I feel the author failed to address the crux of why people argue that "non-statistical" bias is bad – that we should be judged by our actions, and not by factors out of our control such as race, class, the family we were born into, or where we were born.
If we included every aspect about a person in some statistical model, we may discover "uncomfortable truths" that hold true for the general population. But these truths, while statistically correct, may fail our test for what we consider to be philosophically fair, and ultimately undermine an individual's agency to act independently.
So perhaps in your experiment, the problem is that our feature selection is not reflective of the values we'd like to uphold, and that aspects like "had lead poisoning as a child" is not a sound feature to include in our model because it measures aspects of a person outside their control. Instead maybe our feature set should only include aspects that measure facets that are under the individual's control such as community service, whether they still associate with other criminals, whether they have or are pursuing education, whether they have children to care for, etc. (or some other feature set that's more thought out and sound, but you get the gist)
This still may not have as good accuracy as a model that included other features about the person, but it's arguable that this system would be more fair, especially over a model using more features but was artificially fudged to satisfy some prior about what we consider fair/unbiased.
If we included every aspect about a person in some statistical model, we may discover "uncomfortable truths" that hold true for the general population. But these truths, while statistically correct, may fail our test for what we consider to be philosophically fair, and ultimately undermine an individual's agency to act independently.
So perhaps in your experiment, the problem is that our feature selection is not reflective of the values we'd like to uphold, and that aspects like "had lead poisoning as a child" is not a sound feature to include in our model because it measures aspects of a person outside their control. Instead maybe our feature set should only include aspects that measure facets that are under the individual's control such as community service, whether they still associate with other criminals, whether they have or are pursuing education, whether they have children to care for, etc. (or some other feature set that's more thought out and sound, but you get the gist)
This still may not have as good accuracy as a model that included other features about the person, but it's arguable that this system would be more fair, especially over a model using more features but was artificially fudged to satisfy some prior about what we consider fair/unbiased.