### bias (ethics/fairness)

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#fairness

1. Stereotyping, prejudice or favoritism towards some things, people, or groups over others. These biases can affect collection and interpretation of data, the design of a system, and how users interact with a system. Forms of this type of bias include:

   - automation bias
   - confirmation bias
   - experimenter’s bias
   - group attribution bias
   - implicit bias
   - in-group bias
   - out-group homogeneity bias

2. Systematic error introduced by a sampling or reporting procedure. Forms of this type of bias include:

   - coverage bias
   - non-response bias
   - participation bias
   - reporting bias
   = sampling bias
   - selection bias

Not to be confused with the bias term in machine learning models or prediction bias.