Bibliographie

AstuceRemarque: droits d’auteur

Nous nous efforçons d’utiliser des ouvrages librement accessibles. Si cela n’est pas possible, nous vous prions de vous procurer les ouvrages via la plateforme bibliothécaire LIBER Libraries. Malgré des arguments valables, nous déconseillons l’utilisation de plateformes telles que Anna’s Archive ou Library Genesis.

Voir Karaganis (2018)

Bender, Emily M., Timnit Gebru, Angelina McMillan-Major, et Shmargaret Shmitchell. 2021. « On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 🦜 ». Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (FAccT ’21) (New York, NY, USA), mars 1, 610‑23. https://doi.org/10.1145/3442188.3445922.

Bundesgesetz über den Datenschutz (DSG) (2020). https://www.fedlex.admin.ch/eli/cc/2022/491/de.

Buolamwini, Joy. 2023. Unmasking AI: A Story of Hope and Justice in a World of Machines. First edition. Random House.

Buolamwini, Joy, et Timnit Gebru. 2018. « Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification ». Proceedings of the 1st Conference on Fairness, Accountability and Transparency, PMLR, vol. 81 (janvier): 77‑91. https://proceedings.mlr.press/v81/buolamwini18a.html.

Campbell, Chris. 2025. « The Historian in the Age of AI ». Transactions of the Royal Historical Society, publication en ligne anticipée, décembre 10. https://doi.org/10.1017/S0080440125100509.

Carroll, Stephanie Russo, Ibrahim Garba, Oscar L. Figueroa-Rodríguez, et al. 2020. « The CARE Principles for Indigenous Data Governance ». Data Science Journal 19 (1): 43. https://doi.org/10.5334/dsj-2020-043.

Chen, Zhisheng. 2023. « Ethics and Discrimination in Artificial Intelligence-Enabled Recruitment Practices ». Humanities and Social Sciences Communications 10 (1): 1‑12. https://doi.org/10.1057/s41599-023-02079-x.

D’Ignazio, Catherine. 2024. Counting Feminicide: Data Feminism in Action. The MIT Press. https://doi.org/10.7551/mitpress/14671.001.0001.

D’Ignazio, Catherine, et Lauren F. Klein. 2023. Data Feminism. First MIT Press paperback edition. The MIT Press. https://data-feminism.mitpress.mit.edu/.

Deutsche Forschungsgemeinschaft. 2023. Stellungnahme des Präsidiums der Deutschen Forschungsgemeinschaft (DFG) zum Einfluss generativer Modelle für die Text- und Bilderstellung auf die Wissenschaften und das Förderhandeln der DFG. Deutsche Forschungsgemeinschaft. https://www.dfg.de/resource/blob/289674/ff57cf46c5ca109cb18533b21fba49bd/230921-stellungnahme-praesidium-ki-ai-data.pdf.

Díez García, Lucía, Paula Terleira Fernández, Valentín Cardeñoso-Payo, André F. Sales Mendes, et Álvaro Lozano Murciego. 2025. « Evaluating Vision Language Models for Handwritten Text Recognition ». In New Trends in Disruptive Technologies, Tech Ethics and Artificial Intelligence. Advances in Intelligent Systems et Computing. Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-99474-6_24.

Drage, Eleanor, et Kerry Mackereth. 2022. « Does AI Debias Recruitment? Race, Gender, and AI’s “Eradication of Difference” ». Philosophy & Technology 35 (4): 89. https://doi.org/10.1007/s13347-022-00543-1.

Drucker, Johanna. 2011. « Humanities Approaches to Graphical Display ». Digital Humanities Quarterly 5 (1). https://doi.org/10.63744/r4ysrh7ae534.

European Commission, Directorate-General for Research and Innovation. 2026. Living Guidelines on the Responsible Use of Generative AI in Research: ERA Forum Stakeholders’ Document. Third version. European Commission. https://research-and-innovation.ec.europa.eu/document/download/2b6cf7e5-36ac-41cb-aab5-0d32050143dc_en?filename=ec_rtd_ai-guidelines.pdf.

European Data Protection Board. 2026. Guidelines 1/2026 on Processing of Personal Data for Scientific Research Purposes. Version 1.0. European Data Protection Board. https://www.edpb.europa.eu/our-work-tools/documents/public-consultations/2026/guidelines-12026-processing-personal-data_en.

Fickers, Andreas. 2020. « Update für die Hermeneutik. Geschichtswissenschaft auf dem Weg zur digitalen Forensik? » Zeithistorische Forschungen / Studies in Contemporary History 17 (1): 157‑68. https://doi.org/10.14765/zzf.dok-1765.

