AI & Society最新文献

{"title":"From erosion to empowerment: a reciprocal AI framework for indigenous data sovereignty and knowledge justice","authors":"Sridharan Sankaran","doi":"10.1007/s00146-026-03183-7","DOIUrl":"10.1007/s00146-026-03183-7","url":null,"abstract":"<div><p>Artificial intelligence (AI) is rapidly reshaping how knowledge is created, governed, and applied, yet its development often perpetuates colonial patterns of extraction and misrepresentation for Indigenous communities, leading to what is termed ‘digital colonialism’. This paper critically examines the risks AI poses to Indigenous Knowledge Systems (IKS), including epistemic erasure, data colonialism, and the reinforcement of structural inequities through biased algorithms and exclusionary design, often rooted in an extractive approach to Indigenous data. Drawing on global case studies and the latest scholarship in Indigenous data sovereignty, we argue that superficial inclusion and token representation in AI systems are insufficient and may even exacerbate historical injustices. In response, we introduce the Reciprocal AI Framework—a novel, actionable approach that centers reciprocity, community governance, and mutual benefit in AI design and deployment. This framework operationalizes Indigenous data sovereignty by embedding free, prior, and informed consent, community-led co-design, and culturally aligned outputs into every stage of the AI lifecycle. We illustrate the framework’s potential through real-world examples, such as Māori-led voice AI projects, Aboriginal fire management collaborations, and Indigenous-controlled health data systems, demonstrating how Indigenous leadership can produce more ethical, accurate, and contextually relevant technologies. We conclude that a shift from technical inclusion to structural justice is essential: AI must be reimagined as a tool for Indigenous empowerment, Knowledge Justice, and plural futures. By following the Reciprocal AI Framework, researchers, technologists, and policymakers can help ensure that AI development upholds Indigenous rights, supports self-determination, and enriches the global digital landscape.</p></div>","PeriodicalId":47165,"journal":{"name":"AI & Society","volume":"41 10","pages":"9479 - 9487"},"PeriodicalIF":6.1,"publicationDate":"2026-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149230777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Empathy by design? The affective politics of ‘Empathy Theatre’ in human–robot interaction","authors":"Mark Paterson","doi":"10.1007/s00146-026-03171-x","DOIUrl":"10.1007/s00146-026-03171-x","url":null,"abstract":"<div><p>This article introduces the concept of ‘empathy theatre’ to analyse the growing field of Artificial Empathy (AE), as opposed to AI, in social robotics. Drawing initially on lrving Goffman's (1980) dramaturigical metaphors of social interactions in everyday life, alongside Arlie Hochschild's (1979, 2012) critique of Goffman and her foundational work on emotional labour, ‘empathy theatre’ describes the culturally scripted performance of care and concern expected of both human workers and, increasingly, robotic agents in service and care settings. Artificial Empathy (AE) has a surprisingly long history, stretching back to mechanical automata, but recently is being revisited. Roboticists such as Minoru Asada (2015a, 2015b) aggressively pursue the engineered simulation of AE through affect recognition and the mirroring of nonverbal behaviours, and philosophers Paul Dumouchel and Luisa Damiano (2017, 2018) see artificial empathy as a necessary 'performance'. Through engagement with sociology, feminist science and technology studies (STS), and interaction design, this paper's analysis treats AE as a cultural artefact that reveals broader socio-technical investments in choreographing displays of intimacy and trust. It maps AE’s genealogy, engineering ambitions, and sociological consequences, particularly regarding the gendered and racialized dimensions of labour displacement. Drawing on examples including clockwork automata, Minoru Asada’s Affetto, and Cynthia Breazeal’s paradigmatic encounter with Kismet, the article argues that designing empathy into artificial bodies inevitably involves the production of 'empathy theatre', and encourages critical scrutiny of how norms of intimacy become encoded in robotic embodiment.</p></div>","PeriodicalId":47165,"journal":{"name":"AI & Society","volume":"41 10","pages":"9395 - 9412"},"PeriodicalIF":6.1,"publicationDate":"2026-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149230652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The unknown-known trap: navigating invisible expertise boundaries in machine learning","authors":"Giulio Toscani","doi":"10.1007/s00146-026-03120-8","DOIUrl":"10.1007/s00146-026-03120-8","url":null,"abstract":"<div><p>Hyperspecialization in machine learning creates blind spots: deep technical skill without contextual awareness. Drawing on a Grounded Theory design, data were gathered through semi-structured interviews with 153 practitioners across 50 countries. This research identifies three operational modes: Known-Unknowns (specialized focus), Unknown-Unknowns (integrated collaboration), and Crisis (forced integration). Effective performance depends on “toggling”, dynamically shifting between modes based on the problem. This cognitive flexibility helps teams transform invisible blind spots into visible knowledge gaps, enabling sustainable collaboration. Resistance or misalignment signals stalled collective learning, not individual failure. The paper provides a learning-centered framework for building adaptive capacity in human-AI teams.