Bibliography

This bibliography is a collective work. To enrich it, you will need a zotero account and access to this zotero group. In case you would like to contribute but do not know what zotero is, you can contact Frédéric Clavert.


General

Turing, A. M. (1950). Computing Machinery and Intelligence. Mind, 59(236), 433–460. JSTOR. http://www.jstor.org/stable/2251299
Hicks, M. T., Humphries, J., & Slater, J. (2024). ChatGPT is bullshit. Ethics and Information Technology, 26(2), 38. https://doi.org/10.1007/s10676-024-09775-5
Washburn, J., & McCutchen, J. M. (2024). AI Meets AI: ChatGPT as a Pedagogical Tool to Teach American Indian History. 2(2).
Anatomy of an AI System. (2019, November 25). Anatomy of an AI System. http://www.anatomyof.ai
Merrill, S. (2023). Artificial intelligence and social memory: towards the cyborgian remembrance of an advancing mnemo-technic. In Handbook of Critical Studies of Artificial Intelligence (pp. 173–186). Edward Elgar Publishing. https://www.elgaronline.com/edcollchap/book/9781803928562/book-part-9781803928562-20.xml
The Empirical Triumph of Theory. (2023, June 29). In the Moment. https://critinq.wordpress.com/2023/06/29/the-empirical-triumph-of-theory/
Chun, W. H. K. (2016). Updating to Remain the Same: Habitual New Media. The MIT Press. https://doi.org/10.7551/mitpress/10483.001.0001
Baudrillard, J. (1994). Simulacra and Simulation. University of Michigan Press.
Natale, S. (2021). Deceitful Media: Artificial Intelligence and Social Life after the Turing Test (1st ed.). Oxford University Press. https://doi.org/10.1093/oso/9780190080365.001.0001
Floridi, L. (2023). AI as Agency Without Intelligence: on ChatGPT, Large Language Models, and Other Generative Models. Philosophy & Technology, 36(1), 15, s13347-023-00621-y. https://doi.org/10.1007/s13347-023-00621-y
Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021). On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, 610–623. https://doi.org/10.1145/3442188.3445922
Bender, E. M., & Koller, A. (2020). Climbing towards NLU: On Meaning, Form, and Understanding in the Age of Data. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 5185–5198. https://doi.org/10.18653/v1/2020.acl-main.463
Lindgren, S. (Ed.). (2023). Handbook of critical studies of artificial intelligence. Edward Elgar Publishing.
Gensburger, S. (2016). Halbwachs’ studies in collective memory: A founding text for contemporary ‘memory studies’? Journal of Classical Sociology, 16(4), 396–413. https://doi.org/10.1177/1468795X16656268
Floridi, L., & Chiriatti, M. (2020). GPT-3: Its Nature, Scope, Limits, and Consequences. Minds and Machines, 30(4), 681–694. https://doi.org/10.1007/s11023-020-09548-1
Morton, T. (2011). Here Comes Everything: The Promise of Object-Oriented Ontology. Qui Parle, 19(2), 163–190. https://doi.org/10.5250/quiparle.19.2.0163
Bucher, T. (2017). The algorithmic imaginary: exploring the ordinary affects of Facebook algorithms. Information, Communication & Society, 20(1), 30–44. https://doi.org/10.1080/1369118X.2016.1154086
Kitchin, R. (2017). Thinking critically about and researching algorithms. Information, Communication & Society, 20(1), 14–29. https://doi.org/10.1080/1369118X.2016.1154087
Shneiderman, B., & Muller, M. (2023, Avril). On AI Anthropomorphism. Medium, Human Centered AI. https://medium.com/human-centered-ai/on-ai-anthropomorphism-abff4cecc5ae
Cardon, D., Cointet, J.-P., & Mazières, A. (2018). La revanche des neurones: L’invention des machines inductives et la controverse de l’intelligence artificielle. Réseaux, n° 211(5), 173. https://doi.org/10.3917/res.211.0173