Fickers, Andreas, et Juliane Tatarinov. 2022. « Digital Source Criticism: The Case of the Historian’s Craft in the Digital Age ». Journal of Digital History 2 (1): 1‑20. https://doi.org/10.1515/jdh-2022-0001.

Historisches Institut, Universität Bern. 2026. « Richtlinien zur Verwendung von KI-gestützten Programmen ». Historisches Institut, Universität Bern, août 14. https://www.hist.unibe.ch/studium/plagiate__ki_gebrauch/index_ger.html.

Hodel, Tobias, David Schoch, Christa Schneider, et Jake Purcell. 2021. « General Models for Handwritten Text Recognition: Feasibility and State-of-the Art. German Kurrent as an Example ». Journal of Open Humanities Data 7 (juillet): 13. https://doi.org/10.5334/johd.46.

International Committee of Medical Journal Editors. 2026. « Recommendations for the Conduct, Reporting, Editing, and Publication of Scholarly Work in Medical Journals ». Version Updated January 2026. janvier 1. https://www.icmje.org/recommendations/.

Kapoor, Sayash, Benedikt Stroebl, Zachary S. Siegel, Nitya Nadgir, et Arvind Narayanan. 2024. « AI Agents That Matter ». juillet 1. https://doi.org/10.48550/arXiv.2407.01502.

Karaganis, Joe, éd. 2018. Shadow Libraries: Access to Knowledge in Global Higher Education. The MIT Press. https://doi.org/10.7551/mitpress/11339.001.0001.

Karpathy, Andrej. 2025. Deep Dive into LLMs like ChatGPT. https://www.youtube.com/watch?v=7xTGNNLPyMI.

Lang, Sarah, et Elena Suárez Cronauer. 2026. « Beyond Data Feminism. Towards Ethical Data Work in the (Digital) Humanities ». Zeitschrift für digitale Geisteswissenschaften – Working Papers, nᵒ 4 (février). https://doi.org/10.17175/wp_2026.

Lewis, Patrick, Ethan Perez, Aleksandra Piktus, et al. 2020. « Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks ». mai 22. https://doi.org/10.48550/arXiv.2005.11401.

Luccioni, Alexandra Sasha, Christopher Akiki, Margaret Mitchell, et Yacine Jernite. 2023. « Stable Bias: Analyzing Societal Representations in Diffusion Models ». novembre 9. https://doi.org/10.48550/arXiv.2303.11408.

Luccioni, Sasha, Yacine Jernite, et Emma Strubell. 2024. « Power Hungry Processing: Watts Driving the Cost of AI Deployment? » Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency (FAccT ’24) (New York, NY, USA), juin 3, 85‑99. https://doi.org/10.1145/3630106.3658542.

Mattu, Surya, Julia Angwin, Jeff Larson, et Lauren Kirchner. 2016. « Machine Bias ». ProPublica. https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing.

Meadows, R. Darrell, et Joshua Sternfeld. 2023. « Artificial Intelligence and the Practice of History ». The American Historical Review 128 (3): 1345‑49. https://doi.org/10.1093/ahr/rhad362.

Mehrabi, Ninareh, Fred Morstatter, Nripsuta Saxena, Kristina Lerman, et Aram Galstyan. 2021. « A Survey on Bias and Fairness in Machine Learning ». ACM Computing Surveys 54 (6): 115:1‑35. https://doi.org/10.1145/3457607.

Milligan, Ian. 2019. History in the Age of Abundance? How the Web Is Transforming Historical Research. McGill-Queen’s University Press. https://doi.org/10.2307/j.ctvggx2kh.

Mueller, Milton L. 2025. « It’s Just Distributed Computing: Rethinking AI Governance ». Telecommunications Policy, février, 102917. https://doi.org/10.1016/j.telpol.2025.102917.

Noble, Safiya Umoja. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press.

O’Neil, Cathy. 2016. Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. Crown Publishing Group.

Oberbichler, Sarah, et Cindarella Petz. 2025. Working Paper: Implementing Generative AI in the Historical Studies. Version 1.0. février 25. https://doi.org/10.5281/zenodo.14924737.

Offert, Fabian, et Ranjodh Singh Dhaliwal. 2024. « The Method of Critical AI Studies, A Propaedeutic ». décembre 10. https://doi.org/10.48550/arXiv.2411.18833.

Ouyang, Long et al. 2022. « Training Language Models to Follow Instructions with Human Feedback ». mars 4. https://doi.org/10.48550/arXiv.2203.02155.

