As algorithmic systems increasingly permeate decision-making in healthcare, identity recognition, welfare distribution, public security, online content governance and more, structural forms of inequality are often amplified. This can be particularly acute for those positioned at the margins of legal and social classification systems, individuals whose sex, gender, and sexuality do not conform to dominant categories. Responding to these challenges, this book rethinks the role of equality law in the age of artificial intelligence. 
The book evaluates how different legal systems respond to three categories of algorithmic bias: foundational, technical, and interpretative. These models are assessed by their ability to implement the three legal strategies proposed in the book: equality by design, equality by participation, and equality by education. Moving "from the margins to the core", the book uses queer perspectives as a methodological lens through which to expose the structural limitations of existing approaches to equality and to rethink their foundations. It demonstrates that equality must not remain strictly a formal value or ex post remedy but must be embedded as a structural criterion of legitimacy in the design, regulation, and deployment of AI systems.
The book will be of interest to researchers in the fields of diversity and equality, queer and gender law, artificial intelligence and law, and emerging technologies.