Ressources sur les systèmes de génération automatique de textes#
Information
Ressources
Auteurs : Philippe Dessus, Inspé & LaRAC, Univ. Grenoble Alpes, Alexandra Salou, IMSIC, Univ. Aix-Marseille, et Benjamin Serventon, DAPI, Univ. Grenoble Alpes.
Date de création : Juin 2023.
Nombre de références : 272.
Résumé : Ceci est une liste de ressources sur les systèmes de génération de textes (SGAT, ou agents/robots conversationnels), dans la lignée de ChatGPT, dans une perspective éducative.
Voir aussi : generation-textes.
Note#
Les abréviations suivantes sont utilisées plus bas : IA : intelligence artificielle ; SGAT : systèmes de génération automatique de textes (IA génératrice de textes) ; LLM : large language models (grands modèles de langage).
Avertissement : La plupart des ressources ci-dessous ne sont pas passées par un processus de relecture par les pairs. Il convient donc de prendre avec précaution les résultats exposés. La nouveauté du thème de recherche et la vivacité du champ rend très difficile la tâche de proposer des ressources fiables.
Sites de ressources générales sur l’IA et les SGAT#
Ressources diverses#
Daily Papers (Hugging Face)
École branchée. Eduquer les élèves à l’IA
N° spécial 136 ERCIM sur les LLM
Mills, A. (2024). AI Text Generators. Sources to stimulate discussions among teachers
Centre de culture numérique, Univ. Strasbourg. Liste de ressources
Liste d’outils#
Arthur, R. (2023). AI Tools for teachers
Applications à base de SGAT#
Type d’outils : https://twitter.com/heykahn/status/1638544259925299203?s=20
SGAT pour l’enseignement#
SGAT pour la recherche#
Sambar, M., Vázquez, G. R., Vázquez, A. V., & Vázquez, F. X. (2024, Sept.). A ChatGPT Assisted Reading Protocol for Undergraduate Research Students Engaging with Biophysics Literature. BioArXiv Preprint. https://doi.org/10.1101/2024.09.11.612473
“Détecteurs” d’utilisation de SGAT#
Travaux généraux sur l’IA et la société#
Ressources générales#
Rapports#
Entretiens, opinions#
Barret Bertelloni, M. (2023, 15 juillet). Nick Srniček : « On peut imaginer un agenda radical en matière de nouvelles technologies ». AOC Média. [Accès payant]
Heikkilä, M. (2023, 30 mai). How to talk about AI (even if you don’t know much about AI). MIT Technology Review.
Histoire des SGAT#
Coa et al. (2023, 7 mars). A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT. ArXiV.
Stone, M., Goodlad, L. M. E., & Sammons, M. (2024). The Origins of Generative AI in Transcription and Machine Translation, and Why That Matters. Critical AI, 2(1). https://doi.org/10.1215/2834703x-11256853
L’impact environnemental des SGAT#
Anonyme (2023, 11 sept.). Artificial intelligence technology behind ChatGPT was built in Iowa — with a lot of water
Luccioni, A. S., et al. (2022). Estimating the carbon footprint of BLOOM, A 176b parameter language model. ArXiV.
Luccioni, A. S., Jernite, Y., & Strubell, E. (2024). Power Hungry Processing: Watts Driving the Cost of AI Deployment?. ArXiV.
Tomlison, B., et al. (2023, 8 mars). The Carbon Emissions of Writing and Illustrating Are Lower for AI than for Humans. ArXiV.
IA et vie privée#
Solove, D. J. (2024). Artificial Intelligence and Privacy. SSRN Electronic Journal.
Microtravail#
Dzieza, J. (2023, 20 juin). AI is a lot of work. The Verge.
Meaker, M. (2023, 11 sept.). These prisoners are training AI. Wired.
Shitawa, W. (2024). They Are All the Same: Poor Pay and Long Hours for Data Annotators in Kenya’s Outsourcing Industry. In: M. Miceli, A. Dinika, L. Sachenbacher, C. Salim Wagner, and K. Kauffman (eds), The Data Workers‘ Inquiry. https://data-workers.org/wilington
Tubaro, P. & Coville, M. & Le Ludec, C. & Casilli, A. A. (2022). Hidden inequalities: the gendered labour of women on micro-tasking platforms Internet Policy Review, 11(1).
Veselovsky V. et al. (2023, 13 juin)Artificial Artificial Artificial Intelligence: Crowd Workers Widely Use Large Language Models for Text Production Tasks. ArXiV.
Les SGAT comme aide à la recherche#
Bouchard, A. (2024). Au-delà de ChatGPT. Recherche d’informations académiques et intelligence artificielle. Paris : URFIST.
Dwivedi, Y. K., et al. (2023). Opinion Paper: “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71. https://doi.org/10.1016/j.ijinfomgt.2023.102642
Grossmann, I., Feinberg, M., Parker, D. C., Christakis, N. A., Tetlock, P. E., & Cunningham, W. A. (2023). AI and the transformation of social science research. Science, 280(6650), 1108–1109. https://doi.org/10.1126/science.adi1778
Hoover, A. (2023, août). Use of AI Is Seeping Into Academic Journals—and It’s Proving Difficult to Detect. Wired.
Liang, W. et al. (2023, oct.). Can large language models provide useful feedback on research papers? A large-scale empirical analysis. ArXiV.
Lockwood, A. B., & Castleberry, J. (2024). Examining the Capabilities of GPT-4 to Write an APA-Style School Psychology Paper. Contemporary School Psychology. https://doi.org/10.1007/s40688-024-00500-z
Nam, B. H., & Bai, Q. (2023). ChatGPT and its ethical implications for STEM research and higher education: a media discourse analysis. International Journal of STEM Education, 10(1). https://doi.org/10.1186/s40594-023-00452-5
Srivastava, M. (2023, mars). A day in the life of ChatGPT as an academic reviewer: Investigating the potential of large language model for scientific literature review. ArXiV.
