Algorithmic Bias: When Code Creates Unfair Outcomes
Algorithmic bias is a mirror reflecting flawed human data, leading to systematically unfair outcomes. It appears in hiring tools favoring one gender or loan systems denying certain groups. The footgun is assuming tech is neutral; the bias is in the data.
Algorithmic bias is a mirror reflecting flawed human data, creating systematic and repeatable unfair outcomes. It privileges one group over another, often unintentionally. This shows up in hiring tools that favor one gender or loan systems that deny certain demographics. The biggest footgun is thinking technology is neutral; the bias is often baked into the historical data the algorithm learns from, not a simple bug in the code.
Read the original → Wikipedia: Algorithmic bias
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