Discovery / podcast: Season 2
Guest: Ifeoma Ajunwa, Assistant Professor of Labor and Employment Law, Industry and Labor Relations School, Cornell University
We live in an age when algorithmic decision-making impacts more of our lives than ever before, from college admissions and job offers to financial opportunities and more.
But does relying on automation for these kinds of crucial decisions actually amplify, rather than eliminate, the implicit bias it is supposed to curb?
Law and technology expert Ifeoma Ajunwa argues algorithmic decision-making can in fact hide bias under the veneer of objectivity — and gaps in current legal architecture foment the ability to do so.
She joins DISCOVERY to explore present challenges and how viewing the issue through a legal lens provides opportunities for potential solutions.