[MUSIC] So when we actually make decisions, how do we process all this information? Well, a very influential early theory of decision making, and one that still has a lot of influence today, is called expected utility theory. Expected utility theory, or EUT for short, was developed int he 19th century by two economists, Pascal and Bernoulli. They proposed that when we make decisions this is what we do. Consider all the possible options. Consider the outcomes of each option. Consider the values. That's the benefits and the costs of each outcome. Consider the probabilities of each outcome. Multiple the probability of each outcome by its value. Adopt the results across all the outcomes of an option. And finally, choose the option with the highest summed value. These all sounds very complicated, but it isn't really. Let's use an example to explain how it works. Imagine that you have just two options, to study a Coursera program entitled A Practical Guide to Managing People at Work, or not to study it. I know you've already made that choice, of course, so let's go back to the moment when you made the decision to study on this course. Let's assume that when you made the choice there were just two outcomes of each option. You believe that if you decided to do the course there would be just two possible outcomes, that you would find the course interesting and that you wouldn't learn anything useful. Of course, in reality, there are many more possible outcomes than this when you decided to take the course. But let's keep it simple and assume that there were only two outcomes. In the same way, let's also assume that you associated just two outcomes with the decision not to sign up for the course. The first is that you would have extra free time. And the second is that you would, in the end, waste this free time. Right. So we have to outcomes for each option. Now, let's put some values on the options. If we assign a value of plus ten to a really good outcome, and minus ten to a really bad outcome, we'll assume that the values you assign to finding a course interesting was seven. That's seven out of ten, because that would be very good for you. You assign a value of minus 6, on the other hand, to the outcome that you won't learn anything useful, because obviously that would be pretty bad. And let's you say assign values of plus 5 and minus 4 to the two possible outcomes of not signing up for the Coursera course. So now, we have two outcomes for each decision and a value for each outcome. Before we start processing this information and making a choice about what to do, we need one more type of information, the probability of each outcome. Of course, we don't generally know the exact probability of the outcomes of the decisions we make, but we can assign our own subjective probability. If I were to ask you how likely you are to be happy next December, you won't know for sure. But you could make a guess about it. That's what we generally do when we assess the probability that particular decision outcomes would occur. To assign a probability or likelihood to an outcome, we usually give it a value of between zero, meaning we are certain that it won't happen, and 1, meaning that we are certain it will happen. So, a probability of 0.5 would indicate that there is a 50% chance that something will happen. It's 50, 50. And a value of 0.8 would indicate that it has an 80% chance of happening. Okay, so let's assign some probabilities to our four outcomes here. We'll assume that you think it very likely that you'll find the course interesting. Let's give that a probability of 0.8, or 80%. But you also think that there is a 0.5 chance, that's 50% chance, that the things you learn won't be very useful. In the same way, you attach your own probabilities to the outcomes of not signing up for the course. Let's say 0.8 that you'll have more free time, and 0.9, or 90%, that if you have the free time you'll end up wasting it. Now, finally, we have all the information we need in order to make the decision in the way that Pascal and Bernoulli's expected utility theory says that we should. First, we multiply the value of each outcome by its probability. So, in the case of the outcome, I will find the Coursera program interesting, you multiply the value associated with it, 7, by the probability, 0.8. The result is 5.6 because 7 times 0.8 is 5.6. You do the same thing for the other three outcomes. The results are minus 3 for the things you learn not being useful. 4 for having more free time. A minus 3.6 for wasting your free time. We are almost there now. All that's left to do is to add up these values for each option. So for the option sign up for the Coursera program, the result is 2.6. And the option don't sign up for the Coursera program, the answer is 0.4. All we have to do now is choose the option with the highest number. As the option of signing up for the Coursera program at 2.6 has a higher value than not doing so at 0.4, the right choice, according to expected utility theory, is to sign up for Coursera. [MUSIC]