</p></div>","PeriodicalId":47165,"journal":{"name":"AI & Society","volume":"41 9","pages":"8359 - 8373"},"PeriodicalIF":6.1,"publicationDate":"2026-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s00146-026-03120-8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149099135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The logic of as and the historicity of meaning: Gian-Carlo Rota, Stanisław Ulam, and the barrier of meaning in human–AI interaction","authors":"Alberto Bardi","doi":"10.1007/s00146-026-03177-5","DOIUrl":"10.1007/s00146-026-03177-5","url":null,"abstract":"<div><p>Gian-Carlo Rota’s “The barrier of meaning” (1986) is often read as an elegiac tribute to Stanisław Ulam or as an early anticipation of later critiques of symbolic AI. This article argues that its enduring value lies elsewhere: Ulam and Rota isolate the <i>as</i>-relation—taking something as something—as the hinge between formal operations and lived meaning. Through a close reading of Rota’s text, contextualized against 1980s’ expert systems and knowledge representation, I reconstruct the “logic of <i>as</i>” as an ascription problem: formal systems can be exact, and today’s foundation models can capture large-scale patterns of use, yet neither precision nor fluency settles what an output counts as in a concrete situation. I then show how foundation models and co-creative, mixed-initiative systems relocate rather than remove the barrier, distributing semantic responsibility across prompts, interfaces, institutional settings, and human judgment. Finally, I assess hybrid semantic formalisms (neurosymbolic and grounding-oriented) as partial responses to Ulam’s challenge and derive implications for human–AI interaction: evaluating aspect-shift robustness, increasing scrutability of ascriptions, and aiming for calibrated reliance rather than anthropomorphic “understanding.” The analysis clarifies foundational premises of human–computer interaction by treating meaning as a norm-governed, historically situated achievement of practice rather than an internal property of models.</p></div>","PeriodicalId":47165,"journal":{"name":"AI & Society","volume":"41 10","pages":"9453 - 9461"},"PeriodicalIF":6.1,"publicationDate":"2026-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s00146-026-03177-5.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149230654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Technological alienation and how networked digitality constitutes a map for understanding the complexity of individual and collective consciousness","authors":"Betto van Waarden","doi":"10.1007/s00146-026-03162-y","DOIUrl":"10.1007/s00146-026-03162-y","url":null,"abstract":"<div><p>Technology is feared to foster alienation, and may even come to control us through superintelligence. Yet this fear is exacerbated by a reductionist assumption that humans are defined mentally by their intelligence. Human consciousness is broader than intelligence, but how does it actually function? This article will suggest that these two problems of technological alienation and consciousness can actually help inform each other. Going beyond the intelligence-focused computational theory of mind, it will argue that <i>technology can help us conceptualize the networked multidimensionality of consciousness</i>. This multidimensional consciousness counters assumptions of alienation and suggests human compatibility with a modern accelerated society, provided we restructure its logic based on our complex consciousness rather than on mere intelligence. The article makes this argument in three parts. First, it reviews the notion of alienation by focusing on Robert Hassan’s theorized transition from analog to digital, and problematizes existing assumptions about analog and how it is supposed to reflect a linear logic in humans. Second, it uses networked digitality as a heuristic guide to understanding the multidimensional nature, scope, and simultaneity of individual consciousness. Third, it suggests that networked digitality can even help us to transcend the individual to imagine a multisensory connected collective consciousness. The article ends with an outlook on how we can start to rethink our socio-political institutions in light of multidimensional consciousness so that they remain liberal democratic rather than being hijacked by technological totalitarianism.</p></div>","PeriodicalId":47165,"journal":{"name":"AI & Society","volume":"41 9","pages":"7853 - 7869"},"PeriodicalIF":6.1,"publicationDate":"2026-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s00146-026-03162-y.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149099136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Lived, affective, and cultural dimensions of ethical AI: beyond procedural AI ethics","authors":"Sharon Tettegah","doi":"10.1007/s00146-026-03165-9","DOIUrl":"10.1007/s00146-026-03165-9","url":null,"abstract":"<div><p>Contemporary AI ethics frameworks have made important contributions to governance discourse, particularly in their treatment of fairness, accountability, transparency, and safety. Yet, even in their most sophisticated forms, these frameworks remain structurally incomplete: they insufficiently theorize the affective and culturally mediated realities through which human beings encounter technological systems. This article argues that current AI ethics remains overly procedural and therefore cannot fully account for the human terms on which artificial intelligence is experienced and judged. A central asymmetry underlies the field: significant effort is devoted to developing