Penedo, Guilherme et al. 2024. « The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale ». octobre 31. https://doi.org/10.48550/arXiv.2406.17557.

Putnam, Lara. 2016. « The Transnational and the Text-Searchable: Digitized Sources and the Shadows They Cast ». The American Historical Review 121 (2): 377‑402. https://doi.org/10.1093/ahr/121.2.377.

Risam, Roopika, et Alex Gil. 2022. « Introduction: The Questions of Minimal Computing ». Digital Humanities Quarterly 16 (2). https://digitalhumanities.org/dhq/vol/16/2/000646/000646.html.

Romein, Christel Annemieke, Achim Rabus, Gundram Leifert, et Phillip Benjamin Ströbel. 2025. « Assessing Advanced Handwritten Text Recognition Engines for Digitizing Historical Documents ». International Journal of Digital Humanities 7 (1): 115‑34. https://doi.org/10.1007/s42803-025-00100-0.

Russell, Stuart J., et Peter Norvig. 2020. Artificial Intelligence: A Modern Approach. 4ᵉ éd. Pearson.

Spirling, Arthur. 2023. « Why Open-Source Generative AI Models Are an Ethical Way Forward for Science ». Nature 616 (7957): 413. https://doi.org/10.1038/d41586-023-01295-4.

Stark, Luke. 2023. « Artificial intelligence and the conjectural sciences ». BJHS Themes 8 (août): 35‑49. https://doi.org/10.1017/bjt.2023.3.

Sternfeld, Joshua. 2023. « AI-as-Historian ». The American Historical Review 128 (3): 1372‑77. https://doi.org/10.1093/ahr/rhad368.

Strien, Daniel van, Kaspar Beelen, Mariona Coll Ardanuy, Kasra Hosseini, Barbara McGillivray, et Giovanni Colavizza. 2020. « Assessing the Impact of OCR Quality on Downstream NLP Tasks ». Proceedings of the 12th International Conference on Agents and Artificial Intelligence (ICAART 2020) (Setúbal), février 22, 484‑96. https://doi.org/10.5220/0009169004840496.

The Turing Way Community. 2022. « The Turing Way: A Handbook for Reproducible, Ethical and Collaborative Research ». Zenodo. https://doi.org/10.5281/zenodo.3233853.

The University of Chicago Press Editorial Staff. 2024. The Chicago Manual of Style. 18ᵉ éd. The University of Chicago Press. https://press.uchicago.edu/ucp/books/book/chicago/C/bo213648716.html.

Turpin, Miles, Julian Michael, Ethan Perez, et Samuel R. Bowman. 2023. « Language Models Don’t Always Say What They Think: Unfaithful Explanations in Chain-of-Thought Prompting ». mai 7. https://doi.org/10.48550/arXiv.2305.04388.

Verordnung (EU) 2016/679 zum Schutz natürlicher Personen bei der Verarbeitung personenbezogener Daten (Datenschutz-Grundverordnung), Amtsblatt der Europäischen Union 1 (2016). https://eur-lex.europa.eu/eli/reg/2016/679/oj/deu.

Verordnung (EU) 2024/1689 zur Festlegung harmonisierter Vorschriften für künstliche Intelligenz (Verordnung über künstliche Intelligenz), Amtsblatt der Europäischen Union (2024). https://eur-lex.europa.eu/eli/reg/2024/1689/oj/deu.

Walters, William H., et Esther Isabelle Wilder. 2023. « Fabrication and Errors in the Bibliographic Citations Generated by ChatGPT ». Scientific Reports 13 (1): 14045. https://doi.org/10.1038/s41598-023-41032-5.

Wei, Jason, Xuezhi Wang, Dale Schuurmans, et al. 2022. « Chain-of-Thought Prompting Elicits Reasoning in Large Language Models ». janvier 28. https://doi.org/10.48550/arXiv.2201.11903.

Wilkinson, Mark D., Michel Dumontier, IJsbrand Jan Aalbersberg, et al. 2016. « The FAIR Guiding Principles for scientific data management and stewardship ». Scientific Data 3: 160018. https://doi.org/10.1038/sdata.2016.18.

Zuboff, Shoshana. 2017. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. PublicAffairs. https://www.hachettebookgroup.com/titles/shoshana-zuboff/the-age-of-surveillance-capitalism/9781610395694/.

Note

Cette page répertorie toutes les références citées dans le projet Critical AI Literacy pour les Historiens. La bibliographie est automatiquement générée à partir de toutes les citations utilisées dans les exercices et la documentation.