Ethics

Beaudouin, V., & Velkovska, J. (2023). Enquêter sur l’« éthique de l’IA »: Réseaux, N° 240(4), 9–27. https://doi.org/10.3917/res.240.0009
Makhortykh, M. (2023). No AI After Auschwitz? Bridging AI and Memory Ethics in the Context of Information Retrieval of Genocide-Related Information. In A. Mukherjee, J. Kulshrestha, A. Chakraborty, & S. Kumar (Eds.), Ethics in Artificial Intelligence: Bias, Fairness and Beyond (pp. 71–83). Springer Nature. https://doi.org/10.1007/978-981-99-7184-8_4
Pisano, A. (n.d.). Big data e sedimentazioni etiche. La memoria tra il simbolico e il sub-simbolico.
Presner, T. (2016). 8. The Ethics of the Algorithm: Close and Distant Listening to the Shoah Foundation Visual History Archive. In C. Fogu, W. Kansteiner, & T. Presner (Eds.), Probing the Ethics of Holocaust Culture (pp. 167–202). Harvard University Press. https://doi.org/10.4159/9780674973244-009

Legal Approaches

Shur-Ofry, M., & Pessach, G. (2020). Robotic Collective Memory. Washington University Law Review, 97(3), 975–1005. https://doi.org/10.2139/ssrn.3364008
Brittain, B. (2023, August 21). AI-generated art cannot receive copyrights, US court says. Reuters. https://www.reuters.com/legal/ai-generated-art-cannot-receive-copyrights-us-court-says-2023-08-21/
Heikkilä, M. (2022, September 16). This artist is dominating AI-generated art. And he’s not happy about it. MIT Technology Review. https://www.technologyreview.com/2022/09/16/1059598/this-artist-is-dominating-ai-generated-art-and-hes-not-happy-about-it/

Prompts

Domestic Data Streamers. (2022, October). Prompt book for data lovers II ❤️. https://docs.google.com/presentation/d/1V8d6TIlKqB1j5xPFH7cCmgKOV_fMs4Cb4dwgjD5GIsg/edit#slide=id.g172b1e76bae_0_18
Domestic Data Streamers. (2022, October). Prompt book for data lovers I ❤️. https://www.are.na/block/18903974
Thompson, C. (2022, October 22). The Psychological Weirdness of “Prompt Engineering.” Medium. https://clivethompson.medium.com/the-psychological-weirdness-of-prompt-engineering-3846755df50c
Saravia, E. (2022). Prompt Engineering Guide. https://github.com/dair-ai/Prompt-Engineering-Guide (Original work published 2022)
ChatGPT. (2022). Prompt – Imagine a dialogue between a historian and a sociologist about the concept of “collective memory.”

Teaching

Exploring Speculative Landscapes with Multimodal AI: Visualizing the Plan of St. Gall – Exploring AI Pedagogy. (2023, November 27). https://exploringaipedagogy.hcommons.org/2023/11/27/exploring-speculative-landscapes-with-multimodal-ai-visualizing-the-plan-of-st-gall/
Transforming Writing Assignments with AI – The WAC Clearinghouse. (n.d.). Retrieved February 16, 2024, from https://wac.colostate.edu/repository/collections/textgened/ai-literacy/transforming-writing-assignments-with-ai/

AI & art and litterature

Chakrabarty, T., Laban, P., Agarwal, D., Muresan, S., & Wu, C.-S. (2024). Art or Artifice? Large Language Models and the False Promise of Creativity (No. arXiv:2309.14556). arXiv. http://arxiv.org/abs/2309.14556
Benjamin, W. (1969). The Work of Art in the Age of Mechanical Reproduction (H. Zohn, Trans.). In H. Harendt (Ed.), Illuminations. Schocken Books.
Brittain, B. (2023, August 21). AI-generated art cannot receive copyrights, US court says. Reuters. https://www.reuters.com/legal/ai-generated-art-cannot-receive-copyrights-us-court-says-2023-08-21/
Searle, J. R. (1980). Minds, brains, and programs. Behavioral and Brain Sciences, 3(3), 417–424. https://doi.org/10.1017/S0140525X00005756
Heikkilä, M. (2022, September 16). This artist is dominating AI-generated art. And he’s not happy about it. MIT Technology Review. https://www.technologyreview.com/2022/09/16/1059598/this-artist-is-dominating-ai-generated-art-and-hes-not-happy-about-it/
Raffa, M., & Pronzato, R. (2021). The algorithmic imaginary of cultural producers. Towards platform-optimized music? H-Ermes. Journal of Communication, 2021(19), 293–321. https://doi.org/10.1285/i22840753n19p293
Langlais, P.-C. (n.d.). L’écrivain est un robot: générer des pastiches littéraires avec GPT-2 [Billet]. Sciences communes. Retrieved January 29, 2021, from https://scoms.hypotheses.org/1036
Yang, G. (2021). Online lockdown diaries as endurance art. Ai & Society, 1–10. https://doi.org/10.1007/s00146-020-01141-5

