  As generative Artificial Intelligence (genAI) technologies proliferate across
sectors, they offer significant benefits but also risk exacerbating
discrimination. This chapter explores how genAI intersects with
non-discrimination laws, identifying shortcomings and suggesting improvements.
It highlights two main types of discriminatory outputs: (i) demeaning and
abusive content and (ii) subtler biases due to inadequate representation of
protected groups, which may not be overtly discriminatory in individual cases
but have cumulative discriminatory effects. For example, genAI systems may
predominantly depict white men when asked for images of people in important
jobs.
  This chapter examines these issues, categorizing problematic outputs into
three legal categories: discriminatory content; harassment; and legally hard
cases like unbalanced content, harmful stereotypes or misclassification. It
argues for holding genAI providers and deployers liable for discriminatory
outputs and highlights the inadequacy of traditional legal frameworks to
address genAI-specific issues. The chapter suggests updating EU laws, including
the AI Act, to mitigate biases in training and input data, mandating testing
and auditing, and evolving legislation to enforce standards for bias mitigation
and inclusivity as technology advances.