Underwood, T. (2023, mars). Using GPT-4 to measure the passage of time in fiction. Billet de blog.
Yao X. et al. (2024, février). Evaluating the efficacy of artificial intelligence tools for the automation of systematic reviews in cancer research: A systematic review. Cancer Epidemiol., 88.
Ziems et al. (2023, avril) Can LLM transform computational social science?.
SGAT et épistémologie#
Schneider, S. (2024). Chatbot epistemology. PhilPapers Archive. https://philpapers.org/rec/SCHCEJ-2
Travaux généraux sur l’IA et l’éducation#
Rapports#
AMUE (2023, déc.). IA et enseignement supérieur : quels enjeux et impacts ?
Artificial intelligence and teaching, Univ. Monash, Australie
De la Higuera, C., & Iyer, J. (2023). IA pour les enseignants : un manuel ouvert.
DNE-TN2 (2023). Intelligence artificielle et éducation : Apports de la recherche et enjeux pour les politiques publiques. Éducation, numérique et recherche. Paris : MEN.
Office of Educ. Technol. (2023, mai). Artificial intelligence and the future of teaching and learning.
Romero, M. et al. (2023, 13 mars). Enseigner et apprendre à l’ère de l’intelligence artificielle. Canopé).
Unesco (2021). IA et éducation. Guide pour les décideurs politiques
Ressources pédagogiques pratiques sur l’IA#
Goodlad, L. M. E., & Stoerger, S. (2023). Teaching critical AI literacy. Rutgers Univ.
Masure, A. IA et pédagogie : état de l’art
Université de Bordeaux (2023). Intelligences artificielles génératives : ressources
Entretiens critiques sur l’utilisation de l’IA dans l’éducation#
Andronikidis, K. (2023). Meaningful and ethical use of data in schools. Data4Learning Webinar Series. European Schoolnet. Brussels, Belgium [Transcription de webinaires].
Boullier, D. (2023, 7 fév.). Sciences Po a eu raison d’interdire ChatGPT. AOC. Accès payant.
Collin, S. M., & Marceau, E. (2021). L’intelligence artificielle en éducation : enjeux de justice. Formation et Profession, 29(2), 1. https://doi.org/10.18162/fp.2021.a230
Goodlad, L. M. E., & Stone, M. (in press). Beyond Chatbot-K: On Large Language Models, “Generative AI,” and Rise of Chatbots: An Introduction. Critical AI.
IA et apprentissage#
Costello, T. H., Pennycook, G., & Rand, D. G. (2024). Durably reducing conspiracy beliefs through dialogues with AI. PsyArXiv preprint.
Gweon, H., Fan, J., & Kim, B. (2023). Socially intelligent machines that learn from humans and help humans learn. Philos Trans A Math Phys Eng Sci, 381(2251), 20220048.
Lehmann, M., Cornelius, P. B., & Sting, F. J. (2024). AI Meets the Classroom: When Does ChatGPT Harm Learning? ArXiv preprint. https://arxiv.org/abs/2409.09047
Aspects éthiques de l’utilisation de l’IA en éducation#
Noguera, P. (Ed.). (2024). Critical thinking and ethics in the age of generative AI in education. USC Rossier Center for Generative AI and Society. https://today.usc.edu/wp-content/uploads/2024/02/USC_GenerativeAI_011624_FINAL.pdf.
Littéracie de l’IA#
Abegglen, S., Nerantzi, C., Martinez-Arboleda, A., Kartsiori, M., Atenas, J., & Rowell, C. (2024). Towards AI Literacy: 101+. https://zenodo.org/records/11613520
Watkins, M. (s.d.). Exploring Neural Networks with Quick, Draw!
L’IA générative (les SGAT) et l’éducation#
Guides généraux d’utilisation des SGAT à l’université#
Atlas, S. (2023). ChatGPT for Higher Education and Professional Development: A Guide to Conversational AI.
Lukes, D. (s.d.). Integrating AI into Academic Practice: Guide to Reflective Exploration.
Lukes, D. (s.d.). Code of Conduct for AI Literacy and Policy Practitioners
Miao, F. & Holmes, W. (2023). Guidance for generative AI in education and research. Paris: Unesco. Version Française
Npuls (2023). Smarter education with AI
Unesco (2024). Cadres de compétences en IA pour les enseignants et les étudiants.
Rapports#
Nathan, A., Grimberg, J., & Rhodes, A. (2024). Gen AI: Too much spend, too little benefit?. Top of Mind, 129, 1–31.
Sabzalieva, E. & Valentini, A. (2023). ChatGPT and artificial intelligence in higher education. Paris : UNESCO.
Cours#
Facciolo, L. (2024, Février). You & AI
Stanford (Teaching commons). Defining AI and chatbots
Stanford (Teaching commons). Exploring the pedagogical uses of AI chatbots
Stanford (Teaching commons). Analyzing the implications of AI for your course
Stanford (Teaching commons). Creating your course policy on AI
Revues générales sur les SGAT et l’éducation#
Albadarin, Y. (2023, 9 mai). Usages de chatGPT en éducation.
Amer-Yahia, S., Bonifati, A., Chen, L., Li, G., Shim, K., Xu, J., & Yang, X. (2023). From Large Language Models to Databases and Back: A Discussion on Research and Education. In 28th International Conference on Database Systems for Advanced Applications (DASFAA 2023), Tianjin.
Association EPI (2023, mars). A propos de ChatGPT.
Banerjee, P. et al. (2023, Avril). Understanding ChatGPT: Impact Analysis and Path Forward for Teaching Computer Science and Engineering. TecRxiV.
Bhullar, P. S., Joshi, M., & Chugh, R. (2024). ChatGPT in higher education - a synthesis of the literature and a future research agenda. Education and Information Technologies. https://doi.org/10.1007/s10639-024-12723-x
Cao, L., & Dede, C. (2023). Navigating A World of Generative AI: Suggestions for Educators. The Next Level Lab at Harvard Graduate School of Education. President and Fellows of Harvard College: Cambridge, MA.
