The study of human-AI collaboration has reached an inflection point, with 17 scholars across philosophy, STS, law, and information science now producing work that directly theorizes how humans and intelligent machines can work together. This bibliography captures the most recent publications from foundational thinkers whose frameworks—from extended mind theory to algorithmic accountability—now converge on the central question of our time: how should human and artificial intelligence relate?
Philosophy of mind and consciousness
David J. Chalmers University Professor of Philosophy and Neural Science, New York University Co-Director, Center for Mind, Brain, and Consciousness
Most Recent Major Publication: Chalmers, David J. "Could a Large Language Model Be Conscious?" ArXiv 2303.07103 (2023, updated August 2024). https://arxiv.org/abs/2303.07103
Chalmers addresses the question that underlies all human-AI collaboration ethics: whether AI systems might possess consciousness and therefore moral status. He identifies key obstacles—lack of recurrent processing, absence of global workspace dynamics, no unified agency—but concludes these may be surmountable in the near future. His framework distinguishes between consciousness as phenomenal experience versus functional behavior, providing essential conceptual tools for evaluating AI collaborators. The paper has been downloaded over 26,000 times on PhilArchive, reflecting its centrality to current debates.
Andy Clark Professor of Cognitive Philosophy, University of Sussex, UK Affiliated with Sackler Centre for Consciousness Science
Most Recent Major Publication: Clark, Andy. "Extending Minds with Generative AI." Nature Communications 16, Article 4627 (May 19, 2025). https://doi.org/10.1038/s41467-025-59906-9
Clark's 2025 article is perhaps the most direct theoretical treatment of human-AI collaboration from a major philosopher. Applying his influential extended mind thesis to generative AI, he argues humans are "natural-born cyborgs" whose cognitive boundaries have always extended beyond the biological brain. AI tools like ChatGPT can become genuine cognitive extensions—part of hybrid thinking systems. He advocates developing "extended cognitive hygiene" and new epistemological frameworks, warning against both uncritical acceptance and dismissive fear. Supported by ERC Synergy Grant (XSCAPE) with 46,000+ accesses since publication.
Douglas R. Hofstadter College of Arts and Sciences Distinguished Professor, Indiana University Bloomington Director, Center for Research on Concepts and Cognition; Director, Fluid Analogies Research Group
Most Recent Major Publication: Hofstadter, Douglas R. Ambigrammia Between Creation and Discovery (ABCD). New Haven: Yale University Press, 2025. 320 pp.
Hofstadter has undergone a dramatic revision of his views on AI. In widely discussed 2023 interviews, he described being "terrified" by LLM capabilities, stating that GPT-4 made some of his "core beliefs" from Gödel, Escher, Bach "collapse." He now acknowledges the human mind may be "not so mysterious and complex" as he believed. His concerns about AI's potential to "undermine the nature of truth" are crucial warnings for human-AI collaboration: can collaborative systems preserve genuine human creativity and authentic truth-seeking?
Susan Schneider William F. Dietrich Distinguished Professor of Philosophy, Florida Atlantic University Founding Director, Center for the Future of AI, Mind, and Society
Most Recent Major Publication: Schneider, Susan. "Chatbot Epistemology." Social Epistemology 39, no. 5 (2025): 570–589. https://doi.org/10.1080/02691728.2025.2500030
Schneider articulates the "boiling frog problem"—the gradual, unnoticed erosion of human autonomy through chatbot interactions. She identifies threats including epistemic deficits in LLMs (hallucinations, opacity), misplaced trust in AI companions, personality profiling, and the "diachronic justification" problem (models changing unpredictably over time). Her earlier work developing the ACT test for AI consciousness provides frameworks for determining whether AI collaborators might possess moral status. Essential reading for understanding epistemic risks in human-AI partnerships.
