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Bias detectives: the researchers striving to make algorithms fair

As machine learning infiltrates society, scientists are trying to help ward off injustice.
  1. Rachel Courtland

    1. Rachel Courtland is a science journalist based in New York City.

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In 2015, a worried father asked Rhema Vaithianathan a question that still weighs on her mind. A small crowd had gathered in a basement room in Pittsburgh, Pennsylvania, to hear her explain how software might tackle child abuse. Each day, the area’s hotline receives dozens of calls from people who suspect that a child is in danger; some of these are then flagged by call-centre staff for investigation. But the system does not catch all cases of abuse. Vaithianathan and her colleagues had just won a half-million-dollar contract to build an algorithm to help.

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Nature 558, 357-360 (2018)

doi: https://doi.org/10.1038/d41586-018-05469-3

References

  1. Chouldechova, A. Preprint at https://arxiv.org/abs/1703.00056 (2017).

  2. Chouldechova, A., Putnam-Hornstein, E., Benavides-Prado, D., Fialko, O. & Vaithianathan, R. Proc. Machine Learn. Res. 81, 134–148 (2018).

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  3. Reisman, D., Schultz, J., Crawford, K. & Whittaker, M. Algorithmic Impact Assessments: A Practical Framework for Public Agency Accountability (AI Now, 2018).

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  4. Wachter, S., Mittelstadt, B. & Floridi, L. Sci. Robotics 2, eaan6080 (2017).

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