rTiimia

A fool and his money are soon parted. —Old English proverb

New technologies can have the unin tended side effect of diminishing older

skills. For example, computing technology reduced the use of cursive writing, and

many elementary schools no longer teach it. Microsoft decided the thesaurus in

Microsoft Word 2000 (and some later ver

sions) should list the verb "trick" as the only meaning for "fool." It omitted noun synonyms "clown," "blockhead," "idiot," "ninny," "dunderhead," "ignoramus," and others that were all present in earlier

versions. Standard references such as

dictionaries and Roget's Thesaurus con tain some of these and more choices.

Microsoft said it eliminated words

"that may have offensive uses."^^* Was this a dunderheaded decision that dulls

the language and reduces literacy? Do producers of widely used reference works have an ethical responsibility to report the substance of their field accurately, or a

social responsibility to remove potentially offensive words from the language?

"Microsoft restored some synonyms meaning a fool ish person but continues to omit the more colorful and more offensive terms.

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How is this relevant to political news or social issues? Here is one example: Eli Pariser, president of the liberal organization MoveOn.org, includes conserva tives among his Facebook friends because he wants to be aware of views differ ent from his own. He does not communicate with those people regularly, and, over time, he realized he was no longer receiving updates from them. Although Facebook members can turn off the filtering of news feeds, most people are not aware of it. Pariser considered the problem of filtered information so disturbing that he wrote a book about it.*^ What lessons can we learn from Facebook's filter ing? Facebook's choice of a default setting (filtering turned on) might not be best, but, then again, most people might prefer it.

A study by Pew Research found that more than 60% of U.S. adults get news from social media. The question of political bias and influence arose in several instances. An article suggested a liberal bias among Facebook staff who select trending topics (assisted by algorithms). YouTube restricted access to more than a dozen short videos, sponsored by a conservative organization, on current social and political topics. (Ironically, one of the restricted videos was about methods some people use to prevent others from exercising their freedom of speech.) After the 2016 U.S. presidential election, some argued that false stories and right-wing discussions on Facebook may have affected the outcome of the election.'^

If we want to reduce political bias, what works best: human editors, algo rithms, or member feedback? Editors have biases even if unintentional. When Facebook replaced the humans with automation to select trending topics, gos sip and false stories increased; the algorithms were not good enough alone, without some human judgment. YouTube explained that its algorithm considers community input in deciding which videos to restrict. Yet, putting too much weight on member or community feedback allows people with one point of view to block another. After the 2016 election, Facebook said it would use evaluations from fact-checking organizations to help determine what should be flagged as untrue. But such organizations also have biases and make mis takes. One of them changed its designation of a 2008 political campaign state ment from "accurate" to "the lie of the year" after events proved its falseness. The problem of determining which statements or claims are true and fair is fundamentally difficult. Constant care and oversight are necessary to reduce bias. What features could help? One journalist suggested an "alternative view points" button.

Overall, does the Internet narrow our information stream and significantly diminish access to different points of view on controversial social and political topics? Does it encourage ideological isolation? People tend to select and read articles that match their own point of view (as they have done since long before the Internet). Thus, we must consider human nature as well as biased advocates and the mechanisms of the Web when seeking ways to make it more likely that we and others see accurate information and a variety of points of view.

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arrowmg academic resea

The phenomenon of using the Information that Is easy to get occurs in other fields besides politics, of course. A researcher analyzed millions of academic articles published over 50 years and found that as journals moved online, authors tended to cite fewer articles, more recent ones, and articles from a narrower set. The specu

lation is that researchers using search

engines to find articles related to theirwork select from among the ones that appear high in search results—the ones that are already cited frequently. Those articles might indeed be the most important, but this approach reinforces previous choices and can lead researchers to miss less

popular but very relevant work. Research ers have far more (and easier) access to articles and journals online than they had in the stacks of libraries. However, as the

author of the study says, searching online "puts researchers in touch with prevailing

opinions, but this may accelerate consen sus and narrow the range of findings and ideas built upon."^'' The effect of acceler ating consensus and narrowing results is similar to what researchers saw with the

wisdom of the crowd when crowd mem

bers were not independent, though the mechanism is different. Clearly, it is good for researchers to be aware of this phe

nomenon and to broaden their searches

when appropriate.

The number of scholarly papers pub lished has grown enormously to over two million a year. Is it the tendency to use search tools in a somewhat lazy way—or

the sheer number of papers—that causes

some valuable work to be missed? Will

more sophisticated, Al-based, search tools read all the articles for us and do

a better job, or will biases in their pro gramming (intentional or not) restrict the results?

must be extremely cautious about becoming arbiters of truth ourselves. —Mark Zuckerberg, CEO of Facebook'^

Abdicating responsibility

The convenience of using a computer system and abdication of responsibility to exercise judgment can encourage a mental laziness with serious consequences. A trucker in Britain got his truck stuck on a small farm road by unquestioningly following the directions of a navigation system and ignoring a sign saying the road was not suitable for large vehicles. A newspaper editor in Pakistan received a letter to the editor by email and inserted it into the newspaper without reading beyond the title. The letter contained an attack on the prophet Muhammad, and angry Muslims set fires in the newspaper office. Several editors were arrested and charged with blasphemy, in some cases punishable by death. Back when newspaper content was still typeset and copyedited, such an accident would have been unlikely.

Businesses make decisions about loan and insurance applications with the help of software that analyzes risks. School districts make decisions about the prog ress of students and the careers of administrators based on computer-graded tests.

7.1 Evaluating Information 365

Doctors, judges, and pilots use software to guide decisions. When decision mak ers are unaware of system limitations or errors, they may make poor or incorrect choices.

Sometimes reliance on a computer system rather than human judgment becomes "institutionalized" in the sense that an organization's management and the legal system can exert strong pressure on individual professionals or employees to do what the computer says. In bureaucracies, a decision maker might feel that there is less personal risk (and less bother) in just accepting what the software produces rather than doing additional checking or making a decision the software does not support. Computer programs advise doctors on treatments for patients. It is critical to remember that, in complex fields, the computer systems might provide valuable information and ideas but might not be good enough to substitute for an experienced professional's judgment. In some institutions, when something goes wrong, "I did what the program recommended" is a stronger defense (to superiors or against a lawsuit) than "I did what my professional judgment and experience recommended." Such insti tutions are encouraging abdication of personal responsibility, with potentially harmful results.

A few examples above and some in Chapters 8 and 9 show dangers of depending on the results of software that is not good enough to make deci sions without human oversight. On the other hand, there are many examples where the software does a better job than people do. As artificial intelligence systems improve, managing this dichotomy becomes more complex. Users have a responsibility to understand the capabilities and limitations of the systems they use.

7.1.2 Computer Models

Likeness to truth is not the same thing as truth.

—Peter L. Bernstein"

Evaluating models

Computer-generated predictions based on mathematical models of subjects with important social impact frequently appear in the news. Figure 7.1 shows a few examples of such topics. A mathematical model is a collection of data and equations describing, or simulating, characteristics and behavior of the thing stud ied. The models and simulations of interest to us here require so much data and/ or computation that they must be run on computers. Researchers and engineers do extensive modeling to simulate both physical systems, such as the design for a new car or the flow of water in a river, and intangible systems, such as parts of the econ omy. Models allow us to simulate and investigate the possible effects of different designs, scenarios, and policies. Simulations and models provide many social and economic benefits, from helping to train operators of power plants, submarines.

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Population growth

The cost of a proposed government program

The number of lives that a new drug will save

When we will run out of a critical natural resource

The effects of a tax cut on the economy

The threat of global warming

When a big earthquake is likely to occur

Figure 7.1 Some problems studied with computer models.

and airplanes to projecting trends and enabling us to consider alternatives, thus making better decisions that reduce waste, cost, and risk.

Models are simplifications. Although the models we consider are abstract (i.e., mathematical), the meaning of the word "model" here is similar to its meaning in "model airplane." Model airplanes generally do not have an engine or wiring and the wing flaps might not move. In a chemistry class, we could use sticks and balls to build models of molecules to help us understand their properties. These mol ecule models might not show the components of the individual atoms. Similarly, mathematical models often do not include equations for every factor that could influence the outcome, but are instead comprised of simplified equations because the correct ones are unknown or too complicated.

Physical models are usually not the same size as the real thing. Model planes are smaller; the molecule model is larger. In mathematical models, time, rather than physical size, often differs fi-om reality. Computations done on a computer to model a complex physical process in detail often take more time than the actual process takes. For models of long-range phenomena, such as population growth and climate change, the computa tion must take a lot less time than the real phenomenon for the results to be useful.

Predictions from expensive computers and complex computer programs impress people, but models vary enormously in quality. Some are worthless while others are very reliable. Politicians and special interest groups use model predic tions to justify multibillion-dollar programs and laws with significant impact on the economy and the standard of living and choices of millions of people. It is impor tant for both computer professionals and the general public to have some idea of what is in such computer programs, where the uncertainties and weaknesses might lie, and how to evaluate the claims. It is the professional and ethical responsibility of those who design and develop models for public issues to describe honestly and accurately the results, assumptions, and limitations of their models.

The following questions help us determine the accuracy and usefulness of a model.

1. How well do the modelers understand the underlying science or theory of the system they are studying (be it physics, chemistry, economics, or whatever)?

7.1 Evaluating Information 367

How well understood are the relevant properties of the materials involved? How accurate and complete are the data?

2. Models necessarily involve assumptions and simplifications of reality. What are the assumptions and simplifications in the model?

3. How closely do the results or predictions of the model correspond with results from physical experiments or real experience?

Three different models developed to predict the change in health care costs that would result if the United States adopted a national health system gave pre dictions that varied by hundreds of billions of dollars.Why was there such a difference? There are both political and technical reasons why models might not be accurate. Political goals can influence the weighting of many critical fac tors in the model. In addition to technical reasons suggested earlier (incomplete knowledge, incomplete or inaccurate data, and faulty assumptions or oversim plification), other reasons are that computing power could be inadequate for the number of computations needed to model the full complexity of the system, and the difficulty, if not impossibility, of numerically quantifying variables that rep resent human values and choices.

Are reusable (washable cloth) diapers better for the environment than dispos able diapers? When environmentalists proposed bans and taxes on disposable dia pers, this controversy consumed almost as much energy as diaper manufacturing. Several groups developed computer models to study the question. A model that attempts to consider the resource use and environmental effects of all aspects of a product, including manufacture, use, and disposal, is called a life cycle analy sis model. To illustrate the difficulty of doing an accurate study of such a topic, Figure 7.2 lists a few of the questions about which the diaper modelers made assumptions. Depending on the assumptions, the conclusions differed.'^ It is worth noting also that the models focused on one quality—environmental impact. To make a personal decision, we might consider the results of such a model (if we think it reliable), and we might also consider other factors such as cost, aesthetics, convenience, comfort, and health risks.

• How many times do parents reuse a cloth diaper before discarding it? (Values ranged from 90 to 167.)

• Should the model give credit for energy recovered from incineration of waste? Or does pollution from incineration counterbalance the benefit?

• How many cloth diapers do parents use each time they change a baby? (Many parents use two at once for increased protection.) Numbers in the models ranged from 1.72 to 1.9.

• How should the model count pesticides used in growing cotton?

Figure 7.2 Factors in diaper life cycle modeling.

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The importance of testing

Many judges use software that provides a risk assessment telling how likely it is that a person convicted of a crime will commit another crime in the future. If the model on which the software is based does a good job, this is a valuable tool to help make humane and socially valuable decisions about sentencing convicted criminals. One widely used model bases its assessment on more than 100 factors, including, for example, whether or not the person has a parent who spent time in jail. It might be known that this and the other factors in the model correlate with repeat crimes. The model does not include race or national ori gin. And yet, a study of the results found that the model has a bias against black people.^® That is, the black people it rated as high risk for repeat offenses were actually significantly less likely to commit another crime than the white people with the high risk rating. The company that developed the model disputed the methodology and results of the study. We take no position on who is correct but use the example to illustrate the issue of causality and the importance of testing.

Why might the model be wrong? One possibility is that some criteria the model uses correlate with repeated crimes but also correlate with other factors such as income or race. As you may have often heard, correlation does not mean causation. For many phenomena, the causes are unknown and people work with the best information available. But with something as important as determining prison sentences, how should judges use such software? A critical task for any model is testing, in this case, comparing the later behavior of the actual crimi nals to the assessments. This can take many years and requires careful statistical methodology. In the meantime, such a program is a tool that might be useful, but judges need to know how it works (or, at least, how well it works) and must remain skeptical and use good judgment in incorporating its output into their decisions.

Example: Modeling car crashes^^

Car crash analysis programs use a technique called the finite-element method. They superimpose a grid on the frame of a car, as in Figure 7.3, dividing the car into a finite number of small pieces, or elements. The model also uses data describing the specifications of the materials making up each element (e.g., density, strength, and elasticity). Suppose we are studying the effects on the structure of the car from a head-on collision. Engineers initialize data to represent a crash into a wall at a specified speed. The program computes the force, acceleration, and displacement at each grid point and the stress and strain within each element. It repeats these calculations to show what happens as time passes in very tiny increments. These programs require intensive computation to simulate the first 40—100 milliseconds of real time after the impact.

7.1 Evaluating Information 369

MMA In

Figure 7.3 Simulating a frontal car crash. (The grids are simplified.) Used with permission of Livermore Software Technology Corporation.

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A real crash test can include building and testing a unique prototype for a new car design and cost several hundred thousand dollars. The crash analysis programs allow engineers to consider alternatives—^for example, to vary the thickness of steel for selected components, or change materials altogether—and discover the effect with out building another prototype for each altemative. But how good are the models?

How well is the physics of car crashes understood? How accurate and complete are the data? Force and acceleration are basic principles. The physics involved in these programs is straightforward. Engineers know the relevant properties of steel, plastics, aluminum, glass, and other materials in a car fairly well, and there are good data on the density, elasticity, and other characteristics of materials used. However, although they understand the behavior of the materials when force is applied gradu ally, they know less about the behavior of some materials under abrupt acceleration, as in a high-speed impact, and their behavior near or at breaking point.

What simplifications do the programs make? The grid pattern is the most obvi ous simplification. A car is smooth, not made up of little blocks. Also, time is con tinuous; it does not pass in discrete steps. The accuracy of a simulation depends in part on how fine the grid is and how small the time intervals are. Current computer speeds allow updating the calculations on fine grids (e.g., a few millimeters per ele ment) with small time intervals (e.g., less than one millionth of a second).

How do the computed results compare to actual crash tests on real cars ? High speed cameras record real crash tests. Engineers attach sensors to the car and mark reference points on the frame and compare the values the sensors record with val ues the program computes. They physically measure the distortion or displacement of the reference points, and then compare these measurements to the computed positions of the points. Starting with the results of the physical crash, the engineers use elementary physics to calculate backward and determine the deceleration and other forces acting on the car and compare these to the values computed in the simulation. The conclusion? Crash analysis programs do an extremely good job. In part because of the confidence that developed over time in the validity of the results, engineers use variations of the same crash analysis modeling programs in a large variety of other impact applications, including those in Figure 7.4.

