Evan Lerner
Monroe Kennedy III graduated from the doctoral program in Mechanical Engineering and Applied Mechanics in 2019 and is now an assistant professor of Mechanical Engineering at Stanford University. Focusing on human-robot interaction during his time in the GRASP lab, he is the director of Stanford’s Assistive Robotics and Manipulation Lab, which aims to develop technology that can better anticipate people’s needs and act accordingly.
Kennedy is also the academic co-lead of Black in Robotics, a new organization that advocates for diversity and inclusion in the robotics community. He and fellow academic co-lead Ayanna Howard, chair of the School of Interactive Computing in the College of Computing at Georgia Tech, recently published an editorial in the journal Science Robotics, outlining how outwardly fair and objective technologies can be imbued with the biases of their creators.
Most roboticists focus on the design of intelligent machines with the goal of positively affecting the world, i.e., building robots in service to humanity. To this end, roboticists should embrace the concept in which our robot systems are explicitly designed to work with uniformly positive performance across the diversity of users. Unfortunately, researchers have shown that this is not always the case. Object detection systems, of the kinds used in autonomous vehicles, have uniformly poorer performance when it comes to detecting pedestrians with darker skin tones Researchers have also shown that racial bias exists in commercial facial recognition application programming interfaces or APIs.
It is not just the responsibility of society or governing bodies to take on the challenge of fixing racial bias and inequity. Roboticists also need to take on the responsibility to make sure we do not cause equivalent harm in developing new technologies. And if the harm we are creating is negatively affecting one group or groups more than another, it is our responsibility to fix that. After all, roboticists are pretty skilled at finding solutions to hard, seemingly unsolvable problems. It is time to apply those skills to fix this one.
Continue reading at Science Robotics.