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The researcher, the machine and the world. Artificial Intelligence(es): interdisciplinary approaches in human and social sciences.

AI/HUMANITIES CLERMONT-FERRAND

URL: https://www.uca.fr
Event Date: 2026-03-31 ~ 2026-04-03
Submission Date: 2025-09-10
Location: Clermont-Ferrand, France

Artificial Intelligence Humanities, Literature & Arts (General) Social Sciences (General)

CALL FOR PAPER

International conference

The researcher, the machine and the world.

Artificial Intelligence(es): interdisciplinary approaches in human and social sciences.

Clermont-Ferrand

From March 31st to April 3rd 2026

Supported by the Institut Lettres, Langues, Sciences Humaines et Sociales, as part of the Graduate Track for Humanities and Social Sciences programme.

Conference languages: French and English.

Key dates:

Deadline for submissions: September 10, 2025

Notification of acceptance: October 31, 2025

Organizing Committee:

Michaël Grégoire (Université Clermont Auvergne / LRL), Paolo Dias Fernandes (UCA / CELIS), Khaled Zouari (UCA / Communication et Sociétés), Marcos Ramos Pinto (UCA / LRL), Naïs Sabatier (UCA / PHIER).

More than a technical reality, AI today designates a naturalized device as well as a cultural Being from the point of view of its reception.1

The upheavals brought about by the increasingly widespread use of artificial intelligence tools are more than ever at the heart of discussions in the humanities and social sciences. Since the appearance, or should we say the media coverage, of LLMs2 at the end of 2021, researchers and artists have put forward a variety of ideas about their uses and forms, and the host of sociological, philosophical and aesthetic questions that these tools raise3 . If the role of the humanities and social sciences in the design and reflection on Artificial Intelligences has yet to be demonstrated, let's take a look at the purpose of the "AI Act" proposed by the European Union, which came into effect at the beginning of 2025:

The purpose of this Regulation is to improve the functioning of the internal market and promote the uptake of human-centric and trustworthy artificial intelligence (AI).4

ChatGPT, Dall-E, Sora and the other established avatars of deeplearning5 have made their way into everyday research, be it as vainly waved scarecrows or as the basis of a new academic utopia.

The strange sense of novelty of the subject is currently crystallising the enthusiasm around the concepts of artificial intelligence and language models. Yet the foundations of this thinking did not wait for the technical revolutions of OpenAI, Microsoft and other tech powers. In 1981, in the journal Computers and the Humanities, then in its nineteenth volume, researcher Elaine Rich published an article entitled "Artificial Intelligence and Humanities"6 . She established the link between Artificial Intelligence, which was only referred to in the singular at the time, and the Humanities by putting forward the following argument:

Artificial intelligence tries to solve problems that occur in the world as it exists. Many of these center on people and the cultures they have created. Perhaps the most important class of such problems involves language, but other problems require an understanding of how people think about the problems that they solve; this understanding can then be used to tell us what knowledge would enable a machine to solve those same problems.7

In recent years, and particularly in recent months, there has been a considerable increase in the number of articles, books and other scientific events. So, while scientific events on the subject are multiplying, our proposal calls for an initial assessment involving interdisciplinary and even transdisciplinary approaches. With this in mind, proposals for national and international contributions may be made in the following non-exhaustive sub-themes:

1. Towards an epistemology of AIs: research methods and methodologies, construction of theoretical agreements and disagreements, practices and globalization

Seth Stephens-Davidowitz (2017) argues that the social sciences will never be the same because of Big Data, which allows researchers to no longer rely on small samples to generalize conclusions, but rather to work with huge corpora to draw their conclusions. This ability to aggregate and analyze data previously reserved for technical specialists is now spreading to other scientific fields thanks to AI, which simplifies this process. Big Data and AI have a mutually reinforcing relationship: one has enabled the development of the other, which in turn creates new possibilities for exploiting massive data. This synergy means that huge bodies of data can now be analyzed without the need for any technical prerequisites, leaving researchers to concentrate on their research questions and theorizing.

