Sasha Luccioni: Connecting the Dots Between AI's Environmental and Social Impacts
The Gradient: Perspectives on AI
Exploring Values, Biases, and Ethics in AI Research
The importance of delving into the values embedded in AI research and systems is highlighted to move away from broad terms like 'ethical' that carry implicit assumptions. It is emphasized that ethical considerations should be context-specific, focusing on validating outputs, acknowledging biases, and communicating failure cases to make users aware of limitations and prevent misuse of AI models. The need to quantify, test, evaluate, and openly discuss biases, failure modes, and restrictions is crucial for ensuring responsible and informed use of AI technology.
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