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.

Tackling bias in artificial intelligence (and in humans)

Addressing Bias in AI

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Applied Sciences, Free Full-Text

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

Towards algorithmic equality. Organisations need to assess and

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The Coming Regulation of AI in the US - John B. Quinn - New Thinking

A Call to Action on Assessing and Mitigating Bias in Artificial