AI & history, oral history and archive

Arias Hernández, R., & Rockembach, M. (2025). Building trustworthy AI solutions: integrating artificial intelligence literacy into records management and archival systems. AI & SOCIETY. https://doi.org/10.1007/s00146-025-02194-0
Green, P. (2025). AI and the visualisation needs of researchers using email archives. AI & SOCIETY. https://doi.org/10.1007/s00146-025-02187-z
McKean, C., & Randall, C. (2025). Data analysis and network visualisation as tools for curating hybrid correspondence archives. AI & SOCIETY. https://doi.org/10.1007/s00146-025-02200-5
Vetter, M. A., Jiang, J., & McDowell, Z. J. (2025). An endangered species: how LLMs threaten Wikipedia’s sustainability. AI & SOCIETY. https://doi.org/10.1007/s00146-025-02199-9
Canning, D., & Jaillant, L. (2025). AI to review government records: new work to unlock historically significant digital records. AI & SOCIETY. https://doi.org/10.1007/s00146-025-02221-0
Liu, Y., Heitman, C., Soh, L.-K., & Whiteley, P. (2025). Machine learning methods for isolating indigenous language catalog descriptions. AI & SOCIETY. https://doi.org/10.1007/s00146-025-02223-y
Jaillant, L., Mitchell, O., Ewoh-Opu, E., & Hidalgo Urbaneja, M. (2025). How can we improve the diversity of archival collections with AI? Opportunities, risks, and solutions. AI & SOCIETY. https://doi.org/10.1007/s00146-025-02222-z
Jansen, G., & Marciano, R. (2025). Developing computer vision and machine learning strategies to unlock government-created records. AI & SOCIETY. https://doi.org/10.1007/s00146-025-02231-y
Reusens, M., Adams, A., & Baesens, B. (2025). Large Language Models to make museum archive collections more accessible. AI & SOCIETY. https://doi.org/10.1007/s00146-025-02227-8
Leme Lopes, A. P. (2023). Artificial history? Inquiring ChatGPT on historiography. Rethinking History, 27(4), 709–749. https://doi.org/10.1080/13642529.2023.2234227
De Ninno, F., & Lacriola, M. (2025). Mussolini and ChatGPT. Examining the Risks of A.I. writing Historical Narratives on Fascism. Journal of Modern Italian Studies, 1–23. https://doi.org/10.1080/1354571X.2025.2457250
Van Der Werf, T., & Van Der Werf, B. (2022). Will archivists use AI to enhance or to dumb down our societal memory? AI & SOCIETY, 37(3), 985–988. https://doi.org/10.1007/s00146-021-01359-x
MAKINGHISTORIES. (2023). Wulf Kansteiner: “Historical dialogue and machine learning: ChatGPT” [Video recording]. https://www.youtube.com/watch?v=i7uP4b4a-Rs
Alenichev, A., Kingori, P., & Koen Peeters, G. (2023, April 10). When a black viking meets a black slave trader. Africa Is a Country. https://africasacountry.com/2024/04/when-a-black-viking-meets-a-black-slave-trader/
Rolan, G., Humphries, G., Jeffrey, L., Samaras, E., Antsoupova, T., & Stuart, K. (2019). More human than human? Artificial intelligence in the archive. Archives and Manuscripts, 47(2), 179–203. https://doi.org/10.1080/01576895.2018.1502088
