Algorithms and Human Freedom

40 Pages Posted: 5 Apr 2019 Last revised: 24 Apr 2019

See all articles by Robert H. Sloan

Robert H. Sloan

University of Illinois at Chicago

Richard Warner

Chicago-Kent College of Law

Date Written: March 13, 2019

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.

Keywords: machine learning, predictive analytics, artificial intelligence, coordination norms, public policy, federal trade commission

Suggested Citation

Sloan, Robert H. and Warner, Richard, Algorithms and Human Freedom (March 13, 2019). Available at SSRN: https://ssrn.com/abstract=3351960 or http://dx.doi.org/10.2139/ssrn.3351960

Robert H. Sloan

University of Illinois at Chicago ( email )

1200 W Harrison St
Chicago, IL 60607
United States

Richard Warner (Contact Author)

Chicago-Kent College of Law ( email )

565 West Adams St.
Chicago, IL 60661
United States

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