An Intelligence in Our Image: The Risks of Bias and Errors in Artificial Intelligence
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TL;DR
Some of the shortcomings of algorithmmic decisionmaking are illustrated, key themes around the problem of algorithmic errors and bias are identified, and some approaches for combating these problems are examined.
Abstract
Machine learning algorithms and artificial intelligence influence many aspects of life today and have gained an aura of objectivity and infallibility. The use of these tools introduces a new level of risk and complexity in policy. This report illustrates some of the shortcomings of algorithmic decisionmaking, identifies key themes around the problem of algorithmic errors and bias, and examines some approaches for combating these problems.