IDEAS home Printed from https://ideas.repec.org/p/osf/socarx/vm43w.html
   My bibliography  Save this paper

How to Promote AI in the US Federal Government: Insights from Policy Process Frameworks

Author

Listed:
  • Khan, Muhammad Salar
  • Shoaib, Azka
  • Arledge, Elizabeth

Abstract

When it comes to routine government activities, such as immigration, justice, social welfare provision and climate change, many people believe that the US federal government operates slowly. One potential solution to increase the productivity and efficiency of the federal government is to adopt AI technologies and devices. AI technologies and devices already provide unique capabilities, services, and products, as demonstrated by smart homes, autonomous vehicles, delivery drones, GPS navigation, and virtual assistants such as Amazon's Alexa. However, incorporating massive AI into the US federal government would present several challenges, including ethical and legal concerns, outdated infrastructure, unprepared human capital, institutional obstacles, and a lack of social acceptance. How can US policymakers promote policies that increase AI usage in the face of these challenges? This will require a comprehensive strategy at the intersection of science, policy, and economics that addresses the aforementioned challenges. In this paper, we survey literature on the interrelated policy process to understand the advancement, or lack thereof, of AI in the US federal government, an emerging area of interest. To accomplish this, we examine several policy process frameworks, including the Advocacy Coalition Framework (ACF), Multiple Streams Approach (MSA), Punctuated Equilibrium Theory, Internal Determinants and Diffusion (ID&D), Narrative Policy Framework (NPF), and Institutional Analysis and Development (IAD). We hope that insights from this literature will identify a set of policies to promote AI-operated functionalities in the US federal government.

Suggested Citation

  • Khan, Muhammad Salar & Shoaib, Azka & Arledge, Elizabeth, 2023. "How to Promote AI in the US Federal Government: Insights from Policy Process Frameworks," SocArXiv vm43w, Center for Open Science.
    • Handle: RePEc:osf:socarx:vm43w
    DOI: 10.31219/osf.io/vm43w
    as

    Download full text from publisher

    File URL: https://osf.io/download/6446babdc76c074cc1135d4f/
    Download Restriction: no
    File URL: https://libkey.io/10.31219/osf.io/vm43w?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Kumar, Shashank & Raut, Rakesh D. & Queiroz, Maciel M. & Narkhede, Balkrishna E., 2021. "Mapping the barriers of AI implementations in the public distribution system: The Indian experience," Technology in Society, Elsevier, vol. 67(C).
    2. Daron Acemoglu & Pascual Restrepo, 2018. "Artificial Intelligence, Automation, and Work," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 197-236, National Bureau of Economic Research, Inc.
    3. Daron Acemoglu & Pascual Restrepo, 2018. "Artificial Intelligence, Automation and Work," Boston University - Department of Economics - Working Papers Series dp-298, Boston University - Department of Economics.
    4. Jenkins-Smith, Hank C. & Sabatier, Paul A., 1994. "Evaluating the Advocacy Coalition Framework," Journal of Public Policy, Cambridge University Press, vol. 14(2), pages 175-203, April.
    5. Christoph H. Loch & Bernardo A. Huberman, 1999. "A Punctuated-Equilibrium Model of Technology Diffusion," Management Science, INFORMS, vol. 45(2), pages 160-177, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gilbert Cette & Lorraine Koehl & Thomas Philippon, 2019. "The Labor Share in the Long Term: A Decline?," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Etudes Economiques (INSEE), issue 510-511-5, pages 35-51.
    2. Mahmut Ozer & Matjaž Perc, 2020. "Dreams and realities of school tracking and vocational education," Palgrave Communications, Palgrave Macmillan, vol. 6(1), pages 1-7, December.
    3. David Rezza Baqaee & Emmanuel Farhi, 2018. "Macroeconomics with Heterogeneous Agents and Input-Output Networks," NBER Working Papers 24684, National Bureau of Economic Research, Inc.
    4. Eleni Giouli & Pisinas Yorgos & Anna-Maria Kanzola, 2021. "Human Capital and Production Structure: Evidence from Greece," European Journal of Economics and Business Studies Articles, Revistia Research and Publishing, vol. 7, January -.
    5. Zilian, Laura S. & Zilian, Stella S. & Jäger, Georg, 2021. "Labour market polarisation revisited: evidence from Austrian vacancy data," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 55, pages 1-7.
    6. Keeheon Lee, 2021. "A Systematic Review on Social Sustainability of Artificial Intelligence in Product Design," Sustainability, MDPI, vol. 13(5), pages 1-29, March.
    7. Venturini, Francesco, 2022. "Intelligent technologies and productivity spillovers: Evidence from the Fourth Industrial Revolution," Journal of Economic Behavior & Organization, Elsevier, vol. 194(C), pages 220-243.
    8. Heyman, Fredrik & Olsson, Martin, 2022. "Long-Run Effects of Technological Change: The Impact of Automation and Robots on Intergenerational Mobility," Working Paper Series 1451, Research Institute of Industrial Economics, revised 29 Jun 2023.
    9. Gabriel López-Martínez & Francisco Eduardo Haz-Gómez & José Eulogio Real Deus, 2023. "Are You Really Your Own Boss? Flexi-Vulnerability and False Consciousness of Autonomy in the Digital Labor Culture of Riders," Social Sciences, MDPI, vol. 12(8), pages 1-18, July.
    10. Colombo, Emilio & Mercorio, Fabio & Mezzanzanica, Mario, 2019. "AI meets labor market: Exploring the link between automation and skills," Information Economics and Policy, Elsevier, vol. 47(C), pages 27-37.
    11. Lu, Jing & Xiao, Qinglan & Wang, Taoxuan, 2023. "Does the digital economy generate a gender dividend for female employment? Evidence from China," Telecommunications Policy, Elsevier, vol. 47(6).
    12. Alejandro Micco, 2019. "The Impact of Automation in Developed Countries," Working Papers wp480, University of Chile, Department of Economics.
    13. 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.
    14. Andreas Irmen, 2021. "Automation, growth, and factor shares in the era of population aging," Journal of Economic Growth, Springer, vol. 26(4), pages 415-453, December.
    15. Zhu, Jun & Zhang, Jingting & Feng, Yiqing, 2022. "Hard budget constraints and artificial intelligence technology," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    16. Gregory Casey & Ryo Horii, 2019. "A Multi-factor Uzawa Growth Theorem and Endogenous Capital-Augmenting Technological Change," ISER Discussion Paper 1051, Institute of Social and Economic Research, Osaka University.
    17. Henrik Schwabe & Fulvio Castellacci, 2020. "Automation, workers’ skills and job satisfaction," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-26, November.
    18. Belitski, Maksim & Korosteleva, Julia & Piscitello, Lucia, 2023. "Digital affordances and entrepreneurial dynamics: New evidence from European regions," Technovation, Elsevier, vol. 119(C).
    19. Chun Song & Lionel J. Beaulieu & Indraneel Kumar & Roberto Gallardo, 2023. "COVID-19-Induced Automation: An Exploratory Study of Critical Occupations," Economic Development Quarterly, , vol. 37(2), pages 183-197, May.
    20. Fran Stewart & Kathryn Kelley, 2020. "Connecting Hands and Heads: Retooling Engineering Technology for the “Smart†Manufacturing Workplace," Economic Development Quarterly, , vol. 34(1), pages 31-45, February.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:osf:socarx:vm43w. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: OSF (email available below). General contact details of provider: https://arabixiv.org .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.