Different sources of bias in AI

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What are the different sources of bias in AI models?

• Training data bias
  • Historical data --> historical bias
  • Sampling --> representation bias (stereotyping, recognition, denigration, underrepresentation, ex-Nomination)
  • Training Data --> labeling / annotation bias
  • Feature selection and data curation --> unconscious Bias
  • Measurement --> measurement bias
• Training bias --> learning bias
• Algorithmic bias
  • Model definition --> aggregation bias
  • Model Evaluation / selection --> evaluation bias
  • Model deployment --> deployment bias
• Human bias and cognitive bias
  • Human in the loop --> automation bias
  • Output skevness --> allocation bias