Artificial intelligence : economic perspectives and models / Wim Naudé, Thomas Gries, Nicola Dimitri.
Material type:
TextLanguage: English Publication details: Cambridge, United Kingdom : Cambridge University Press, 2025.Description: xvi, 360 pagesISBN: - 9781009483094
- 658.056 23/eng/20240318 NAU
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CUTN Central Library Medicine, Technology & Management | Non-fiction | 658.056 NAU (Browse shelf(Opens below)) | Available | 54742 |
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| 658.054 KAL e-Business 2.0: | 658.054 SCH Electronic commerce | 658.0557 WAL From big data to big profits : success with data and analytics | 658.056 NAU Artificial intelligence : economic perspectives and models / | 658.072 MAN Research Methodology in Behavioural Sciences / | 658.076 SIN Logical reasoning and data Interpretation for CAT / | 658.1 HAM Entrepreneurship : resources and strategies / |
Title from publisher's bibliographic system (viewed on 28 May 2024).
1. Introduction; 2. Artificial Intelligence and economics: a gentle introduction; 3. Artificial Intelligence and the economics of decision-making; 4. Artificial Intelligence in the production factor; 5. Artificial Intelligence, growth and inequality; 6. Investing in Artificial Intelligence: breakthroughs and backlashes; 7. Artificial Intelligence arms races as innovation contests; 8. Directing Artificial Intelligence innovation and diffusion; 9. Artificial Intelligence, big data and public policy; 10. The future of Artificial Intelligence and implications for economics.
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Is Artificial Intelligence a more significant invention than electricity? Will it result in explosive economic growth and unimaginable wealth for all, or will it cause the extinction of all humans? Artificial Intelligence: Economic Perspectives and Models provides a sober analysis of these questions from an economics perspective. It argues that to better understand the impact of AI on economic outcomes, we must fundamentally change the way we think about AI in relation to models of economic growth. It describes the progress that has been made so far and offers two ways in which current modelling can be improved: firstly, to incorporate the nature of AI as providing abilities that complement and/or substitute for labour, and secondly, to consider demand-side constraints. Outlining the decision-theory basis of both AI and economics, this book shows how this, and the incorporation of AI into economic models, can provide useful tools for safe, human-centered AI.
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