Fighting Prejudice in Artificial Intelligence
summary
Examines how human biases in collected datasets can lead AI systems to reproduce and amplify prejudice, and outlines practical measures such as adopting diversity- and inclusion-minded data collection and improved AI training practices. Mentions building AI to a higher standard by recognising unintended harms and adjusting data and training pipelines to mitigate biased outcomes.
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