IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2504.01992.html
   My bibliography  Save this paper

Exploring the Societal and Economic Impacts of Artificial Intelligence: A Scenario Generation Methodology

Author

Listed:
  • Carlos J. Costa
  • Joao Tiago Aparicio

Abstract

This paper explores artificial intelligence's potential societal and economic impacts (AI) through generating scenarios that assess how AI may influence various sectors. We categorize and analyze key factors affecting AI's integration and adoption by applying an Impact-Uncertainty Matrix. A proposed methodology involves querying academic databases, identifying emerging trends and topics, and categorizing these into an impact uncertainty framework. The paper identifies critical areas where AI may bring significant change and outlines potential future scenarios based on these insights. This research aims to inform policymakers, industry leaders, and researchers on the strategic planning required to address the challenges and opportunities AI presents

Suggested Citation

  • Carlos J. Costa & Joao Tiago Aparicio, 2025. "Exploring the Societal and Economic Impacts of Artificial Intelligence: A Scenario Generation Methodology," Papers 2504.01992, arXiv.org.
    • Handle: RePEc:arx:papers:2504.01992
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2504.01992
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Roman Rakowski & Petra Kowaliková, 2024. "The political and social contradictions of the human and online environment in the context of artificial intelligence applications," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-8, December.
    2. Michael Gerlich, 2024. "Brace for Impact: Facing the AI Revolution and Geopolitical Shifts in a Future Societal Scenario for 2025–2040," Societies, MDPI, vol. 14(9), pages 1-17, September.
    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. Michael Gerlich, 2024. "Public Anxieties About AI: Implications for Corporate Strategy and Societal Impact," Administrative Sciences, MDPI, vol. 14(11), pages 1-25, November.
    2. Kaya-Kasikci, Sevgi & Glass, Chris R. & Camero, Eglis Chacon & Minaeva, Ekaterina, 2025. "University Positioning in AI Policies: Comparative Insights from National Policies and Non-State Actor Influences in China, the European Union, India, Russia, and the United States," SocArXiv a42rs_v1, Center for Open Science.

    More about this item

    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:arx:papers:2504.01992. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.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.