Responsibility Gaps, LLMs & Organisations: Many Agents, Many Levels, and Many Interactions.
In this article, we propose a business ethics-inspired approach to address the distribution dimension of responsibility gaps introduced by general-purpose AI models, particularly large language models (LLMs). We argue that the pervasive deployment of LLMs exacerbates the long-standing problem of “ma...
| Published in: | Science & Engineering Ethics Vol. 31; no. 6; pp. 1 - 25 |
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| Main Authors: | , |
| Format: | Article |
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Springer Nature
Dec2025
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| Subjects: | |
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=189377350&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 189377350 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 13533452 GNI jtl: Science & Engineering Ethics issn: 13533452 maglogo: N pubinfo: dt: Dec2025 vid: 31 iid: 6 pid: 237 pub: Springer Nature artinfo: ui: 189377350 10.1007/s11948-025-00560-1 ppf: 1 ppct: 24 formats: fmt: – @attributes: type: T – @attributes: type: P size: 1.1MB tig: atl: Responsibility Gaps, LLMs & Organisations: Many Agents, Many Levels, and Many Interactions. aug: au: Constantinescu, Mihaela Kaptein, Muel affil: https://ror.org/02x2v6p15 Research Center in Applied Ethics (CCEA), Faculty of Philosophy, University of Bucharest, Bucharest, Romania https://ror.org/057w15z03 Rotterdam School of Management, Erasmus University, Rotterdam, Netherlands su: Responsibility Language models Social responsibility of business Business ethics sug: subj: Responsibility Language models Social responsibility of business Business ethics keyword: General-purpose AI models Large language models Many hands problem Moral responsibility Responsibility gaps ab: In this article, we propose a business ethics-inspired approach to address the distribution dimension of responsibility gaps introduced by general-purpose AI models, particularly large language models (LLMs). We argue that the pervasive deployment of LLMs exacerbates the long-standing problem of “many hands” in business ethics, which concerns the challenge of allocating moral responsibility for collective outcomes. In response to this issue, we introduce the “many-agents-many-levels-many-interactions” approach, labelled M3, which addresses responsibility gaps in LLM deployment by considering the complex web of interactions among diverse types of agents operating across multiple levels of action. The M3 approach demonstrates that responsibility distribution is not merely a function of agents’ roles or causal proximity, but primarily of the range and depth of their interactions. Contrary to reductionist views that suggest such complexity inevitably diffuses responsibility to the point of its disappearance, we argue that these interactions provide normative grounds for safeguarding the attribution of responsibility to agents. Central to the M3 approach is identifying agents who serve as nodes of interaction and therefore emerge as key loci of responsibility due to their capacity to influence others across different levels. We position LLM-developing organisations as an example of such agents. As nodes of interactions, LLM-developing organisations exert substantial influence over other agents and should be attributed broader responsibility for harmful outcomes of LLMs. The M3 approach thus offers a normative and practical tool for bridging potential gaps in the distribution of responsibility for LLM deployment. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Science & Engineering Ethics is a copyright of Springer, 2025. All Rights Reserved. item: Science & Engineering Ethics holder: Springer Nature dt: @attributes: year: 2025 holdings: @attributes: islocal: N |
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