AI Bias

Systematic and unfair discrimination in AI system outputs that arises from biased training data, flawed model design, or unrepresentative assumptions embedded in the development process. In accessibility contexts, AI bias can manifest as systems that reinforce stereotypes about disabled or neurodivergent people, generate descriptions using ableist framing, or default to normative assumptions that exclude non-typical experiences. AI bias is particularly harmful when deployed in high-stakes domains like employment, healthcare, or education where marginalised users depend on accurate, personalised support.