Chan, C. K. Y., & Colloton, T. (2024). Generative AI in higher education. The ChatGPT Effect. Routledge.
ChatGPT, une utilité pédagogique Crompton, H., & Burke, D. (2024). The Educational Affordances and Challenges of ChatGPT: State of the Field. TechTrends, 68(2), 380-392. https://doi.org/10.1007/s11528-024-00939-0
Cuban, L. (2023, 13 juin). ChatGPT is going to change education, not destroy it.
Dawson, P. (2023, 13 juin). Don’t fear the robot. Présentation. .
Duguay, S. (2024). Guide pour une approche réflexive de l’IA en éducation.
Fawns, T. (2023, 8 sept). Expanding the unit of analysis of learning.
FII Institute (2023). Will ChatGPT give us a lesson in education?. Nature portfolio.
Fraiwan et al. (2023). A Review of ChatGPT Applications in Education, Marketing, Software Engineering, and Healthcare
Futterer, T., Fischer, C., Alekseeva, A., Chen, X., Tate, T., Warschauer, M., & Gerjets, P. (2023). ChatGPT in education: global reactions to AI innovations. Sci Rep, 13(1), 15310. https://doi.org/10.1038/s41598-023-42227-6
Giannakos, M., Azevedo, R., Brusilovsky, P., Cukurova, M., Dimitriadis, Y., Hernandez-Leo, D., Järvelä, S., Mavrikis, M., & Rienties, B. (2024). The promise and challenges of generative AI in education. Behaviour & Information Technology, 1-27. https://doi.org/10.1080/0144929x.2024.2394886
Goudey, A., Loupiac, P., & Quinio, B. (2024). Regards croisés sur les IA génératives dans l’enseignement supérieur en gestion. Paris: FNEGE https://www.calameo.com/read/00193017163b774979682
Herft, A. (2023). Guide de l’enseignant. L’usage de ChatGPT
Hsu, Y.-C., & Ching, Y.-H. (2023). Generative Artificial Intelligence in Education, Part One: the Dynamic Frontier. TechTrends, 67(4), 603-607. https://doi.org/10.1007/s11528-023-00863-9
IA et éducation : apports de la recherche et focus sur les IA génératives
Journée de réflexion collective sur l’IA générative. Montréal : UQÀM.
Kahn, S. (2023). The amazing AI super tutor for students and teachers. TED Talk.
Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., … Kasneci, G. (2023, January 30). ChatGPT for Good? On Opportunities and Challenges of Large Language Models for Education. https://doi.org/10.35542/osf.io/5er8f
Khosravi, H., Denny, P., Moore, S., & Stamper, J. (2023). Learnersourcing in the age of AI: Student, educator and machine partnerships for content creation. Computers and Education: Artificial Intelligence, 5. https://doi.org/10.1016/j.caeai.2023.100151
Lodge, J. M., Yang, S., Furze, L., & Dawson, P. (2023). It’s not like a calculator, so what is the relationship between learners and generative artificial intelligence? Learning: Research and Practice, 9(2), 117-124. https://doi.org/10.1080/23735082.2023.2261106
Mills, A., Bali, M., & Eaton, L (2023). How do we respond to generative AI in education?. J. Applied Learning & Teaching, 6(1), 1-15.
Mishra, P., Oster, N., & Henriksen, D. (2024). Generative AI, Teacher Knowledge and Educational Research: Bridging Short- and Long-Term Perspectives. TechTrends. https://doi.org/10.1007/s11528-024-00938-1
Mishra, P., Warr, M., & Islam, R. (2023). TPACK in the age of ChatGPT and Generative AI. Journal of Digital Learning in Teacher Education, 39(4), 235-251. https://doi.org/10.1080/21532974.2023.2247480
Mollick, E. R. & Mollick, L. (2022, 13 déc.). New Modes of Learning Enabled by AI Chatbots: Three Methods and Assignments. SSRN.
Monsieur Phi (2024). Enthoven ou ChatGPT : qui est l’imposteur ?
Morgan, G. (2023, 4 mai). The 5 pathologies of EdTech Discourse about Generative AI
Palenski, T., Hills, L., Unnikrishnan, S., & Eynon, R. (2024). How AI Works: Reconfiguring Lifelong Learning. Postdigital Science and Education.
Robinson, G. (2023). Generative AI in Education: An introduction
Rose, R. (2023). ChatGPT in higher education
Searson, M., Langran, E., & Jason, T. (Eds.). (2024). Exploring New Horizons: Generative Artificial Intelligence and Teacher Education. AACE. https://www.learntechlib.org/p/223928/
Sentance, S. (2024). Using generative AI in the classroom: a guide for computing teachers. Univ. of Cambridge.
Sharples, M. (2023). Towards social generative AI for education: theory, practices and ethics. Learning: Research and Practice, 9(2), 159-167. https://doi.org/10.1080/23735082.2023.2261131
Van Rooij, I. (2023, 14 janv.). Stop feeding the hype and start resisting
Williamson, B. (2024, Février). AI in education is a public problem. Blog post.
Williamson, B., Molnar, A., & Boninger, F. (2024, Mars). Time for a pause: Without effective public oversight, AI in schools will do more harm than good. Boulder, CO: National Education Policy Center.
