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How do biases in narrow AI systems create real-world harm?

BiasPolicy & EthicsRisks

Drawn from Lutz Finger's Forbes column, LinkedIn writing, and Cornell teaching. Sources are cited inline so you can read the originals.

AI systems enforce human prejudices at massive scale.

Narrow AI amplifies existing biases at scale. In parole decisions, computers were meant to remove human bias, but when fed biased data, they kept more minorities in jail. Loan application systems with few women in training data couldn’t correctly handle female applicants. The stop and frisk program in New York used a computer to select precincts, but it was racially unjust. When you remove skin color from the data, the system became even more skewed. There’s a logical data science explanation for this.

Bias in, bias out: Addressing the impact of bias in AI · The Edge


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