False positives, false negatives, and AI model Confirmation Bias challenge
Confirmation bias is a cognitive bias that occurs when people give more weight to evidence supporting their existing beliefs while downplaying or ignoring evidence contradicting those beliefs.AI model confirmation bias can occur when the data used to train the model is unrepresentative of the population the model is intended to predict. AI model confirmation bias can lead to inaccurate or unfair decisions and is of significant concern in fields such as employment, college admissions, credit and financing, and criminal justice, where the consequences of incorrect predictions can be severe. ADD
Mitigating model false positives and false negatives plays a vital role in reducing the impact of model confirmation bias and ensuring responsible and effective decision-making. By minimizing false positives, we avoid making incorrect assumptions or taking unnecessary...