Eliminating Algorithmic Bias Is Just the Beginning of Equitable AI
Por um escritor misterioso
Last updated 19 setembro 2024
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.
A step toward building a unified framework for managing AI bias
That's Just Common Sense'. USC researchers find bias in up to 38.6
Addressing bias in health care
Bias In Machine Learning: Concepts, Causes, And How To Fix It
Why are AI devs like this? : r/ChatGPT
Credited Responses: The Future of Ethical AI Design
Eliminating Algorithmic Bias Is Just the Beginning of Equitable AI
Article Archives Digital Data Design Institute at Harvard
Algorithmic fairness in artificial intelligence for medicine and
Tackling bias in artificial intelligence (and in humans)
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