Robert H. Sloan (University of Illinois at Chicago) and Richard Warner (Chicago-Kent College of Law) have published "Algorithms And Human Freedom" on SSRN. Here is the abstract:
Predictive analytics such as data mining, machine learning, and artificial intelligence drive algorithmic decision making. Its “all-encompassing scope already reaches the very heart of a functioning society”. Unfortunately, the legal system and its various tools developed around human decisionmakers cannot adequately administer accountability mechanisms for computer decision making. Antiquated approaches require modernization to bridge the gap between governing human decisionmaking and new technologies.
We divide the bridge-building task into three questions. First, what features of the use of predictive analytics significantly contribute to incorrect, unjustified, or unfair outcomes? Second, how should one regulate those features to make outcomes more acceptable? Third, how can one ensure that the use of predictive analytics sufficiently respects human freedom? We divide the bridge-building task into three questions. First, what features of the use of predictive analytics significantly contribute to “incorrect, unjustified, or unfair” outcomes? Second, how should one regulate those features to make outcomes more acceptable? Third, how can one ensure that the use of predictive analytics sufficiently respects human freedom? You are not free when you are subject to the arbitrary will another, and predictive analytics is no exception. It violates your freedom when it pushes you down an arbitrary and capricious path.
We answer the first question by “profiling” uses of predictive analytics. We adapt the idea of profiling people. A profile of a person is a summary of characteristics relevant to evaluating and predicting the person’s behavior. Our profile consists of five features that significantly affect the extent to which a system will yield “incorrect, unjustified, or unfair” decisions. We answer the second question by explaining how to control predictive systems by regulating the features the profile identifies. Along with others, we propose that a government agency regulate the use of predictive systems. The novel feature of our approach is the use of legal regulation to unify consumer demand in ways that create a type of norm extensive studied in game theory, a coordination norm.
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