Engineers still perform physical crash tests. The computer program is an imple mentation of theory. Although the crash analysis programs are excellent design tools that enable increases in safety with far less development cost, the physical crash test is confirmation.

Example: Modeling climate

Since the late 19th century, global temperatures and sea level have been rising. The average global air temperature has risen approximately 0.8°C. The temperature

'Depending on the particular temperature data sets used and the specific starting year, the temperature rise is reported at various amounts between 0.72° and 0.82°C, with error ranges roughly ±0.2 C.

7.1 Evaluating Information 371

• Predict damage to a hazardous waste container if dropped. Predict damage to an airplane windshield or nacelle (engine covering) if hit by a bird.

• Determine whether beer cans would get dented if an assembly line were speeded up.

Simulate a medical procedure called balloon angioplasty, where doctors insert a balloon in a blocked artery and inflate it to open the artery. The model helps researchers determine how to perform the procedure with less damage to the arterial wall.

Predict the action of airbags and the proper location for sensors that inflate them.

• Design interior parts of cars to reduce injuries during crashes (e.g., from the impact of a steering wheel on a human chest).

• Design bicycle and motorcycle helmets to reduce head injuries. • Design cameras to reduce damage if dropped. • Forecast effects of earthquakes on bridges and buildings.

Figure 7.4 Other uses of crash analysis models.

increase has been particularly steep since the late 1970s. Sea level rose an average of about 1.7 millimeters per year between 1870 and 2000; the rate has increased to roughly 3 millimeters per year.*^^ The reasons for these changes include the ending of the Little Ice Age (roughly 1450—1850), natural climate variability, and human activity. Predictions for future warming and other climate changes are based, in part, on computer models of climate. We consider those models in this section. Since 1990, the Intergovernmental Panel on Climate Change (IPCC), sponsored by the United Nations and the World Meteorological Organization, has published comprehensive reports roughly every five years on the science of climate change and the quality and projections of climate models. Much of the information here comes from those reports.^^

Throughout this section, we give numbers from the IPCC reports and other research sources to make the discussion concrete, but the numbers can be confus ing and occasionally appear inconsistent because of variation in the time ranges of various data, the initialization for model runs, the variety of models used, what they are simulating, the variety of measurement techniques, and other factors. We encourage the reader not to get lost in the numbers but to use them as an aid in understanding the ideas.

Climate models, like the car crash analysis models, calculate relevant variables for grid points and elements (space between the points) for specified simulated time intervals. The grid circles the earth, rises through the atmosphere, and goes

The error ranges are ±0.2 mm for the 20th century data and ±0.4 mm for the more recent higher data.

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down into the oceans. The models contain information about the sun's energy out put; the orbit, inclination, and rotation of the earth; geography; topography; clouds, sea and polar ice; soil and air moisture; and a large number of other factors. Equa tions simulate atmospheric pressure, temperature, wind speed and direction, mois ture, precipitation, ocean currents, and so forth.

As solar radiation reaches the earth, the earth reflects some of it back and gases in the atmosphere trap some. The latter phenomenon, which warms the earth, is known as the greenhouse elfect. Without it, the temperature on the earth would be too cold to support life. Water vapor is the main greenhouse gas, but several oth ers, especially carbon dioxide (CO2), pl^y ̂ significant role. Human activity (e.g., burning of fossil fuels) has increased the concentration of CO2 in the atmosphere. Although an upward trend began roughly 16,000 years ago, CO2 concentration has been increasing at a faster rate since the beginning of the Industrial Revolution, and CO2 emissions increased sharply after 1950. CO2 concentration is now approxi mately 40% higher than in 1750.^^^ One of the applications of climate models is to determine the effects of doubling CO2 concentration in the atmosphere from its pre-industrial level. Models also project the likely increase in global temperature, sea level, and other climate characteristics in various scenarios with assumptions about population, industrial and economic activity, energy use, and so on. Another task for the models is to distinguish how much warming human activity causes and how much is from other factors.

Global warming came to public attention in the late 1980s. The models used in the 1980s and 1990s were quite limited. Here is a brief sampling of simplifications, assumptions, and factors modelers did not fully understand:

• The models did not distinguish day and night."^ • They used a coarse grid (with points roughly 500 kilometers apart).' • They did not include the El Nino phenomenon.

• They did not include aerosols (small particles in the air) that have a cooling effect.

• The representation of the oceans was extremely simplified; computing power was insufficient to do the many calculations needed to simulate ocean behavior.

• Clouds are extremely important to climate, but many processes involved with the formation, effects, and dissipation of clouds were not particularly well understood. The IPCC summarized in 2001: "As has been the case since the first IPCC Assessment Report in 1990, probably the greatest uncertainty in future projections of climate arises from clouds and their interactions with radiation— Clouds represent a significant source of potential error in climate simulations."

*The older data come from measurements of gases trapped in ice cores drilled in Antarctica and Greenland. ^To understand the significance of grid size, think of a rain storm; a model might not represent the storm at all if it falls between grid points, or a model might treat it as large as an entire grid element.

7.1 Evaluating Information 373

When run on past data, some of the early climate models predicted temperature increases three to five times as high as what actually occurred. Thus, it should not be surprising that there has been much skepticism about the climate models and their projections.

Current models are far more detailed and complex. Increased computer power allows the use of much finer grids, fuller representation of oceans, and more experiments with the models. Increased data collection and basic science research have improved the understanding of the behavior and interactions of climate system components.

How well is the science understood? How accurate are the data? Climatolo- gists know an enormous amount about climate. The models incorporate a huge amount of good science and data. But a lot is unknown or not well understood; we mention a few examples.

When the earth warms, water evaporates, and the additional water vapor in the atmosphere absorbs more thermal energy, warming the atmosphere farther. On the other hand, water vapor forms clouds, which reflect incoming solar radiation and thus have a cooling effect. So, clouds have positive (destabi lizing) and negative (stabilizing) feedback effects. The basic science of the mechanisms is fairly well understood, but not the complexity and magnitude of all the feedbacks. The IPCC says that varying treatment of clouds is the largest factor responsible for the wide range of predictions from more than two dozen models for the long-term impact of doubling CO2 concentration in the atmo sphere from the pre-industrial level. Indeed, despite all the increased model sophistication over more than 25 years, the most recent IPCC report says the impact would likely be in the range 1.5-4.5°C, the same range as in the first report.

The records of temperatures since 1850 have a variety of weaknesses, for example, few monitoring stations over the oceans and in remote land areas and variability in the quality of measuring instruments. Various research organizations have developed different temperature data sets by applying statistical methods and other techniques to make corrections and fill in gaps in the actual data.

There is insufficient data on many phenomena for the period before satellites collected data. For example, the IPCC says the shortness of the record of data on Antarctic sea ice contributes to large differences among the models in their simu lation of the ice and to lack of understanding of why the ice has increased since 197928

What are the assumptions and simplifications in the models? Ideally, equations derived from the underlying science (generally, physics and chemistry) would model all the processes that affect climate. This is not possible, because it would

The lechnical term for this long-range impact is equilibrium climate sensitivity. It includes effects of CO, doubling that will occur long after the doubling, after the end of this century. The IPCC considers other factors as well as model results in making this projection.

Chapter 7 Evaluating and Controlling Technology

Science fiction movies about global warm

ing show the buildings of cities underwater. The entertainment industry exaggerates

and dramatizes, of course. But why does an exhibit in a science museum show water up to the middle of the Statue of Liberty (about 200 feet above sea level)? A climate scientist once said: "[T]o cap ture the public's imagination," "we have to offer up scary scenarios, make simplified dramatic statements, and make little men

tion of any doubts we may have. . . . Each of us has to decide what the right balance is between being effective and being hon est."^® Although he said he hoped climate

scientists could be both effective and hon est, there is clearly an ethical problem when we trade honesty for something else. Is it a good idea? A 20-Inch rise in sea level would be a very serious problem, but one we can tackle. Tens or hundreds of feet of sea level rise would be an enormous disaster. Exaggeration might lead people to take constructive action. Or exaggera tion might lead to overreaction and coun terproductive, expensive actions, draining resources from effective approaches. If we hope to solve real potential problems such as flooding in low areas, we must present them accurately.

require too much computation time and because all the underlying science is not known. Simplified equations, called parametrizations, represent many processes; they seem to give realistic results but may not be scientifically accurate. The spe cific parametrizations vary among the models. The IPCC points out that "every bit of added complexity . . . also introduces new sources of possible error (e.g., via uncertain parameters).""^

Model projections based on scenarios, rather than a specific increase in green house gas concentration, include numerous assumptions about technological development, economic development, political control of emissions, population, energy use, and so on, throughout a century.

How well do predictions of the models correspond with actual experience? The IPCC says there is very high confidence that the models reproduce the gen eral features of global average temperature changes, including the warming of the second half of the 20th century.'" Long term trends are consistent with observed temperatures, and the models predict seasonal variations and other broad-scale phenomena. The general patterns of predictions by different models are similar. For example, they all predict warming, and they all predict that more of the warm ing would take place near the poles and in winter.

We can now look back and compare temperature projections for the past few decades with actual data. How well have the models done? The 1990 IPCC report indicated that temperature would increase 0.3°C per decade. Actual tem peratures increased little more than half that much per decade from 1990 to 2010.^^ The 2007 report said the models projected warming of 0.2°C per decade

'with a range of 0.2-0.5°C.

7.2 Neo-Luddite Views OF Computers, Technology, AND Quality OF Life 375

for the next few decades. However, since the late 1990s, and for at least 15 years global temperature rose very little (about 0.05-0.07°C per decade, compared to 0.12°C per decade for the period 1951-2012*). The IPCC refers to the period of small temperature rise as a "hiatus."^ Most of the models did not predict that this would happen. How significant is this discrepancy? The IPCC said that some 15-year periods have been below the trend of the models and some above, and that other aspects of the climate over the hiatus period are consistent with continued warming. It suggested several possible causes of the small tempera- mre increase, including natural climate variability and various possible errors in the models. Other scientists have suggested numerous possible explanations, and some revised the analysis of temperature data and concluded that the hiatus did not happen. It will take more years to fully understand the hiatus and its implications.^^

What about the near future? The IPCC says the models project that, with more than 50% likelihood, the average temperature during the period 2016-2035 will be rC higher than the average for the period 1850-1900 and very unlikely that it will be more than 1.5 C above the 1850—1900 period. We will be able to evaluate the accuracy of these projections within the next two decades.

7.2 Neo-Luddite Views of Computers, Technology, and Quality of Life

The microchip is. . . made of silicon, or sand—a natural resource that is in great abundance and has virtually no monetary value. Yet the combination of a few grains of this sand and the infinite inventiveness of the human mind has led to the creation of a machine that will both create trillions of dollars of added wealth for the inhabitants of the earth in the next century and will do so with incomprehensibly vast savings in physical labor and natural resources.

—Stephen Moore^''

Quite apart from the environmental and medical evils associated with them being produced and used, there are two moral judgments against computers. One is that computerization enables the large forces of our civilization to operate more swiftly and efficiently in their pernicious goals of making money and producing things. . . . And secondly, in the course of using these, these forces are destroying nature with more speed and efficiency than ever before.

—Kirkpatrick Sale'^

With error ranges given in the reports, as usual with all these figures. Some figures vary depending on the exact start and end dates reported. ^Many of the years since 2000 were the hottest on record. This is not inconsistent with the hiatus: The temperature rise from the 1970s through the 1990s brought temperatures to the highest levels since the 19th century; thus any rise could set a record.

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7.2.1 Criticisms of Computing Technologies

The quotations above, both from 1995, illustrate the extreme divergence of views about the anticipated value of computer technology. Evaluations cover the spectrum from "miracle" to "catastrophe." Although most of this book discusses problems that arise with the use of computers, the Internet, and other digital technologies, the implicit (and sometimes explicit) view is that these technologies are a posi tive development bringing us many benefits. The potential for loss of freedom and privacy via government surveillance and the building of consumer dossiers is a serious danger. Computer crime is expensive, and changes in employment are dis ruptive. Our discussion of system failures in the next chapter warns us that some potential applications can have horrifying risks. We might urgently try to prevent implementation of some applications and urgently advocate for increased protec tion from risks, yet not consider the threats and risks as reasons for condemning the technology as a whole. For the most part, we have looked at new risks and negative side effects as problems that occur in the natural process of change, either problems we need to solve or the price we pay for the benefits, part of a trade-off. Many people with quite different political views share this attitude, although they disagree about the significance of specific computer-related problems and about exactly how to solve them.

On the other hand, there are people who utterly reject the view that computing technology is a positive development with many important benefits. They see the benefits as few and overwhelmingly outweighed by the damage done. Neil Postman says that voting, shopping, banking, and getting information online while at home is a "catastrophe." There are fewer opportunities for people to be "co-present," resulting in isolation from neighbors. Richard Sclove and Jeffrey Scheuer argue that electronic communication will erode family and community life to the point that people will mourn the loss of depth and meaning in their lives.^^ A reviewer of this book objected to the "gift of fire" analogy that suggests computers can be very useful and also very dangerous; he thought "Pandora's box" was more appropriate. Pandora's box held "all the ills of mankind." Kirkpatrick Sale, author of Rebels Against the Future, used to demonstrate his opinion of computers by smashing one with a sledgehammer at public appearances.

In England in 1811-1812, people burned factories and mills in efforts to stop the technologies and social changes that were eliminating their jobs. Many were weavers who had worked at home on small machines. They were called Luddites. For 200 years, the memory of the violent Luddite uprising has endured as the most dramatic symbol of opposition to the Industrial Revolution. The term Luddite has long been a derisive description for people who oppose technological progress. More recently, critics of technology have adopted it as an honorable term. Kirkpat rick Sale and many others who share his viewpoint call themselves neo-Luddites, or simply Luddites.

*The name Luddite comes from General Ned Ludd, the fictitious, symbolic leader of the movement.

7.2 Neo-Luddite Views of Computers, Technology, and Quality of Life 377

What do neo-Luddites find so reprehensible about computers and digital technology? Some of their criticisms are problems that also trouble people whose view of computing technology is generally positive, problems we discussed in ear lier chapters. One of the differentiating characteristics of the neo-Luddites is that they focus on these problems, seeing no solutions or trade-offs, and conclude that computers are a terribly bad development for humankind. Among their specific criticisms are the following:

• Computers cause massive unemployment and de-skilling of jobs. "Sweatshop labor is involved in their manufacture."^''

• Computers "manufacture needs"; that is, we use them just because they are there, not because they satisfy real needs.

