An Ethical Analysis of a Child Abuse Detection Algorithm

Developed with talented ethical minds Cristiany Miguel Paulo, Michiel Esseling and Lara de Luca.

One of our key recommendations with such prediction technologies resonates now more than ever, implicit bias gets the best of us:

"Our first recommendations should first and foremost be stressing the importance of implicit bias training for health care workers in general. This would help alleviate bias not only in the context of our project, but would help diminish several discrimination issues and incorrect diagnostics within children's health care."

See the full analysis here.