Age and gender bias in pedestrian detection algorithms

Understand

Pedestrian detection algorithms are important components of mobile robots, such as autonomous vehicles, which directly relate to human safety.

• Performance disparities in these algorithms could translate into disparate impact in the form of biased accident outcomes.
• To evaluate the need for such concerns, we characterize the age and gender bias in the performance of state-of-the-art pedestrian detection algorithms.
• Our analysis is based on the INRIA Person Dataset extended with child, adult, male and female labels.