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>Today, the government relies on machine learning and AI in predictive policing analysis, family court delinquency proceedings, parole decisions, and DNA and fo

>Today, the government relies on machine learning and AI in predictive policing analysis, family court delinquency proceedings, parole decisions, and DNA and forensic science techniques, among other areas, producing a fundamental conflict between civil rights and automated decisionmaking. Most of the methods used for this are basically large matrices with no human understandable way to represent them. Getting the values would only let you recalculate the results, not discover why the results were produced.

phh 6y ago
> Getting the values would only let you recalculate the results, not discover why the results were produced. It also allows you to calculate new results, which can be used to detect when the system is actually wrong, and to detect bias. And actually, yes you can discover why the results were produced, because models leak a ton of data about the training set.
- michaelmrose 6y ago
  You presumably can't get anything at all without very expensive expertise on top of the expensive legal expertise that a lot of people already can't afford. The simple and affordable solution is to ban the use of artificial stupidity in legal decision making.
krona 6y ago
Climate models and recent epidemiological modelling (outliers in terms of their effect on public policy making) are far simpler than say the ML this article seems to suggest. But you don't need a human-understandable representation to understand their limitations.
- p_l 6y ago
  Climate models don't use ML, similarly, most sensible epidemiological modelling doesn't. ML is, afaik, considered too much of "curve fitter" to actually simulate or analyze anything novel instead of rehashing of past events, making it useless in cases like this.
Gunax 6y ago
Humans all ready are black boxes. IMO, if you're worried about a black box AI juror, we all ready have that--they are called (human) jurors.

phh 6y ago

> Getting the values would only let you recalculate the results, not discover why the results were produced. It also allows you to calculate new results, which can be used to detect when the system is actually wrong, and to detect bias. And actually, yes you can discover why the results were produced, because models leak a ton of data about the training set.

michaelmrose 6y ago
You presumably can't get anything at all without very expensive expertise on top of the expensive legal expertise that a lot of people already can't afford. The simple and affordable solution is to ban the use of artificial stupidity in legal decision making.

krona 6y ago

Climate models and recent epidemiological modelling (outliers in terms of their effect on public policy making) are far simpler than say the ML this article seems to suggest. But you don't need a human-understandable representation to understand their limitations.

p_l 6y ago
Climate models don't use ML, similarly, most sensible epidemiological modelling doesn't. ML is, afaik, considered too much of "curve fitter" to actually simulate or analyze anything novel instead of rehashing of past events, making it useless in cases like this.

Gunax 6y ago

Humans all ready are black boxes. IMO, if you're worried about a black box AI juror, we all ready have that--they are called (human) jurors.