Preconceito Codificado

This study examines how artificial intelligence (AI) algorithms reproduce gender-based discriminatory patterns and their social impacts. The growing adoption of AI in sectors such as labor markets, healthcare, and public security raises concerns about the perpetuation of structural inequalities, particularly against women. Based on a literature review and case studies, the research identifies sectors most susceptible to algorithmic discrimination and assesses international mitigation practices. The findings indicate that algorithmic bias stems from unbalanced training data, lack of diversity in development teams, and the absence of adequate regulation

Inequality · Public policy · Social inequality · Social security · Income, Poverty, and Inequality