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The answer entirely depends - "Deliberately altering the model to produce equal results despite unequal patterns in reality" is so vague as to be meaningless in
by gbrown 7y ago
The answer entirely depends - "Deliberately altering the model to produce equal results despite unequal patterns in reality" is so vague as to be meaningless in this discussion.
> Is the goal of the AI model to predict crime rates in a hypothetical world where everyone has equal rates of lead exposure? Or is the goal of the model to predict crime rates in the real world?
The goal is to use the results of a model for something (pet peeve, I hate the use of "AI" to describe what are usually pretty standard statistical or ML models). The model you create, and how you apply/interpret it, depend entirely on what you're actually trying to accomplish or change with the results.
Depending on what that is, the kind of "bias reflection" we're discussing is hugely problematic.
- manfredo 7y agoAnd that "something" we want the AI to do is usually grounded in the real world in some way, be it shopping patterns, or crime. And the real world has disparities. For example, crime rates are not equal between men and women. If we force our AI to assign equal risk of crime to men and women then we will have introduced a bias that either under predicts the rate of male crime, or over prdicts the rate of female crime.
- loopz 7y ago"Truth" is irrelevant and academic. What matters is: What are the outcomes and consequences of active systems, AI or not. For instance: How do the algo cope with derivatives of its own output being fed into itself as input at a later stage?
- manfredo 7y agoIf truth is irrelevant then just return random output and call it a day. The reality is, truth is relevant and sometimes the truth is inconvenient. Tech workers may want to build an AI that measures risk of recidivism that produces uniform risks across race and gender. But the truth is, rates of recidivism is not the same across all groups. If we produce the desired outcome of equal reporting of risk, then the consequence is that men have their risk underreported to put them on parity with women, or vice versa.