Image Credit: F. E. Guerra-Pujol
The New Zealand flag referendum was decided using an instant run-off voting procedure. Under this system of preference voting, the voters rank the choices in order of preferred alternatives. Notice how voting occurs over several stages or rounds and how the choice with the fewest number of votes is eliminated during each round. Here is a reddit thread on this particular vote.
We converted our traditional Christmas tree into an “NFL playoffs tree” after Three Kings’ Day (we completed this makeover while the family was sleeping). Now that the Super Bowl is done, my wife wants me to take down our tree. I, however, want to convert it into a St Valentine’s Tree. Who wins?
Save me!
In our previous posts (here and here), we revisited two of our research papers–one on range voting; the other on the Turing Test–and created alternate legal universes in which jury trials were decided using a range voting procedure or some form of Alan Turing’s “imitation game.” In this post, we shall discuss our 2011 peer-reviewed paper “A Bayesian Model of the Litigation Game” published in the European Journal of Legal Studies. Instead of creating an alternate legal universe (like we did in our previous posts), our Bayesian litigation paper models the existing legal system as is, warts and all. Specifically, we developed a Bayesian model of criminal and civil litigation, a model that is relevant to the central question posed in “making a Murderer”: how confident are you in Steven Avery’s guilt? Our Bayesian model includes a scenario in which the outcome of a trial is purely random (like a coin toss) and in which the moving party is “risk-loving” (i.e. in which the prosecutor is only 60% confident the defendant is guilty). Unfortunately for Mr Avery, the surprising result about our Bayesian model is that even in this random, risk-loving scenario, the posterior probability that the defendant is, in fact, guilty is pretty high.
Painting by S. Uchii
In our previous blog post, we applied the concept of “range voting” to jury trials. Today, we will discuss our 2012 paper “The Turing Test and the Legal Process” (published in volume 21 of the journal of Information & Communication Technology Law) and apply the Turing Test idea to jury trials. The original Turing Test refers to a simple game proposed by the great computer scientist Alan Turing (see video below). In brief, the game, in its original conception, involves three players: a man (player A), a woman (player B), and an interrogator (player C), who may be of either gender. The interrogator is allowed to put questions in writing to players A and B, and based only on the written responses provided by A and B, the interrogator must guess their true genders, or in Turing’s own words: “the object of the game for the interrogator is to determine which of the other two is the man and which is the woman.” Notice, then, the object of player A, the man, in Turing’s game is to deceive or fool the interrogator about the truth of his gender (and about the truth of the other player’s gender as well). Now consider a jury trial, like Steven Avery’s murder case in “Making a Murderer.” One of the things we did not like about Mr Avery’s legal strategy was his decision not to testify at trial, a common strategy in most criminal cases. But what would happen if criminal defendants were required to play a Turing game? That is, what would happen if the Turing Test were applied to jury trials? In other words, imagine an alternate legal universe in which player A assumes the role of the moving party (i.e., the prosecutor); player B, the role of the defendant; and player C, the judge or jury. In this alternate legal universe, the interrogator would be allowed to put questions directly to the parties in order to more accurately guess whether player B has committed a crime or other wrongful act or not. Although such a game may sound strange when applied to a legal dispute, isn’t such a “Turingesque” procedure more likely to generate the truth rather than the current criminal justice system, which encourages defendants not to testify?
Hey, what’s up? For our part, we’ve just finished watching season 1 of the amazing Netflix documentary series Making a Murderer, which shows beyond a reasonable doubt how one criminal suspect, Steven Avery, was framed (not once, but twice) by the Manitowoc County Sheriff’s Department. Also, for what it’s worth, several of our recent research papers are very relevant to the issues raised in the series. In this blog post, we will discuss our 2015 paper “Why don’t juries try ‘range voting’” published in volume 51 of the Criminal Law Bulletin. Briefly, instead of requiring jurors to vote all-or-nothing, i.e. “guilty” or “not guilty,” why not replace this binary tradition with a more nuanced range voting procedure. Specifically, why not let jurors score or rate the prosecution’s case on a scale of 0 to 10. Under our range voting proposal, the highest possible score the prosecution could receive would be a perfect 120, while the lowest possible score would be 0, and the defendant would be found guilty only if the sum of the juror’s individual scores exceed a certain threshold, say 100.
