Does Swarm Learning Solve Federation Opacity? The Need for Governance Beyond Decentralization.
The article focuses on the ethical and epistemic challenges posed by "federation opacity" in federated learning (FL), a machine learning approach where data remain decentralized and inaccessible for direct inspection by stakeholders. It discusses how FL’s distributed architecture complicates account...
| Publicado en: | American Journal of Bioethics Vol. 26; no. 8; pp. 136 - 140 |
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| Autores principales: | , , , , , , , |
| Formato: | commentary Journal Article |
| Publicado: |
Taylor & Francis Ltd
Aug2026
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=195895403&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 195895403 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 15265161 FKZ jtl: American Journal of Bioethics issn: 15265161 maglogo: N pubinfo: dt: Aug2026 vid: 26 iid: 8 pid: 377 pub: Taylor & Francis Ltd place: Philadelphia, Pennsylvania artinfo: ui: 195895403 195895403 195895403 10.1080/15265161.2026.2690963 195895403 ppf: 136 ppct: 4 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Does Swarm Learning Solve Federation Opacity? The Need for Governance Beyond Decentralization. aug: au: Bak, Marieke Warnat-Herresthal, Stefanie Willem, Theresa Zimmermann, Bettina Schulte-Schrepping, Jonas Ribeiro, Lucas Secchim Schultze, Joachim McLennan, Stuart affil: Technical University of Munich sug: subj: Federated Learning Decentralization Machine Learning Data Quality Professional Compliance Electronic Health Records Data Security ab: The article focuses on the ethical and epistemic challenges posed by "federation opacity" in federated learning (FL), a machine learning approach where data remain decentralized and inaccessible for direct inspection by stakeholders. It discusses how FL’s distributed architecture complicates accountability, data quality assessment, and vulnerability to attacks, despite its appeal for privacy in healthcare. The article then examines Swarm Learning (SL), a more decentralized alternative that removes the central aggregation server by using peer-to-peer coordination and blockchain technology, potentially enhancing auditability and reducing certain risks associated with FL. However, it emphasizes that both FL and SL require robust governance frameworks—covering data quality standards, responsibility, and fairness—to address ethical concerns, as technical decentralization alone does not resolve issues of transparency or accountability in medical machine learning. pubtype: Academic Journal doctype: commentary Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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