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Course Documents/PSY 540 Transcript for Cognitive Psychology Decision Making.docx

PSY 540 Transcript for Cognitive Psychology: Decision Making

[00:00] Music playing.

[00:11]: NICHOLAS NARDI: Dr. Nardi here. Back with another video. And in this video, we are going to talk about reasoning and decision making. Now you are faced with choices every day and you constantly have to make decisions. Researchers and, I would argue, psychologists would argue that most of our day is consumed by reasoning and decision making. Now, we often believe that our decisions are logical and then we make the right choices. However, we might not follow the standards of formal logic. So, in this video, we will cover what situations maybe cause us to act illogically and maybe which conditions do we deviate from logic.

[01:03]: Now you have to ask yourself: Are you more like Spock from Star Trek?

Captain Kirk: It’s logic Spock. Do you like that?

Nicholas Nardi: Or are you more like Captain Kirk? Think about that for a minute. Logical or emotional?

Spock: Your highly emotional reaction is most illogical.

Nicholas Nardi: Now, before we get into everything, I want to define some terms. Deductive reasoning. We refer to that as making arguments from general information to more specific information.

[01:39]: So back to my Spock example. If we know that Vulcans are logical and Spock is a Vulcan, then we can conclude that Spock is the logical.

Star Trek character: Logic. Logic. I’m sick to death of logic.

Nicholas Nardi: In contrast, inductive reasoning is argumentation from a specific instance to a more general relationship.

[02:05]: For example, in “A Scandal in Bohemia,” Sherlock Holmes reasons that Dr. Watson had recently been caught in a rainstorm because, well, he based it on his observation of his shoes. Holmes reasoned that several parallel cuts on the leather must have resulted from careless scraping of the mud from the sole, and the mud resulted from a recent torrential rainstorm. This series of reasoning is an example of inductive reasoning or making and evaluating arguments from specific information to general information.

[02:50]: Now back to deductive reasoning for a moment. Now deductive reasoning is making an evaluation of arguments following a logical set of rules or principles. Generally, there are two types of reasoning that have been the focus of psychologists and philosophers. The first type we’ll talk about is syllogistic, and the second type is conditional reasoning.

[03:16]: Now, I will briefly cover both of these here right now. Now, Aristotle developed the logical rules of syllogistic reasoning. Syllogistic reasoning is the process by which a conclusion follows necessarily from a series of premises statements. If the premises are true, then by the rule of deduction the conclusion must also be true as well. This is referred to as deductive validity of an argument.

[03:48]: In logical arguments syllogisms often take the following form. All As are Bs. That’s the first premise. All Bs are Cs. That’s the second premise. All As are Cs. That’s the conclusion. So the all is the quantifier. Other quantifiers include words like no, some, some or not, and many. The As, Bs, and Cs are things in the world, right? So we could talk about a concrete example here just in one second.

[04:20]: So, for example, all ants are insects. All insects are animals. All ants are animals. Now conditional reasoning, often referred to as prepositional reasoning, has a similar formal structure with the inclusion of connective words like if and then as part of the first premise. Other connective words include and, or, and not. But for simplicity, I won’t talk about these right now.

[04:51]: So conditional reasoning is sometimes referred to, as I said, propositional reasoning because of the connective words in the propositional statements. Propositional statements are those that are either true or false. For a decision of a propositional representation in language. In logical arguments, they are often stated in the form of similar to that used of syllogisms.

[05:17]: Generally, deductive reasoning involves understanding and representing the premises, combining these representations, and drawing a conclusion. Many theories have proposed to explain how we deductively reason. Now Roberts, the famous researcher, classifies these three general approaches as conclusion, identification, representation, explanations, and surface or heuristic approaches.

[05:48]: Now, if we talk about conclusion and interpretation approaches, these approaches propose that errors arise from general bias against making particular conclusions. For example, people may be reluctant to make no valid conclusion responses because they feel that it’s an uninformative conclusion. Another error may result because of the order of the terms can be reversed, called conversions in some premises, but not others. For example, some ants are insects and some insects are ants are logically equivalent. However, all ants are insects, and all insects are ants are not.

[06:33]: Now, if we talk about representation explanation approaches. Theories of this type focus on how we represent the arguments. The difficulty of an argument and the likelihood of making an error are the results of either incomplete information or incorrect representation of the argument. Reasoning that requires complex chains of rules places demands on working memory. The higher the demands, the more difficult the reasoning. Now, real world problems typically involve more uncertainty and incomplete information, which is difficult, if not impossible, to think through all possible reasoning steps.

[07:12]: Now one of these major differences across these theories is the kind of representation that is assumed. Surface approaches. Now surface approaches propose that reasoning relies primarily on general heuristics focused on the surface properties or the quantifiers in the argument, rather than on the reasoning analytically. For example, if the argument contains premises about universals all and no, then the conclusion probably is universal. Or if the argument contains a negative premise, no, some, or not, then the conclusion will be negative.

[07:51]: Now, researchers have also kind of taken a dual framework approach and they kind of look at this dual framework approach. And basically they say we have maybe two ways of thinking or two ways of reasoning. And they break it down to different systems.

