Fair AI

Fair AI research aims to mitigate bias and discrimination in artificial intelligence systems, focusing on developing methods to ensure equitable outcomes across different demographic groups. Current research emphasizes both technical solutions, such as incorporating fairness constraints into model training (e.g., using regularization techniques) and exploring various model architectures for improved fairness, and broader societal considerations, including the need for interdisciplinary collaboration and the development of standardized bias metrics. This work is crucial for building trustworthy AI systems and addressing the ethical implications of AI deployment in various sectors, impacting both the scientific understanding of bias and the development of fairer, more equitable technologies.