Headline, June 10 2022/ ''' '' STUDENTS PERSUASION STARTERS '' '''


 STARTERS '' '''

WELCOME TO THE WORLD OF BAYESIAN PERSUASION : Getting people to do what you want ........... Tommy James & the Shondells sang '' Crystal Blue Persuasion.'' Economists have their own shade of Bayesian. 

BAYESIAN PERSUASION AN IDEA ONLY A LITTLE more than a decade old that's being used to study phenomena as varied as advertising, the law, bond ratings and parking enforcement.

A working paper this month uses it to analyze political lies. The authors conclude that politicians will lie more when they know they're being fact-checked. [Finding a real-life example of that behavior is left as an exercise for the reader.]

Thomas Bayes was an 18th-century English statistician, philosopher and Presbyterian minister. He developed a statistical model for how to update your predictions in light of old and new knowledge.

Let's say you test positive for a rare, fatal disease. If the false positive rate is only 1 percent, you might start putting your affairs in order. But a Bayesian would incorporate, among other things, the prior knowledge of the rarity of the disease - say, one in a million people would get it - and conclude that the test result is probably wrong.

BAYESIAN PERSUASION is a technique that uses information rather than bribes or threats to get people to see the world differently and change their behaviour in desired ways. It assumes all people have prior beliefs about the world that they update as new information, such as a diagnostic test result, comes in.

There is a ''sender'' and a ''receiver.'' The goal for the sender is to share the information that will most effectively persuade the receiver to act in a certain way.

This week I spoke with Emir Kamenica, one of the two authors of ''Bayesian Persuasion,'' the 2009 paper that gave birth to the new field. When I got Mr. Kamenica on the phone, he had just finished teaching a class on the topic at the University of Chicago's Booth School of Business.

He gave me a hypothetical situation to illustrate the basic idea:

Imagine a wrongful death case where the judge wants to get the verdict right but the plaintiff just wants to win the case. It's a civil case so the standard of proof is simply the preponderance of evidence.

Let's say the judge and the plaintiff think there's a 30 percent chance the defendant is responsible for the wrongful death.

There's blood evidence from the person who caused the death and a blood sample from the defendant. The plaintiff could order DNA tests on the blood samples that would establish beyond doubt if the accused person is liable.

But the plaintiff can improve his chances of winning the case if instead just orders tests for blood type. Why?

Let's say the blood at the scene is Type A. If the defendant is liable, his blood will also be Type A. But even if he didn't do it, there's still about a 40 percent probability that his blood will be Type A, given the prevalence of that blood type in the population. That's a high rate of false positives.

Still, a rational judge who learns the defendant is Type A would conclude that this piece of evidence from the plaintiff raises the likelihood of the defendant's responsibility from 30 percent [before] to slightly more than 50 percent [after].

The blood test isn't conclusive by itself but it adds weight to the case against the defendant, who was already under some suspicion.

''The judge understands statistics, he understands prevalence, but we're getting him to rule against nearly twice as many people as are actually responsible,'' Mr.Kamenica said.

The courtroom scene shows the power of being able to control information that is conveyed. If the plaintiff were just spewing cheap talk, he would always simply claim guilt, but such empty claims would never provide any information to a rational judge. ''The ability to commit to what type of information will be generated is a powerful tool,'' Mr. Kamenica said.

NOW for some other applications of Bayesian persuasion :

The paper about lying politicians that came out this month is by Florian Ederer of the Yale School of Management and Weicheng Min of Yale's economics department.

Politicians would have no incentive to lie if fact-checkers caught 100 percent of their lies, the authors write, but if the probability of catching a lie is sufficiently low, a politician will compensate for the fact-checking by lying even more.

The sender [in this case, a politician] ''noises up the information environment,'' Mr. Ederer said in an interview.

[You might think that lying doesn't fit into a Bayesian persuasion framework, but Mr. Ederer says it can fit as long as the politician ''commits to sending a truthful or an untruthful message with a certain probability'' that can depend on the state of the world.]

The Honour and Serving of the Latest Global Operational Research on 'Getting people to do what you want, continues.'  The World Students Society thanks author Peter Coy. 

With respectful dedication to the Global Founder Framers of The World Students Society, Politicians, Grandparents, Parents, Students, Professors and Teachers of the world.

See Ya all prepare and register for Great Global Elections on The World Students Society - for every subject in the world : wssciw.blogspot.com and Twitter - !E-WOW! - The Ecosystem 2011 :

Good Night and God Bless

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