Yan, L., Sha, L., Zhao, L., Li, Y., Martinez‐Maldonado, R., Chen, G., Li, X., Jin, Y., & Gašević, D. (2023). Practical and ethical challenges of large language models in education: A systematic scoping review. British Journal of Educational Technology, 55(1), 90-112. https://doi.org/10.1111/bjet.13370
Yang, Z., Wu, J. G., & Xie, H. (2024). Taming Frankenstein’s monster: Ethical considerations relating to generative artificial intelligence in education. Asia Pacific Journal of Education, 1-14. https://doi.org/10.1080/02188791.2023.2300137
Régulation de l’IA générative#
Ulnicane, I. (2024). Governance fix? Power and politics in controversies about governing generative AI Policy and Society, https://doi.org/10.1093/polsoc/puae022
SGAT et éducation : questions plus spécifiques#
Impact des SGAT sur les performances académiques#
Banihashem, S. K., Bergdahl, N., Bond, M., & Khosravi, H. (2024). A Systematic Mapping Review at the Intersection of Artificial Intelligence and Self-Regulated Learning: A call for increased theoretical grounding, focus on motivation and diversifying context. ResearchGate Preprint. https://doi.org/10.13140/RG.2.2.13057.47207
Niloy, A. C., Akter, S., Sultana, N., Sultana, J., & Rahman, S. I. U. (2023). Is Chatgpt a menace for creative writing ability? An experiment. Journal of Computer Assisted Learning, 40(2), 919-930. https://doi.org/10.1111/jcal.12929
Wecks, J. O., Voshaar, J., Jost Plate, B., & Zimmermann, J. (2024). Generative AI Usage and Academic Performance. ArXiv preprint. https://arxiv.org/pdf/2404.19699
Impact des SGAT sur les pratiques évaluatives#
Carrefour, Le (2023). 10 stratégies pour éviter le plagiat lors de l’utilisation d’un agent conversationnel (ChatGPT) dans les évaluations. UQUÀM.
Crozat, S. (2023, 26 sept.). IA génératives : la fin des exercices rédactionnels à l’université ?
Docq, F., Polain, C., Warnier, L., & Wouters, P. (2023). ChatGPT et les outils d’IA : quels enjeux sur les mémoires en 2023 ? Formation organisée pour les enseignant·es de l’UCLouvain, Louvain. https://oer.uclouvain.be/jspui/bitstream/20.500.12279/901/1/Formation_IA_memoires_2023-03-17.pdf
Farazouli, A., Cerratto-Pargman, T., Bolander-Laksov, K., & McGrath, C. (2023). Hello GPT! Goodbye home examination? An exploratory study of AI chatbots impact on university teachers’ assessment practices. Assessment & Evaluation in Higher Education, 1-13. https://doi.org/10.1080/02602938.2023.2241676
Fawns, T., & Schuwirth, L. (2024). Rethinking the value proposition of assessment at a time of rapid development in generative artificial intelligence. Med Educ, 58(1), 14-16. https://doi.org/10.1111/medu.15259
Francis, N., & Smith, D. (2023). Generative AI in assessment. Guidance staff. Edge Hill Univ.
Hutson, J. & Plate, D. (2023). Working With (Not Against) the Technology: GPT3 and Artificial Intelligence (AI) in College Composition. Lindenwood Univ.
Lang, J. M. (2023, 4 avril)How to Create Compelling Writing Assignments in a ChatGPT Age
Le, A. V., & Metzger, W. (2024). Assessing the impact and challenges of AI-based language models on the education sector: a proposal for new assessment strategies and design. Journal of Teaching in Travel & Tourism, 24(2), 167-178. https://doi.org/10.1080/15313220.2024.2311907
Liu, D., & Bridgeman, A. (2023, 8 juin). ChatGPT is old news: How do we assess in the age of AI writing co-pilots?
Lodge, J. M. (2023, 1er mai). Assessment redesign for generative AI: A taxonomy of options and their viability.
Mollick, E. (2023, 1er Juillet). The homework apocalypse. Billet de blog.
Rodriguez, D. (2023). Prendre Position : Charte pour une utilisation socialement responsable de ChatGPT à l’Icam. Conférence au SIUP, Univ. Toulouse, Toulouse.
Swiecki, Z., Khosravi, H., Chen, G., Martinez-Maldonado, R., Lodge, J. M., Milligan, S., Selwyn, N., & Gašević, D. (2022). Assessment in the age of artificial intelligence. Computers and Education: Artificial Intelligence, 3. https://doi.org/10.1016/j.caeai.2022.100075
Tate, T. P., Steiss, J., Bailey, D., Graham, S., Ritchie, D., Tseng, W., Moon, Y., & Warschauer, M. (2023, 7 déc.). Can AI Provide Useful Holistic Essay Scoring? OSF Preprint. https://doi.org/https://osf.io/preprints/osf/7xpre
TEQSA (2023, sept.). Assessment reform for the age of artificial intelligence.
Xia, Q., Weng, X., Ouyang, F., Lin, T. J., & Chiu, T. K. F. (2024). A scoping review on how generative artificial intelligence transforms assessment in higher education. International Journal of Educational Technology in Higher Education, 21(1). https://doi.org/10.1186/s41239-024-00468-z
Tricherie et détection d’usage de l’IA générative#
Antoun, W. et al. (2023). Towards a Robust Detection of Language Model-Generated Text: Is ChatGPT that Easy to Detect?. TALN 2023 Conf.
Aylsworth, T., & Castro, C. (2024). Should I Use ChatGPT to Write My Papers? Philosophy & Technology, 37(4). https://doi.org/10.1007/s13347-024-00809-w
Bogost, I. (2023, 16 mai). The first year of AI College ends in Ruin
Bohlmann, M., & Berger, A. M. (2024). ChatGPT and the Writing of Philosophical Essays. Teaching Philosophy, 47(2), 233–253. https://doi.org/10.5840/teachphil202451200
Carrefour, Le. 10 stratégies pour éviter le plagiat lors de l’utilisation d’un agent conversationnel dans les évaluations
Chaka, C. (2023). Detecting AI content in responses generated by ChatGPT, YouChat, and Chatsonic: The case of five AI content detection tools. Journal of Applied Learning & Teaching, 6(2).
Chen, B., Lewis, C. M., West, M., & Zilles, C. (2024). Plagiarism in the Age of Generative AI: Cheating Method Change and Learning Loss in an Intro to CS Course. L@S ’24, Atlanta.
