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The Lure (and Lore) of Big Data: Beware of Big Data Bigfoot!

“This is a world where massive amounts of data and applied mathematics replace every other tool that might be brought to bear. Out with every theory of human behavior…Who knows why people do what they do? The point is they do it, and we can track and measure it with unprecedented fidelity. With enough data, the numbers speak for themselves.

There is now a better way. Petabytes allow us to say: ‘Correlation is enough.’ We can analyze the data without hypotheses about what it might show.”

The Lore…

Types of Business Data

Transaction data1

Reference data2

Master data3

Metadata4

‘Big Data’ data5

Transactions, purchases, business records, etc.

Categorization, classification, lookup data, etc.

Subject-specific, links all company-specific data

Data about data (what, where, why, when, how)

It’s just data…it becomes “big” when it gains

Volume – massive amounts Velocity – speed collected Variety – extreme heterogeneity

Big Data, Big Impact: How and Where?

What Does Big Data Promise?

Living Up to The Promise?

What Does Big Data Do?

What Does Big Data Do? Common “Algorithm” Tasks 1.Classification 2.Regression (aka predictive modeling) 3.Similarity matching 4.Cluster analysis 5.Co-occurrence analysis (aka association rule learning) 6.Profiling (aka neural networks) 7.Link prediction (aka network analysis) 8.Data reduction 9.Causal modeling

Machine Learning and Algorithms

ALGORITHM

Data

Output

$$ $

All AI, All of the Time?

“You cannot legitimately test a hypothesis on the same data that first suggested that hypothesis. The remedy is clear. Once you have a hypothesis, design a study to search specifically for the effect you now think is there. If the result of this test is statistically significant, you have real evidence at last.”

“Big Data Hubris”

“Assumption of Infallibility”

“It’s troubling enough that British teenager Molly Russell sought out images of suicide and self-harm online before she took her own life in 2017. But it was later discovered that these images were also being delivered to her, recommended by her favorite social media platforms. Her Instagram feed was full of them. Even in the months after her death, Pinterest continued to send her automated emails, its algorithms automatically recommending graphic images of self- harm, including a slashed thigh and cartoon of a young girl hanging. Her father has accused Instagram and Pinterest of helping to kill his 14-year-old daughter by allowing these graphic images on their platforms and pushing them into Molly’s feed.”

“Unlike a human examiner/judge, a computer vision algorithm or classifier has absolutely no subjective baggages [sic], having no emotions, no biases whatsoever due to past experience, race, religion, political doctrine, gender, age, etc., no mental fatigue, no preconditioning of a bad sleep or meal. The automated inference on criminality eliminates the variable of meta-accuracy (the competence of the human judge/examiner) all together.” (p. 2)

“...are a perfect match, and their agenda appears to be to create a political movement where Soros and his political machine and Clinton are two of the only major players. This is the first time Soros and Clinton have been caught on tape directly colluding in promoting the same false narrative. One of the key revelations in the leaked audio was Clinton's admission to a Russian banker that she knew about the Uranium One deal before it was approved by Congress. Clinton was shown sharing the same talking points that were originally drafted by a Fusion GPS contractor hired by an anti-Trump Republican donor. The leaked audio is the clearest evidence yet that the Clinton campaign and the Hillary Foundation colluded with Fusion GPS to manufacture propaganda against President Trump.”

Elon Musk and Sam Altman cofounded a research institute called OpenAI to make new AI discoveries and give them away for the common good.

AI system designed to learn the patterns of language (very accurate). But when researchers configured the system to generate text…

Type in the phrase: “Hillary Clinton and George Soros”…

“Tom Simonite does not keep it simple. He doesn’t give you enough info on a subject to make the reading of the book enjoyable. He has over 400 pages of footnotes, so that is a way of getting your work for a subject out of the way. And of course, you never really feel like the author has a clear vision of his subject. He does not give you enough details on how a group of people is going to come together to solve a problem or come about a solution to a problem. This book was so depressing to me, I can't even talk about it without feeling like I want to punch the kindle.”

Elon Musk and Sam Altman cofounded a research institute called OpenAI to make new AI discoveries and give them away for the common good.

AI system designed to learn the patterns of language (very accurate). But when researchers configured the system to generate text…

Prompted to write a 1-star review: “I hate Tom Simonite’s book”…

Proceedings of the 33rd Annual ACM Conference (2015)

Population = 27% female; Images = 11%

Population = 34% female; Images = 30%

Population = 91% female; Images = 97%

A Cautionary Tale…

A Cautionary Tale… “The Enlightenment sought to submit traditional verities to a liberated, analytic human reason. The internet’s purpose is to ratify knowledge through the accumulation and manipulation of ever expanding data. Human cognition loses its personal character. Individuals turn into data, and data become regnant.”

1. AI may achieve unintended results 2. In achieving intended goals, AI may

change human thought processes and human values

3. AI may reach intended goals, but be unable to explain the rationale for its conclusions

More Uplifting Quotes…

“Big data is the idea that a sufficiently large pile of horseshit will (with a probability of one) somehow contain a pony…”

~ Carl Bergstrom

“Big data is like teenage sex: everyone talks about it, nobody really knows how to do it, and everyone thinks everyone else is doing it, so everyone claims they are doing it…”

~ Dan Ariely