I suspect as a start that it would result in a smaller percentage of defendants being found guilty at trial.
I disagree. The most obvious reason is that were our system that efficient, prosecutorial behaviour would change.
But more significantly, a Bayesian processing system would not need to exclude relevant evidence. The only evidence it would exclude would (presumably) be that obtained in violation of the defendant's rights. By incorporating and accurately weighting certain forms of character and hearsay evidence that are not available to a jury, I believe one could prove many cases beyond a reasonable doubt that currently impossible (drug lords and mafia bosses, for example, would be rather easier to convict of something).
Guilty people getting off is, in general, not big news, unless the defendant or crime is already very high profile. Moreover, since the criminal cannot be retried under double jeopardy, no one really goes about examining the wrongfully freed. One can be freed after being wrongfully convicted, so there is some incentive to examine the wrongly convicted. (If you count the people who could be proven guilty to a Bayesian intelligence, but not to a jury, this is a much more significant problem).
In other words, you may well be right, but I think you need a lot more evidence to get to that conclusion. And that still requires prosecutorial behaviour to be exogenous, which is an unreasonable assumption.
I've tried to think about the problem of idealized Bayesian Justice before, but usually I start by replacing the judge with a robot, and then the jury, and then the lawyers, and then Congress and the Supreme Court and the entire Executive Branch, and pretty soon I've reinvented FAI badly or I find myself trying to rewrite the US Code in Python.
I think "idealized" might be too high a standard.
My question for Less Wrong: Just how innocent is Cameron Todd Willingham? Intuitively, it seems to me that the evidence for Willingham's innocence is of higher magnitude than the evidence for Amanda Knox's innocence.
In both instances, the prosecution case amounts to roughly zero bits of evidence. However, demographics give Willingham a higher prior of guilt than Knox, perhaps by something like an order of magnitude (1 to 4 bits). I am therefore about an order of magnitude more confident in Knox's innocence than Willingham's.
...Challenge question: What do
I would heartily suggest grave caution in having high confidence in conclusions based on media accounts. In this case, the forensic arson investigation was badly flawed. I don't know the other evidence well enough to speak, though I know as a loyal Bayesian, I could make an estimate of guilt. Still, I'd have very low confidence in that estimate, and it could be easily changed (as by reading the entire trial transcript.)
It's very difficult to see these assertions without at least a nod to Roger Keith Coleman's case. That case received a great deal of post-e...
As ever, both stories are studies in irrelevancy and emotional appeal.
Which probably reflects a good bit of what's wrong with the criminal justice system.
Though unscientific scientific testimony is also a serious problem, apparently also seen in this case.
What prior are you using for Knox? The pre-murder "chances a nice, pretty upper-middle class American girl would be involved in a murder in the next year" or the "chances the nice, pretty, upper-middle class American girl was involved in murder, given that her roommate was stabbed to death?
The major difference is going to end up being that Meredith Kercher was actually murdered and Willingham's children were not.
What is this supposed to teach us about rationality that we did not learn from the Amanda Knox case?
I don't think it is a good idea to invoke any sort of controversy without some specific novel point to make. I would not object were it just a thought experiment in an open thread, but good cause is necessary for a top-level post.
The prior probability of 0.13 is wrong. That would be correct if 13% of fires resulting in fatalities of children were intentionally set by the children's dad.
I think Bayesian justice would result in a larger percentage of defendants being found guilty at trial, because instead of "guilty beyond a reasonable doubt", the prosecution would only have to prove "expected value of conviction > expected value of no conviction".
EDIT: On the other hand, if someone committed an awful crime, but can convince you that they won't do it again; or if they might, but they pay a lot of taxes; let them go.
If the standard used is value to society, then if the defendant is judged to have no value to society, ...
What does an idealized form of Bayesian Justice look like?
To begin with "beyond reasonable doubt" needs to be replaced with "beyond X% certainty" where 100-X is whatever percent of innocent convictions we're comfortable with.
I think the coolest idea for justice systems that I've heard of (dunno its origin) is to have decisions done though prediction markets.
There's a couple ways I can see to keep it grounded to reality. The 'jury' (which would include people that think they can make money doing it) could not be given all of the evidence all the time, and their predictions would be checked (and their bets payed off) on the cases where they were withholding strong evidence.
There could also be two markets, and they have to predict the other juries verdict (possibly given more ev...
The evidence is important and neither Grann nor Jackson are very helpful.
A more thorugh review. I have also read the trial transcript and the police wtiness statement interviews.
"Cameron Todd Willingham: Another Media Meltdown", A Collection of Articles http://homicidesurvivors.com/categories/Cameron%20Todd%20Willingham.aspx
The evidence is important and neither Grann nor Jackson are very helpful.
A more thorugh review. I have also read the trial transcript and the police wtiness statement interviews.
"Cameron Todd Willingham: Another Media Meltdown", A Collection of Articles http://homicidesurvivors.com/categories/Cameron%20Todd%20Willingham.aspx
The "challenge question" is the most interesting part of the post. The article you linked to in that paragraph has a lot of implications for justice systems, namely that jurors need a better understanding of probability, especially as DNA fingerprinting and similar forms of forensic evidence become more and more precise. Though the article does point out how probability can be misinterpreted or skewed by both the defense and prosecution, jurors would be better prepared to assess such arguments if they had a better intuitive understanding of probability theory.
In 2004, The United States government executed Cameron Todd Willingham via lethal injection for the crime of murdering his young children by setting fire to his house.
In 2009, David Grann wrote an extended examination of the evidence in the Willingham case for The New Yorker, which has called into question Willingham's guilt. One of the prosecutors in the Willingham case, John Jackson, wrote a response summarizing the evidence from his current perspective. I am not summarizing the evidence here so as to not give the impression of selectively choosing the evidence.
A prior probability estimate for Willingham's guilt (certainly not a close to optimal prior probability) is the probability that a fire resulting in the fatalities of children was intentionally set. The US Fire Administration puts this probability at 13%. The prior probability could be made more accurate by breaking down that 13% of intentionally set fires into different demographic sets, or looking at correlations with other things such as life insurance data.
My question for Less Wrong: Just how innocent is Cameron Todd Willingham? Intuitively, it seems to me that the evidence for Willingham's innocence is of higher magnitude than the evidence for Amanda Knox's innocence. But the prior probability of Willingham being guilty given his children died in a fire in his home is higher than the probability that Amanda Knox committed murder given that a murder occurred in Knox's house.
Challenge question: What does an idealized form of Bayesian Justice look like? I suspect as a start that it would result in a smaller percentage of defendants being found guilty at trial. This article has some examples of the failures to apply Bayesian statistics in existing justice systems.