De Silva, D., Mills, N., El-Ayoubi, M., Manic, M., & Alahakoon, D. (2023). ChatGPT and Generative AI Guidelines for Addressing Academic Integrity and Augmenting Pre-Existing Chatbots. 2023 IEEE International Conference on Industrial Technology (ICIT).
Denkin, R. (2024, May). On Perception of Prevalence of Cheating and Usage of Generative AI. ArXiv preprint. https://doi.org/10.48550/arXiv.2405.18889
Eaton, S.E. AI and academic Integrity
Ellis, C., & Murdoch, K. (2024). The educational integrity enforcement pyramid: a new framework for challenging and responding to student cheating. Assessment & Evaluation in Higher Education, 1-11. https://doi.org/10.1080/02602938.2024.2329167
Fendler, R., Beard, D., & Godbey, J. (2024). A Robust Examination of Cheating on Unproctored Online Exams. Electronic Journal of E-learning, 22(5), 26-38. https://doi.org/10.34190/ejel.22.5.3173
Firth, D. R., Derendinger, M., & Triche, J. (2024). Cheating Better with ChatGPT: A Framework for Teaching Students When to Use ChatGPT and other Generative AI Bots. Information Systems Education Journal, 22(3), 47–60.
Fröhling L, Zubiaga A. (2021). Feature-based detection of automated language models: tackling GPT-2, GPT-3 and Grover. PeerJ Computer Science, 7:e443
Jiang, Z. et al. (2023, 5 mai). Evading Watermark based Detection of AI-Generated Content. ArXiV.
Kan, M. (2023). Instructor Accuses Texas A&M Class of Using ChatGPT, Withholds Grades
Kazley, A. S., Andresen, C., Mund, A., Blankenship, C., & Segal, R. (2024). Is use of ChatGPT cheating? Students of health professions perceptions. Med Teach, 1-5. https://doi.org/10.1080/0142159X.2024.2385667
Kirchenbauer J. et al. (2023, 9 juin). On the Reliability of Watermarks for Large Language Models.
Klee, M. (2023, 6 juin). She Was Falsely Accused of Cheating With AI — And She Won’t Be the Last
Kobak, D. et al. (2024, Juin). Delving into ChatGPT usage in academic writing through excess vocabulary. ArXiV.
Walsh, J., Krienert, J., Cannon, K., & Honan, S. (2024). Professors Call it Cheating, Students Call it Teamwork. Journal of the Scholarship of Teaching and Learning, 24(2). https://doi.org/10.14434/josotl.v24i2.35191
Liang et al. (2023). GPT detectors are biased against non-native English writers
Mindner, L. et al. (2023, Août). Classification of Human- and AI-Generated Texts: Investigating Features for ChatGPT. ArXiV.
Mitrovic, S., Davide, A., & Ayoub, O. (2023). ChatGPT or human? Detect and explain. Explaining decisions of machine learning model for detecting short ChatGPT-generated text. ArXiv preprint.
Mizumoto, A., Yasuda, S., & Tamura, Y. (2024). Identifying ChatGPT-Generated Texts in EFL Students’ Writing: Through Comparative Analysis of Linguistic Fingerprints. Applied Corpus Linguistics. https://doi.org/10.1016/j.acorp.2024.100106
Newton, P., & Xiromeriti, M. (2024). ChatGPT performance on multiple choice question examinations in higher education. A pragmatic scoping review. Assessment & Evaluation in Higher Education, 1-18. https://doi.org/10.1080/02602938.2023.2299059
OpenAI (2023). How can educators respond to students presenting AI-generated content as their own?.
Rüth, M., Jansen, M., & Kaspar, K. (2024). Cheating behaviour in online exams: On the role of needs, conceptions and reasons of university students. Journal of Computer Assisted Learning. https://doi.org/10.1111/jcal.12994
Sadasivan et al. (2023). Can AI-generated text be reliably detected.
Scarfe, P., Watcham, K., Clarke, A., & Roesch, E. (2024). A real-world test of artificial intelligence infiltration of a university examinations system: A “Turing Test” case study. PLoS ONE, 19(6), e0305354. https://doi.org/10.1371/journal.pone.0305354
Shaw, D., Morfeld, P., & Erren, T. (2023). The (mis)use of ChatGPT in science and education: Turing, Djerassi, “athletics” & ethics. EMBO Rep, 24(7), e57501. https://doi.org/10.15252/embr.202357501
Sheinman Orenstrakh et al. (2023, juil.). Detecting LLM-Generated Text in Computing Education: A Comparative Study for ChatGPT Cases. ArXiV.
Šigut, P., & Foltýnek, T. s. (2023). Can We Detect ChatGPT-generated Texts in Czech and Slovak Languages? In A. Horák, P. Rychlý, & A. Rambousek (Eds.), Proc. Recent Advances in Slavonic Natural Language Processing (RASLAN 2023) (pp. 35–43). Tribun EU.
Tang, R. et al. (2023, juin). The Science of Detecting LLM-Generated Texts. ArXiV
Vetter, M. A., Lucia, B., Jiang, J., & Othman, M. (2024). Towards a framework for local interrogation of AI ethics: A case study on text generators, academic integrity, and composing with ChatGPT. Computers and Composition, 71. https://doi.org/10.1016/j.compcom.2024.102831
Weber-Wulff, D. et al. (2023, 10 Juil.). Testing of Detection Tools for AI-Generated Text. ArXiV.
Yu, P., Chen, J., Feng, X., & Xia, Z. (2023). CHEAT: A Large-scale Dataset for Detecting ChatGPT-writtEn AbsTracts. ArXiv preprint.
Tricherie et intégrité académique (hors IA)#
Bretag, T., & Harper, R. (2019). Contract cheating and assessment design: exploring the connection
Cole, S., & McCabe, D. L. (1996). Issues in academic integrity. New Directions for Student Services, 73, 67–76.
