AI for Not Bad

Jared Moore

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Ethics and Social Impacts of AI Artificial Intelligence Applications Innovation, Technology, and Society

Abstract

Hype surrounds the promotions, aspirations, and notions of "artificial intelligence (AI) for social good" and its related permutations. These terms, as used in data science and particularly in public discourse, are vague. Far from being irrelevant to data scientists or practitioners of AI, the terms create the public notion of the systems built. Through a critical reflection, I explore how notions of AI for social good are vague, offer insufficient criteria for judgement, and elide the externalities and structural interdependence of AI systems. Instead, the field known as "AI for social good" is best understood and referred to as "AI for not bad."

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References

2018AI4People—An Ethical Framework for a Good AI Society: Opportunities, Risks, Principles, and Recommendations 1999What Is the Point of Equality?2014Big data: a revolution that will transform how we live, work, and think 2019Fairness and Abstraction in Sociotechnical Systems 2002Black Feminist Thought 2019Ghost Work: How to Stop Silicon Valley from Building a New Global Underclass 2016The social power of algorithms 2013Algorithmic governmentality and prospects of emancipation

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2020Towards a more representative politics in the ethics of computer science 2021‘AI for Social Good’: Whose Good and Who’s Good? Introduction to the Special Issue on Artificial Intelligence for Social Good 2025The ethics of AI value chains 2023Enlarging the model of the human at the heart of human-centered AI: A social self-determination model of AI system impact 2022Trade Union Revitalisation: The Impact of Artificial Intelligence and Gig Economy

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