AI (or Algorithmic) Bias: According to the first edition of the EU-U.S. terminology and taxonomy for artificial intelligence, the term “AI (or Algorithmic) Bias” means:
Harmful AI bias describes systematic and repeatable errors in AI systems that create unfair outcomes, such as placing privileged groups at systematic advantage and unprivileged groups at systematic disadvantage. Different types of bias can emerge and interact due to many factors, including but not limited to, human or system decisions and processes across the AI lifecycle. Bias can be present in AI systems resulting from pre-existing cultural, social, or institutional expectations; because of technical limitations of their design; by being used in unanticipated contexts; or by non-representative design specifications.