Rüth, M., Jansen, M., & Kaspar, K. (2024). Cheating behaviour in online exams: On the role of needs, conceptions and reasons of university students. Journal of Computer Assisted Learning. https://doi.org/10.1111/jcal.12994
Opinions des étudiants et enseignants#
Compilatio-Le Sphinx (2023). Enseignants et étudiants confrontent leurs regards sur l’IA
Pôle Leonard de Vinci, RM Conseil & Talan (2024, avril). L’impact des IA génératives sur les étudiants
Politiques d’usage des SGAT dans les universités#
Chartes d’universités#
Artificial intelligence and teaching, Univ. Monash, Australie.
Boston Univ. (2023). Using Generative AI in Coursework.
Hôpitaux universitaires de Genève (2024). Charte d’utilisation des intelligences artificielles
Sciences Po Grenoble (2024). Les bons usages de l’Intelligence Artificielle Générative
Université de Bretagne occidentale (s.d.). Charte de l’IA à l’UBO
Université Laval (2024). Principes directeurs concernant l’intelligence artificielle dans l’enseignement et l’apprentissage
Université de Liège (2023). Charte ULiège d’utilisation des intelligences artificielles génératives dans les travaux universitaires
Université de Mons (s.d.). Charte d’utilisation des systèmes d’intelligence artificielle générative dans les travaux universitaires à l’UMONS
Université d’Orléans (2024). Charte intelligence artificielle
Yale Univ. (2023). Resources on ChatGPT and other AI software
Yale Univ. (2023). AI guidance
Travaux de recherche sur les politiques d’usage des SGAT#
Bukar, U. A., Sayeed, M. S., Razak, S. F. A., Yogarayan, S., & Amodu, O. A. (2024). An integrative decision-making framework to guide policies on regulating ChatGPT usage. PeerJ Comput Sci, 10, e1845. https://doi.org/10.7717/peerj-cs.1845
Conrad, K. (2023). A blueprint for an AI bill of rights for education
Dotan, R., Parker, L. S., & Radzilowicz, J. G. (2024). Responsible Adoption of Generative AI in Higher Education: Developing a “Points to Consider” Approach Based on Faculty Perspectives. Proc. FAccT ’24 Int. Conf., Rio de Janeiro.
Dunnigan, J., Henriksen, D., Mishra, P., & Lake, R. (2023). “Can we just Please slow it all Down?” School Leaders Take on ChatGPT. TechTrends, 67(6), 878-884. https://doi.org/10.1007/s11528-023-00914-1
Eaton, L. (2023). Classroom policies for AI generative tools
Evans, A. (2024, 19 mai). How Can Professors Prevent Plagiarism in a World of ChatGPT?. Billet de blog.
Furze, L., Perkins, M., Roe, J., & MacVaugh, J. (2024). The AI Assessment Scale (AIAS) in action: A pilot implementation of GenAI supported assessment. ArXiv preprint. https://arxiv.org/pdf/2403.14692
Luo, J. (2024). A critical review of GenAI policies in higher education assessment: a call to reconsider the “originality” of students’ work. Assessment & Evaluation in Higher Education, 1-14. https://doi.org/10.1080/02602938.2024.2309963
Mucharraz y Cano et al. (2023, 1er Fév.). ChatGPT and AI Text Generators: Should Academia Adapt or Resist?. Harvard Business Publishing Education.
Russell Group (2023, 4 Juillet). New principles on use of IA in education.
Stanford Univ. (2023). Generative AI Policy Guidance.
Sullivan, M., Kelly, A., & Mclaughlan, P. (2023). ChatGPT in higher education: Considerations for academic integrity and student learning. Journal of Applied Learning & Teaching, 6(1), 1–10. https://doi.org/10.37074/jalt.2023.6.1.17
TeachAI (2024). [AI Guidance for school toolkit](https://www.teachai.org/toolkit.
Univ. de Leeds (s.d.). Generative AI resources
Welker, G. (2023). BBJ: Academic unit at Boston Univ. adopts guidelines for use of generative AI.
Xiao, P., Chen, Y., & Bao, W. (2023). Waiting, Banning, and Embracing: An Empirical Analysis of Adapting Policies for Generative AI in Higher Education. ArXiv preprint. https://arxiv.org/pdf/2305.18617
Les représentations de l’IA par les usagers#
Ada Lovelace Institute, & Alan Turing Institute. (2023). How do people feel about AI? A nationally representative survey of public attitudes to artificial intelligence in Britain. London.
Avry, S., Mondada, F., Liégeois, G., Vaucher, E., Martinez, F., & Dehler Zufferey, J. (2023). ChatGPT. L’avis des enseignant·es. Lausanne: EPFL.
Ethique et SGAT#
Danaher, J., & Nyholm, S. (2024). The ethics of personalised digital duplicates: a minimally viable permissibility principle. AI and Ethics.
Gabriel, I., Manzini, A., Keeling, G., Hendricks, L. A., Rieser, V., Iqbal, H., Tomašev, N., Ktena, I., Kenton, Z., Rodriguez, M., El-Sayed, S., Brown, S., Akbulut, C., Trask, A., Hughes, E., Bergman, A. S., Shelby, R., Marchal, N., Griffin, C., … Manyika, J. (2024). The ethics of advanced AI assistants. Google DeepMind Report.
Kay, J., Kasirzadeh, A., & Mohamed, S. (2024). Epistemic injustice in Generative AI. Proc. 7th AAAI/ACM Conference on AI, Ethics, and Society (AIES2024).
Trust, T. (2024). GenAI & Ethics. Investigating ChatGPT, Gemini, & Copilot. Presentation slides.
SGAT et pédagogie#
Effets sur l’apprentissage#
Bastani, H., Bastani, O., Sungu, A., Ge, H., Kabakcı, Ö., & Mariman, R. (2024). Generative AI Can Harm Learning. SSRN Electronic Journal.
Les manuels génératifs#
Wiley, D. (2023, 6 Juillet). Generative Textbooks-A brief example.