Science and technology studies and posthumanism
Karen Barad Distinguished Professor of Feminist Studies, Philosophy, and History of Consciousness, University of California, Santa Cruz Director of Teaching, Science & Justice Research Center
Foundational Work (applied extensively 2023–2025): Barad, Karen. Meeting the Universe Halfway: Quantum Physics and the Entanglement of Matter and Meaning. Durham: Duke University Press, 2007. https://doi.org/10.1215/9780822388128
While Barad has not published new monographs in this period, her concepts are being extensively applied to AI studies by other scholars. Her framework of "intra-action"—the mutual constitution of entities through their relationships—and "agential cuts"—how apparatuses create distinctions—is being used to theorize AI as a material-discursive apparatus that co-constitutes human identities and knowledge. Recent 2024–2025 applications include Frabetti and Drage's feminist AI analysis and work on algorithmic radicalization in deep neural networks.
Rosi Braidotti Distinguished University Professor Emerita, Utrecht University Honorary Professor, RMIT University; Fellow, Australian Academy of the Humanities
Most Recent Major Publication: Klumbytė, Goda, Emily Jones, and Rosi Braidotti, eds. Posthuman Convergences: Transdisciplinary Methods and Practices. Edinburgh: Edinburgh University Press, 2025. https://doi.org/10.1515/9783111336688
Braidotti's "posthuman convergence" framework directly addresses human-technology relations at the intersection of advanced cognitive capitalism (including AI) and ecological crisis. She argues for relational subjectivity—understanding humans as embodied, embedded, and technologically mediated beings—and affirmative ethics that move beyond critique toward creative reimagining of human-technology assemblages. Her anti-anthropocentrism challenges human exceptionalism while maintaining attention to power, gender, and race in AI systems.
Donna Haraway Distinguished Professor Emerita, History of Consciousness and Feminist Studies, University of California, Santa Cruz 2025 Erasmus Prize Laureate; 2024 Venice Biennale Golden Lion for Lifetime Achievement
Recognition (2025): Awarded the €150,000 Erasmus Prize (November 25, 2025) by King Willem-Alexander for work on "the pursuit of what binds us." Donna Haraway Papers (1966–2024) newly processed and available at UCSC McHenry Library Special Collections.
Haraway's cyborg theory remains foundational for understanding human-technology entanglement—the cyborg as hybrid of machine and organism that destabilizes nature/culture and human/machine binaries. Her concept of "situated knowledges"—that all knowledge is partial and positioned—applies directly to AI systems as embodying particular perspectives rather than neutral objectivity. In her 2025 Erasmus Prize lecture, she explicitly critiqued binary thinking while noting "I am a compostist, not a posthumanist."
Bruno Latour (1947–2022) Final Position: Emeritus University Professor, Sciences Po Paris Deceased October 9, 2022
Most Recent Posthumous Publications: Latour, Bruno. How to Inhabit the Earth: Interviews with Nicolas Truong. Translated by Julie Rose. Cambridge: Polity Press, 2024. 112 pp. ISBN: 978-1-5095-5947-3. Latour, Bruno. If We Lose the Earth, We Lose Our Souls. Translated by Catherine Porter and Sam Ferguson. Cambridge: Polity Press, 2024. 110 pp. ISBN: 978-1-509560-46-2.
Latour's Actor-Network Theory (ANT) is directly applicable to human-AI collaboration. ANT treats human and non-human actors symmetrically as "actants" in networks, providing frameworks for analyzing AI as equal participants in sociotechnical assemblages. His concepts of translation and mediation—how different actors transform relationships and goals—are applicable to AI as translator/mediator. Theory, Culture & Society 41(5), 2024 published a memorial dossier with contributions from Michel Callon and Antoine Hennion.
Critical AI studies and digital humanities
Virginia Eubanks Associate Professor of Political Science, University at Albany, SUNY Rockefeller College of Public Affairs & Policy; Founding Member, Our Data Bodies Project
Most Recent Major Publication: Eubanks, Virginia. "What if the Body Politic Kept the Score?" Public Books (December 11, 2024). https://www.publicbooks.org/
Eubanks is currently gathering oral histories of the global automated welfare state with Andrea Quijada for Voice of Witness (forthcoming). Her foundational critique of automated decision-making systems demonstrates how AI mediation between governments and vulnerable populations can perpetuate or challenge existing power structures. Her work emphasizes that meaningful human oversight and community voice must be central to any AI governance framework.
