But even the smartest algorithms can sometimes behave in unexpected and unwanted ways—for example, picking up gender bias from the text or images they are fed.

Researchers who dug through nearly 50,000 records discovered that the algorithm effectively low-balled the health needs of the hospital’s black patients. Using its output to help select patients ...

One worry, for example, is that advanced natural-language algorithms like GPT-3 could supercharge online disinformation. Another is that large-scale algorithms also contain built-in bias and that it ...

Interaction Bias A unfortunately common example of Interaction Bias is facial recognition algorithms trained on datasets containing more Caucasian faces than African American faces.

The first case might occur, for example, if a deep-learning algorithm is fed more photos of light-skinned faces than dark-skinned faces.

For example, at the start of the COVID-19 pandemic, scientists published an algorithm that could predict coronavirus infections from lung photos.