Now, let’s apply our alternative range voting procedure to the Avery murder trial depicted in “Making a Murderer.” In the series finale, we learn that two of the jurors in the Avery case were undecided at the start of deliberations; three jurors were ready to convict, and the remaining seven initially had reasonable doubts. Accordingly, the two undecided jurors could have assigned a “5” to the prosecution’s case, the mid-point between 0 and 10. By contrast, each of the three pro-conviction jurors could have rated the prosecution’s case a 9 if they were 90% certain of the defendant’s guilt, an 8 if they were only 80% certain, and so on. Lastly, each one of the seven reasonable-doubt jurors could have scored the prosecution’s case a 1 if they were 10% certain of the defendant’s guilt, a 2 if they were only 20% certain, and so on. Once each juror assigns a score or rating to the prosecution’s case, they would then add up all the scores, and Avery would have been declared guilty only if the sum of all the juror’s scores exceeded the threshold value.
How confident are you in the prosecution’s case?
That is a new feature from the Open Syllabus Project, an online database of university syllabi. (What a great idea, by the way!) Last month’s featured syllabus, which is just one page long (!!!), is for Professor Kieran Healy’s graduate-level course “Social Theory Through Complaining.” (Dr Healy teaches sociology at Duke.) Here is the course description:
This course is an intensive introduction to some main themes in social theory. It is required of first-year Ph.D. students in the sociology department. Each week we will focus on something grad students complain about when they are forced to take theory. You are required to attend under protest, write a paper that’s a total waste of your time, and complain constantly. Passive-aggressive silence will not be sufficient for credit.
I think we would ace this course!
Via Cliff Pickover’s entertaining and educational Twitter timeline, we discovered this beautiful essay by Evelyn Lamb, a promising postdoc at the University of Utah. Dr Lamb describes the fascinating and paradoxical topology of a strange surface–the Möbius strip–a surface with only one side and only one boundary. Among many other things we did not know is this: “You may have heard of the four-color theorem: any map can be colored using four distinct colors so that no bordering countries share a color. This theorem is not quite true as stated. We need to specify that the map is on a sphere or plane. Different surfaces have different ___-color map theorems, and for the Möbius strip, it’s the six-color map theorem.” Bravo!
Credit: Evelyn Lamb
For reasons that are obscure to us, the State of Iowa holds the first presidential primary in the nation every four years. (Shouldn’t the first presidential primary vote be allocated at random to a different State every four years?) This year, the Iowa Caucus took place on 1 February 2016. Aside from the outcome of the caucuses, it is also being reported (see here, for example) that a total of six “county delegates” were allocated to Hillary Clinton by six separate coin tosses and that Secretary Clinton won all six coin tosses! Although such an outcome appears highly improbable, since there is only a 1-in-64 (or a 1.56%) chance of all six coin flips going Clinton’s way, scientist Ethan Siegel explains in this informative essay that the true probability of one candidate winning all six coin tosses is in reality 3.12%:
Sure, there might have only been a 1.56% chance that Clinton would win all six, but those odds aren’t all that long, especially when you consider that there’s also a 1.56% chance that Sanders could’ve won all six, for a total chance of 3.12% that someone would have won all six. Three percent may not be a lot, but it’s not that small either: if you had a three percent chance of getting run over the next time you crossed the street, you just might think twice before doing so.
More importantly, while we’re on the subject of randomness, the voters in Iowa have a pretty bad track record at predicting the eventual nominee (sorry, Senator Cruz). According to Wikipedia (emphasis added), “Since 1972, the Iowa caucuses have had a 43% success rate at predicting which Democratic candidate … and a 50% success rate at predicting which Republican candidate … will go on to win the nomination of their political party [for president] …” In other words, with respect to the Republican candidates, the results of the Iowa caucuses are historically no better than random, like a coin toss! And with respect to the Democratic candidates, in a two-man race you’d have a better chance of predicting the eventual nominee by flipping a coin.
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