Le tutorat, le feedback#
Phung et al. (2023, 29 juin). Generative AI for Programming Education: Benchmarking ChatGPT, GPT-4, and Human Tutors. ArXiV.
Schultze, T., Kumar, V. S., McKeown, G. J., O’Connor, P. A., Rychlowska, M., & Sparemblek, K. (2024, March 12). Using Large Language Models to Augment (Rather Than Replace) Human Feedback in Higher Education Improves Perceived Feedback Quality. PsyArXiV Preprint. https://doi.org/10.31234/osf.io/tvcag
Les SGAT et le raisonnement scientifique#
Goldstein, J. A., Chao, J., Grossman, S., Stamos, A., & Tomz, M. (2024). How persuasive is AI-generated propaganda? PNAS Nexus, 3(2), pgae034. https://doi.org/10.1093/pnasnexus/pgae034
Nikolic, S., Daniel, S., Haque, R., Belkina, M., Hassan, G. M., Grundy, S., Lyden, S., Neal, P., & Sandison, C. (2023). ChatGPT versus engineering education assessment: a multidisciplinary and multi-institutional benchmarking and analysis of this generative artificial intelligence tool to investigate assessment integrity. European Journal of Engineering Education, 48(4), 559-614. https://doi.org/10.1080/03043797.2023.2213169
Perkowitz, S. (2023, 28 mars). What Does ChatGPT Know About Science?. Nautilus, 49.
Les SGAT et la programmation#
Nie, A., Chandak, Y., Suzara, M., Malik, A., Woodrow, J., Peng, M., Sahami, M., Brunskill, E., & Piech, C. (2024). The GPT Surprise: Offering Large Language Model Chat in a Massive Coding Class Reduced Engagement but Increased Adopters’ Exam Performances. ArXiv preprint. https://doi.org/10.31219/osf.io/qy8zd
Les SGAT et l’enseignement des langues#
Jeon, J., & Lee, S. (2023). Large language models in education: A focus on the complementary relationship between human teachers and ChatGPT. Education and Information Technologies. https://doi.org/10.1007/s10639-023-11834-1
Les SGAT et la formation des enseignants et des étudiants#
Dillig, M., Böhmer, A., Mason, J., Bolaji, S., Isso, I., Stănescu, M. H., Sahin, H., & Kuraner, A. (2024). A Segue From Search to Dialogue. In Transforming Education With Generative AI (pp. 1-34). IGI Press https://doi.org/10.4018/979-8-3693-1351-0.ch002
Lupetti, M. L., & Murray-Rust, D. (2024). (Un)making AI Magic: A Design Taxonomy. Proceedings of the CHI Conference on Human Factors in Computing Systems.
Les SGAT pour la créativité et la curiosité#
Abdelghani, R. et al. (2022, nov.). GPT-3-driven pedagogical agents for training children’s curious question-asking skills. ArXiV.
Bellemare-Pepin, A., Lespinasse, F. o., Thölke, P., Harel, Y., Mathewson, K., Olson, J. A., Bengio, Y., & Jerbi, K. (2024). Divergent Creativity in Humans and Large Language Models.
Chakrabarty, T., Laban, P., Agarwal, D., Muresan, S., & Wu, C.-S. (2024). Art or Artifice? Large Language Models and the False Promise of Creativity. Proceedings of the CHI Conference on Human Factors in Computing Systems (CHI’24).
Girota, K. et al. (2023, août). Ideas are Dimes a Dozen: Large Language Models for Idea Generation in Innovation. SSRN.
Haase, J. & Hanel, P.H.P. (2023, mars). Artificial muses: Generative Artificial Intelligence Chatbots Have Risen to Human-Level Creativity. ArXiV.
Luchini, S. et al. (2023, oct.)? Automatic Scoring of Creative Problem-Solving with Large Language Models: A Comparison of Originality and Quality Ratings. PsyArXiv.
Mollick, E. (2023, 13 août). Automating creativity. Blog.
Si, C. et al. (2024, sept.). Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP Researchers.ArXiV.
Aspects techniques#
Le fonctionnement des SGAT#
Bycroft, B. (2023). LLM Visualization.
Copyleaks (2024). Copyleaks Research Finds Nearly 60% of GPT-3.5 Outputs Contained Some Form of Plagiarized Content.
Lee, J., Chen, J., Le, T., & Lee, D. (2023). Do Language Models Plagiarize?. WWW 2023, Austin.
OpenAI (2023, mars). GPT-4 Technical Report. ArXiV.
Ornes, S. (2023). Modèles massifs de langage. D’où viennent les coups de génie de l’IA ? Pour la Science, 549, 47–51.
Prince, S. J. D. (2023, 8 mai). Understanding deep learning. MIT Press.
Shanahan, M. (2023, fév.). Talking about large language models. ArXiV.
Vafa, K. et al. (2024, juin). Evaluating the World Model Implicit in a Generative Model. ArXiv.
Vig, J. (2019). A Multiscale Visualization of Attention in the Transformer Model. Ann. Meeting of the ACL.
Visual storytelling team & Murgia, M. (2023). Generative AI exists because of the transformer. Financial Times.
Vu, T. et al. (2023, oct.). FreshLLMs: Refreshing Large Language Models with Search Engine Augmentation. ArXiV.
La fiabilité des SGAT#
Farquhar, S., Kossen, J., Kuhn, L., & Gal, Y. (2024). Detecting hallucinations in large language models using semantic entropy. Nature, 630(8017), 625-630.
Hannigan, T. R., McCarthy, I. P., & Spicer, A. (2023). Beware of botshit: How to manage the epistemic risks of generative chatbots. SSRN Electronic Journal.
Hicks, M. T., Humphries, J., & Slater, J. (2024). ChatGPT is bullshit. Ethics and Information Technology, 26(2).
Makhortykh, M. & Mann, H. (2024). AI and the Holocaust: rewriting history? The impact of artificial intelligence on understanding the Holocaust.