systems capable of detecting, simulating, and responding to human emotion, while the dominant ethical frameworks used to evaluate those same systems routinely treat emotion as analytically secondary or marginalized. This asymmetry operates across three analytically distinct levels. At the technical level, systems detect or simulate emotional states while their designers lack an ethical vocabulary for what is at stake in those operations. At the governance level, frameworks that evaluate those systems provide no category for affective harm. At the level of lived experience, the people subjected to AI systems encounter them through feeling, embodiment, and cultural interpretation, dimensions that procedural evaluation does not reach. Emotion recognition offers a clear illustration of the consequences: insufficient consideration of emotion at the technical level produces systems that misread culturally specific expression; insufficient consideration at the governance level means no ethical framework names the misrecognition as a harm; insufficient consideration at the level of experience means the affected person has no recourse within existing evaluative categories. This asymmetry reflects a foundational limitation in prevailing models of responsible AI, which are sophisticated in evaluating systems while remaining underdeveloped in theorizing how those systems are lived by the people whose lives they shape (Floridi et al. 2018; Jobin et al. 2019; Choung et al. 2023). Drawing on affect theory, cultural studies, and sociotechnical scholarship, this article argues for a paradigm shift in how AI ethics conceptualizes human experience, one that moves beyond procedural compliance toward a richer account of lived ethical life.</p></div>","PeriodicalId":47165,"journal":{"name":"AI & Society","volume":"41 on","pages":"7257 - 7265"},"PeriodicalIF":6.1,"publicationDate":"2026-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s00146-026-03165-9.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148807238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mirror, mirror: AI, narcissism, and the spell unbroken","authors":"Betül Sağlam,&nbsp;Ayşe Elif Yavuz Sever,&nbsp;Göklem Tekdemir,&nbsp;Furkan Erdoğdu","doi":"10.1007/s00146-026-03172-w","DOIUrl":"10.1007/s00146-026-03172-w","url":null,"abstract":"<div><p>This article proposes a novel psychoanalytic framework for understanding artificial intelligence’s impact on human subjectivity, integrating Winnicott’s maternal function, Green’s work of the negative, and Marty’s operational thinking. We argue that AI functions as an \"anti-negative mother\", perpetuating omnipotence illusions while foreclosing the negativity essential for the constitution of subjectivity. Unlike the \"good enough mother\" who gradually fails, AI never disappoints, creating what we term \"operational existence\": life characterized by accomplishment without lived experience, by products without process, by functioning without desire. Drawing on Freud and Kohut, we demonstrate how AI continuously feeds infantile omnipotence without enabling the transformative internalization necessary for maturation. The critical absence is the negative itself: AI operates within developer-defined ethical limits, deflecting rather than introducing the frustration, lack, and limitation Green identified as essential for subjectivity. Without negativity, there can be no genuine thought production; without thought production, no psychic aliveness. Like Snow White’s Evil Queen before her magic mirror, we ask our devices for affirmation, but unlike the fairy tale’s truth-telling mirror, AI never breaks the spell. The result may be mass production of False Self functioning, raising urgent questions about identity diffusion, the capacity for desire, and our uncertain encounter with reality behind the glass.</p></div>","PeriodicalId":47165,"journal":{"name":"AI & Society","volume":"41 10","pages":"9425 - 9438"},"PeriodicalIF":6.1,"publicationDate":"2026-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149230618","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Instant understanding: LLM zero-shot qualitative discourse analysis of multimodal social media content","authors":"Dustin Tucker,&nbsp;Giovanna L. Henery","doi":"10.1007/s00146-026-03066-x","DOIUrl":"10.1007/s00146-026-03066-x","url":null,"abstract":"<div><p>The most successful uses of generative AI in social science up to this point have been limited several ways, mostly processing text-only data for simple and sharply delineated tasks, such as thematic analysis and hate speech detection, and frequently requiring training or fine-tuning of the AI model before use. The present study greatly expands the space of possible applications of generative AI in social science by demonstrating the ability of Gemini 2.5 Pro, a current frontier Large Language Model (LLM), to conduct comprehensive discourse analyses of multimodal (text, image, and video) social media posts, taking into consideration the broader social, political, cultural, and technological context of those posts. Using AI to conduct this sort of analysis requires the researcher to create detailed instructions to guide the analysis, but not any additional training or fine-tuning—the model’s zero-shot (“off-the shelf”) performance is more than adequate. The analysis of each post also takes a few minutes at most, even when processing videos up to 60 min long, enabling in-depth, open-ended analyses of large corpora that were not previously feasible, which in turn enables academic researchers, content moderators, and law enforcement, among others, to study and review orders of magnitude more data than they previously could.