• Computers cause social inequity. • Computers cause social disintegration; they are dehumanizing. They weaken

communities and lead to isolation of people from each other. • Computers separate humans from nature and destroy the environment. • Computers benefit big business and big government most. • Use of computers in schools thwarts development of social skills, human

values, and intellectual skills in children. They create an "ominous uniformity of knowledge" consistent with corporate values.^®

• Computers do little or nothing to solve real human problems. For example, Neil Postman, in response to claims of the benefits of access to information, argues that if families break up, children are mistreated, crime terrorizes a city, education is impotent, it does not happen because of inadequate information."^^

Some of these criticisms might seem unfair. The conditions in computer factories hardly compare to conditions in the sweatshop factories of the early Industrial Revolution. In Chapter 6, we saw that computers eliminate some jobs, and that the pace of computerization causes disruptions, but the case that computers, and technology in general, cause massive unemployment is not convincing. Blaming computers for social inequity in the world ignores thousands of years of history. Postman is right that inadequate information is not the source of most social prob lems. A computer in the classroom does not replace good parents in the home. But should this be a criticism of computers and information systems? Access to information and communication can assist in solving problems and is not likely to hurt. The main problem for ordinary people. Postman says, is how to find meaning in life. We need answers to questions like "Why are we here?" and "How are we supposed to behave?'"^ Is it a valid criticism of computing technology that it does not solve fundamental social and philosophical problems that have engaged us for thousands of years?

To neo-Luddites, the view that computers are fundamentally malevolent is part of a wider view that almost all of technology is malevolent. To the modem-day

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Luddites, computer technology is just the latest, but in many ways the worst, stage in the decline of what was good in human society. Computers are worse than earlier technologies because of their enormous speed and flexibility. Computers increase the negative trends that technology causes. Thus, if one points out that a particular problem blamed on computers already existed because of an earlier technology, Luddites consider the distinction to be a minor one.

The depth of the antipathy to technology in the Luddite view is perhaps made clearer by attitudes toward common devices most of us use daily. For example, Sale has said, "I find talking on the phone a physical pain, as well as a mental anguish." Sven Birkerts, another critic of computers, says that if he lived in 1900, he would probably have opposed the telephone.* Speaking of the invention of the printing press. Sale laments that "literacy... destroys oraUty." He regards not only computers but civilization as a catastrophe. Some of us see modem medicine as a life-saving and life-enhancing boon to humanity; some Luddites point out that it gave us the population explosion and extended senility.'^'

Having read and listened to the arguments of technology enthusiasts and tech nology critics, we find it striking that different people look at the same history, the same society, the same products and services, the same jobs—and come to diamet rically opposed conclusions about what they see. There is a fundamental difference between the world views of supporters and opponents of technology. It is more than the difference between seeing a glass as half full or half empty. It seems to be one of drastically differing views about what should be in the glass and whether it is filling or draining. Supporters of technology see an upward trend in quality of life, beginning with people Uving at the mercy of nature with an empty glass that technology has been gradually filling. Neo-Luddites view the glass as originally full when people lived in small communities with little impact on nature; they see technology as draining the glass.

The neo-Luddite perspective is associated with a particular view of an appro priate way of life for human beings. For example. Sale's first point, in the quo tation at the beginning of this section, makes the moral judgment that making money and producing things is pernicious. His introductory remark and his second point barely hint at the unusually high valuation he places on not disturbing nature (unusually high even in the contemporary context, where there is much awareness of the importance of protecting the environment). We explore these views further.

7.2.2 Views of Economics, Nature, and Human Needs

Luddites generally have a negative view of business, markets, consumer prod ucts, factories, and modem forms of work. They see the profit-seeking goals of

'critics of telephones complained that they replaced true human interaction with disembodied, remote voices. Telephones actually expanded and deepened social relationships for isolated people for example, women (farm wives, in particular) and the elderly.'*^

12 Neo-Luddite Views OF Computers, Technology, AND Quality OF Life 379

businesses as in fundamental conflict with the well-being of workers and the natu ral environment. They see work in factories, large offices, and business in general as dehumanizing, dreary, and bad for the health of the workers. Hence, for exam ple, the Luddite criticisms of the clock. Neil Postman describes the invention of the clock as the technology of greatest use to men who wished to devote themselves to the accumulation of money.'"*^

Choice of words, making subtle differences in a statement, sometimes illus trates the difference in perspective between Luddites and non-Luddites. What is the purpose of technology? To the Luddites, it is to eliminate jobs to reduce the costs of production. To proponents of technology, it is to reduce the resources needed to pro duce goods and services. The two statements say nearly the same thing, but the first suggests massive unemployment, profits for capitalists, and a poorer life for most workers. The second suggests improvements in wealth and the standard of living.

The Luddite view combines a negative attitude toward business with a high estimation of the power of corporations to manipulate and control workers and con sumers. For example, Richard Sclove describes telecommuting as being "imposed by business." (Interestingly, one of the common criticisms of the Industrial Revolu tion was that working in factories instead of at home weakened families and local community.)

Luddites make particularly strong criticisms of automobiles, of cities, and of most technologies involved in communications and transportation. Thus, it is worth noting that most of us get both personal and social benefits from them. Cities are centers of culture, wealth production, education, and job opportunities.'*^ Modem transportation and communication reduce the price of products and increase their variety and availability. For example, we can look up menus and movie schedules on our smartphone to find what we want and we can shop worldwide on the Web. We can eat fresh fruits and vegetables all year and commute a long distance to take a better job without having to sell our house and move, or we can work from home. If we move to a new city for college or a job, modem conveniences such as airplanes, telephones, and the Intemet make the separations less unpleasant. We can visit more often in person and share greetings and activities with friends and family mem bers via social media. Luddites and other critics of technology do not value these advantages highly. In their point of view, the advantages are merely ameliorating other problems technology causes. For example. Postman quotes Sigmund Freud's comment, "If there had been no railway to conquer distances, my child would never have left his native town and I should need no telephone to hear his voice."'*^

Does the technology create the need for itself?

Luddites argue that technology causes production of things we do not need. Sale argued that small, portable computers do not "meet any known or expressed need," but companies produce them simply because miniaturization of computing com ponents made it possible. People have bought many billions of laptops, tablet

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computers, and mobile phones. While the number of possible uses is phenomenal, does a mobile device meet a needl It depends on what we mean by need. Do we need to do homework in the backyard or hsten to music on a smartphone? Does an architect or contractor need a laptop at a construction site? Those who emphasize the value of individual action and choices argue that needs are relative to goals, and goals are held by individuals. Thus, should we ask whether we, as a society, need a particular device? Or should this be an individual decision with different responses? The Luddites, who believe that advertising, work pressure, or other external forces manipulate buyers, reject an individual-oriented view.

Environmental and anti-technology groups use computers and the Web. The editor of Wild Earth, who considers himself a neo-Luddite, said he "inclines toward the view that technology is inherently evil," but he "disseminates this view via E-mail, computer, and laser printer.'"*^ An interviewer reported that, after a long career attacking computers, Kirkpatrick Sale was using a laptop. The question is: Are Sale and the editor of Wild Earth using the technology because of an artificial need or because it is useful and helpful to them? Sale sees the use of computers as an uncomfortable compromise. The use of computers, he says, insidiously embeds into the user the values and thought processes of the society that makes the technology.

As the Internet of Things expands to umbrellas and tampons, we might want to reconsider Sale's point of view and ask: Do we really need everything connected to the Internet? Technology columnist Joanna Stem poked fun at this highly con nected life by calling the loT the "Internet of Every Single Thing.'"*^ Do we need a refrigerator that notifies us that we are low on eggs, or takes a photo of the inside of the fridge whenever we close the door, so we can check our current inventory while at the grocery store? Why not just make a grocery list as we did in the past? Do we need trash cans and water bottles connected to the Intemet? The answer to some of these questions is no; some products will disappear because consumers will not buy them. But when we consider all the unanticipated uses of past innova tions, can we be sure we or anyone can determine in advance which new gadgets will be useful and which will not? Some items on the loT will save lives. For many, the main benefit will be convenience. Some that we might at first laugh at will be very helpful to special populations. Can you think of examples?

The argument that businesses or technologies manipulate people to buy things they do not really want, like the argument that use of computers has an insidi ously corrupting effect on computer users, displays a low view of the judgment and autonomy of ordinary people. It is one thing to differ with another person s values and choices. It is another to conclude that, because of the difference, the other per son is weak and incapable of making his or her own decisions. The Luddite view of the appropriate way of life puts little value on modem comforts and conveniences or on the availability of a large variety of goods and services. Perhaps most people value these things more highly than the Luddites do. To get a clearer understanding of the Luddite view of a proper lifestyle, we consider some of their comments on the relationship of humans and nature.

7.2 Neo-Luddite Views of Computers. Technology, and Quality of Life

versus downtown and communil

Does electronic commerce force changes on communities that no one wants?

Richard Sclove and Jeffrey Scheuer think They use the analogy of a Walmart

store draining business from downtown shops, resulting in the decline of the downtown community, a "result that no consumers wanted or intended." They gen eralize from the Waimart scenario to cyber space. As we conduct more economic

transactions electronically, we lose more local stores, local professional and social services, and convivial public spaces like the downtowns of small towns. Consum ers are "compelled" to use electronic ser

vices, "like it or not." Other strong critics of technology share the underlying point of view of Sciove and Scheuer, so it is worth examining their argument.

The Walmart analogy is a good one; it is useful for illustrating and clarify ing some issues about the impact of e-commerce on communities. Suppose, say Sciove and Scheuer, that a new

Walmart store has opened just outside of town and about half the town residents

begin to do about a third of their shop ping there, while the others continue to do ail their shopping downtown. Everyone shops downtown, and everyone wants the downtown stores to remain. But down town stores have lost about 16.5% of their

sales, and many will not survive. Sciove and Scheuer describe this as an "invol

untary transformation" that no consumer

wanted or intended. It occurs, they say. because of a "perverse market dynamic." The changes, however, are not involuntary or perverse. The core of the problem with Sclove's and Scheuer's interpretation is their failure to make two important dis tinctions: the distinction between wanting something and the willingness to pay for

it, and the distinction between something being coerced or involuntary, on the one hand, and being unwanted, unintended, or unexpected on the other.

Consider a simpler situation for a moment. Suppose, we poll the adult resi dents of a small town with a population of, say, 3000 and ask if they would like to have a fine French restaurant in town.

Almost everyone says yes. Will a French restaurant open in the town? Probably not. Almost everyone wants it, yet there is not enough potential business for it to sur vive. There is a market dynamic at work, but it is not perverse. The fact that con

sumers want a particular service, store, or product is Irrelevant if not enough people are willing to pay the prices that make the business viable. In Sclove's and Scheuer's Waimart scenario, the downtown stores could stay in business if the people were willing to pay higher prices to make up for the 16.5% of revenue lost to Walmart. But we know that if the stores raise prices, they will almost certainly lose even more customers. The town residents are not

willing to pay what it costs to keep the downtown stores in business. You might object: The townspeople did not have to pay the higher prices before. Why now? Because now the people who shop at Walmart—or online—have another choice. Whatever price advantage or convenience lured them, they were not getting that ben efit before. Again, a market dynamic is at work, but not a perverse one: competition.

The second issue about the Walmart/ e-commerce scenario is whether the change is an "involuntary" transformation. Sciove and Scheuer say that, as local busi nesses decline, people will be compelled to use electronic services, like it or not. Is

this accurate? No more so than Walmart

{continued)

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shoppers or cyberspace enthusiasts were compelled to shop downtown (or from other offline stores), like it or not, before they had the new option. The new status quo is no more involuntary than the previ ous one. Aithough no one wants to see the downtown decline, the actions that could lead to that result are all voluntary. When a new store opens (online or offline), no one is forced to shop there. The impact on the downtown stores might not have been obvi ous to all the townspeople at the beginning (aithough now it is common enough that they might anticipate it), but an unexpected or unintended result is not the same as a

coerced result. In a free society, individuals make millions of decisions based on their

knowledge and preferences. This decen tralized, individualized decision making produces a constantly changing pattern of stores, services, and investments (not to mention social and cultural patterns). No one can predict exactly what the result will be, but (apart from government subsidies, prohibitions, and regulations) the actions of the consumers and merchants are vol untary. No one person can expect to have exactly the mix of shopping options (or other community characteristics) that he or she wants. If the result flows from the myriad decisions that consumers and pro ducers make, it is not coerced. It is the pro cess, not the result, that tells us whether an outside force is coercing people.

Nature and human lifestyles

Luddites argue that technology has made no improvement in life, or at best improve ments of little importance. Sale's list of benefits includes speed, ease, and mass access—all of which he disdains. Sale says that although individuals might feel their lives are better because of computers, the perceived benefits are "industrial virtues that may not be virtues in another morality." He defines moral judgment as "the capacity to decide that a thing is right when it enhances the integrity, stabil ity, and beauty of nature and is wrong when it does otherwise."^® Jerry Mander, founder of the Center for Deep Ecology and author of books critical of technology and globalization, points out that thousands of generations of humans got along without computers, suggesting that we could do just fine without them too. While some people evaluate trade-offs between negative side effects of pesticides and the benefits of reducing diseases or protecting food crops, Mander s objections to technology lead him to the conclusion that there can be no "good" pesticide. While many people work on technological, legal, and educational approaches to reducing the gasoline usage of automobiles, Mander says there can be no good automobile.^'

What are the underlying premises behind these comments by Sale and Mander? We consider Sale's comment on moral judgment first. Many debates about the environment set up a humans-versus-nature dichotomy.^^ This is not the true con flict. Nature, biodiversity, forests, a hospitable climate, clean air and water, open space away from cities—these are all important and valuable to humans. But so are life-saving medical techniques and shelter from the rain, cold, and heat. Con flicts about the environment are not conflicts between humans and nature. They are conflicts between people with different views about how to meet human needs.

7.2 Neo-Luddite Views of Computers, Technology, and Quality of Life 383

In contrast to Sale s statement, moral judgment, to many people, and for many cen turies, has meant the capacity to choose that which enhances human life, reduces misery, and increases freedom and happiness. Sale's comment chooses nature, not humanity, as the primary standard of moral value.

Whether an automobile or electronic device is "good," by a human-centered standard, depends on whether it meets our needs, how well it does so, at what cost (to the environment and society, as well as to our bank account), and how well it compares to alternatives. Critics of modem technologies point out their weak nesses but often ignore the weaknesses of alternatives—for example, the millions of acres once needed to grow feed for horses and the hundreds of tons of horse manure dropped on the streets of cities each day, a century ago.^^ Candles, gas lamps, and kerosene lamps filled homes with fumes and soot. Do we need electric ity? Do we need hot water on tap, movies, and symphony orchestras? Or do we need nothing more than food and shelter? Do we need an average life expectancy of more than 25 years? Do we want to merely exist—do we need even that? Or do we want long, happy, comfortable lives filled with time for love, interesting activi ties, and an opportunity to use our marvelously inventive brains?

