Arbeitspapier

The direction of technical change in AI and the trajectory effects of government funding

Government funding of innovation can have a significant impact not only on the rate of technical change, but also on its direction. In this paper, we examine the role that government grants and government departments played in the development of artificial intelligence (AI), an emergent general purpose technology with the potential to revolutionize many aspects of the economy and society. We analyze all AI patents filed at the US Patent and Trademark Office and develop network measures that capture each patent's influence on all possible sequences of follow-on innovation. By identifying the effect of patents on technological trajectories, we are able to account for the long-term cumulative impact of new knowledge that is not captured by standard patent citation measures. We show that patents funded by government grants, but above all patents filed by federal agencies and state departments, profoundly influenced the development of AI. These long-term effects were especially significant in early phases, and weakened over time as private incentives took over. These results are robust to alternative specifications and controlling for endogeneity.

Sprache
Englisch

Erschienen in
Series: LEM Working Paper Series ; No. 2021/41

Klassifikation
Wirtschaft
Innovation and Invention: Processes and Incentives
Technological Change: Choices and Consequences; Diffusion Processes
Technological Change: Government Policy
Network Formation and Analysis: Theory
Thema
R&D
Technical change
Government subsidies
Technology policy
General purpose technology

Ereignis
Geistige Schöpfung
(wer)
Iori, Martina
Martinelli, Arianna
Mina, Andrea
Ereignis
Veröffentlichung
(wer)
Scuola Superiore Sant'Anna, Laboratory of Economics and Management (LEM)
(wo)
Pisa
(wann)
2021

Handle
Letzte Aktualisierung
10.03.2025, 11:43 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Iori, Martina
  • Martinelli, Arianna
  • Mina, Andrea
  • Scuola Superiore Sant'Anna, Laboratory of Economics and Management (LEM)

Entstanden

  • 2021

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