So how and under what conditions can artificial intelligence tools help with traditionally time-consuming tasks such as analyzing textual data, transcribing interviews or data mining? What protocols should be put in place, what initial biases should be identified, what credit should be given and what precautions should be taken with regard to the results produced? This sub-theme will of course include Large Language Models (LLM) (such as Chat GPT, LLaMa, Mistral etc.) and their various applications in the human and social sciences. However, these tools are not limited to language models. Generally speaking, artificial intelligences for analyzing data (images, statistics, texts, sounds, etc.) will be at the heart of our epistemological questions

Faced with immense and ever-growing data sets, it seems indeed obvious to question the nature of knowledge with global claims. In his inaugural lecture at the conference of the Société Française de Littérature Générale et Comparée in 2024, William Marx spoke of the nature of a global library and asked the question: how do we find our way around it?

Contributions may address the conditions under which these generative AIs are produced and the biases they may introduce into data processing. Others may question the scientific validity of the results produced using these AIs. Theoretical and practical exploration of existing or to-be-developed means of measuring bias, error and interpretative margins would be greatly appreciated. In short, the aim of this theme is to question the epistemic value of the results obtained using AI.

2. Cultural and creative industries, communication, the artist and the machine: thinking about the links between creation and artificial intelligence.

This sub-theme of research focuses on the nature of the reflections and debates around the usage and the users of AI in the media, communicational and creative cultural industries. In line with the critical work already initiated by the Frankfurt school (Adorno, Horkeimer)8, discussed and enriched by researchers9 from French (Miège, Bouquillion) and Canadian (Tremblay, Lacroix, Georges) universities and the various proposals put forward in recent months, we wish to place the question of creation at the heart of this conference. The aim will be to present the corpora and objects of study resulting from creative processes involving AI(s) and affecting the various sectors of culture, communication and the media (arts, cinema, music, press, TV,design, publishing, etc.). It should be noted that an experimental typology could be developed to distinguish purely 'artificial' creations from hybrid objects and to identify those that are more representative of the phenomenon.

From a historical and synthetic perspective, it will also be essential to discuss the forms of cultural creation and production associated with digital technology and their future in the age of artificial intelligence. Questions relating to digital rewritings and translation, and all the nuances that this implies, could be at the heart of the discussions in this sub-theme. The issues linked to the changes in the cultural and creative industries10 (production, distribution, consumption, commodification), which are hotly debated by researchers in the social sciences and humanities (information and communication sciences, sociology of culture, etc.) wishing to address these research questions and theoretical and empirical analyses, could also be the subject of proposals.

Contributions related to this sub-theme and falling within the field of research and creation are strongly encouraged.

3. AIs as levers for educational transformation: resilience and adaptation

The conference also offers a scientific exploration of the transformations brought about by AI in education, through theorized and contextualized contributions. Artificial intelligence is strongly disrupting teaching practices, changing teaching methods and the role of teachers. They also imply the need to rethink students' skills in critical analysis, evaluation and creativity.

Based on research focusing in particular on the impact of generative AI on the development of metacognition and self-regulation, contributions in this sub-theme may draw on theoretical and empirical analyses that provide a better understanding of the dynamics at work in the use of AI in education. It is possible, for example, to explore how AIs can foster the resilience of players (learners, teachers) by moving beyond the debates on plagiarism and cheating, while encouraging self-regulation and critical use.

The contributions proposed in this sub-theme will seek to answer the following questions: How can AIs be used to enhance learners' ability and agentivity? Is it then possible to perceive the conversational robot as a kind of collaborator enabling the co-elaboration of knowledge? Can this collaboration be envisaged in any teaching discipline in the form of epistemic agentivity? And, if so, under what conditions? What are the impacts on learning and literacy: acquisition of disciplinary writing codes, conceptualization of the target audience, comparison between peer tutoring and tutoring by AIs? How can we ensure that inequalities in the use of new technologies do not increase with the use of AIs?

4. IAs seen from elsewhere: interculturality and otherness.

Artificial intelligences open up many new avenues in terms of data storage, and even more in terms of data access. We therefore need to take a decentered look at artificial intelligences, which seem to operate only in major languages, in the sense that Deleuze and Gattari (1975) gave to the term. AIs for the general public bring into play a very exclusive and uniform relationship to knowledge, discourse and creation. Artificial intelligence from an intercultural perspective is therefore of particular interest to the human and social sciences. For example, we are proposing a decentering of the AI phenomenon, which until now has been described essentially from a Western point of view. What relationships to machines and technology can comparative studies

bring to light? What are the political, economic and aesthetic issues for non-Western areas? What representations and uses are there for regions of the world isolated from technological abundance? This session will therefore be an opportunity to look at the vision of these countries, which are represented very little if at all by AIs, in their algorithms or in their parameters.