Accomplishments of technology

It is easy to miss the extreme changes in quality of life that have taken place over the past few centuries. We mention here a scattering of examples.

Technology and the Industrial Revolution have had a dramatic impact on life expectancy. A study in 1662 estimated that only 25% of people in London lived to age 26. Records from 18th-century French villages showed that the median age of death was lower than the median age of marriage. Until recent generations, parents had to endure the deaths of several of their children. Starvation was common. In the United States, life expectancy at birth increased from 47.3 years in 1900 to 79 in 2016. Worldwide average life expectancy increased from approximately 30 in 1900 to approximately 71.1 in 2015. Science and technology (along with other fac tors such as education and increased wealth) reduced or almost eliminated typhoid, smallpox, dysentery, plagues, and malaria in most of the world. Deaths at work, during travel, and by accidents, declined dramatically.^'*

In the early 2000s, Americans spent less than 10% of family income on food, compared to approximately 47% in 1901. Agronomist Norman Borlaug, who won a Nobel Peace Prize for his work in improving agricultural productivity, reported that when new forms of wheat and crop management were introduced in India, yields rose from 12.3 million tons in 1965 to 73.5 million tons in 1999. In about the same timeframe, U.S. production of its 17 most important crops increased from 252 million tons to 596 million tons, but used 25 million fewer acres. Nicholas Eberstadt, an expert on population, reported that food supplies and gross domestic product have been growing faster than population for decades in most areas of the world, in both developing and developed countries.^^

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Environmental impacts

We considered including a section in this book on environmental impacts of com

puters, mobile devices, and the Internet. While reviewing data, we concluded that attempts to quantify environmental ben efits and costs would be subject to the

same weaknesses and criticisms of mod

els that we discussed in Section 7.1.2. It

is extremely difficult to measure impacts and to determine how to compare to

impacts of technologies and activities that computing technology replaces. However, we can make some observations.

Production of computers is energy intensive and uses hazardous materials.

Because of these materials, disposal of electronic devices is an issue, as it is for

fluorescent light bulbs. Running and cooling the millions of servers on the Internet in the

United States accounts for about 2% of elec

tric power usage, more than the usage of the U.S. auto industry and less than the usage of the chemical industry.^® There are estimates that production of computers uses roughly twice as much energy as operating them though this disparity is decreasing as major manufacturers of computers, smartphones,

and other digital devices move to make their manufacturing more energy efficient.

On the other hand, digitally controlled machinery uses less power than older elec tromechanical controls. Digital sensors

and controls for regulating lighting, heating, air conditioning, and farm irrigation (among many other examples) save resources by determining just what is needed and thus reduce waste. Microprocessors control hybrid cars, reducing gasoline use. Tele commuting, e-commerce, and online infor mation sources significantly reduce the need for driving and flying and thus, the need for fuel. One fiber-optic cable, with

about 150 pounds of silica, carries more

messages than a ton of copper wire.®^

Digital storage of documents, data, photos, and so on reduces the need for paper and the amount of trash produced. Specific examples suggest the reductions: A large insurance company reduced its use of paper by ICQ million pages in a nine- month period by storing its manuals digitally instead of printing them. A computerized system for recording insurance claims replaced more than 30 million index cards. We text and send email instead of sending

letters and cards on paper. Electronic pay ments eliminate paper bills and checks. We read books, newspapers, magazines, and so on, on tablets, e-readers, and smart- phones, reducing paper use. The decline in business for the U.S. Postal Service and

printed newspapers, while population and economic activity grow, are indications of these reductions. But do we actually use

less paper than we did before? We could not find clear data for total paper use.

However, between 2001 and 2011, annual consumption of newsprint for daily news

papers in the United States dropped by an estimated 61%, and the number of pieces

of first class mail dropped by about 24%.®® For a long time, companies that sell fur

niture and appliances built rooms (e.g., kitch ens) to photograph for their catalogs, and then tore them down and discarded much

of the material. IKEA now uses 3D graphics programs to create some of its room images for catalogs, with obvious savings of natural resources (as well as time and money).

We take, post, and share far more

photos (billions per month) than we did when we made prints and slides. This is

an example of a phenomenon that occurs in many fields: As a product or service becomes more efficient and cheaper, we

use more of it. We see the same effect

with medical technology, education, and other services that bring us benefits.

7.3 Digital Divides 385

The benefits of telecommunications and information technology are enormous in developing countries. A report of a United Nations Conference on Trade and Development, for example, observes that developing economies can make produc tivity gains worth billions of dollars by encouraging the growth of electronic com merce. The report said that "it is because the internet revolution is relevant not just to the high-tech, information-intensive sectors but also to the whole organisation of economic life that.. . developing countries stand a better chance of sharing in its benefits earlier than in previous technological revolutions."^^

Technology is certainly not the only factor in improving quality of life. Prog ress against disease, discomfort, and early death depends on the stability, freedom, and flexibility of political and economic systems as well. Measuring quality of life is subjective, and some find other measures more important than the few we cited above. But, for many people, these data suggest that technology has contributed much to human well-being.

7.3 Digital Divides

Despite the views of Neo-Luddites, most people continue to expand their use of com puting technology and the Internet The term digital divide refers to the fact that some groups of people regularly use the various forms of modem information technology, while others do not and cannot. In the 1990s, the discussion about the digital divide focused on gaps in access to computers and the Internet for various groups within the United States and other developed countries. As Intemet access and mobile phones spread, focus shifted to the rest of the world. The global digital divide shrank faster than many long-standing global divides in, for example, access to fresh water and toi lets, but many very difficult problems still thwart access to computer and Intemet tech nology in poor and developing countries. In this section, we review trends in access in the United States, and then look at problems of access in other parts of the world.

In most of this book, we examine problems that digital technologies cause. Thus, it is interesting to observe that this section looks at problems related to the lack of the technology; the implicit assumption is that digital technology is highly desirable for people all over the world. The question is how to get it to them.

7.3.1 Trends in Access in the United States

When personal computers and later the Intemet were first available to the public in the United States, a small minority enjoyed them. In 1990, personal computers cost nearly 10% of the average U.S. household income. We connected to the Internet using slow, noisy dial-up modems. Frequent Internet use required a second phone line since we could not make or receive phone calls while connected to the Inter net. There were few applications useful to most people, and users needed technical skills. Many people could not afford computers and Internet access, and many did not see much point in having them.

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As the value of computers and Internet access became clearer, people became concerned about the gaps in ownership and access. In 1990, only 22% of house holds in the United States owned a computer. Access in rural and remote regions lagged access in cities. Black and Hispanic households were about half as likely as the general population to own a computer. Poor children had little access to com puters both in schools and at home. Only 10% of Internet users in the early 1990s were women, and people over 65 rarely used computers.^

Software innovations, such as point-and-click graphical user interfaces. Web browsers, and search engines, made computer use simpler for ordinary people. With lower prices, more useful applications, and easier use, ownership and access spread. By 1997, the gender gap had vanished. By 2000, most public libraries provided free Internet access for the public and 98% of U.S. high schools had Internet access—though the quality of that access still varies greatly. In 2001, 84% of homes with children in middle and high school had a computer and Inter net access. By the early 2000s, the gaps among Hispanic, black, and white peo ple almost completely disappeared among those with the same education levels. Businesses, community organizations, foundations, and government programs all played roles. Federal and local governments spent billions of dollars on technol ogy for communities and schools. Companies such as Apple, Microsoft, and IBM contributed hundreds of millions of dollars in equipment and training programs.^'

The price of computing power continued to drop, and the trend in ease of use continued with the development of touch interfaces for tablets and mobile phones. By 2015, 92% of adults in the United States owned a mobile phone and 67% had a smartphone.^^

As computers, phones, and Internet access spread, the focus changed to dispar ity in quality of access, for example, access to a broadband, or high speed, Internet connection. In 2003, fewer than 20% of all U.S. households had what the gov ernment then defined as broadband: four megabits per second (Mbps) download speed. But as broadband spread and improved, the U.S. Federal Communications Commission (FCC) changed the definition from four Mbps to 25 Mbps.* As of 2016, 80% of U.S. households met the new higher standard, while 6.3% still did not have four Mbps service.^^ Slow or no access makes it more difficult to find employment opportunities, access news and information, attend online courses, and make use of online health information.

Several million households with school-age children still do not have Internet access at home. The lack of Internet connections makes it difficult for children to

complete some school assignments and use online resources. As an example of one program to address this problem and of the care required in such programs. Sprint offered free data connections to low-income students, and then discovered that the

*The definition of broadband includes a minimum upload speed also; the FCC raised it from one Mbps to three Mbps.

7.3 Digital Divides 387

program was not fully successful because the students lacked devices on which to use the data. Sprint then began a program to provide one million devices (phones, laptops, and tablets) and free data to low-income high school students.

While broadband spread dramatically in 13 years, from fewer than 20% of households having four Mbps to 80% of households having more than 25 Mbps, we need to remain aware of those in low-income households who lack the devices and connections that could help improve their hves.

7.3.2 Reaching the Next Billion Users*

Almost three and a half billion people worldwide can access the Internet from their homes, more than 10 times as many as in the late 1990s^—^but about the same number of people cannot. Only a decade ago, most people in the world had never made a telephone call. There are now roughly as many mobile phone subscriptions as people in the world (see Figure 7.5). That does not mean everyone has one: In developed countries, many individuals and businesses have multiple subscrip tions, while large numbers of people, especially in poor countries, do not have phones. In many parts of the world, if you give someone a free smartphone, it would be useless—there is no place to charge it.

(per 100 people)

100 7.3 billion people

7.1 billion

subscriptions World

population

Mobile

phone

3.2 billion users

Internet

1995 2015

Figure 7.5 Progress in Internet and mobile phone access.^^

*When the World Wide Web first reached a billion people around the world, roughly a decade ago, some nonprofit organizations and companies began using the phrase "the next billion users" for the people in developing countries whom they hoped would be online in the near future.

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From one perspective, the spread of mobile phones and Internet access is an extraordinary accomplishment in a very short time. From another perspective, it means a large part of the world's population is missing out on technologies that could provide them with access to information, education, and healthcare important services that can help lift individuals and communities out of extreme poverty. Here, we consider problems that thwart the spread of computer and Inter net technology in poor and developing countries, some projects that attempt to help, and some reasons why such projects sometimes fail.

First, we give a little more data to provide some context. In the developing world, very approximately,* 50% of the population uses the Internet, compared with 87% in the most economically advanced countries. In dozens of the poorest countries, the rate is less than 10%. Broadband Internet is becoming more widely available and affordable, but is still out of reach in many developing countries. As in the early Internet days in the United States, some communities have Internet cafes where people can use computers and access the Internet, but often the equipment is old and shares a single low-speed connection. While many people around the world have a mobile phone, in poor countries few have smartphones.^*^

Lack of access to the Internet in much of the world has many of the same causes as lack of health care and education: poverty, isolation, poor economies, and poli tics. Many companies and organizations in the developed world have embarked on projects to improve access. They often focus on providing computers and Internet access to schools where there is the potential to improve education—a key fac tor in reducing poverty. They give computers and train teachers to use technol ogy in classrooms. But providing computers, communication, and Internet access to remote and poor communities in useful ways can be very difficult, and many projects fail. Lack of success in various programs reinforces an important lesson: Giving out technology and walking away will not close the digital divide. The success of a program implementing technology into school curricula, for example, depends on the presence of supporting technical and social infrastructures such as electricity, networks, technical support, parental support, teacher attitudes toward technology, and administrative school support. To gain local community support, programs to increase access must address local cultural issues and work with com munity members whose business or status the project may impact negatively.

We consider a few hurdles to the spread of computer and communications technology: power, connectivity, climate, and culture.

About 1.2 billion people worldwide still live without access to electricity,^^ and in many parts of the world power is unreliable. On a game day, the Dallas Cow boys stadium draws more than three times the amount of power that the country of Liberia can supply to its power grid.^^ Mobile phone users in many regions must travel to areas that have power and then pay to charge their phones. Voltage spikes.

*The numbers change quickly, and various studies count differently; use of the Internet typically means access to the Net from home, but some figures include owning a smartphone and some do not.

7.3 Digital Divides 389

brownouts, and outages damage computer equipment. Local power generation, such as from a gasoline generator or solar cells, can be expensive to install or expensive to maintain and operate. A few projects have tried innovative approaches such as human-powered bicycle generators that operate equipment or charge batteries.

Cellphone and Internet connection in many areas is available sometimes but is unreliable or slow. In response, Google developed a version of its YouTube app to work on slow networks. Clearly, more apps designed for low data transmission would be helpful. To improve access to the Web, several companies are experi menting with projects such as huge drones or satellites to provide network nodes over regions with no or poor Internet connectivity. The United Nations reports that more than 65 million people are displaced from their homes because of war or famine.''^ Communication can be invaluable to these people, but it is difficult to provide reliable power and Internet connection in refugee camps.

The nonprofit organization One Laptop per Child (OLPC) recognized a prob lem often overlooked: extreme climates. OLPC developed a laptop computer spe cially designed for elementary school children in developing countries. It works in extreme heat or cold, extremes of humidity, and dusty or rainy environments, and the power requirements are very low, but the price (approximately $200) is too high for many poor countries.^"

Culture and social attitudes can slow the spread of technology. Women gen erally report that a mobile phone gives them independence, access to jobs, and access to the political system, but large gender gaps in ownership of mobile phones exist in Africa, the Middle East, and south Asia. In India, for example, 28% of women own mobile phones (see Figure 7.6) while 43% of men do. In India, Bangladesh, and Pakistan, roughly three times as many men as women use Facebook.

Figure 7.6 Indian women share a mobile phone.

Chapter 7 Evaluating and Controlling Technology

In some communities, men do not allow their wives and daughters to own phones. Large companies and foundations, including the Gates Foundation, are working to reduce the gender gap. Google and Tata Trusts send thousands of trained women, riding on bicycles, to rural villages in India to teach women how to use the Web.^'

Political and social views affect acceptance; for example, some Net neutrality and Countries wclcome programs that provide free partial or limited

m3.7 access to the Internet for people who cannot afford access, while others that place high value on net neutrality reject these programs.

How important are computers and Internet access in poor countries? Some gov ernments and local officials criticize programs that promote acquisition of computer equipment because, they argue, basic health care for children and clean water are higher priorities. On the other hand, communication and access to information can contribute to solutions for these problems. In many developing countries, farmers and fishers use the Internet or their mobile phones to find nearby villages where they get a better price for their crops or catch (see Figure 7.7). As the technology spreads.

Figure 7.7 A farmer compares prices for her crop in various markets in Burkina Faso.

