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Ethics & Safety
Responsible development and deployment of AI systems.
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Key Ethics & Safety concepts
A characteristic or feature of an object or concept
automation biasThe tendency to over-rely on automated systems and ignore or underweight human judgment
biasA systematic error or distortion in a machine learning model's results
bias (math) or bias termA constant added to a linear combination of inputs in a machine learning model
calibration layerA component in a neural network that adjusts the output to match the true probabilities of a task
ConfabulationWhen an AI produces a confident, fluent answer that sounds true but is factually wrong — generating plausible language without a reliable link to reality.
confirmation biasThe tendency to favor information that confirms existing beliefs or expectations
counterfactual fairnessA fairness metric in AI that ensures decisions are fair by comparing actual outcomes with hypothetical outcomes where a sensitive attribute is different