The question also arises as to how AIs are understood and perceived in different cultures: how do people see AIs and how are public authorities dealing with this issue? Do they promote them, encourage their use, raise awareness or regulate them? Between the development of AI in the United States and China, can research in the social sciences and humanities in Europe find a middle way, culturally anchored in its own model and prioritizing specific aspects of AI, particularly (but not exclusively) generative AIs?

An eminent symbol of otherness, the machine and especially the learned machine, the one that at least seems to know, is a paradoxical object of concern and fascination that should be studied through the prism of interculturality. We might consider discussing these relationships with the machine, which raise questions from a wide range of disciplines in the social and human sciences.

Anonymous proposals of a maximum of 500 (five hundred) words accompanied by a brief bibliography should be sent to the following address: iashs.clermontferrand2026@proton.me

Scientific Committee :

Damien Chabanal (UCA / LRL, France), Dacia Dressen-Hammouda (UCA / ACTé, France), Anne Sardier (UCA / ACTé, France), Henri Galinon (UCA / PHIER), Béatrice Drot-Delange (UCA / ACTé, France), Christine Blanchard-Rodrigues (UCA / LRL, France), Irene Cacopardi (UCA / CELIS, France), Chloé Chaudet (UCA / CELIS / IUF, France), Yvan Daniel (UCA / CELIS, France), Karine Rance (UCA / CHEC, France), Romy Sauvayre (UCA / Clermont Auvergne INP / LAPSCO, France), Dimitrios Fiotadis (Univ. Ioannina / Flagship Project FAITH, Greece), Vasilis Pezoulas (Univ. Ioannina /MEDLAB, Greece), Thomas Lebarbé (Université Grenoble Alpes, France), Jackson Sousa (Univ. Federal da Bahia, Brazil), João Neto (Univ. Federal da Bahia, Brazil), Olivier Baude (CNRS Paris, Director of IR* Huma-Num), Pierre Mounier-Kuhn (CNRS / Paris-Sorbonne), Yves Laberge (Univ. Ottawa, Canada).

Notes

1 Eugène Favier-Baron, "Que fait l'Intelligence Artificielle à l'intelligence?", Appareil [En ligne], 26 | 2023, online 23 November 2023, accessed 10 October 2024. URL: http://journals.openedition.org/appareil/6943; DOI: https://doi.org/10.4000/appareil.6943. (Emphasis added)

2 LLMs (Large Language Models) are at the heart of generative artificial intelligence. These models are trained to predict the next most likely word in a text, thereby generating coherent textual content.

3 Nicolas Sauret, "Intelligence artificielle & Sciences humaines et sociales (SHS)". I2D - Information, données & documents, 2022, no. 1, pp. 97-103.

4 "AI ACT", available online, consulted on 11 February 2025, URL: https://artificialintelligenceact.eu/article/1/.

5 According to the CNIL: "Machine learning is a field of study in artificial intelligence that aims to give machines the ability to "learn" from data, using mathematical models. More precisely, it is the process by which relevant information is extracted from a set of training data". On-line, consulted on 10 October 2024. URL: https://www.cnil.fr/fr/definition/apprentissage-automatique.

6 Elaine Rich, "Artificial Intelligence and the Humanities", Computers and the Humanities, vol. 19, no. 2, 1985, p.117-122. JSTOR, http://www.jstor.org/stable/30204398. Accessed 11 Oct. 2024.

7 Ibid.

8 Max Horkeimer, Theodor Adorno, The Dialectic of Reason, Paris, Gallimard, 1974 (French version).

9 Bernard Miège, "La théorie des industries culturelles (et informationnelles), composante des SIC", Revue française des sciences de l'information et de la communication [Online], 1 | 2012, online since 01 September 2012, accessed 16 March 2025. URL : http://journals.openedition.org/rfsic/80 ; DOI : https://doi.org/10.4000/rfsic.80

10 Bernard Miège, Les industries culturelles et créatives, Grenoble, PUG, 2017.

Indicative bibliography

Aifang Ma, « L'IA en Chine : état des lieux », Constructif , 2019/3 N° 54, p.33-37, 2019. DOI: 10.3917/const.054.0033. URL : https://shs.cairn.info/revue-constructif-2019-3-page-33?lang=fr.

