How long until they just send armed drones automatically after them based on the software's algorithm? 10-20 years?
An automated justice system wouldn't be biased by human prejudice, ignorance or fear. It doesn't get tired, doesn't feel pain or pity or remorse. It would be able to impartially and accurately process vast amounts of data - far more than a human, and the actions of the drones could be completely auditable. Drones won't lie on the stand to protect their fellow drones, or tamper with evidence.
You could walk down the street surrounded by police drones and be confident that you're not being profiled based on racist or religious bigotry, but pure mathematics and statistics. In every conceivable way, an armed drone with a license to kill is safer, faster, more reliable than a human. One only has to look at the current justice system in any country to see that humans are simply not capable of properly judging the motives of, or punishing, other humans in any reasonable way.
People will simply have to accept that the day will come when human-applied justice is viewed with the same ridicule and scorn that witch-burning is today... as the vicious, superstitious barbarism of an ignorant past.
An automated system is written by people and those prejudices can still sneak in...
http://www.nytimes.com/2015/07/10/upshot/when-algorithms-dis...
http://www.salon.com/2013/02/04/online_advertisings_racism_m...
Of course, being in the NYTimes and Salon, they need to obfuscate this point and appeal to standard mood affiliation.
Also, describing the results of any code/program written by a human as a "completely inhuman intelligence" is a tenuous claim at best.
If you want to make normative arguments, go ahead. My first principles tend to be very individualistic (I view individual humans as being the sole carriers of moral consideration), so our normative claims will likely disagree.
Also, describing the results of any code/program written by a human as a "completely inhuman intelligence" is a tenuous claim at best.
Clearly you've never written such systems. If they behaved remotely the way humans think my job (building them and making them usable by humans) would be vastly easier.
Appeals to authority and accomplishments aside, I don't need to have written such systems to understand, infer, and conclude things about aspects of their behavior. My point is this: something created by humans cannot be, by definition, inhuman. Two methodologies, the "human approach" and the "ML approach", might have radically different steps but come to the same conclusions. It would appear from your comments that you are OK with these conclusions ("An unbiased methodology produced these results, therefore, it's OK!"). Are you morally satisfied by the conclusions discussed above? Do the results of "such systems" influence your satisfaction?
The implication for society (assuming these findings generalize) is that most likely, we cannot solve statistical disparities via unbiased processes - we can have fair treatment of individuals or statistically representative distribution of spoils, but not both. As noted above, I'm very individualistic, so I favor fair treatment of individual humans.
Appeals to authority and accomplishments aside, I don't need to have written such systems to understand, infer, and conclude things about aspects of their behavior. My point is this: something created by humans cannot be, by definition, inhuman.
I don't know what you mean by "inhuman". It sounds like you mean the term to be "never tainted by the ephemeral emanations of humanity". I merely mean "inhuman" as "thought processes so radically different that intuitions about a human mind are completely useless".
Concretely, do you believe a random forest can somehow infer that the variable x[27] represents gender, and that to make it's sexist creator happy it should reduce the objective function in order to screw some women over? If you look at the internals of sklearn, that's just not what random forests do.
Two methodologies, the "human approach" and the "ML approach", might have radically different steps but come to the same conclusions. It would appear from your comments that you are OK with these conclusions ("An unbiased methodology produced these results, therefore, it's OK!"). Are you morally satisfied by the conclusions discussed above? Do the results of "such systems" influence your satisfaction?
I don't know what you mean by "morally satisfied". A fact about the world is either true or false. In computer science terms, I believe "morally satisfied" has type `satisfied: HumanAction -> Boolean`. Your question consists of applying `satisfied` to a value of type `WorldState` - it's a type error. In human terms, your question doesn't make sense.
In terms of my own individual happiness (as distinguished from moral satisfaction), this fact reduces my happiness. Because I believe many of these facts to be true, I'm forced to either lie about my beliefs (which causes me disutility) or suffer social opprobrium from anti-intellectual types and lazy thinkers influenced by them.
Even an unbiased analysis system can reach bad conclusions from bad data, and a biased justice system can produce bad data. So the conclusions can be biased even if the program is unbiased.
Is it your belief that we can cook up better algos/data collection methods/etc and all the people complaining about "bias" in algorithms will be satisfied? I don't believe that is the case, given that no one is actually complaining that the algorithms are getting the (factually) wrong answer.
If the arresting officers are biased, the number of arrests are probably biased. I'm not sure that you can fix that with better data collection methods; the problem isn't with the data collection. The problem also isn't with the analysis.
It may be possible, at least in theory, to create an algorithm that will determine whether the officers are biased, or whether the race in question actually commits more crimes. I'm not optimistic about that working in reality, though.
The core question - do you believe the problem will be fixed by better machine learning algorithms? Going back to the current example, do you believe that a Bayes-optimal machine learning algorithm for predicting criminal behavior will be "unbiased" (in the sense of social justice, not in the sense of statistics)?
Or, more concretely, do you believe that the only problem that mtgx and smtddr are complaining about is that our ML algorithms aren't good enough and that maybe we need deep learning instead of random forests?
When we get super-human AI, then maybe we can hope for that.
We can't outsource our moral imperative to computers, no matter how much we don't want to have the conversation about actual causes of crime and incarceration in the US...