The Political Economy of AI: Towards Democratic Control of the Means of Prediction

Maximilian Kasy

No 16948, IZA Discussion Papers from Institute of Labor Economics (IZA)

Abstract: This chapter discusses the regulation of artificial intelligence (AI) from the vantage point of political economy, based on the following premises: (i) AI systems maximize a single, measurable objective. (ii) In society, different individuals have different objectives. AI systems generate winners and losers. (iii) Society-level assessments of AI require trading off individual gains and losses. (iv) AI requires democratic control of algorithms, data, and computational infrastructure, to align algorithm objectives and social welfare. The chapter addresses several debates regarding the ethics and social impact of AI, including (i) fairness, discrimination, and inequality, (ii) privacy, data property rights, and data governance, (iii) value alignment and the impending robot apocalypse, (iv) explainability and accountability for automated decision-making, and (v) automation and the impact of AI on the labor market and on wage inequality.

Keywords: AI; machine learning; regulation; fairness; privacy; value alignment; explain-ability; automation (search for similar items in EconPapers)
JEL-codes: O3 P00 (search for similar items in EconPapers)
Pages: 30 pages
Date: 2024-04
New Economics Papers: this item is included in nep-ain, nep-big and nep-reg
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Related works:
Working Paper: The political economy of AI: Towards democratic control of the means of prediction (2023)
Working Paper: The Political Economy of AI: Towards Democratic Control of the Means of Prediction (2023)
Working Paper: The political economy of AI: Towards democratic control of the means of prediction (2023)
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