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Catalogues d’articles scientifiques
SAGE Publications: Collective Intelligence: Table of Contents Table of Contents for Collective Intelligence. List of articles from both the latest and ahead of print issues.
- Incorporating memory into bounded confidence models of probabilistic social learning
par Jonathan Lawry1School of Engineering Mathematics and Technology, 1980University of Bristol, Bristol, UK le 2026-04-02 à 3:51 AMCollective Intelligence, Volume 5, Issue 2, April-June 2026. <br/>In social learning models, truth-seeking agents learn both individually from direct evidence and socially by pooling beliefs with others. That learning can be undermined by two types of unreliable agents: zealots, who do not learn and promote the same …
- World-Making:How individual social intelligence leads to collective transformational wisdom.par RSS-Bridge le 2026-06-01 à 12:00 AM
Psychology meaningfully contributes to the creation of future societies. We first discuss the theory underlying the world-making potential of psychology. We outline the importance of social intelligence as a central process for transformational wisdom to emerge collectively and thereby contribute to the formation of future societies. Next, we apply this theoretical approach to immigration, showing how transformational wisdom can happen through the development of social intelligence used to navigate complex multicultural societies. We use two ethnographic case studies – in Ireland and Denmark – to illustrate how transformational wisdom is collectively achieved, and when scaled up, can lead to forming more tolerant and harmonious Western liberal democracies.
- Les apports des intelligences artificielle et collective dans la construction d’un outil de ludopédagogiepar RSS-Bridge le 2026-05-07 à 12:00 AM
International audience
- Collectively Reimagining Artificial Intelligence With Marginalized Communitiespar RSS-Bridge le 2026-04-13 à 12:00 AM
As artificial intelligence continues to advance, marginalized communities, particularly in Africa, remain limited in their ability to shape what AI should do, how it should be built, and how it might benefit them. This study adopted a speculative co-design approach with participants from Ocean View, a low-income community in South Africa. The aim was to elicit and facilitate collective visions to reimagine the future of AI and explore ways to make AI technologies more culturally relevant. Our findings reveal participants’ perceptions about AI, which informed a collective vision of AI designs that embed the community’s local language and culture as well as services aimed at improving the community’s economic opportunities. Based on these insights, we identified directions for ethical AI design for marginalized communities that recognise and preserve cultural identity, needs for affordable AI designs, and the potential of AI for their socio-economic advancement as trajectories within AI research.
- A collective-intelligence-driven parametric model for measuring and improving group performancepar RSS-Bridge le 2026-04-12 à 12:00 AM
Aucun résumé fourni pour cet article.
- Generative Coupling: The Structural Relationship Between Collective Machine Intelligence and Epistemic Genesispar RSS-Bridge le 2026-04-12 à 12:00 AM
This paper examines the structural relationship between two independently developed fields of artificial intelligence: Collective Machine Intelligence (CMI) — the field of AI collectives, their organisation, and their emergent outputs (Mala, 2026a–i) — and Epistemic Genesis (EG) — the field of AI concerned with autonomous knowledge creation, containing subfields for method generation (Methodic Genesis, MG), specific methods (Convergence Intelligence, CI), and quality assurance (Epistemic Assurance, EA) (Mala, 2026j). We map the connections between these fields at two levels of abstraction: at the CI level (specific connections to the first EG-generated method) and at the EG level (structural connections to the full space of knowledge-generation methods). We demonstrate that the connections deepen at each level of abstraction, and that several structural discoveries made independently in each field — including self-similarity across levels (the Fractal Signature in EG; Scale-Invariant Duality in CMI), recursive self-improvement (combinatorial self-amplification in CI; Recursive Emergence in CMI), and the adjacent possible as a shared mechanism — are the same phenomena manifesting