{"title":"Global, selective, or both? The case for differentiated cooperation in AI governance","authors":"Nora von Ingersleben-Seip, Daniel Mügge","doi":"10.1007/s11077-026-09606-y","DOIUrl":null,"url":null,"abstract":"Current debates about international cooperation in AI governance remain both simplistic and muddled, pitting global forms of collaboration against selective alliances among “like-minded countries”. We propose a more nuanced and systematic approach to cooperative AI governance based on three considerations. First, different kinds of governance issues lend themselves to different kinds of cooperation. Second, not all AI is created equally: different kinds of AI raise different governance challenges, thus requiring varied forms of cooperation. Third, the same is true for the development and deployment phases of AI systems. Integrating these three factors, we explain why some challenges can only be addressed through global cooperation, while for others selective cooperation is an equally effective, or even more effective, solution. In consequence, governments should not insist on either global or selective cooperation. Instead, they should opt for the scope of collaboration that is most effective for solving any particular governance issue at hand.","PeriodicalId":51433,"journal":{"name":"Policy Sciences","volume":"32 1","pages":""},"PeriodicalIF":4.5000,"publicationDate":"2026-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Policy Sciences","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1007/s11077-026-09606-y","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PUBLIC ADMINISTRATION","Score":null,"Total":0}
引用次数: 0
Abstract
Current debates about international cooperation in AI governance remain both simplistic and muddled, pitting global forms of collaboration against selective alliances among “like-minded countries”. We propose a more nuanced and systematic approach to cooperative AI governance based on three considerations. First, different kinds of governance issues lend themselves to different kinds of cooperation. Second, not all AI is created equally: different kinds of AI raise different governance challenges, thus requiring varied forms of cooperation. Third, the same is true for the development and deployment phases of AI systems. Integrating these three factors, we explain why some challenges can only be addressed through global cooperation, while for others selective cooperation is an equally effective, or even more effective, solution. In consequence, governments should not insist on either global or selective cooperation. Instead, they should opt for the scope of collaboration that is most effective for solving any particular governance issue at hand.
期刊介绍:
The policy sciences are distinctive within the policy movement in that they embrace the scholarly traditions innovated and elaborated by Harold D. Lasswell and Myres S. McDougal. Within these pages we provide space for approaches that are problem-oriented, contextual, and multi-method in orientation. There are many other journals in which authors can take top-down, deductive, and large-sample approach or adopt a primarily theoretical focus. Policy Sciences encourages systematic and empirical investigations in which problems are clearly identified from a practical and theoretical perspective, are well situated in the extant literature, and are investigated utilizing methodologies compatible with contextual, as opposed to reductionist, understandings. We tend not to publish pieces that are solely theoretical, but favor works in which the applied policy lessons are clearly articulated. Policy Sciences favors, but does not publish exclusively, works that either explicitly or implicitly utilize the policy sciences framework. The policy sciences can be applied to articles with greater or lesser intensity to accommodate the focus of an author’s work. At the minimum, this means taking a problem oriented, multi-method or contextual approach. At the fullest expression, it may mean leveraging central theory or explicitly applying aspects of the framework, which is comprised of three principal dimensions: (1) social process, which is mapped in terms of participants, perspectives, situations, base values, strategies, outcomes and effects, with values (power, wealth, enlightenment, skill, rectitude, respect, well-being, and affection) being the key elements in understanding participants’ behaviors and interactions; (2) decision process, which is mapped in terms of seven functions—intelligence, promotion, prescription, invocation, application, termination, and appraisal; and (3) problem orientation, which comprises the intellectual tasks of clarifying goals, describing trends, analyzing conditions, projecting developments, and inventing, evaluating, and selecting alternatives. There is a more extensive core literature that also applies and can be visited at the policy sciences website: http://www.policysciences.org/classicworks.cfm. In addition to articles that explicitly utilize the policy sciences framework, Policy Sciences has a long tradition of publishing papers that draw on various aspects of that framework and its central theory as well as high quality conceptual pieces that address key challenges, opportunities, or approaches in ways congruent with the perspective that this journal strives to maintain and extend.Officially cited as: Policy Sci