Algorithms Are Biased, But We Can Make Them Fairer
By Alexandra Wood, Harvard University & Micah Altman, MIT
Machines don't fix our biases, they mirror them. Algorithms can make things fairer only if we design them with fairness in mind.
Alexandra Wood
Disciplines:
LawAlexandra Wood is a Fellow at the Berkman Klein Center for Internet & Society at Harvard University. As a contributor to the Privacy Tools for Sharing Research Data project, she explores new and existing legal and regulatory frameworks for data privacy and develops legal instruments to facilitate the sharing and use of research data while preserving privacy, transparency, and accountability. Previously, Alexandra served as a legal fellow assisting with the technology, telecommunications, and intellectual property portfolio of U.S. Senator Barbara Boxer. As a law student, she worked with the Center for Democracy & Technology and the Electronic Privacy Information Center on privacy projects addressing emerging electronic surveillance, facial recognition, and mobile payments technologies. Alexandra holds a law degree from George Washington University Law School, a master’s degree in public policy from the University of Southern California, and a bachelor’s degree in economics from Reed College.