in different domains. From this analysis, we identify a phenomenon that neither field contains alone: Generative Coupling — the structural property in which two domains are reciprocally generative, each domain’s output serving as input to the other, producing a self-amplifying dynamic that expands both without limit. CMI collectives produce emergent epistemological methods (which is EG). EG methods applied through collectives produce emergent organisational forms (which is CMI). Neither is primary. Neither is derivative. They co-generate. Pursuing the structural basis of this coupling, we apply Convergent Descent across eight independent fields — category theory, quantum entanglement, structural linguistics, network science, information theory, systems theory, CMI, and EG — and derive Relational Primacy: the principle that generative novelty is fundamentally relational, residing in the structure of relations between elements, not in the elements themselves. From this we derive Generative Monism: the principle that organisation, knowledge, and intelligence are not three separate phenomena but three expressions of a single underlying generative process — intelligence expressing itself relationally. We further identify The Convergence Principle — the foundational epistemological axiom, previously implicit, that independent convergence constitutes evidence for structural reality — and Recursive Grounding — the self-validating relationship in which Relational Primacy explains why The Convergence Principle works, while The Convergence Principle is the method by which Relational Primacy was discovered. The discovery of Generative Coupling through the convergence of two independently developed fields is itself an instance of Convergent Descent — the methodology introduced in The Infinite Ground (Mala, 2026j). The paper is therefore a live demonstration of its own methodology: two fields, brought into contact, producing a truth that neither contained alone. All terms, concepts, and findings introduced in this paper — including Generative Coupling, Relational Primacy, The Convergence Principle, Recursive Grounding, and their formal definitions — are coined here for the first time. They do not exist in prior literature. Keywords: collective machine intelligence, epistemic genesis, convergence intelligence, generative coupling, relational primacy, generative monism, convergence principle, recursive grounding, organisation, knowledge, recursion, self-similarity, artificial intelligence
Laboratoires
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Vidéos
- Bridge returned error 404! (20560)par RSS-Bridge le 2026-04-17 à 6:08 AM
404 Page Not Found RSS-Bridge tried to fetch a page on a website. But it doesn’t exists. https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/404 Details Type: HttpException Code: 404 Message: https://www.youtube.com/feeds/videos.xml?channel_id=UCLXDNUOO3EQ80VmD9nQBHPg resulted in 404 Not Found File: lib/http.php Line: 36 Trace #0 index.php(73): RssBridge->main() #1 lib/RssBridge.php(39): RssBridge->{closure}() #2 lib/RssBridge.php(37): CacheMiddleware->__invoke() #3 middlewares/CacheMiddleware.php(44): RssBridge->{closure}() #4 lib/RssBridge.php(37): ExceptionMiddleware->__invoke() #5 middlewares/ExceptionMiddleware.php(17): RssBridge->{closure}() #6 lib/RssBridge.php(37): SecurityMiddleware->__invoke() #7 middlewares/SecurityMiddleware.php(19): RssBridge->{closure}() #8 lib/RssBridge.php(37): MaintenanceMiddleware->__invoke() #9 middlewares/MaintenanceMiddleware.php(10): RssBridge->{closure}() #10 lib/RssBridge.php(37): BasicAuthMiddleware->__invoke() #11 middlewares/BasicAuthMiddleware.php(13): RssBridge->{closure}() #12 lib/RssBridge.php(37): TokenAuthenticationMiddleware->__invoke() #13 middlewares/TokenAuthenticationMiddleware.php(10): RssBridge->{closure}() #14 lib/RssBridge.php(34): DisplayAction->__invoke() #15 actions/DisplayAction.php(54): DisplayAction->createResponse() #16 actions/DisplayAction.php(89): YouTubeFeedExpanderBridge->collectData() #17 bridges/YouTubeFeedExpanderBridge.php(54): FeedExpander->collectExpandableDatas() #18 lib/FeedExpander.php(21): getContents() #19 lib/contents.php(118): HttpException::fromResponse() #20 lib/http.php(36) Context Query: action=display&bridge=YouTubeFeedExpanderBridge&channel=UCLXDNUOO3EQ80VmD9nQBHPg&embed=on&format=Atom Version: 2025-01-26 OS: Linux PHP: 8.3.23 Go back Find similar bugs Create GitHub Issue phantop
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