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ISS305 Michigan State Dishonesty and Future of Humankind Questions

ISS305 Michigan State Dishonesty and Future of Humankind Questions

Question Description

Please answer each question at least 300 words. Rubric is provided.

Q1: Dishonesty and the Future of Humankind

Do Ariely’s findings about dishonesty make you overall optimistic or pessimistic about human nature and society? On one hand, he finds that people can be tempted to cheat and steal on a small scale pretty easily. On the other hand, he finds that there is often a limit to the extent to which they do so. And yet he also finds that we are even more likely to steal, and to a greater extent, when tempted by something that isn’t cash, which is increasingly the case. And Ariely offers very little advice as to how to curb these propensities. So are we all doomed to endlessly take advantage of one another, or do Ariely’s studies give us reason to hope that we could structure our society in such a way that we’re generally on good behavior? What can you think of that might serve as a solution to our propensities toward dishonesty?

Q2: You’re Now Ariely

Now that you’ve had the opportunity to read about a number of Ariely’s experimental designs, choose one of his studies and think about how it might be conducted differently. That is, take one of Ariely’s ideas about passion, marketing and consumer behavior, social justice and deviance, or irrationality in general, and develop your own experimental design to test the behavioral mechanisms that Ariely seems to find in his respective study. How will you establish a control group and a treatment group? What will the treatment be? How will you measure the behavior of your subjects? How will you know that you have isolated the effects of your treatment and can rule out other potential factors? Would you predict that your findings will match those of Ariely’s study, or might they contradict Ariely’s findings?

Q3: The Power and Perils of Statistics

In your opinion, wherein lies the greatest potential benefit of statistical inference? That is, are the greatest advances and gains to be made within the field of medicine, economics, or some other field? Why this field? Name at least one specific benefit that your chosen field might bring in the near future with the help of statistics, and precisely how statistics can help. Next, wherein lies the greatest danger of the abuse of statistical inference? That is, in what field would such abuse have the worst consequences? (This may be either the same field whose potential advances you’ve already discussed, or a different field.) Again, why this field? Name a specific possible abuse of statistics that you think could lead the field’s research astray in such a way as to have such consequences.

Q4: Programmatic Self-Evaluation

Think about the kinds of program evaluations that would relate to your life, the comparisons that might be made between you as you are now and certain counterfactuals in which one of your characteristics is changed. For example, you are most likely seeking a college degree, but how would certain ‘dependent variables’ – like your life expectancy or your likely wealth at age 65 – be changed if you weren’t? Wheelan touches on this example, so come up with two different characteristics of your own life (ideally, the outcomes of some of the more important decisions that you’ve made in the past, like the decision to seek a degree), and imagine yourself without each of these characteristics (one at a time, of course, so as to isolate the effects of each). Don’t worry about how you would design a test of the effects of each characteristic – each ‘treatment’ – but think about what these effects might be. What might the significant differences be between yourself and each of your two counterfactuals, in terms of things like long-term health, long-term earnings, long-term happiness, etc.? For each of your two comparisons, make two suggestions as to what the ‘treatment effects’ of your two real-life characteristics might be. (You probably won’t be able to be very precise, but that’s okay.)

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