[08:09]: Typically, system one processes are assumed to be largely automatic, rapid, and unconscious. And then they also talk about system two. And this by contrast, our processes are typically assumed to be controlled, slow, and often conscientious. So if system one is automatic, fast, and often unconscious way of thinking, it’s autonomous and efficient, requiring little energy or attention, but it’s prone to biases and systematic errors.

[08:39]: Conversely, system two is effortful, slow, and controlled way of thinking. It requires energy and cannot work without attention. But once engaged, has the ability to filter the instincts of system one. Now, I’ve talked mostly about deductive reasoning, and this has been the focus of pretty much this whole video. However, deductive reasoning is about absolute truth, which is rare in our day-to-day lives.

[09:07]: On the other hand, inductive reasoning examines the likelihood of conclusions being true rather than its absolute truth. This is something we do in everyday reasoning. It’s beyond your reasoning. You’re beyond our reasoning. Now, there are many forms of inductive reasoning, some of which are reviewed in this video and some are not. But what ties them all together is a cohesive set in which they all involve reasoning from specific data. So it’s based on both observation and knowledge to a broader generalization. As a result, these generate generation of new information.

[09:47]: Now, there are different types of inductive reasoning. There’s making analogies, and this is the type of thinking that probably relies on analogies. So you make analogies to kind of make comparisons.

Video clip speaker: It’s a stupid analogy. Oh, okay.

Nicholas Nardi: There’s also a categorical based induction, knowing that a property is true of a category. This leads members to conclude that the property is true for other category members. So if you know you can kind of make these reasoning across categories.

Video clip speaker: I made brownies. And I made cookies. Same category.

[10:21]: Nicholas Nardi: There’s causal reasoning, is the process of identifying causality. The relationship between a cause and its effect.

Video clip speaker: No effect.

Nicholas Nardi: There’s also hypothesis testing. Now, this is my favorite as being a researcher, as being a psychologist. Basically, what we do here is we test p value. So if you think back to your research, these are probability values. So with the probability, we assume that the null hypothesis is true. We start with the premise that the null hypothesis is true until we have information that may disprove that or disconfirm.

Video clip speaker: Interesting hypothesis.

[11:00]: Nicholas Nardi: And then we also have counterfactual thinking. And this is a concept in psychology that involves humans and their tendency to create possible alternatives to life events that have already occurred, something that is contrary to what has already happened. Evidence must be factual.

[11:19]: Now, at the end of the day, making decisions is about assessing and making choices between different options. Our days are filled with decisions. Some big, right? What to do with my life after I graduate? Which house should I buy? Or they can be small. Should I order a peanut butter and jelly sandwich for lunch? Do I need paper or plastic at the grocery store? As was the case with your self-assessment about your reasoning abilities, if you think about do you make deductive or inductive reasoning, we can also kind of talk about how we make decisions and the limitations based on our cognitive system.

[11:58]: Now, a couple of things to keep in mind when you’re making decisions is goals. Goals are a great thing to do. These are mental representations of the desired state of affairs. Good decisions are those that get us closer to our goals. Now, once you’ve set your goals, then you need to acquire information needed to make the decision. This information includes your options, the likelihood of different outcomes and the criteria used to make your decision. Once we have our goals and have assembled our information, we need to organize the information in a way that will be useful for making decisions.

[12:34]: Consider the common practice of making a list of pros and cons. Now, after collecting the information and organizing it to make comparisons, it’s time to actually choose an option. This is not always an easy task, and sometimes there’s no obvious correct choice. When we make decisions, we usually make our selections based on information, and we’re loaded with uncertainty.

[13:00]: And the last step in this decision-making model is often overlooked. We often overlook this, and we don’t spend much time on it. But there’s also kind of little research that examines this final phase. The general attitude is that if a decision has been made, then it’s time to move on. However, remember that we make our decisions every day. An important part of our cognitive processes is what we have in memory? Our past decisions impact later decisions. So interpreting our choices and evaluating what went wrong or right is also important when we talk about decision making.

Video clip speaker: Remember.

[13:39]: Nicholas Nardi: Finally, I will mention represent another way of kind of making decisions. And it’s based on heuristics. And with heuristics comes biases. The availability heuristic is a mental shortcut that relies on immediate examples that come into someone’s mind when they’re evaluating a topic, right?

[14:00]: So you might be able to think of a bunch of different examples and it might bias your thinking. For example, if you can imagine right now, shark attacks.

Video clip speaker: You’re going to need a bigger boat.

Nicholas Nardi: You might see a lot of shark attacks. You might have seen the movie, Jaws; you might have seen the movie Deep Blue where sharks are biting people. Then you might think, “Oh, my gosh, shark attacks are very likely.” However, the data says otherwise. But you can think of so many examples that you have an availability heuristic.

[14:28]: There’s also the framing effect that creeps in. And this is an example of a cognitive bias in which people react to a particular choice in different ways depending on how it’s presented, if you present it as a loss or a gain. So that covers all of our heuristics and potential biases. So remember, we’re not robots, right? We engage in multiple ways of making decisions. So I hope you learned something from this video. If you could think of more, if I’ve made mistakes, leave comments down below. Like, subscribe, share this video, and I’ll see you all in the next one. Take care. Bye-bye.