IDEAS home Printed from https://ideas.repec.org/p/osf/socarx/mtz4d_v1.html

Policy-driven innovation: The science-policy nexus in artificial intelligence research in Germany

Author

Listed:
  • Cruz Romero, Roberto

    (Deutches Zentrum für Hochschul- und Wissenschaftsforschung (DZHW))

  • Stahlschmidt, Stephan

Abstract

This study reconstructs and characterises the science-policy nexus in the field of artificial intelligence research in Germany, examining the alignment between normative policy goals and empirical research outcomes. Adopting a narrative policy framework, the research investigates transition dynamics across policy, scholarly, and innovation levels, tracing the interconnectedness in stages of patents, papers, and publicly funded projects. The research employs a two-pronged empirical approach: 1) identifying German contributions to AI research through patent citations and bibliometric data, and 2) linking these outputs to the policy instances that funded and enabled them. This methodology reveals the complex pathways through which policy intentions translate into research outcomes, highlighting the mostly indirect nature of this relationship. Key findings emphasise significant challenges in data quality and availability, particularly in linking research outputs to higher-level policy dimensions. While the study successfully identifies German-affiliated papers through patent and bibliometric datasets, it uncovers fundamental disconnections between stated policy objectives and actual research trajectories. These dimensions are compounded by administrative bottlenecks, asynchronous implementation settings, and entangled funding periods. The study concludes that AI development is heavily influenced by geopolitical and strategic decisions extending beyond academia, and that academic research into AI is part of a larger narrative of policy and political design. The study offers a framework for assessing the nuances of science-policy pathways while acknowledging the limitations of fully characterising this nexus. The systematisation presented serves as a foundation for future research, emphasising the need for comprehensive and coherent data sources to evaluate the phases and connections within scholarly and policy narratives.

Suggested Citation

  • Cruz Romero, Roberto & Stahlschmidt, Stephan, 2026. "Policy-driven innovation: The science-policy nexus in artificial intelligence research in Germany," SocArXiv mtz4d_v1, Center for Open Science.
  • Handle: RePEc:osf:socarx:mtz4d_v1
    DOI: 10.31219/osf.io/mtz4d_v1
    as

    Download full text from publisher

    File URL: https://osf.io/download/69aaa27eb4fc5ffb04e7d15c/
    Download Restriction: no

    File URL: https://libkey.io/10.31219/osf.io/mtz4d_v1?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
    ---><---

    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:osf:socarx:mtz4d_v1. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.