Pessanha, F., & Salah, A. A. (2021). A Computational Look at Oral History Archives. Journal on Computing and Cultural Heritage, 15(1). https://doi.org/10.1145/3477605
Barlindhaug, G. (2022). Artificial Intelligence and the Preservation of Historic Documents. Proceedings from the Document Academy, 9(2). https://doi.org/10.35492/docam/9/2/9
Bultmann, D., Makhortykh, M., Simon, D., Ulloa, R., & Zucker, E. M. (2022). Digital Archive of Memorialization of Mass Atrocities (DAMMA) Workshop Whitepaper. Yale University Genocide Studies Program: Mass Atrocities in the Digital Era Working Paper, 3. https://gsp.yale.edu/digital-archive-memorialization-mass-atrocities-damma-workshop-whitepaper
Jaillant, L. (Ed.). (2022). Archives, Access and Artificial Intelligence: Working with Born-Digital and Digitized Archival Collections (1st ed., Vol. 2). Bielefeld University Press / transcript Verlag. https://doi.org/10.14361/9783839455845
Clavert, F., Mahroug, S., & Schafer, V. (2022). Préservation et distorsion : l’espace-temps des réseaux socio-numériques et du web archivé. Revue d’histoire culturelle, 2022(5). https://doi.org/10.56698/rhc.2791
Kansteiner, W. (2022). Digital Doping for Historians: Can History, Memory, and Historical Theory Be Rendered Artificially In℡ligent? History and Theory, 61(4), 119–133. https://doi.org/10.1111/hith.12282
Ebbrecht-Hartmann, T., Stiassny, N., & Henig, L. (2023). Digital visual history: historiographic curation using digital technologies. Rethinking History, 27(2), 159–186. https://doi.org/10.1080/13642529.2023.2181534
Hutchinson, D. (n.d.). What Do AIs “Know” About History? A Digital History Experiment. Retrieved October 5, 2023, from https://dr-hutchinson-what-do-ais-know-about-history-app-i3l5jo.streamlit.app/
Jones, M. L. (2023). AI in History. The American Historical Review, 128(3), 1360–1367. https://doi.org/10.1093/ahr/rhad361
Soh, L.-K., Lorang, L., Pack, C., & Liu, Y. (2023). Applying Image Analysis and Machine Learning to Historical Newspaper Collections. The American Historical Review, 128(3), 1382–1389. https://doi.org/10.1093/ahr/rhad369
Schmidt, B. (2023). Representation Learning. The American Historical Review, 128(3), 1350–1353. https://doi.org/10.1093/ahr/rhad363
Meadows, R. D., & Sternfeld, J. (2023). Artificial Intelligence and the Practice of History: A Forum. The American Historical Review, 128(3), 1345–1349. https://doi.org/10.1093/ahr/rhad362
Broussard, M. (2023). The Challenges of AI Preservation. The American Historical Review, 128(3), 1378–1381. https://doi.org/10.1093/ahr/rhad366
Sternfeld, J. (2023). AI-as-Historian. The American Historical Review, 128(3), 1372–1377. https://doi.org/10.1093/ahr/rhad368
Tilton, L. (2023). Relating to Historical Sources. The American Historical Review, 128(3), 1354–1359. https://doi.org/10.1093/ahr/rhad365
Crawford, K. (2023). Archeologies of Datasets. The American Historical Review, 128(3), 1368–1371. https://doi.org/10.1093/ahr/rhad364