7.4 Control of Our Devices and Data 391

food production and distribution, and thus health and economic well-being improve. In wealthier countries, although we enjoy many life-saving and life-enhancing ben efits of digital technologies, most people use our tech tools far more for entertain ment and convenience than for basic needs. As Internet access continues to spread to the billions of people without it, the impact can be far greater because of the potential to improve the lives of people who are devastatingly poor.

7.4 Control of Our Devices and Data

In Chapters 4 and 5, we saw that Apple tries to control which apps people can install on their iPhones and that some users found ways to deactivate the controls, but doing so can increase the risk of a hacking attack. Here, we look at situa tions in which the companies that provide devices, software, or data can reach into our devices and delete or modify our stuff. Their intervention may be helpful and may protect us, or it may serve needs of the company, or both. In any case, it is an example of our loss of control of our devices and data. For the situations we consider, think about the balance between benefits and disadvantages.

7.4.1 Remote Deletion of Software and Data

Soon after Amazon began selling electronic books for its Kindle ebook readers, the company discovered a publisher was selling books in Amazon's online store that the publisher did not have legal rights to sell in the United States. Amazon deleted the books from its store and from the Kindles of people who had bought them; it refunded customer payments. A reasonable and appropriate response? Many customers and media observers did not think so. Customers were outraged that Amazon remotely deleted books from their Kindles. People were startled to learn that Amazon could do so.* The response was so strong that Amazon announced that it would not remove books from customer Kindles again. Few realized at that time that Apple's iPhones already had a way for Apple to remotely delete apps from phones. When a software developer discovered malicious code in an app for Android phones, Google quickly removed the app from its store and from more than 250,000 phones. Although this was a good example of the purpose of remote deletion and a beneficial use, the fact that Google could do so disturbed people.

Perhaps this extended reach should not have been a surprise, since in many businesses the IT department has access to all desktop computers and can install— or delete—software. Software on personal devices communicates with businesses and organizations regularly, without our direct command, to check for updates of software, news, and our friends' activities. When we enable updates of software, a company remotely deletes old versions.

"Ironically, one of the books Amazon removed was George Orwell's 1984—a novel about a totalitarian government that regularly sent documents down a "memory hole" to destroy them.

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A main purpose of remote deletion by companies such as Google and Apple is security—to remove illegal or malicious software that the company discovers in an app after users have downloaded it. Indeed, companies that provide popular app stores see it as a serious responsibility to protect users from malicious apps. Millions of phones running a malicious app could have a devastating impact on our entire com munications network. Some companies tell us about their removal capability in their terms of use agreements, but as we have noted before, such agreements can run to thousands of words and have vague, general statements and few people read them.

What are some potential uses and risks of remote deletion? Malicious hack ers might find a way to use the delete mechanism for pranks or ransom. For more than 2000 years, governments and religious and social organizations have burned books that displeased them. What pressures might governments put on companies to delete material they disapprove of? Will the impact of electronic deletion be more devastating than destruction of scrolls, ancient books, and printed material?

7.4.2 Automatic Software Upgrades

We use Microsoft's upgrade from Windows 7 to Windows 10 to illustrate general problems and questions about automatic software upgrades. In 2016, users of Micro soft Windows 7 found their computers automatically and unexpectedly upgrading to Windows 10. The long upgrade time inconvenienced many who were in the middle of an important project while others had more serious problems. Some users had selected to receive operating system updates but did not expect that the entire oper ating system would be upgraded to a newer version. Microsoft said Windows 10 installed only if the user gave explicit permission. Some users may have allowed the upgrade without realizing they did, but some system administrators said they saw the upgrade performed on test systems where they had not given explicit permission.

Why would an operating system vendor push strongly to upgrade older sys tems? In this case, as in others, the newer operating system provides many improved security features and better compatibility across various hardware platforms the company supports (for example, PCs, Xbox, and Surface). It is easier for a com pany to provide user support when all users are on the same version of an operating system. Why would some users not want the upgrade? Some people use software that may be incompatible with the new system, some simply prefer the older user interface, and some do not want an interruption—with potential for unknown prob lems—in the middle of a large project. As we mentioned in Chapter 5, automatic software updates can create headaches for IT staif who have not had the opportu nity to test the update for compatibility and security.

Software updates for cars, medical devices, and so forth can have serious impacts on safety. You would not want your self-driving car to pause on a high way while an update installs. One maker of semi-autonomous cars automatically downloads software updates to the vehicles, informs the owner, and lets the owner schedule installation, say, at night. If the owner does not install the update, he or she could be putting others at unnecessary risk. How should the company handle that?

7.5 Making Decisions About Technology 393

Where should control of updates lie? Do software vendors do a good enough job of telling users the category of update (security patch, new features, etc.—or a whole new operating system)? How should update policies vary with the type of device—phone, tablet, television, automobile, radiation treatment machine?

7.5 Making Decisions About Technology

No one voted for this technology or any of the various machines and processes that make it up.

—Kirkpatrick Sale^"

7.5.1 Questions

We saw in Section 12 that the determination of what are true needs depends on our choice of values. Throughout this book, we saw controversies about specific prod ucts, services, and applications of computer technology (for example, personalized advertising, anonymous Web surfing, and face recognition systems). How should we make decisions about the basic question of whether to use a whole technology, or major segments of it, at all? Who would make such decisions?

Most people in science, engineering, and business accept, almost without question, the view that people can choose to use a technology for good or ill. Some critics of technology disagree. They argue that technologies are not "neutral." Neil Postman says, "Once a technology is admitted [to our culture], it plays out its hand; it does what it is designed to do."" This view sees the technologies them selves as being in control.

In the view of some critics of computing technology, big corporations and governments make decisions about uses of the technology without sufficient input or control from ordinary people. Kirkpatrick Sale's lament at the beginning of this section expresses this view: There was never a vote on whether we should have computers, the Internet, mobile phones, or toothbrushes that tell us how long to brush. Some people argue that we should not use a new technology at all until we have studied it, figured out its consequences, and made a determination that the consequences are acceptable. The idea is that if the technology does not meet cer tain criteria, we would not permit its development and use.

This view leads to a few basic questions. Can a society choose to have certain specific desirable modem inventions while prohibiting others or prohibiting whole technologies? How well can we predict the consequences of a new technology or application? Who would make the decisions? We consider the first question here and the others in the next few sections.

How finely can we make decisions about acceptable and unacceptable technolo gies? In response to a criticism that the tribal life he extolled would have no pianos, no violins, no telescope, no Mozart, Sale replied, "[I]f your clan thought that the violin was a useful and nonharmful tool, you could choose to invent that."" Perhaps critics

194 Chapter 7 Evaluating and Controlling Technology

of computing technology who recognize its value to disabled people would permit development of applications for them. The question is whether it is possible for a clan or society to choose to invent a violin or a camera-equipped cane that warns a blind person of obstacles without the technological and economic base on which develop ment of these products depends. That base includes the freedom to innovate, a large enough economy to get materials from distant sources, and a large number of potential applications that make the research, development, and production of the basic ingre dients of these products economically feasible. It is unlikely that anyone would even think of developing the cane for the blind if some of the components did not already exist in prior products (for example, perhaps, small cameras in mobile phones). Nor would drones exist to quickly deliver life-saving medical supplies in Rwanda, bypass ing poor roads, if companies did not sell drones for many other purposes.

7.5.2 The Difficulty of Prediction

A brief look at the development of communications and computer technology sug gests the difficulty of evaluating the consequences and future applications of a new technology. Early computers were developed to calculate ballistics trajectories for the military. The personal computer was originally a tool for doing computation and writing documents. Only a few visionaries imagined most of their current uses. Each new technology finds new and unexpected uses. When physicists began developing the World Wide Web, who would have predicted online auctions, social

leiemeGK ff tdcftinology?

In Chapter 1, we described long-distance medicine, or telemedicine, as a benefit of computer technology. Computer and communications networks make possible

remote consultations and examination of

patients, and they make possible remotely controlled medical procedures. You may be able to think of potential privacy and

safety problems with such systems. Should we ban telemedicine?

Several states passed laws prohibit ing the practice of telemedicine by doc tors who are not licensed in that state.

The main argument they give for the laws is safety, or concern about out-of-state "quacks." The laws will "keep out the char latans and snake-oil salesmen," according

to one supporter.^® Also, telemedicine could increase the influence of large.

well-financed medical centers—^to the det

riment of local physicians in private prac tice. Large hospitals might become the "Walmarts of medicine," says one writer. Telemedicine might make medical care even more impersonal than it is already.

Is concern for patients the real reason for the laws? The arguments about char latans and quacks seem weak, consider ing that the laws target doctors who are licensed, but in another state. Many doc tors who support the bans see telemedi cine as a significant competitive threat. As the director of one state medical board put

it, "They're worried about protecting their turf."^® The laws restrict competition and protect established special interests—a risk of any mechanism designed to pro hibit a new technology or product.

7.5 Making Decisions About Technology 395

networking, or sharing home video? Would anyone have predicted even a small fraction of the ways we use smartphones? Postman's statement that a technol ogy does "what it is designed to do" ignores human responsibility and choice, innovation, discoveries of new uses, unexpected consequences, and social action to encourage or discourage specific applications. Computer scientist Peter Den ning takes a different view: "Although a technology does not drive human beings to adopt new practices, it shapes the space of possibilities in which they can act: people are drawn to technologies that expand the space of their actions and rela- tionships."'' Denning says people adopt technologies that give them more choices. Note that he does not say more choices of consumer products, but more actions and relationships. Don Norman also suggests that society influences the role of a technology when he says, "The failure to predict the computer revolution was the failure to understand how society would modify the original notion of a computa tional device into a useful tool for everyday activities."^®

How well can a government committee, a think tank, or a computer industry executive predict the consequences of a new technology? The history of technology is full of wildly wrong predictions—some overly optimistic, some overly pessi mistic. Some scientists were skeptical of air travel, space travel, and even railroads. (They believed that passengers would not be able to breathe on high-speed trains.) Consider the quotations in Figure 7.8.* Some of them reflect a lack of imagination about the myriad uses people would find for each new technology, about what the public would like, and about what they would pay for. The quotes demonstrate humorously that many experts can be utterly wrong. John von Neumann, a brilliant mathematician and early computer scientist, recognized this when he said, in 1949, "It would appear that we have reached the limits of what it is possible to achieve with computer technology, although one should be careful with such statements, as they tend to sound pretty silly in 5 years."^^

We examine the prediction problem more seriously and in more depth by considering arguments made by computer scientist Joseph Weizenbaum against the development of a particular computer technology: speech recognition sys- tems.®° We now have more than 40 years of hindsight since Weizenbaum wrote in 1975. However, many inexpensive applications of speech recognition had already appeared by the early 1990s. Here are Weizenbaum's objections, accompanied by comments from our perspective today.

"The problem is so enormous that only the largest possible computers will ever be able to manage it" Speech recognition software runs on mobile phones.

"... a speech-recognition machine is bound to be enormously expensive, . . . only governments and possibly a very few very large corporations will therefore be able to afford it." Millions of people use applications that include speech recognition.

'Many false or out-of-context quotes of this type circulate on the Internet. We have tried to eliminate false ones and provide context for others; the endnote on Figure 7.8 contains sources.

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• My personal desire would be to prohibit entirely the use of alternating currents. They are unnecessary as they are dangerous. —^Thomas Edison, 1899

• Teievision won't be able to hold on to any market it captures after the first six months. People will soon get tired of staring at a plywood box every night. —Darryl Zanuck, 20th Century Fox, 1946

• Computers in the future may... only weigh 1.5 tons. —Popuiar Mechanics, 1949

• The U.S. will have 220,000 computers by the year 2000. —Official forecast by RCA Corporation, 1966. The actual number was close to 100 million.

• Cellular phones will absolutely not replace local wire systems. —Marty Cooper, 1981 (Cooper, director of research at Motorola, invented an early cellphone but thought they would always be too expensive.)

• I predict the Internet... will soon go spectacularly Supernova and in 1996 catastrophicaily collapse. —Bob Metcalfe, 1995 (Metcalfe, an inventor of the Ethernet, thought the Internet infrastructure was insufficient to handle increasing traffic.)

• Everyone's always asking me when Apple will come out with a ceil phone. My answer is, 'Probably never.' —David Pogue, technology writer for The New York Times, 2006

• There's no chance that the iPhone is going to get any significant market share. No chance.

—Steve Ballmer, CEO of Microsoft, in an interview in 2007 shortly before the iPhone went on sale

Figure 7.8 Predictions.^'

"What can it possibly be used for?" Speech recognition technology is a multibil- lion-dollar industry. Here are just few of its current uses, and we are still in its infancy:

• We can search for information, send text messages, make appointments, control home appliances, and so on with our voices. We can check airline flight schedules, get stock quotes and weather information, conduct banking transactions, and buy movie tickets on the phone by speaking naturally instead of pushing buttons.

• We can call a business, speak the name of the person we want to reach, and automatically connect to that person's extension.

• Software creates transcripts from audio tracks of video and television for deaf people to read and for search engines to index.

• Training systems (e.g., for air traffic controllers) and various tools that help disabled people use computers and control appliances in their homes use speech recognition.

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• People who suffer from repetitive strain injury use speech recognition input instead of a keyboard. IBM advertised speech-input software for poets, so they can concentrate on poetry instead of typing. People with dyslexia use speech recognition software so that they can write by dictation.

• Speech translation systems recognize speech and translate it into other languages. They are very helpful to tourists, businesspeople, social service workers, hotel reservations clerks, and many others.

• Speech-activated, hands-free operation of mobile phones, music systems, and other appliances in automobiles eliminates some of the safety hazards of using these devices while driving.

• Going beyond simply recognizing words, software can analyze emotions in voice tones. One suggested application is marriage counseling. What other uses can you think of?

The military planned to control weapons by voice command,"a long step toward a fully automated battlefield." Speech recognition in a battlefield situation is still a challenging problem, but we have already automated some aspects of warfare, for example, by using drones. Some argue that we should have the best possible weapons to defend ourselves. Others argue that, if wars are easier to fight, governments fight more of them. If countries fight wars with remotely controlled automated weapons and no humans on the battlefield, is that an improvement over wars in which people are slaughtered? What if only one side has the high-tech weapons? Would that cause more wars of aggression? Is there any technology that the military cannot or does not use? Should we decline to develop strong fabrics because the military can use them for uniforms? Clearly, military use of high-tech tools raises serious ethical and policy questions. Are these questions sufficient rea son to abandon or condemn a technology?

Governments can use speech recognition to increase the efficiency and effec tiveness of wiretapping. And they do: Governments use speech recognition to fil ter thousands of hours of recorded conversations. Weizenbaum's concern was the potential for increased abuse of wiretapping; he does not explicitly mention legal wiretapping of criminal suspects. One can argue that governments can use the same tool beneficially in legal wiretapping of suspected criminals and terrorists, but it is true that speech recognition, like many other technological tools, can be a danger in the hands of governments. Protection against abuses depends in part on the recognition of the importance of strictly controlling government power and in part on the appropriate laws and enforcement mechanisms to do so.

