In safety engineering, ergonomic differences between men and women are important.
Conventional seat belts do not fit pregnant women properly and motor vehicle crashes are the leading cause of fetal death related to maternal trauma. Analyses of sex differences have led to the development of pregnant crash test dummies that enhance safety in automobile testing and design.
In medicine, osteoporosis has been conceptualized primarily as a women's disease, yet after a certain age men account for nearly a third of osteoporosis-related hip fractures. Tragically, when men break their hips, they tend to die. We don't know why. Analyzing the interaction between sex and gender in osteoporosis has led to new diagnostics for men, and the search for better treatments is underway.
In these and many other cases, historian Londa Schiebinger points out that if we don't consider sex or gender analysis, past bias may be perpetuated into the future, even when governments, universities and companies have implemented policies to foster equality.
The big question now, she says, is: How can humans automate processes that also contribute to creating a fair and equal society? Schiebinger highlights examples of efforts where computer scientists are working to create mathematically rigorous definitions of fairness in order to develop and optimize algorithms that guarantee fairness. There is much work to be done, but as Scheibinger sees it, there is a big opportunity for these algorithms as well as the robotic systems they will enable to challenge and eventually reconfigure gender norms.
Join host Russ Altman and historian of science Londa Schiebinger for a closer look at how to employ methods of sex and gender analysis as a resource to create new knowledge and stimulate novel design.