AI & Holocaust and mass atrocities

Mälksoo, M. (2023). Chapter 1: Politics of memory: a conceptual introduction. https://www.elgaronline.com/edcollchap/book/9781800372535/book-part-9781800372535-6.xml
Makhortykh, M., UNESCO, & World Jewish Council. (2024). AI and the Holocaust: rewriting history? The impact of artifi cial intelligence on understanding the Holocaust (p. 26). UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000390211
Le Priol, M. (2024, June 18). L’Unesco alerte sur la « réécriture de l’Holocauste » par l’intelligence artificielle. La Croix, 10. https://nouveau-europresse-com.proxy.bnl.lu/Search/ResultMobile/0
Walden, V. G., & Marrison, K. (2023). Recommendations for using Artificial Intelligence and Machine Learning for Holocaust Memory and Education. REFRAME. https://doi.org/10.20919/ELVH8804
Makhortykh, M. (2023). No AI After Auschwitz? Bridging AI and Memory Ethics in the Context of Information Retrieval of Genocide-Related Information. In A. Mukherjee, J. Kulshrestha, A. Chakraborty, & S. Kumar (Eds.), Ethics in Artificial Intelligence: Bias, Fairness and Beyond (pp. 71–83). Springer Nature. https://doi.org/10.1007/978-981-99-7184-8_4
Makhortykh, M. (2023). Open Forum: Possibilities and Risks of Artificial Intelligence for Holocaust Memory. Eastern European Holocaust Studies, 0(0). https://doi.org/10.1515/eehs-2023-0053
Makhortykh, M., Vziatysheva, V., & Sydorova, M. (2023). Generative AI and Contestation and Instrumentalization of Memory About the Holocaust in Ukraine. Eastern European Holocaust Studies. https://doi.org/10.1515/eehs-2023-0054
Zucker, E. M., & Simon, D. J. (Eds.). (2020). Mass Violence and Memory in the Digital Age: Memorialization Unmoored. Springer International Publishing. https://doi.org/10.1007/978-3-030-39395-3
Lothe, J., Suleiman, S. R., & Phelan, J. (2012). After Testimony: The Ethics and Aesthetics of Holocaust Narrative for the Future. The Ohio State University Press. https://kb.osu.edu/handle/1811/51398
Presner, T. (2016). 8. The Ethics of the Algorithm: Close and Distant Listening to the Shoah Foundation Visual History Archive. In C. Fogu, W. Kansteiner, & T. Presner (Eds.), Probing the Ethics of Holocaust Culture (pp. 167–202). Harvard University Press. https://doi.org/10.4159/9780674973244-009
Walden, V. G. (2021). Afterword: Digital Holocaust Memory Futures: Through Paradigms of Immersion and Interactivity and Beyond. In V. G. Walden (Ed.), Digital Holocaust Memory, Education and Research (pp. 267–296). Palgrave. https://doi.org/10.1007/978-3-030-83496-8_11
Walden, V. G. (Ed.). (2021). Digital Holocaust Memory, Education and Research. Springer International Publishing. https://doi.org/10.1007/978-3-030-83496-8
Makhortykh, M. (2021, February 4). Algorithmic Auditing, the Holocaust, and Search Engine Bias. Digital Holocaust Memory. https://reframe.sussex.ac.uk/digitalholocaustmemory/2021/02/04/algorithmic-auditing-the-holocaust-and-search-engine-bias/
Bultmann, D., Makhortykh, M., Simon, D., Ulloa, R., & Zucker, E. M. (2022). Digital Archive of Memorialization of Mass Atrocities (DAMMA) Workshop Whitepaper. Yale University Genocide Studies Program: Mass Atrocities in the Digital Era Working Paper, 3. https://gsp.yale.edu/digital-archive-memorialization-mass-atrocities-damma-workshop-whitepaper
Makhortykh, M., Zucker, E. M., Simon, D. J., Bultmann, D., & Ulloa, R. (2023). Shall androids dream of genocides? How generative AI can change the future of memorialization of mass atrocities. Discover Artificial Intelligence, 3(1), 28. https://doi.org/10.1007/s44163-023-00072-6