Safiya Umoja Noble David O. Sears Presidential Endowed Chair of Social Sciences, University of California, Los Angeles Professor of Gender Studies, African American Studies, and Information Studies; Director, Center on Resilience & Digital Justice; 2021 MacArthur Fellow
Most Recent Major Publication: Hoffman, Steve, Kelly Joyce, Safiya Umoja Noble, et al. Chapter in Handbook of Children and Screens: Digital Media, Development, and Well-Being from Birth Through Adolescence. Springer, 2024.
Noble's concept of "algorithmic oppression" is essential for understanding that human-AI collaboration cannot be neutral—it reflects the values, biases, and power structures of its creators. Her ongoing leadership of the Minderoo Initiative on Tech & Power and co-editorship of The Intersectional Internet Vol II (forthcoming, Peter Lang) continues her work demonstrating that any framework for human-AI collaboration must address embedded inequities and include diverse perspectives in design and governance.
Lucy Suchman Professor Emerita, Anthropology of Science and Technology, Lancaster University, UK Former President, Society for Social Studies of Science; Faculty Advisor, AI Now Institute
Most Recent Major Publications: Dhaliwal, Ranjodh Singh, Théo Lepage-Richer, and Lucy Suchman. Neural Networks. Minneapolis: University of Minnesota Press, 2024. 122 pp. https://www.upress.umn.edu/book-division/books/neural-networks
Suchman, Lucy, and Caja Thimm. "There Is No Such Thing as a Machine That Acts Outside of Relations With Humans." Human-Machine Communication 9 (December 2024): 25–35. https://doi.org/10.30658/hmc.9.2
Suchman is among the most important theorists for human-AI collaboration. Her foundational concept of "situated action" challenges assumptions that AI systems can fully model human intentionality. Her 2024 article title directly articulates her position: AI systems are always embedded in human practices, organizations, and power structures. Her Neural Networks book deconstructs how cognition came to be framed as computational, while her chapter in The Realities of Autonomous Weapons (Bristol UP, 2025) critiques "meaningful human control."
N. Katherine Hayles Distinguished Research Professor of English, University of California, Los Angeles James B. Duke Professor Emerita of Literature, Duke University
Most Recent Major Publication: Hayles, N. Katherine. Bacteria to AI: Human Futures with Our Nonhuman Symbionts. Chicago: University of Chicago Press, 2025. 304 pp. ISBN: 9780226835983. https://press.uchicago.edu/ucp/books/book/chicago/B/bo238941793.html
This is perhaps the most directly relevant book for human-AI collaboration theory published in 2024–2025. Hayles develops an "Integrated Cognitive Framework" (ICF) spanning bacteria to AI, building on her influential concept of the "cognitive nonconscious." Key chapters include "Can Computers Create Meanings? A Technosymbiotic Perspective," "Inside the Mind of an AI," "GPT-4: The Leap from Correlation to Causality," and "Collective Intelligences: Assessing the Roles of Humans and AIs." She argues for understanding human and machine cognition not as separate entities but as technosymbionts in ongoing relationship.
Technology policy, management, and applied theory
Ryan Calo Lane Powell and D. Wayne Gittinger Professor of Law, University of Washington School of Law Co-Director, UW Tech Policy Lab; Co-Founder, UW Center for an Informed Public
Most Recent Major Publication: Angel, María P., and Ryan Calo. "Distinguishing Privacy Law: A Critique of Privacy as Social Taxonomy." Columbia Law Review 124 (2024): 507–562. https://columbialawreview.org/content/distinguishing-privacy-law-a-critique-of-privacy-as-social-taxonomy/
Calo examines how privacy law has evolved to encompass algorithmic bias, consumer manipulation, and AI-driven harms—creating direct conflicts with AI accountability needs. For human-AI collaboration theory, this work illuminates critical tensions: AI accountability, explainability, and accuracy require more data processing, directly opposing privacy minimization principles. Calo testified before the U.S. Senate (July 2024) on AI and privacy, emphasizing that "AI fuels an insatiable demand for consumer data."