Discussion of Weizenbaum's objections is important for several reasons: (1) Although Weizenbaum was an expert in artificial intelligence, of which speech recognition is a subfield, he was mistaken in his expectations about the costs and ben efits. (2) His objections about militaiy and government use highlight the dilemma: Should we decline to develop technologies that people can misuse, or should we

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develop the tools because of their beneficial uses, and use other means, including our votes and our voices, to influence government and military policy? (3) Weizenbaum's argument against development of a technology because of its expected cost is similar to arguments expressed by others about current and future computer applications and other technologies. For example, a common objection to some new medical tech nologies is that they are so expensive that only the rich will be able to aiford them. This shortsighted view can result in the denial of benefits to the whole population. For many new inventions, prices are high at first but quickly come down.

Weizenbaum was not trying to evaluate computer technology as a whole but was focusing on one specific application area. If we are to permit the government, or experts, or the people via a majority vote to prohibit development of certain technologies, it is essential at least that we be able to estimate the consequences— both risks and benefits—of the technology fairly accurately. We cannot do this; nor can the experts do it.

But what if a technology might threaten the survival of the human race? We consider such an example in the next section.

7.5.3 Intelligent Machines and Superintelligent Humans—Or the End OF THE Human Race?

Prominent technologists such as Hans Moravec, Ray Kurzweil, and Vemor Vinge describe a not-very-distant future in which intelligence-enhancing devices, artificial intelligence, and intelligent robots change our society and our selves in profound ways.^^ The more optimistic scenarios include human use of intelligent machines and services of many kinds. People might acquire advanced mental powers through brain implants and computer-brain interfaces. When someone has a stroke, doctors might remove the damaged part of a brain and replace it with a chip that performs the lost functions, perhaps with a large amount of extra memory, or a chip to access the Web directly. \\Tiy wait for a stroke? Once the technology is available, healthy people will likely buy and install such implants. MIT robotics researcher Rodney Brooks, for example, suggested in 2003 that by 2020 we might have wireless Internet interfaces that doctors can implant in our heads. He says people might be just as comfortable with them as they are with getting laser eye surgery at a mall You could be reading this in 2020. Are such implants available? Do such implants make someone less human than a heart transplant or pacemaker does? What social problems could intelligence enhance ment cause in the next few decades? What philosophical and ethical problems arise when we combine human and machine intelligence in such intimate ways?

Going farther into the future, will we "download" our brains to long-lasting robot bodies? If we do, will we still be human?

The technological singularity

The term technological singularity refers to the point at which artificial intelli gence or some combined human-machine intelligence advances so far that we

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cannot comprehend what lies on the other side. It is plausible, says computer scien tist Vemor Vinge, that "we can, in the fairly near future, create or become creatures who surpass humans in every intellectual and creative dimension. Events beyond such a singular event are as unimaginable to us as opera is to a flatworm."®'*

Some technologists welcome the idea of humanity transforming into an unrec ognizable race of superintelligent, genetically engineered creatures within this cen tury, Others find it horrifying—and others unlikely. Some see potential threats to the survival of the human race. They see the possibility of the machines themselves achieving human-level intelligence, and then rapidly improving themselves to a superhuman level. Once robots can improve their design and build better robots, will they outcompete humans? Will they replace humans just as various species of animals displace others? And will it happen soon, say within the next 20 years or so?

Two estimates support these scenarios. One is an estimate of the computing power of the human brain. The other is based on Moore's Law, the observation Gordon Moore, a co-founder of Intel, made in 1965 that the computing power of new microprocessors doubles roughly every 18 to 24 months. Moore's Law held true for nearly 50 years. But now, the electronics on chips are so small (less than 14 or even 10 nanometers) that chip manufacturers began running into problems in quality manufacturing and problems related to laws of physics that slowed the process. Doubling computing power now takes between 2.5 and 3 years. If the progress of hardware power continues at this rate, then by roughly 2040 computer hardware will be about as powerful as a human brain, sufficiently powerful to sup port the computation requirements of intelligent robots.

Both those who think an extreme advance in machine intelligence is likely in the near future and those who criticize these ideas provide several reasons why it might not happen. First, hardware progress might continue to slow down. Second, we might not be able to develop the necessary software in the next few decades, or at all. Developments in AI, particularly in the area of general intelligence, have been slower than researchers expected when the field began. (On the other hand, some experts did not expect recent achievements, such as a computer beating a Go master, for another decade.) Third, the estimates of the "hardware" computing power of the human brain (the sophistication of the computing power of neurons) might be drastically too low. Finally, some philosophers argue that robots pro grammed with AI software cannot duplicate the full capability of the human mind.

Responding to the threats of intelligent machines

Whether the singularity occurs within a few decades, or later, or not at all, many in the relevant fields foresee general-purpose intelligent machines within your life time. By its definition, we cannot prepare for the aftermath of the singularity, but we can prepare for more gradual developments. Many of the issues we explored in previous chapters are relevant to enhanced intelligence. Will software bugs or other malfunctions kill thousands of people? Will hackers hack brains? Will a large division open between the superintelligent and the merely humanly intelligent?

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We saw that protections for safety and privacy in computer systems are often weak because they were not designed in from the start. It is valuable to think about potential problems of superintelligent systems and intelligence enhancement for humans well before they confront us so that we can design the best protections.

Bill Joy cofounded Sun Microsystems (now owned by Oracle) and was a key developer of Berkeley Unix and the Java programming language. In his article "Why the Future Doesn't Need Us,"^^ Joy describes his worries about robotics, genetic engineering, and nanotechnology. He observes that these technologies will be more dangerous than technologies of the 20th century (such as nuclear weap ons) because they will be self-replicating and will not require rare and expensive raw materials and huge factories or laboratories. Joy foresees profound threats, including possibly the extinction of the human race.

What protections do people who fear for the future of humanity recommend? Joy describes and criticizes some before suggesting his own. Space enthusiasts sug gest creating colonies in space and several private organizations are working toward that goal, but Joy believes it may not happen soon enough. If it does, it might save the human race, though not the vast majority of humans on earth. And if colonists take the current technologies with them, the threat goes too. A second solution is to develop protections that can stop the dangerous technologies from getting out of con trol. Futurist Virginia Postrel suggests "a portfolio of resilient responses."^^ Joy argues that we could not develop "shields" in time, and if we could, they would necessarily be at least as dangerous as the technologies they are supposed to protect us against.

Joy recommends "relinquishment," by which he means we must "limit devel opment of the technologies that are too dangerous, by limiting our pursuit of certain kinds of knowledge." He cites, as earlier examples, treaties to limit development of certain kinds of weapons and the United States's unilateral decision to abandon development of biological weapons. However, relinquishment has the same kinds of weaknesses Joy attributes to the approaches he rejects: They are "either undesir able or unachievable or both." Enforcing relinquishment would be extraordinarily difficult, if not impossible.

As Joy recognizes, intelligent robots and the other technologies that concern him have huge numbers of potentially beneficial applications, many of which will save lives and improve quality of life. At what point should governments stop pur suit of knowledge and development? Ethical professionals will refuse to partici pate in development of some AI applications, but they too face the difficult problem of where to draw the line. Suppose we develop the technology to a point where we get useful applications with legal and technological safety controls. How will we prevent visionary or insane scientists, hackers, teenagers, aggressive govern ments, or terrorists from circumventing the controls and going beyond the pro hibited level? Joy sees a relinquishment verification program on an unprecedented scale, in cyberspace and in physical facilities, with privacy, civil liberties, business autonomy, and free markets seriously curtailed. Thus, relinquishment means not

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only that we might lose development of innovative, beneficial products and ser vices, but also that we would lose many basic liberties.

Although we can find flaws with all proposals to protect against the dangers of powerful technologies, that does not mean we should ignore the risks. We need to choose appropriate elements from the various proposals and develop the best protections we can.

Prediction is difficult, especially about the futureF

7.5.4 A Few Observations

We have presented arguments against the view that we should evaluate and perhaps ban new technologies at the start. Does this mean that no one should make decisions about whether it is good to develop a particular application of a new technology? No. The arguments and examples suggest two things: (1) that we limit the scope of decisions about development of new technology, perhaps to particular products, and (2) that we decentralize the decision-making process and make it noncoercive, to reduce the impact of mistakes, avoid manipulation by entrenched companies who fear competition, and prevent violations of liberty. We cannot often predict the decisions and the results of decisions made by individual engineers, researchers, programmers, entrepreneurs, venture capitalists, customers, and teenagers who tin ker in their garages, but they have a valuable robustness. The fundamental problem is not what decision to make about a specific technology. Rather, it is to select a decision-making process that is most likely to produce what people want, to work well despite the difficulty of predicting consequences, to respect the diversity of personal opinions about what constitutes a desirable lifestyle, and to be relatively free of political manipulation.

When we consider the most extreme potential developments, such as super- intelligent robots, what level of certainty of dire consequences should we require before restricting the freedom to develop technologies and products that might have marvelous benefits?

Exercises

Review Exercises

7.1 What is one significant criticism of Wikipedia?

7.2 What questions do we use to evaluate computer models?

7.3 Give one of the neo-Luddite criticisms of electronic commerce.

7.4 What is one common use of mobile phones in rural areas or developing countries? 7.5 What is one reason Google or Apple might remove an app from people's smartphones? 7.6 Give an example of a mistaken prediction made about computers.

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General Exercises

7.7 Consider a social media website on which display of news stories depends on the votes of readers. Is it an ethical obligation of the site operators to ensure that votes are not bought and sold, or is it merely a good business policy? Or is it both?

7.8 Describe a scenario in which biased or incorrect information a child finds on the Web might harm him or her. Suggest and evaluate one mechanism for preventing such harm.

7.9 (a) Give an example (actual or hypothetical) of digital manipulation of an image or video for which there is no ethical problem; it is clearly ethical.

(b) Give an example (actual or hypothetical) of digital manipulation of an image or video for which no complex argument is needed; it is clearly unethical.

(c) Give an example (actual or hypothetical) of digital manipulation of an image or video for which deciding whether it is ethical is not simple, where there are reasonable argu ments on both sides, or the context might be important. Elaborate; give an argument for each side.

7.10 We mentioned a journalist's idea of an "alternative viewpoints" button for controversial topics on the Web. What are some weaknesses of this idea?

7.11 Give an example of a bad decision or poor work that you attribute to mental laziness encouraged by computers or the Internet. (Try for one not described in the text.)

7.12 Suppose a computer program uses the following data to determine in how many years an important natural resource (say, copper) will run out.

• The number of tons in the known reserves of the resource.

• The average amount of the resource used per person (worldwide) per year. • The total population of the world.

• An estimate of the rate of population increase for the next few decades.

(a) List all the reasons you can think of why this program is not a good predictor of when we will run out of the resource.

(b) In 1972, a group called the Club of Rome published a study, "The Limits to Growth," using computer models that implied that the world would run out of several important natural resources (e.g., tin, silver, and mercury) in the 1980s and several more by the end of the 20th century. Even with the enormously increased demand from China and other developing countries, we have not run out. Why do you think many people accepted the predictions in the study?

7.13 How do the opportunities for "co-present," or in-person, social interactions today compare with those of 150 years ago?

7.14 Discuss some advantages and disadvantages (to students and to society in general) of students getting college degrees online instead of at traditional colleges where they are co-present with faculty and other students.

7.15 The number of small neighborhood bookstores declined because of competition from both large chain megabookstores and online stores like Amazon.com. Should a law have pro hibited Amazon.com from opening? If not, should we prohibit it from selling used books, to help preserve small neighborhood used-book stores? Give reasons. Suppose you like to shop in your neighborhood bookstore and fear it might go out of business. What can you do?

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7.16 Many games that children used to play on boards with dice, cards, and plastic pieces are now computer games. Is this an example of unnecessary use of technology just because it is there? Describe some advantages and disadvantages of replacing a board game with a computer version.

7.17 Analyze the following argument that we are forced to have a mobile phone. Is it convincing? Some people do not want to own or use a mobile phone. Technology advocates say if you don't want one, you don't have to buy one. But this is not true. We must have one. Before mobile phones became popular, there were coin-operated telephones all over, on street comers, in and near stores, in restaurants, at gas stations, and so on. If we needed to make a call while away from home or work, we could use a pay phone. Now most pay phones are gone, so we must have a mobile phone whether we want to or not.

7.18 Which of the Luddite criticisms of computers listed in Section 7.2.1 do you consider the most valid and significant? Why?

Recall the discussion in the box "Walmart and e-commerce versus downtown and commu nity" (Section 7.2.2), and consider these questions: Do people have a right to shop in small neighborhood stores rather than online? Do people in a small town have a right to eat in a French restaurant? Distinguish between negative and positive rights (Section 1.4.2).

7.20 Identify one item on the Internet of Things that seems very silly and/or unnecessary. Then think up and describe a special situation where it might be useful.

7.21 After development of software to help parents and Internet service providers block access to material inappropriate for children, some governments adapted the software to block access to political and religious discussions. In what way does this example illustrate the views that technology will inevitably have negative uses and that, as Neil Postman said, "once a technology is admitted,... it does what it is designed to do"?

7.22 In the mid-1990s, approximately 70% of the computers connected to the Internet were in the United States. Did this suggest a growing gap between "have" and "have-not" nations? Give your reasons. (Try to find out what percentage of computers or websites are in the United States now.)

7.23 Approximately 6000 languages are spoken in the world. This number is declining rapidly as a result of increased communication and transportation, globalization of business and trade, and so on—all side effects of increased technology in general and of the Internet in particular. What are the advantages and disadvantages of losing languages? Overall, is it a significant problem?

7.24 Suppose you are a neo-Luddite. Argue that the spread of mobile phones to poor countries is a bad thing.

7.25 In Section 3.7, we described the Free Basics program that provides free partial access to the Internet in countries where many people cannot afford access. Compare the value of such programs for helping decrease the digital divide to the value of net neutrality.

7.26 Some writers express concern about a digital divide between content consumers and con tent producers on the Internet.®^ Internet users create blogs. Web pages, videos, and product reviews. Being a content creator empowers a user to communicate his or her message to a large number of people. The Internet can be a strong agent for change for those who have the skills, education, and tools to create content. Content creators tend to be more edu cated, and the content-production divide shows a gap among users based on socioeconomic

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status. How should we view the Internet content-production divide? Consider comparisons with content production before the Internet.

7.27 U.S. government traffic safety agencies want to require that all new heavy vehicles such as trucks and buses have electronic controls that limit their maximum speed. (Regulators are considering a limit of somewhere between 60 and 68 miles per hour.) Give arguments for and against such a requirement.

7.28 A philosopher writing more than a decade ago argued against the use of speech synthesis. He found it unsettling and dangerous that a person might have a telephone conversation with a machine and think it was a real person. Describe a few uses of speech synthesis. What are the benefits? What are reasons for concern?