Rétroingénierie des SGAT#
Les corpus d’entraînement des SGAT#
Gao, L. et al. (2020). The Pile: An 800GB Dataset of Diverse Text for Language Modeling. ArXiV.
Les LLM en tant que modèles psychologiques (ou pas)#
Abdurahman, S., Atari, M., Karimi-Malekabadi, F., Xue, M. J., Trager, J., Park, P. S., Golazizian, P., Omrani, A., & Dehghani, M. (2024). Perils and opportunities in using large language models in psychological research. PNAS Nexus, 3(7), pgae245.
Atari, M. et al. (2023, avril). Contextualized Construct Representation: Leveraging Psychometric Scales to Advance Theory-Driven Text Analysis. PsyArXiV.
Atari, M. et al. (2023, sept.). Which humans?. PsyArXiV.
Bajohr, H. (2023). Dumb meaning: ML and artificial semantics. Image., sur le symbol grounding](https://hal.science/hal-04013223v2/file/202303_LivreBlanc_UsagesCreatifsIA_GTnum_Scol_IA_R02.pdf).
Bakhtin, A. et al. (2023). Human-level play in the game of Diplomacy by combining language models with strategic reasoning. Science, 378, 1067-1074.
Birhane, A., & McGann, M. (2024). Large Models of What? Mistaking Engineering Achievements for Human Linguistic Agency. ArXiv preprint. https://arxiv.org/pdf/2407.08790
Blank, I. A. (2023). What are large language models supposed to model? Trends Cogn Sci. https://doi.org/10.1016/j.tics.2023.08.006
Connell, L. & Lynott, D. (2024). What Can Language Models Tell us About Human Cognition?. OSF Preprint.
Cuskley, C., Woods, R., & Flaherty, M. (2024). The Limitations of Large Language Models for Understanding Human Language and Cognition. Open Mind, 8, 1058-1083. https://doi.org/10.1162/opmi_a_00160
Demszky, et al. (2023). Using large language models in psychology. Nature Reviews Psychology. https://doi.org/10.1038/s44159-023-00241-5
Dillion, D., Tandon, N., Gu, Y., & Gray, K. (2023). Can AI language models replace human participants? Trends Cogn Sci, 27(7), 597-600. https://doi.org/10.1016/j.tics.2023.04.008
Guha, N. et al. (2023). LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models. ArXiV.
Grieve, J., Bartl, S., Fuoli, M., Grafmiller, J., Huang, W., Jawerbaum, A., Murakami, A., Perlman, M., Roemling, D., & Winter, B. (2024). The sociolinguistic foundations of language modeling. ArXiv preprint.
Gurnee, W. & Tegmark, M. (2023, 3 oct.). Language Models Represent Space and Time. ArXiV
Ho, N. et al. (2023, 13 juin). Large Language Models Are Reasoning Teachers. ArXiV.
Jones, C., & Bergen, B. (2023, 31 oct.). Does GPT-4 Pass the Turing Test?. ArXiV.
Lucchi, N. (2023). ChatGPT: A Case Study on Copyright Challenges for Generative Artificial Intelligence Systems. European Journal of Risk Regulation, 1-23. doi:10.1017/err.2023.59
Park, P.S. et al. (2023, 28 août). AI Deception: A Survey of Examples, Risks, and Potential Solutions. arXiV.
Rathje, S., Mirea, D.-M., Sucholutsky, I., Marjieh, R., Robertson, C. E., & Bavel, J. J. V. (2024). GPT is an effective tool for multilingual psychological text analysis. PsyArXiv Preprint. https://osf.io/preprints/psyarxiv/sekf5
Saha, D., Brooker, P., Mair, M. and Reeves, S. (2023). Thinking Like a Machine: Alan Turing, Computation and the Praxeological Foundations of AI. Science & Technology Studies. https://doi.org/10.23987/sts.122892
Shi et al. (2023). KokoMind: Can LLMs Understand Social Interactions?
Yax, N. et al. (2023). Studying and improving reasoning in humans and machines. ArXiV.
Zador, A. et al. (2023, 22 mars). Catalysing next-generation Artificial intelligence through NeuroAI. Nature Communications, 14:1597.
SGAT et biais culturels#
Tao, Y., Viberg, O., Baker, R. S., & Kizilcec, R. F. (2024). Cultural bias and cultural alignment of large language models. PNAS Nexus, 3(9), pgae346. https://doi.org/10.1093/pnasnexus/pgae346
Ecrire des prompts#
Akin, F. K. (s.d.). The art of ChatGPT prompting
Eager, B., & Brunton, R. (2023). Prompting Higher Education Towards AI-Augmented Teaching and Learning Practice
Kadavath, S. et al. (2022, nov.)Language Models (Mostly) Know What They Know. ArXiV.
Mollick, E. (2023, 26 avril) A guide to prompting AI
Mollick, E. R., & Mollick, L. (2023, 12 juin). Assigning AI: Seven Approaches for Students, with Prompts. SSRN Archive.
Mollick, E. R., & Mollick, L. (2023, 24 mars). Using AI to Implement Effective Teaching Strategies in Classrooms: Five Strategies, Including Prompts. SSRN.
Schulhoff, S. et al. (2024, 15 Juill.). The Prompt Report: A Systematic Survey of Prompting Techniques. ArXiV.
Le réglage (fine tuning)#
Parthasarathy, V. B., Zafar, A., Khan, A., & Shahid, A. (2024). The Ultimate Guide to Fine-Tuning LLMs from Basics to Breakthroughs: An Exhaustive Review of Technologies, Research, Best Practices, Applied Research Challenges and Opportunities. ArXiv preprint. https://arxiv.org/abs/2408.13296
La crise du copyright (model collapse)#
Pasquale, F., & Sun, H. (2024). Consent and Compensation: Resolving Generative AI’s Copyright Crisis. SSRN Electronic Journal. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4826695