Algorithmic Bias

Algorithmic bias refers to systematic and repeatable errors in computer systems that create unfair outcomes, often disadvantaging certain demographic groups. Current research focuses on identifying and mitigating these biases across various machine learning models, including those used in healthcare, hiring, and social media, with a particular emphasis on understanding how data characteristics and model architectures contribute to unfairness. This is a critical area of investigation because biased algorithms can perpetuate and amplify existing societal inequalities, demanding the development of fairer and more equitable AI systems.