Thomas W. Malone Patrick J. McGovern (1959) Professor of Management, MIT Sloan School of Management Founding Director, MIT Center for Collective Intelligence
Most Recent Major Publication: Vaccaro, Michelle, Abdullah Almaatouq, and Thomas W. Malone. "When Combinations of Humans and AI Are Useful: A Systematic Review and Meta-Analysis." Nature Human Behaviour 8, no. 12 (December 2024): 2293–2303. https://doi.org/10.1038/s41562-024-02024-1
This is the first large-scale meta-analysis examining when human-AI combinations outperform either alone. Key findings: human-AI combinations performed significantly worse than the best of humans or AI alone on average; decision-making tasks showed performance losses for human-AI teams; creative tasks showed significant gains. When humans outperform AI alone, combinations show gains; when AI outperforms humans, combinations show losses. Essential empirical grounding for collaboration theory.
Ethan Mollick Ralph J. Roberts Distinguished Faculty Scholar, The Wharton School, University of Pennsylvania Co-Director, Generative AI Labs at Wharton; TIME 100 Most Influential in AI (2024)
Most Recent Major Publication: Mollick, Ethan. Co-Intelligence: Living and Working with AI. New York: Portfolio/Penguin, 2024. 256 pp. ISBN: 9780593716717. https://www.penguinrandomhouse.com/books/741805/co-intelligence-by-ethan-mollick/
New York Times Bestseller; Economist and Financial Times Best Book of 2024. Mollick provides the definitive practical guide to human-AI collaboration. He introduces the concepts of "Centaurs" (humans who divide tasks with AI) and "Cyborgs" (humans who fully integrate AI into workflows), proposing AI as "co-worker, co-teacher, and coach." His Substack newsletter "One Useful Thing" reaches 381,000+ subscribers with ongoing analysis of AI implications for work and education.
Bracha L. Ettinger "Marcel Duchamp" Chair, Professor of Art and Psychoanalysis, European Graduate School Distinguished Professor of Philosophy, GCAS University, Dublin; Practicing Psychoanalyst
Most Recent Major Publication: Ettinger, Bracha L. "Artist-Theorist Invocation: BRACHA Ettinger's Notebook Pages." Artizein: Arts and Teaching Journal 9, no. 1, Article 3 (2024). https://opensiuc.lib.siu.edu/atj/vol9/iss1/3/
While Ettinger does not directly address AI, her matrixial theory offers philosophical frameworks for reconceptualizing collaborative intelligence. Her concept of "matrixial subjectivity-as-encounter"—that subjectivity emerges through shared, pre-individual encounters rather than isolated selfhood—parallels discussions of human-AI "centaurs" and "cyborgs." Her ethics of care through vulnerability ("com-passion and self-fragilization") offers frameworks for AI systems designed for empathy. Major 2024 exhibition at Centre Pompidou, Paris.
Conclusion: converging frameworks for human-AI collaboration
This bibliography reveals a remarkable theoretical convergence across disciplines. Philosophers of mind (Clark, Chalmers, Schneider) are directly engaging with whether and how AI systems might extend human cognition or possess consciousness. STS scholars (Barad, Latour, Haraway) provide frameworks—intra-action, actor-networks, cyborg theory—that dissolve rigid human/machine boundaries while maintaining attention to power asymmetries. Critical AI scholars (Noble, Eubanks, Suchman, Hayles) insist that any collaboration framework must address algorithmic bias, epistemic harm, and the situated nature of all machine action.
The most striking development is the emergence of empirically grounded collaboration theory. Malone's 2024 meta-analysis provides evidence that human-AI combinations excel at creative tasks but often underperform on decisions—a finding with immediate practical implications. Mollick's "Centaur" and "Cyborg" models offer practical frameworks now being widely adopted.
The key theoretical tension remains unresolved: whether AI systems are genuine cognitive partners or sophisticated tools. Clark argues for extended minds; Suchman insists machines never act "outside of relations with humans"; Hayles proposes "technosymbiosis" as a middle path. This bibliography provides the essential readings for navigating that question—and for building human-AI collaborations that are effective, ethical, and epistemically sound.
Bibliography compiled December 2025. All institutional affiliations verified through official university faculty pages and recent publication bylines.