IB Digital Society 2.3C Intersectionality and Identity Factors Key Definitions

A systematic error in an algorithm that produces unfair outcomes, often by favouring one group over another.

The gap between people who have reliable access to digital systems and the skills to use them and those who do not, a gap that tends to follow existing lines of income, age, geography, and ability.

The idea that a person's identity is made of several factors at once, such as gender, race, class, age, and ability, which overlap and combine to shape their experience rather than acting one at a time.

The set of examples used to teach a machine learning model. The quality, quantity, and representativeness of the training data shape what the model learns and any bias it inherits.