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The Technological Elements of Artificial Intelligence

In: The Economics of Artificial Intelligence: An Agenda

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  • Matt Taddy

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  • Matt Taddy, 2018. "The Technological Elements of Artificial Intelligence," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 61-87, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberch:14021
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    References listed on IDEAS

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    3. David Silver & Julian Schrittwieser & Karen Simonyan & Ioannis Antonoglou & Aja Huang & Arthur Guez & Thomas Hubert & Lucas Baker & Matthew Lai & Adrian Bolton & Yutian Chen & Timothy Lillicrap & Fan , 2017. "Mastering the game of Go without human knowledge," Nature, Nature, vol. 550(7676), pages 354-359, October.
    4. Volodymyr Mnih & Koray Kavukcuoglu & David Silver & Andrei A. Rusu & Joel Veness & Marc G. Bellemare & Alex Graves & Martin Riedmiller & Andreas K. Fidjeland & Georg Ostrovski & Stig Petersen & Charle, 2015. "Human-level control through deep reinforcement learning," Nature, Nature, vol. 518(7540), pages 529-533, February.
    5. Bresnahan, Timothy, 2010. "General Purpose Technologies," Handbook of the Economics of Innovation, in: Bronwyn H. Hall & Nathan Rosenberg (ed.), Handbook of the Economics of Innovation, edition 1, volume 2, chapter 0, pages 761-791, Elsevier.
    6. David Silver & Aja Huang & Chris J. Maddison & Arthur Guez & Laurent Sifre & George van den Driessche & Julian Schrittwieser & Ioannis Antonoglou & Veda Panneershelvam & Marc Lanctot & Sander Dieleman, 2016. "Mastering the game of Go with deep neural networks and tree search," Nature, Nature, vol. 529(7587), pages 484-489, January.
    7. Deaton, Angus S & Muellbauer, John, 1980. "An Almost Ideal Demand System," American Economic Review, American Economic Association, vol. 70(3), pages 312-326, June.
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    Citations

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    Cited by:

    1. J. Klinger & J. Mateos-Garcia & K. Stathoulopoulos, 2018. "Deep learning, deep change? Mapping the development of the Artificial Intelligence General Purpose Technology," Papers 1808.06355, arXiv.org.
    2. Verstappen, Ksenia, 2018. "Economics of big data: review of best papers for January 2018," MPRA Paper 85520, University Library of Munich, Germany.
    3. Gordon H. Hanson, 2021. "Immigration and Regional Specialization in AI," NBER Working Papers 28671, National Bureau of Economic Research, Inc.
    4. Jens Prüfer & Patricia Prüfer, 2020. "Data science for entrepreneurship research: studying demand dynamics for entrepreneurial skills in the Netherlands," Small Business Economics, Springer, vol. 55(3), pages 651-672, October.
    5. Ajay Agrawal & Joshua Gans & Avi Goldfarb, 2019. "Economic Policy for Artificial Intelligence," Innovation Policy and the Economy, University of Chicago Press, vol. 19(1), pages 139-159.
    6. Davide Proserpio & John R. Hauser & Xiao Liu & Tomomichi Amano & Alex Burnap & Tong Guo & Dokyun (DK) Lee & Randall Lewis & Kanishka Misra & Eric Schwarz & Artem Timoshenko & Lilei Xu & Hema Yoganaras, 2020. "Soul and machine (learning)," Marketing Letters, Springer, vol. 31(4), pages 393-404, December.
    7. Lili Yan Ing & Gene Grossman & David Christian, 2022. "Digital Transformation:‘Development for All’?," Chapters, in: Lili Yan Ing & Dani Rodrik (ed.), New Normal, New Technologies, New Financing, chapter 7, pages 75-88, Economic Research Institute for ASEAN and East Asia (ERIA).
    8. Lee, Chien-Chiang & Yan, Jingyang, 2024. "Will artificial intelligence make energy cleaner? Evidence of nonlinearity," Applied Energy, Elsevier, vol. 363(C).
    9. Joel Klinger & Juan Mateos-Garcia & Konstantinos Stathoulopoulos, 2021. "Deep learning, deep change? Mapping the evolution and geography of a general purpose technology," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 5589-5621, July.
    10. Andrea Szalavetz, 2019. "Artificial Intelligence-Based Development Strategy in Dependent Market Economies - Any Room amidst Big Power Rivalry?," Central European Business Review, Prague University of Economics and Business, vol. 2019(4), pages 40-54.
    11. Dominic Chalmers & Niall G. MacKenzie & Sara Carter, 2021. "Artificial Intelligence and Entrepreneurship: Implications for Venture Creation in the Fourth Industrial Revolution," Entrepreneurship Theory and Practice, , vol. 45(5), pages 1028-1053, September.
    12. Li, Chengming & Xu, Yang & Zheng, Hao & Wang, Zeyu & Han, Haiting & Zeng, Liangen, 2023. "Artificial intelligence, resource reallocation, and corporate innovation efficiency: Evidence from China's listed companies," Resources Policy, Elsevier, vol. 81(C).
    13. Xueling Li & Xiaoyan Zhang & Yuan Liu & Yuanying Mi & Yong Chen, 2022. "The impact of artificial intelligence on users' entrepreneurial activities," Systems Research and Behavioral Science, Wiley Blackwell, vol. 39(3), pages 597-608, May.
    14. Lenz, Fulko, 2020. "Plattformökonomie – zwischen Abwehr und Wunschdenken," Zeitthemen 03, Stiftung Marktwirtschaft / The Market Economy Foundation, Berlin.
    15. Nils Grashof & Alexander Kopka, 2023. "Widening or closing the gap? The relationship between artificial intelligence, firm-level productivity and regional clusters," Bremen Papers on Economics & Innovation 2304, University of Bremen, Faculty of Business Studies and Economics.
    16. Aránzazu Guillán Montero & David Le Blanc, 2019. "Lessons for Today from Past Periods of Rapid Technological Change," Working Papers 158, United Nations, Department of Economics and Social Affairs.
    17. Kopka, Alexander & Grashof, Nils, 2022. "Artificial intelligence: Catalyst or barrier on the path to sustainability?," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    18. Alexander Kopka & Dirk Fornahl, 2024. "Artificial intelligence and firm growth — catch-up processes of SMEs through integrating AI into their knowledge bases," Small Business Economics, Springer, vol. 62(1), pages 63-85, January.
    19. Knudsen, Eirik Sjåholm & Lien, Lasse B. & Timmermans, Bram & Belik, Ivan & Pandey, Sujit, 2021. "Stability in turbulent times? The effect of digitalization on the sustainability of competitive advantage," Journal of Business Research, Elsevier, vol. 128(C), pages 360-369.

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    More about this item

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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