Algorithm bias, in the context of artificial intelligence and machine
learning, refers to a systematic and unfair discrimination or
favoritism exhibited by an algorithm when making decisions or
predictions. This bias can result in unjust and discriminatory
outcomes for specific individuals or groups based on their
characteristics, such as race, gender, age, socioeconomic status,
or other protected attributes. Algorithm bias is typically an
unintended consequence of the algorithm’s training data, design,
or implementation, and it can have significant ethical, legal, and
social implications. Efforts to detect and mitigate algorithm bias are
essential to ensure the fairness and equity of AI systems.
Definitions – Algorithm bias