AI & Memory

Poletti, A. (2024). Memory and Artificial Intelligence. In A. Erll, S. Knittel, & J. Wüstenberg (Eds.), Dynamics, Mediation, Mobilization (pp. 129–134). De Gruyter. https://doi.org/10.1515/9783111439273-019
Matei, S. (2024). Generative artificial intelligence and collective remembering. The technological mediation of mnemotechnic values. Journal of Human-Technology Relations, 2. https://doi.org/10.59490/jhtr.2024.2.7405
Jérémy Torres. (2024). Quand l’intelligence artificielle permet de créer des images du passé à partir de simples souvenirs. Libération (site web). https://nouveau.europresse.com/Link/U030612T_1/news%c2%b720240610%c2%b7LIF%c2%b7015
Kidd, J., & Nieto McAvoy, E. (2023). Deep Nostalgia: Remediated memory, algorithmic nostalgia and technological ambivalence. Convergence: The International Journal of Research into New Media Technologies, 29(3), 620–640. https://doi.org/10.1177/13548565221149839
Makhortykh, M. (2023). The user is dead, long live the platform? Problematising the user-centric focus of (digital) memory studies. Memory Studies, 16(6), 1500–1512. https://doi.org/10.1177/17506980231202849
Mandolessi, S. (2023). The digital turn in memory studies. Memory Studies, 16(6), 1513–1528. https://doi.org/10.1177/17506980231204201
Landsberg, A. (2004). Prosthetic Memory: The Transformation of American Remembrance in the Age of Mass Culture. Columbia University Press.
Bannon, L. (2000). Towards Artificial Memories? Le Travail Humain, 63(3), 277–285. https://www.jstor.org/stable/40660263
Kvasnička, V., & Pospíchal, J. (2015). Artificial Intelligence and Collective Memory. In P. Sinčák, P. Hartono, M. Virčíková, J. Vaščák, & R. Jakša (Eds.), Emergent Trends in Robotics and Intelligent Systems (pp. 283–291). Springer International Publishing. https://doi.org/10.1007/978-3-319-10783-7_31
Horsley, N. (2020). Intellectual autonomy after artificial intelligence: The future of memory institutions and historical research. In N. Lushetich (Ed.), Big Data—A New Medium? Routledge.
Makhortykh, M. (2021). Memoriae ex machina: How Algorithms Make Us Remember and Forget. Georgetown Journal of International Affairs, 22(2), 180–185. https://doi.org/10.1353/gia.2021.0027
Shur-Ofry, M., & Pessach, G. (2020). Robotic Collective Memory. Washington University Law Review, 97(3), 975–1005. https://doi.org/10.2139/ssrn.3364008

AI & Philosophy

Event – Philosophers and AI Ethics: A Roadmap – let’s φ! (n.d.). Retrieved January 28, 2021, from https://letsphi.com/event-philosophers-and-ai-ethics-a-roadmap/
Weinberg, J., Chalmers, D., Askell, A., Montemayor, C., Khoo, J., Rini, R., Thi Nguyen, C., Shevlin, H., Vallor, S., & GPT-3. (2020). Philosophers On GPT-3 (updated with replies by GPT-3). Daily Nous. https://dailynous.com/2020/07/30/philosophers-gpt-3/

AI & time and temporalities

de Faria Pereira, M. H., & Lopes de Araujo, V. (2024). “Updatism” and the Understanding of Time and History. Bloomsbury. https://www.bloomsbury.com/uk/updatism-and-the-understanding-of-time-and-history-9781350410732/
Pereira, M. H. D. F., & Araujo, V. L. de. (2020). Updatism: Gumbrecht’s broad present, Hartog’s Presentism and beyond. Diacronie Studi Di Storia Contemporanea. https://www.academia.edu/44447315/Updatism_Gumbrechts_broad_present_Hartogs_Presentism_and_beyond
Pereira, M. H. de F., & Araujo, V. L. de. (2021). Updatism: Pandemic and Historicities in the Never-Ending 2020. Journal of Foreign Languages and Cultures, 5(2), 090. https://www.academia.edu/71112229/Updatism_Pandemic_and_Historicities_in_the_Never_Ending_2020

AI services & projects

Korostoff, M. (2021, March 16). 535,000 faces. Comprehending the Death Toll of Covid-19. https://mkorostoff.github.io/hundred-thousand-faces/
Critical Algorithm Studies: a Reading List. (2015, November 5). Social Media Collective. https://socialmediacollective.org/reading-lists/critical-algorithm-studies/
Home/Accueil. (n.d.). EyCon. Retrieved October 5, 2023, from https://eycon.hypotheses.org/
Project: Fireside Chats – Honest Abe’s. (n.d.). Retrieved October 5, 2023, from https://honestabes.info/fireside-chats/
Knowing machines. (n.d.). Critical Dataset Studies Reading List. Retrieved October 5, 2023, from https://knowingmachines.org/reading-list
bigscience/bloom · Hugging Face. (n.d.). Retrieved October 5, 2023, from https://huggingface.co/bigscience/bloom
CulturIA – Une Histoire culturelle de l’Intelligence Artificielle. (2023, August 28). https://cultureia.hypotheses.org/
Perplexity. (n.d.). Retrieved October 5, 2023, from https://www.perplexity.ai/
Hutchinson, D. (n.d.). What Do AIs “Know” About History? A Digital History Experiment. Retrieved October 5, 2023, from https://dr-hutchinson-what-do-ais-know-about-history-app-i3l5jo.streamlit.app/