The Challenges for Socially Responsible AI for Well-being

Abstract

In this AAAI Spring Symposium 2023, we discuss Socially Responsible AI for Well-being. For AI to truly benefit society, it must go beyond mere productivity and economic advantages; embrace social responsibility; and emphasize fairness, transparency, safety, and other key principles. For instance, AI diagnostic systems should not only be accurate but also free from bias, ensuring equitable data representation across races and locations. This highlights the need for ongoing discussions on the nature of "social responsibility" in AI applications. There are two main perspectives: (1) Individually Responsible AI: Focuses on designing AI systems that consider individual well-being, such as understanding how digital experiences influence emotions and quality of life. (2) Socially Responsible AI: Emphasizes broader societal impacts, striving for decisions that are fair and beneficial for all. Addressing biases in AI is crucial to achieving fairness. Additionally, the knowledge produced by AI, such as health advice, should be universally applicable and not only beneficial to a subset of individuals. This paper outlines the underlying motivations, key terms, areas of focus, and research inquiries for this symposium.

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