AI and the Opportunity for Shared Prosperity: Lessons from the History of Technology and the Economy

Guy Ben-Ishai, Jeff Dean, James Manyika, Ruth Porat, Hal Varian and Kent Walker

Papers from arXiv.org

Abstract: Recent progress in artificial intelligence (AI) marks a pivotal moment in human history. It presents the opportunity for machines to learn, adapt, and perform tasks that have the potential to assist people, from everyday activities to their most creative and ambitious projects. It also has the potential to help businesses and organizations harness knowledge, increase productivity, innovate, transform, and power shared prosperity. This tremendous potential raises two fundamental questions: (1) Will AI actually advance national and global economic transformation to benefit society at large? and (2) What issues must we get right to fully realize AI's economic value, expand prosperity and improve lives everywhere? We explore these questions by considering the recent history of technology and innovation as a guide for the likely impact of AI and what we must do to realize its economic potential to benefit society. While we do not presume the future will be entirely like that past, for reasons we will discuss, we do believe prior experience with technological change offers many useful lessons. We conclude that while progress in AI presents a historic opportunity to advance our economic prosperity and future wellbeing, its economic benefits will not come automatically and that AI risks exacerbating existing economic challenges unless we collectively and purposefully act to enable its potential and address its challenges. We suggest a collective policy agenda - involving developers, deployers and users of AI, infrastructure providers, policymakers, and those involved in workforce training - that may help both realize and harness AI's economic potential and address its risks to our shared prosperity.

Date: 2024-01, Revised 2024-02
New Economics Papers: this item is included in nep-ain, nep-ino and nep-tid
References: Add references at CitEc
Citations:

Downloads: (external link)
http://arxiv.org/pdf/2401.09718 Latest version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2401.09718

Access Statistics for this paper

More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators (help@arxiv.org).