7.29 Speaker recognition software analyzes speech to determine who the speaker is (not what words the speaker is saying, as in speech recognition). Describe some potentially useful and some potentially threatening or risky applications.

7.30 Assume you are a professional working in your chosen field. Describe specific things you can do to reduce the impact of any two problems we discussed in this chapter. (If you can not think of anything related to your professional field, choose another field that might interest you.)

7.31 Think ahead to the next few years and describe a new problem, related to issues in this chapter, likely to develop from digital technology or devices.

Assignments

These exercises require some research or activity.

7.32 Find an article in Wikipedia on a subject that you already know a lot about. Read and review the article. Is it accurate, well done, complete?

7.33 Find websites that provide recommendations about how much Vitamin C a person should consume each day. Try to find at least one site that is extreme in some way and at least one that you consider reasonably reliable. Describe the sites and explain the basis for your characterization of them.

7.34 This exercise explores whether the wisdom of the crowd can successfully run a soccer team. In 2008, thousands of soccer fans chipped in via a website, MyFootBallClub.co.uk, to buy a British soccer team. The plan was to make management decisions by voting on the Web. Find out how well it worked and how well the team did.

7.35 Find a website that regularly reports on the validity of myths, rumors, and "urban legends" that circulate on the Internet and in social media. Give the site reference and describe any one story that you find there.

7.36 Recent predictions for population growth in the 21 st century are quite different from pre dictions made several decades ago. Find reports of older population models (say, from the 1960s, 1970s, or 1980s), and find reports of recent population models. How do they differ? How have the assumptions in the models changed?

7.37 Three-dimensional "printers" create 3D structures, layer by layer, using glues, resins, and other materials under direction of software. Find some applications of these devices. Sup pose someone described 3D printers 15 years ago as a potential invention and asked. Will they fill any real needs? How do you think most people would have answered? What is your answer now?

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Class Discussion Exercises

These exercises are for class discussion, perhaps with short presentations prepared in advance by small groups of students.

7.38 Some people who consider themselves capable of distinguishing reliable information from unreliable information on the Web are concerned that most ordinary people are not edu cated, experienced, or sophisticated enough to do so. They are likely to believe lies, they might follow dangerous medical or financial advice, and so on. How serious a problem do you believe this is? How do you suggest addressing it?

7.39 Some critics of tools that enable us to select sources of news and information we receive on the Web or in social media argue that the tools encourage fragmentation of society along political lines. Some argue that when most people got their news from three TV networks, there was a more cohesive, shared background of information. How serious is the problem of people seeing only one political point of view on the Web?

7.40 Some people advocate a law requiring Google to make public the algorithms it uses to rank websites for display in response to search queries. Considering issues in this chapter, and any other relevant issues, discuss arguments in favor of such a requirement and arguments against it.

7.41 In a murder case, a mix of DNA from at least three people was found on a piece of evi dence, making it difficult to determine if any belonged to the suspect. A computer pro gram that analyzes DNA samples concluded that the suspect's DNA was indeed there. The defense attorneys asked to have the software examined by an expert to see how it worked and to look for errors. The company that produces the software said disclosure of the code would expose trade secrets and would harm the company. Discuss arguments on both sides. Suggest and evaluate alternative methods for judging the validity of the software without seeing the code.

7.42 Which of the following models do you think would produce very accurate results? Which do you think would be poor, and which in the middle? Give your reasons. (a) A model developed by a team of mathematicians in 1895, using projections of popu

lation growth, economic growth, and traffic increase, to project the tonnage of horse droppings on city streets in 1995

(b) A model to determine the impact of various immigration policies on gross domestic product

(c) A model to predict the position of the moon in relation to the earth 30 years from now (d) A model to predict how much optical fiber a major city will need 30 years from now (e) A model to predict how much carbon dioxide the burning of fossil fuel for energy will

emit worldwide 30 years from now

(f) A model to predict the speed of a new racing-boat hull design under specified wind conditions

7.43 Some neo-Luddites acknowledge that computing technology is beneficial to many people, but they see the main beneficiaries as government and big business. They say the key ques tion is: Who benefits most? Consider the following questions and discuss the issue of who benefits most.

When a drug company develops a new cancer drug and its executives make millions of dol lars as the stock goes up, while people who had that cancer live 20 extra years, who benefits

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most? Who benefits most from social media: governments, businesses, or ordinary users? Who benefits most from access to the Internet: you or someone your age in a rural village with no landline telephones and poor roads?

7.44 What form will the "digital divide" likely take 10 years from now? How do digital divides differ from social divisions that occurred with the introduction of earlier, nondigital infor mation and communication technologies?

7.45 In the Prometheus myth, Zeus, the king of the gods, was furious at Prometheus for teach ing science and technological skills to mankind because they made people more powerful. Zeus was jealous of his power and determined to withhold fire from mankind so that people would have to eat their food raw. Zeus and the Luddites represent different viewpoints on who benefits most from technology.

(a) Give arguments in support of Zeus' view that technology helps the less powerful, reducing the advantage of the more powerful.

(b) Give arguments in support of the Luddite view that technology helps the more power ful (e.g., governments and large corporations) most.

7.46 Read Bill Joy's article, "Why the Future Doesn't Need Us," and the reply by Virginia Postrel (see endnotes 85 and 86 for the references). Whose arguments are more convincing? Why?

Notes

1. From Pope's poem "An Essay on Criticism." In Greek mythology, the Pierian spring in Macedonia inspired the Muses and others who drank from it. Pope s poem turned it into a metaphor for knowledge.

2. Quoted in Stacy Schiff, "Know It All: Can Wikipedia Conquer Expertise?" New Yorker, July 31, 2006, www.newyorker.eom/archive/2006/07/31/060731fa_fact. McHenry was an editor at the Encyclopedia Britannica.

3. Soraya Nadia McDonald, "How Internet Hoaxers Tricked the World into Believ ing this Random Sikh Guy Was a Paris Terrorist," Washington Post, Nov. 16, 2015, www. washingtonpost.com/news/the-intersect/wp/2015/11/16/how-intemet-hoaxers- tricked-the-world-into-believing-this-random-sikh-guy-was-a-paris-terrorist/.

4. Robert Fox, "News Track: Everybody Must Get Cloned," Communications of the ACM, Aug. 2000,43:8, p. 9. Lisa Guernsey, "Software Is Called Capable of Copying Any Human Voice," New York Times, July 31,2001, pp. Al, C2.

5. Adrian Chen, "The Agency," The New York Times Magazine, June 2, 2015, www. nytimes.com/2015/06/07/magazine/the-agency.html?_r=0.

6. "Wikipedia: Size Comparisons," Wikipedia, en.wikipedia.org/wiki/Wikipedia:Size_ comparisons; www.britannica.com.

7. Jan Lorenz, Heiko Rauhut, Frank Schweitzer, and Dirk Helbing, "How Social Influence Can Undermine the Wisdom of Crowd Effect," Proceedings of the National Academy of Sciences, May 10, 2011, www.pnas.org/content/early/2011/05/10/1008636108. full.pdf. James Surowieki, The Wisdom of Crowds, Anchor, 2005. A course on deci sion making taught by Michael Roberto and an article by Jonah Lehrer led me (SB) to these ideas and references.

Notes 407

8. Joseph Rago, "The Blog Mob," Wall Street Journal, Dec. 20, 2006, p. A18. 9. Examples include: American Library Association, "Using Primary Sources on the

Web," www.ala.org/rusa/sections/history/resources/primarysources; Johns Hopkins University library, "Evaluating Information Found on the Internet," guides.library. jhu.edu/evaluatinginformation; and University of California, Berkeley, library, "Evaluating Web Pages: Techniques to Apply & Questions to Ask," guides.lib.berke- ley.edu/evaluating-resources.

10. Jonah Lehrer, "When We're Cowed by the Crowd," Wall Street Journal, May 28,2011, online.wsj.eom/article/SB10001424052702304066504576341280447107102.html.

11. From Microsoft's explanation of its policy, quoted in Mark Goldblatt, "Bowdlerized by Microsoft," New York Times, Oct. 23,2001, p. A23, www.nytimes.com/2001/10/23/ opinion/bowdlerized-by-microsoft. html.

12. Eli Pariser, The Filter Bubble: What the Internet Is Hiding from You, Penguin Press 2011.

13. Jeffrey Gottfried and Elisa Shearer, "News Use Across Social Media Platforms 2016," Pew Research Center, www.joumalism.org/2016/05/26/news-use-across- social-media-platforms-2016/. Georgia Wells, "Facebook's 'Trending' Feature Exhibits Flaws Under New Algorithm," Wall Street Journal, Sept. 6, 2016, www.wsj.com/articles/facebooks-trending-feature-exhibits-flaws-under-new- algorithm-1473176652. "YouTube and PragerU," Wall Street Journal (editorial), Oct. 30, 2016, www.wsj.com/articles/youtube-and-prageru-1477866319. Max Readj "Donald Trump Won Because of Facebook," New York Magazine, Nov. 9, 2016, nymag.com/selectall/2016/ll/donald-trump-won-because-of-facebook.html. Mike Isaac, "Facebook, in Crosshairs After Election, Is Said to Question Its Inffuence," New York Times, Nov. 12,2016, www.nytimes.com/2016/11/14/technology/facebook- is-said-to-question-its-inffuence-in-election.html.

14. James A. Evans, "Electronic Publication and the Narrowing of Science and Scholarship," Science, July 18, 2008 (Vol. 321, no. 5887, pp. 395-399), www.sciencemag.org/coii- tent/321/5887/395.abstract. I (SB) learned of this article from an article by Jonah Lehrer.

15. Isaac, "Facebook, in Crosshairs after Election." 16. Barry Bearak, "Pakistani Tale of a Drug Addict's Blasphemy," New York Times, Feb

19,2001,pp.Al,A4. 17. Peter L. Bernstein, Against the Gods: The Remarkable Story of Risk, John Wiley &

Sons, 1996, p. 16. 18. Amanda Bennett, "Strange 'Science': Predicting Health-Care Costs," Wall Street

Journal, Feb. 7, 1994, p. Bl. 19. Cynthia Crossen, "How 'Tactical Research' Muddied Diaper Debate," Wall Street

Journal, May 17, 1994, pp. Bl, B9. 20. Julia Angwin, Jeff Larson, Surya Mattu, and Lauren Kirchner, "Machine Bias," Pro-

Publica, May 23, 2016, www.propublica.org/article/machine-bias-risk-assessments- in-criminal-sentencing.

21. A much earlier version of this section appeared in Sara Baase, "Social and Legal Issues," a chapter in An Invitation to Computer Science by G. Michael Schneider and Judith L. Gersting, West Publishing Co., 1995. (Used with permission.)

22. T. F. Stocker et al, "2013: Technical Summary," in Climate Change 2013: The Physi cal Science Basis, Intergovernmental Panel on Climate Change, Cambridge Univer sity Press, p. 37, www.climatechange2013.org/images/report/WGlAR5_TS_FINAL.

408 Chapter 7 Evaluating and Controlling Technology

pdf. Christopher S. Watson et at, "Unabated Global Mean Sea-Level Rise Over the Satellite Altimeter Era," Nature Climate Change, 5, 565-568, May 11, 2015, www. nature.coiTi/nclimate/joumal/v5/n6/full/nclimate2635.html. NASA, Global Climate Change; Sea Level, climate.nasa.gov/vital-signs/sea-level/.

23. The IPCC reports (published by Cambridge University Press): T. F. Stocker et ai, Climate Change 2013: The Physical Science Basis; S. Solomon et ai, eds.. Climate Change 2007: The Physical Scientific Basis, 2007 (Technical Summary at ipcc-wgl.ucar.edu/wgl/wgl-report.html); J. T. Houghton et ai, eds.. Climate Change 2001: The Scientific Basis, 2001; J. T. Houghton et ai, eds.. Climate Change 1995: The Science of Climate Change, 1996; J. T. Houghton, B. A. Callander, and S. K. Varney, eds.. Climate Change 1992: The Supplementary Report to the IPCC Scientific Assessment, 1992; J. T. Houghton, G. J. Jenkins, and J. J. Ephraums, eds.. Climate Change: The IPCC Scientific Assessment, 1990. Various IPCC reports are available at www.ipcc.ch/publications_and_data/publications_and_data_reports. shtml. I (SB) also used a large variety of other books and articles for background.

24. T. F. Stocker et ai, "2013: Technical Summary," p. 50 and p. 51. 25. One reason why this distinction is important is that temperature records for large areas

of the northern hemisphere showed a larger rise in the nighttime winter lows than in the daytime summer highs, a potentially benign or beneficial form of warming.

26. D. L. Albritton et ai, "Technical Summary," in Houghton, Climate Change 2001, pp. 21-83; see p. 49.

27. Gregory Flato et ai, Chapter 9: Evaluation of Climate Models, in Stocker, Climate Change 2013, p. 817. The issue of clouds is mentioned in several places in the reports. Solomon, "Technical Summary," Climate Change 2007, p. 70. "Greenhouse Gases Frequently Asked Questions," National Oceanic and Atmospheric Adminis tration National Climatic Data Center, www.ncdc.noaa.gov/oa/climate/gases.html. Long-term projection: Stocker et ai, "2013: Technical Summary," p. 81.

28. Stocker et ai, "2013: Technical Summary," p. 69. 29. Flato, Chapter 9: Evaluation of Climate Models, p. 824. 30. Stephen Schneider, quoted in Jonathan Schell, "Our Fragile Earth," Discover, Oct.

1989, pp. 44-50. 31. Stocker, "2013: Technical Summary," p. 75. 32. David J. Frame and Daithi A. Stone, "Assessment of the First Consensus Prediction

on Climate Change," Nature Climate Change, 3,357-359 (2013), Figure 1: Changes in global mean temperature over the 1990-2010 period, www.nature.com/nclimate/ joumal/v3/n4/fig_tab/nclimate 1763_Fl.html. National Oceanic and Atmospheric Administration, National Climatic Data Center, "State of the Climate Global Analy sis Annual 2011," Dec. 2011, www.ncdc.noaa.gov/sotc/global/2011/13.

33. 2007 projections: Solomon, "Technical Summary," Climate Change2007,Tab\eTS.6, p. 70. The 0.05°C figure (for 1998-2012): IPCC, "Climate Change 2014 Synthesis Report Summary for Policy Makers," pp. 3—4, www.ipcc.ch/pdf/assessment-report/ ar5/syr/AR5_SYR_FINAL_SPM.pdf. The 0.07°C figure (for 1999-2008): J. Knight et ai, "Do Global Temperature Trends Over the Last Decade Falsify Climate Predic tions?" pp. 22-23, within T. C. Peterson and M. O. Baringer, eds., "State of the Climate in 2008," Bulletin of the Meteorological Society, 90, Aug. 2009, 1-196, journals.ametsoc.org/doi/pdf/10.1175/BAMS-90-8-StateoftheClimate. The hiatus: Stocker, "2013: Technical Summary," p. 37, p. 67.

