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.

The AI Opportunity - CIRSD

News – Duke AI Health

Navigating Bias and Fairness Challenges in AI/ML Development

That's Just Common Sense'. USC researchers find bias in up to 38.6

Dealing With Bias in Artificial Intelligence - The New York Times

Biased Algorithms Are Easier to Fix Than Biased People - The New

Addressing Bias in AI

Credited Responses: The Future of Ethical AI Design

Ethics and discrimination in artificial intelligence-enabled

Understanding the role of racist algorithms in AI ethics discourse