Beligné Max, Lefort Isabelle et Loudcher Sabine, « Une épistémologie numérique des disciplines est-elle possible ? Étude d’un corpus de revues francophones en sciences humaines et sociales », Humanités numériques [En ligne], 2020, N°1, mis en ligne le 01 janvier 2020.

Bonnet Gilles, Pour une poétique numérique. Littérature et Internet, Hermann, 2017.

Cardon Dominique, Culture numérique, Paris, Presses de Sciences Po, « Les petites humanités », 2019.

Cetinic Eva & She James, « Understanding and Creating Art with AI: Review and Outlook », ACM Trans. Multimedia Comput. Commun. Appl. 18, 2, Article 66, 2022. DOI : https://doi.org/10.1145/3475799

Deleuze Gilles & Guattari Félix, Kafka. Pour une littérature mineure, Paris, Minuit, 1975.

Dwi Mariyono & Alif Hidayatullah Akmal Nur, « Exploring AI’s Role in Supporting Diversity and Inclusion Initiatives in Multicultural Marketplaces », International Journal of Religion, 2024.

Favier-Baron Eugène, « Que fait l’Intelligence Artificielle à l’intelligence ? », Appareil[ En ligne], 2023, N°26, mis en ligne le 23 novembre 2023, consulté le 10 octobre 2024. URL : http://journals.openedition.org/appareil/6943 ; DOI : https://doi.org/10.4000/appareil.6943.

Gefen Alexandre, « IA : pour une histoire culturelle», Revue d'histoire culturelle. XVIIIe-XXIe siècles, 2022.

Hannaford Ewan (dir.), « Our heritage, our stories: developing AI tools to link and support community-generated digital cultural heritage », Journal of Documentation, 80(5), p. 1133-1147, 2024.

Horkeimer Max & Adorno Theodor, La dialectique de la raison, Paris, Gallimard, 1974 (version française).

Jannidis Fotis (dir.), Digitale Literaturwissenschaft, J.B Metzler, Stuttgart, 2022.

Lebrun Tom & Audet René, « Une poésie machinique ? Génération automatisée, intelligence artificielle et création littéraire. », Communication & langages, 2020/1 N° 203, p.151-173. DOI : 10.3917/comla1.203.0151. URL : https://shs.cairn.info/revue-communication-et-langages-2020-1-page-151?lang=fr.

Miège Bernard, « La théorie des industries culturelles (et informationnelles), composante des SIC », Revue française des sciences de l’information et de la communication [En ligne], 2012, N°3, mis en ligne le 01 septembre 2012, consulté le 16 mars 2025. URL : http://journals.openedition.org/rfsic/80 ; DOI : https://doi.org/10.4000/rfsic.80

Miège Bernard, Les industries culturelles et créatives, Grenoble, PUG, 2017.

Porter Brian, « AI-generated poetry is indistinguishable from human-written poetry and is rated more favorably », Sci Rep 14, 26133, 2024.

Rich Elaine, « Artificial Intelligence and the Humanities », Computers and the Humanities, vol. 19, n° 2, 1985, p.117–122. JSTOR. URL : http://www.jstor.org/stable/30204398.

Seth Stephens-Davidowitz, Everybody lies: Big data, new data, and what the internet can tell us about who we really are, HarperCollins, New York, 2019.

Toews Rob, “12 Thought-Provoking Quotes About Artificial Intelligence”. Forbes, 2020. URL : https://www.forbes.com/sites/robtoews/2020/03/28/12-thought-provoking-quotes-about-artificial-intelligence/

Tsai C-W, Ma Y-W, Chang Y-C and Lai Y-H, « Integrating Multiculturalism Into Artificial Intelligence-Assisted Programming Lessons: Examining Inter-Ethnicity Differences in Learning Expectancy, Motivation, and Effectiveness », Front. Psychol. 2022. DOI: 10.3389/fpsyg.2022.868698.

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