Citation

Algorithms as Discrimination Detectors

Author:
Kleinberg, Jon; Ludwig, Jens; Mullainathan, Sendhil; Sunstein, Cass R.
Publication:
Proceedings of the National Academy of Sciences
Year:
2020

Preventing discrimination requires that we have means of detecting it, and this can be enormously difficult when human beings are making the underlying decisions. As applied today, algorithms can increase the risk of discrimination. But as we argue here, algorithms by their nature require a far greater level of specificity than is usually possible with human decision making, and this specificity makes it possible to probe aspects of the decision in additional ways. With the right changes to legal and regulatory systems, algorithms can thus potentially make it easier to detect—and hence to help prevent—discrimination.