Notes 409

34. Stephen Moore, 'The Coming Age of Abundance," in Ronald Bailey, ed.. The True State of the Planet, Free Press, 1995, p. 113.

35. Interview with the Luddite" (Kevin Kelly, interviewer). Wired, June 1995, pp. 166-168, 211-216 (see pp. 213-214).

36. Alexandra Eyle, "No Time Like the Co-Present" (interview with Neil Postman), NetGuide, July 1995, pp. 121-122. Richard Sclove and Jeffrey Scheuer, "On the Road Again? If Information Highways Are Anything Like Interstate Highways— Watch Out!' in Rob Kling, ed.. Computerization and Controversy: Value Conflict and Social Choices, 2nd ed.. Academic Press, 1996, pp. 606-612.

37. Kirkpatrick Sale, Rebels Against the Future: The Luddites and Their War Against the Industrial Revolution: Lessons for the Compw/er Age, Addison-Wesley, 1995, p. 257.

38. Jerry Mander, In the Absence of the Sacred: The Failure of Technology and the Sur vival of the Indian Nations, Sierra Club Books, 1991, p. 61.

39. Neil Postman, Technopoly: The Surrender of Culture to Technology, Alfred A. Knopf 1992, p. 119.

40. Eyle, "No Time Like the Co-Present." 41. Harvey Blume, "Digital Refusnik" (interview with Sven Birkerts), Wired, May 1995,

pp. 178-179. Kelly, "Interview with the Luddite." 42. From a study by sociologist Claude Fisher, reported in Charles Paul Freund, "The

Geography of Somewhere," Reason, May 2001, p. 12. 43. Postman, Technopoly, p. 15. 44. See Jane Jacob's classic The Economy of Cities, Random House, 1969. 45. Postman, Technopoly, p. 6. The Freud quote is from Civilization and Its Discontent

(e.g., the edition edited and translated by James Strachey, W. W. Norton, 1961, p. 35). 46. John Davis, quoted in Sale, Rebels Against the Future, p. 256. 47. Peter Applebome, "A Vision of a Nation No Longer in the U.S.," New York Times,

Oct. 18, 2007, www.nytimes.com/2007/10/18/nyregion/l 8towns.html. Sale, Rebel's Against the Future, p. 257.

48. Joanna Stem, "Smart Tampon? The Intemet of Every Single Thing Must Be Stopped," Wall Street Journal, May 25, 2016, www.wsj.com/articles/smart-tampon- the-intemet-of-every-single-thing-must-be-stopped-1464198157.

49. Sclove and Scheuer, "On the Road Again?" 50. The quotes are from Kelly, "Interview with the Luddite," p. 214 and p. 213. Sale

expresses this point of view also in Rebels Against the Future, p. 213. 51. Sale, Rebels Against the Future, p. 256. 52. This dichotomy has always struck me (SB) as strange, because it almost suggests that

humans are alien creatures who arrived on earth from somewhere else. We evolved here. We are part of nature. A human's house is as natural as a bird's nest, though, unlike birds, we have the capacity to build both ugly and beautiful things.

53. Martin V. Melosi, Garbage in the Cities: Refuse, Reform, and the Environment: 1880—1980, Texas A&M University Press, 1981, p. 24-25.

54. Ian Hacking, The Emergence of Probability, Cambridge University Press, 1975, p. 108. C. P. Snow, "The Two Cultures and the Scientific Revolution," in The Two Cultures: And a Second Look, Cambridge University Press, 1964, pp. 82-83. The population data are from National Center for Health Statistics, Centers for Disease Control and Prevention, www.cdc.gov/nchs/fastats/life-expectancy.htm; Global Health Observatory, World Health Organization, www.who.int/gho/mortality_

410 Chapter 7 Evaluating and Controlling Technology

burden_disease/life_tables/situation_trends/en/; Health, United States, 2010, Table 22, p. 134, National Center for Health Statistics, Center for Disease Control, www. cdc.gov/nchs/data/hus/huslO.pdf; and from the United Nations, reported in Nicholas Eberstadt, "Population, Food, and Income: Global Trends in the Twentieth Century, pp. 21, 23 (in Bailey, The True State of the Planet) and in Theodore Caplow, Louis Hicks, and Ben J. Wattenberg, The First Measured Century: An Illustrated Guide to Trends in America, AEI Press, 2001, pp. 4—5. Nonvehicular accidental deaths declined from 72 per 100,000 people in 1900 to 19 per 100,000 people in 1997 (Caplow et ai. The First Measured Century, p. 149).

55. Moore, "The Coming Age of Abundance," p. 119. Eberstadt, "Population, Food, and Income," p. 34. Family income spent on food: Stephen Moore and Julian L. Simon, It's Getting Better All the Time: The 100 Greatest Trends of the 20th Century, Cato Institute, 2000, p. 53, and U.S. Department of Agriculture Economic Research Service, "Food CPI, Prices and Expenditures: Food Expenditure Tables," Table 7, accessible at www.ers.usda.gov/data-products/food-expenditures.aspx. Ronald Bailey, "Billions Served" (interview with Norman Borlaug), Reason, Apr. 2000, pp. 30-37. Julian L. Simon, "The State of Humanity: Steadily Improving," Cato Policy Report, Sept./Oct. 1995,17:5, pp. 1, 10-11,14-15.

56. Arman Shehabi et ai, "United States Data Center Energy Usage Report," Law rence Berkeley Laboratory, 2016, eta.lbl.gov/publications/united-states-data- center-energy-usag. Steve Hargreaves, "The Internet: One Big Power Suck, CNN Money, May 9, 2011, money.cnn.eom/2011/05/03/technology/intemet_electricity/ index.htm.

57. Optical fiber: Ronald Bailey, ed.. Earth Report 2000: Revisiting the True State of the Planet, McGraw Hill, 2000, p. 51.

58. William M. Bulkeley, "Information Age," Wall Street Journal, Aug. 5, 1993, p. Bl. "Newstrack" ("Claims to Fame"), Communications of the ACM, Feb. 1993, p. 14. Verti cal Research Partners (verticalresearchpartners.com), reported in Jennifer Levitz, 'Tissue Rolls to Mill's Rescue," Wall Street Journal, Feb. 16,2012, p. A3. U.S. Postal Service.

59. United Nations, "E-Commerce and Development Report 2001," quoted in Frances Williams, "International Economy & the Americas: UNCTAD Spells Out Benefit of Internet Commerce," Financial Times, Nov. 21,2001.

60. Most of the data in this paragraph and the next one come from polls and studies by Pew Research Center, Forrester Research, Luntz Research Companies, Ipsos-Reid Corporation, Nielsen//NetRatings, the U.S. Commerce Department, and others, reported in various news media. Susannah Fox and Gretchen Livingston, Latinos Online," Pew Research Center, Mar. 14, 2007, pewresearch.org/pubs/429/latinos- online. Jon Katz, "The Digital Citizen," Wired, Dec. 1997, pp. 68-82, 274-275.

61. See the note above.

62. Lee Rainie and Katheryn Zickuhr, "Always on Connectivity," Aug. 26, 2015 www. pewinternet.org/2015/08/26/chapter- 1-alway s-on-connectivity/.

63. Micah Singleton, "The FCC Has Changed the Definition of Broadband," The Verge, Jan. 29, 2015, www.theverge.com/2015/1/29/7932653/fcc-changed-definition- broadband-25mbps.

64. "Internet Users," www.intemetlivestats.com/intemet-users/. "Human Develop ment Report 2015," Chapter 3, United Nations Development Programme, report. hdr.undp.org. "Increased Competition Has Helped Bring ICT Access to Billions,"

Notes 411

United Nations International Telecommunication Union, Jan. 2011, www.itu.int/net/ pressoffice/stats/2011/01/#. V_uHIneZPOY.

65. "Human Development Report 2015," Chapter 3, United Nations Development Pro gramme, report.hdr.undp.org.

66. Jacob Poushter, "Smartphone Ownership and Internet Usage Continues to Climb in Emerging Economies," Pew Research Center, Feb. 22, 2016, www.pewglobal. org/2016/02/22/smartphone-ownership-and-intemet-usage-continues-to-climb-in- emerging-economies/. "BilUons of People in Developing World Still Without Internet Access, New U.N. Report Finds," United Nations, Sept. 21, 2015, www.un.org/apps/ news/story.asp?NewsID=51924#.WAfmD_RjKOO. Jacob Poushter, "Smartphone Own ership Rates Skyrocket in Many Emerging Economies, but Digital Divide Remains," Pew Research Center, Feb. 22, 2016, www.pewglobal.org/2016/02/22/smartphone- ownership-rates-skyrocket-in-many-emerging-economies-but-digital-divide-remains/.

67. Marianne Lavelle, ''Five Surprising Facts About Energy Poverty," National Geo graphic, May 30, 2013, news.nationalgeographic.com/news/energy/2013/05/ 130529-surprising-facts-about-energy-poverty/.

68. Ben Lefebvre, "What Uses More Electricity: Liberia, or Cowboys Stadium on Game Day? Wall Street Journal, Sept. 13, 2013, blogs.wsj.com/corporate-intelligence/ 2013/09/13/what-uses-more-electricity-liberia-or-cowboys-stadium-on-game-day.

69. Euan McKirdy, "UNHCR Report: More Displaced Now than after WWII," CNN, June 20, 2016, www.cnn.eom/2016/06/20/world/unhcr-displaced-peoples-report/.

70. One Laptop per Child: one.laptop.org. Ruy Cervantes et ai, "Infrastructures for Low Cost Laptop Use in Mexican Schools," Proceedings of the 2011 Annual Conference on Human Factors in Computing Systems, dl.acm.org/citation.cfm?id=1979082.

71. Eric Bellman and Aditi Malhotra, "Why the Vast Majority of Women in India Will Never Own a Smartphone," Wall Street Journal, Oct. 13, 2016, www.

wsj.com/articles/why-the-vast-majority-of-women-in-india-will-never-own-a- smartphone-1476351001. Facebook data: Simon Kemp, "Digital in APAC 2016," We Are Social, Sept. 6, 2016, wearesocial.com/uk/special-reports/digital-in- apac-2016. Cherie Blair, "Women «fe Mobile: A Global Opportunity," p. 16, www. gsma.com/mobilefordevelopment/wp-content/uploads/2013/0 l/GSMA_Women_ and_Mobile-A_Global_Opportunity.pdf. Newley Pumell, "How Google's Bicycle- Riding Tutors Are Getting Rural Indian Women Online," Wall Street Journal, Oct. 3,2016, blogs. wsj.com/indiarealtime/2016/10/03/how-googles-bicycle-riding- internet-tutors-are-getting-rural-indian-women-online/.

72. Sale, Rebels Against the Future, p. 210. 73. Postman, Technopoly, p. 7. 74. Kelly, "Interview with the Luddite." 75. Bill Richards, "Doctors Can Diagnose Illnesses Long Distance, to the Dismay of

Some," Wall Street Journal, Jan. 17, 1996, pp. Al, A10. 76. Richards, "Doctors Can Diagnose Illnesses Long Distance." 77. Peter J. Denning, "The Internet After 30 Years," in Dorothy E. Denning and Peter J.

Denning, eds.. The Internet Besieged, Addison Wesley, 1998, p. 20. 78. Donald A. Norman, Things That Make Us Smart: Defending Human Attributes in the

Age of the Machine, Addison-Wesley, 1993, p. 190. 79. Matt Novak, "7 Famous Quotes About the Future That Are Actually Fake,"

Gizmodo, Sept. 8,2014, paleofuture.gizmodo.com/7-famous-quotes-about-the-future-

412 Chapter 7 Evaluating and Controlling Technology

that-are-actually-fake-1631236877. Novak reports that von Neumann's statement is often quoted without the second half.

80. Joseph Weizenbaum, Computer Power and Human Reason: From Judgment to Calculation, W. H. Freeman and Company, 1976, pp. 270-272.

81. Edison; Thomas Edison, "The Dangers of Electrical Lighting," The Electrical Engi neer, Volume 8, 1899, page 518 (quote is on page 520). Zanuck: George P. Custen, Twentieth Century's Fox: Darryl F. Zanuck and The Culture of Hollywood, Basic Books, 1997. Popular Mechanics, Mar. 1949, p. 258. RCA: Thomas Petzinger Jr., "Meanwhile, from the Journal's Archives," Wall Street Journal, Jan. 1, 2000, p. R5. Cooper: Peter Grier, "Really Portable Telephones: Costly, But Coming?", Christian Science Monitor, Apr. 15, 1981, www.csmonitor.com/1981/0415/041506. html. Metcalfe: Bob Metcalfe, "Predicting the Internet's Catastrophic Collapse and Ghost Sites Galore in 1996," InfoWorld, Dec. 4, 1995, p. 61 (found in books.google. com via search). David Pogue, "Pogue's Posts: iPhone Rumors," New York Times, Sept. 27, 2006, pogue.blogs.nytimes.com/2006/09/27/27pogues-posts-3/?_r=0. Ballmer: David Lieberman, "CEO Forum: Microsoft's Ballmer Having a 'Great Time'," USA Today, Apr. 30, 2007. More information about some of these predic tions appears in Kathy Pretz, "Five Famously Wrong Predictions About Technology," The Institute, IEEE, Dec. 19, 2014, theinstitute.ieee.org/ieee-roundup/members/ achievements/five-famously-wrong-predictions-about-technology.

82. Ray Kurzweil, The Singularity Is Near: When Humans Transcend Biology, Viking, 2005. Hans Moravec, Robot: Mere Machine to Transcendent Mind, Oxford Univer sity Press, 2000. Vernor Vinge, "The Coming Technological Singularity: How to Sur vive in the Post-Human Era," presented at the VISION-21 Symposium (sponsored by NASA Lewis Research Center and the Ohio Aerospace Institute), Mar. 30-31, 1993, www-rohan.sdsu.edu/faculty/vinge/misc/singularity.html.

83. Rodney Brooks, "Toward a Brain-Internet Link," Technology Review, Nov. 2003, www.technologyreview.com/Infotech/13349/.

84. "Superhuman Imagination," interview with Vemor Vinge by Mike Godwin, Reason, May 2007, pp. 32-31.

85. Bill Joy, "Why the Future Doesn't Need Us," Wired, Apr. 2000, www.wired.com/ 2000miioy-2l.

86. Virginia Postrel, "Joy, to the World," Reason, June 2000, reason.com/archives/ 2000/06/01/joy-to-the-world.

87. This statement has been attributed to both Neils Bohr and Albert Einstein; we could not find a reliable source for either.

88. Jen Schradie, "The Digital Production Gap: The Digital Divide and Web 2.0 Collide," Poetics, Vol. 39, No. 2, Apr. 2011, pp. 145—168.