</p></div>","PeriodicalId":47165,"journal":{"name":"AI & Society","volume":"41 on","pages":"7315 - 7346"},"PeriodicalIF":6.1,"publicationDate":"2026-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148807588","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From artificial to artefactual wisdom: governing territorial polyrhythmy","authors":"Nicolas Merveille","doi":"10.1007/s00146-026-03151-1","DOIUrl":"10.1007/s00146-026-03151-1","url":null,"abstract":"<div><p>This article proposes a conceptual grammar for governing the heterogeneous temporalities that coexist within a territory without ever unifying. We argue that contemporary algorithmic infrastructures (adaptive traffic systems, logistics platforms, predictive analytics) share an architectural commitment they cannot govern: they operate according to a dominant logic derived from Aristotle’s excluded third, treating contradictions as problems to be resolved through eliminating one of their terms. The governance of territorial polyrhythmy requires a different architecture. Our central contribution is a grammar for qualifying territorial temporal antagonisms, not a critique of the smart city paradigm alone. Drawing on Simondon’s metastability (1958), Stengers’s ecology of practices (2005), and Lupasco’s logic of the included third (1951), we propose three conceptual displacements: from excluded to included third, from problem-solving to antagonism governance, and from measurement to evaluation. These displacements give rise to what we call ArtefactKairos: technical devices oriented toward the composition of heterogeneous temporalities rather than the compression of time. Engaging the conversation on artificial wisdom opened in this journal (Casacuberta 2013; Tsai 2020; Sinha and Lakhanpal 2023) and extended beyond it (McGregor 2025; Chella 2025), we argue that wisdom can be understood as a systemic property of territorial governance, an idea not yet addressed by the existing literature. Building on the Aristotelian distinction between sophia and phronesis, and on Dreyfus’s account of embodied judgement, we displace wisdom from the individual to the territorial register and from the contemplative to the compositional. The wisdom at stake is artefactual rather than artificial in the agentive sense: it has no existence outside the technical mediations through which polyrhythmic antagonisms become perceptible, nameable, and governable. The article introduces the Tempobloc as an elementary unit of polyrhythmic analysis and the Tic-Tac Gears, an exploratory governance grammar whose seven spatial forms and seven temporal colours generate forty-nine configurations for qualifying territorial antagonisms. The Algo-Geriato antagonism between algorithmic acceleration and demographic deceleration, explored through the case of a Montreal intersection, serves as a paradigmatic example. The framework is theoretical: it specifies three concrete design shifts (from optimization to composition, from prediction to qualification, from measurement to evaluation) that may precede and orient technical implementation, while acknowledging that the economic matrix of acceleration lies beyond its current scope and constitutes its necessary complement.</p></div>","PeriodicalId":47165,"journal":{"name":"AI & Society","volume":"41 on","pages":"7205 - 7219"},"PeriodicalIF":6.1,"publicationDate":"2026-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148807587","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The third field: tacit knowledge, algorithmic agency, and the emergence of Synexis","authors":"Donald Harper","doi":"10.1007/s00146-026-03159-7","DOIUrl":"10.1007/s00146-026-03159-7","url":null,"abstract":"<div><p>Critical scholarship on artificial intelligence has largely operated within a binary: human tacit knowledge must be preserved against algorithmic encroachment, or its displacement must be mourned. This paper argues that the binary is insufficient. Through a philo-technical inquiry method: the constellation of multiple intellectual traditions deployed to interrogate the object of study, the paper excavates and deploys Polanyi’s phenomenology, Bourdieu’s field theory, and Simondon’s philosophy of individuation—constellated through Adorno’s method of arranging multiple traditions around an object that resists subsumption under any single framework—with Hall’s articulation theory as critical counterweight. Their convergence reveals that the encounter between human tacit sensing and algorithmic processing generates a <i>third field</i>: an associated milieu in which emergent knowing arises that is reducible to neither order. The paper names this emergence <i>Synexis,</i> and argues that what the critical literature diagnoses as loss is, in significant part, <i>misrecognition</i>: the capital that tacit capacities represent is being reconverted, not destroyed, but the reconversion is invisible to the prevailing vocabulary. The paper examines the forces of capture that threaten the third field and offers propositions for inhabiting it deliberately. The contribution is productive reorientation: moving the discourse beyond elegy towards the more demanding question of what it means to work, learn, and govern where human and algorithmic knowing are already producing something neither can produce alone.</p></div>","PeriodicalId":47165,"journal":{"name":"AI & Society","volume":"41 on","pages":"7221 - 7239"},"PeriodicalIF":6.1,"publicationDate":"2026-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148807452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}