Capraro, Valerio, Lentsch, Austin, Acemoglu, Daron, Akgun, Selin, Akhmedova, Aisel, Bilancini, Ennio, Bonnefon, Jean-François, Brañas-Garza, Pablo, Butera, Luigi, Douglas, Karen M., and others. (2024) The impact of generative artificial intelligence on socioeconomic inequalities and policy making. PNAS Nexus, 3 (6). Article Number pgae191. ISSN 2752-6542. (doi:10.1093/pnasnexus/pgae191) (KAR id:106230)
|
PDF
Publisher pdf
Language: English 
This work is licensed under a Creative Commons Attribution 4.0 International License.
|
|
|
Download this file (PDF/542kB) |
Preview |
| Request a format suitable for use with assistive technology e.g. a screenreader | |
| Official URL: https://doi.org/10.1093/pnasnexus/pgae191 |
|
Abstract
Generative artificial intelligence (AI) has the potential to both exacerbate and ameliorate existing socioeconomic inequalities. In this article, we provide a state-of-the-art interdisciplinary overview of the potential impacts of generative AI on (mis)information and three information-intensive domains: work, education, and healthcare. Our goal is to highlight how generative AI could worsen existing inequalities while illuminating how AI may help mitigate pervasive social problems. In the information domain, generative AI can democratize content creation and access but may dramatically expand the production and proliferation of misinformation. In the workplace, it can boost productivity and create new jobs, but the benefits will likely be distributed unevenly. In education, it offers personalized learning, but may widen the digital divide. In healthcare, it might improve diagnostics and accessibility, but could deepen pre-existing inequalities. In each section, we cover a specific topic, evaluate existing research, identify critical gaps, and recommend research directions, including explicit trade-offs that complicate the derivation of a priori hypotheses. We conclude with a section highlighting the role of policymaking to maximize generative AI's potential to reduce inequalities while mitigating its harmful effects. We discuss strengths and weaknesses of existing policy frameworks in the European Union, the United States, and the United Kingdom, observing that each fails to fully confront the socioeconomic challenges we have identified. We propose several concrete policies that could promote shared prosperity through the advancement of generative AI. This article emphasizes the need for interdisciplinary collaborations to understand and address the complex challenges of generative AI.
| Item Type: | Article |
|---|---|
| DOI/Identification number: | 10.1093/pnasnexus/pgae191 |
| Additional information: | For the purpose of open access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission. |
| Subjects: |
B Philosophy. Psychology. Religion B Philosophy. Psychology. Religion > BF Psychology |
| Divisions: | Divisions > Division of Human and Social Sciences > School of Psychology |
| Funders: |
National Science Foundation (https://ror.org/021nxhr62)
Google (United Kingdom) (https://ror.org/024bc3e07) Ministerio de Ciencia, Innovación y Universidades (https://ror.org/05r0vyz12) European Research Council (https://ror.org/0472cxd90) University of Turin (https://ror.org/048tbm396) |
| SWORD Depositor: | JISC Publications Router |
| Depositing User: | JISC Publications Router |
| Date Deposited: | 12 Jun 2024 12:07 UTC |
| Last Modified: | 26 Jun 2024 09:48 UTC |
| Resource URI: | https://kar.kent.ac.uk/id/eprint/106230 (The current URI for this page, for reference purposes) |
University of Kent Author Information
Douglas, Karen M..
| Creator's ORCID: |
 https://orcid.org/0000-0002-0381-6924
|
|---|---|
| CReDIT Contributor Roles: |
Everett, Jim A.C..
| Creator's ORCID: |
https://orcid.org/0000-0003-2801-5426
|
|---|---|
| CReDIT Contributor Roles: |
- Link to SensusAccess
- Export to:
- RefWorks
- EPrints3 XML
- BibTeX
- CSV
- Depositors only (login required):
Altmetric
Altmetric
