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As the real-world impact of Artificial Intelligence (AI) systems has beensteadily growing, so too have these systems come under increasing scrutiny. Inresponse, the study of AI fairness has rapidly developed into a rich field ofresearch with links to computer science, social science, law, and philosophy.Many technical solutions for measuring and achieving AI fairness have beenproposed, yet their approach has been criticized in recent years for beingmisleading, unrealistic and harmful.  In our paper, we survey these criticisms of AI fairness and identify keylimitations that are inherent to the prototypical paradigm of AI fairness. Bycarefully outlining the extent to which technical solutions can realisticallyhelp in achieving AI fairness, we aim to provide the background necessary toform a nuanced opinion on developments in fair AI. This delineation alsoprovides research opportunities for non-AI solutions peripheral to AI systemsin supporting fair decision processes.

Inherent Limitations of AI Fairness