Making the Case for Human-Centered AI?

Abstract

This case advocates for the implementation of a Human-Centered AI approach with the rise of artificial intelligence integration into daily life. Self-driving vehicles to content generation, AI systems increasingly impact how we work, communicate, and make decisions. The study tracks benchmarks like Deep Blue's victory at chess and AlphaGo's triumph over a Go grandmaster to depict how rapidly AI has developed, but it continues to emphasize its shortcomings—bias, whimsicalness, and absence of human intuition. The case tracks three levels of design based on Stanford researcher James Landay's framework: user-centered, community-centered, and society-centered AI. Using the case of autonomous vehicles, it shows how a purely user-centric design ignores broader impacts on pedestrians, traffic, and urban planning. Human-Centered AI requires diverse multidisciplinary groups to predict unintended consequences and include ethics, accountability, and social benefit in design upfront. The study argues that this holistic approach is more effective and cheaper in the long run than patching in remedies after deployment. Because AI continues to be controlled by a few big companies, it also challenges students to think about who should make AI policy and how society can achieve a balance between innovation and safeguarding human dignity and equity.