Eliminating Algorithmic Bias Is Just the Beginning of Equitable AI

When it comes to artificial intelligence and inequality, algorithmic bias rightly receives a lot of attention. But it’s just one way that AI can lead to inequitable outcomes. To truly create equitable AI, we need to consider three forces through which it might make society more or less equal: technological forces, supply-side forces, and demand-side forces. The last of these is particularly underemphasized. The use of AI in a product can change how much customers value it — for example, patients who put less stock in an algorithmic diagnosis — which in turn can affect how that product is used and how those working alongside it are compensated.

How AI developers can assure algorithmic fairness

Generative AI in VC Investment: Expert Q&A

A Call to Action on Assessing and Mitigating Bias in Artificial

How AI developers can assure algorithmic fairness

PDF) ARTIFICIAL INTELLIGENCE'S ALGORITHMIC BIAS: ETHICAL AND LEGAL

FTC's order to delete AI algorithms will have consequences - Protocol

Newsroom - Harvard Business School

AI Bias: Definition, Occurrence, Types, Causes, and Prevention

A Call to Action on Assessing and Mitigating Bias in Artificial

News – Duke AI Health

Eliminating Algorithmic Bias Is Just the Beginning of Equitable AI