Call for Papers – Special Issue of AI-Linguistica: "The notion of authenticity in hybrid human/AI productions", ed. by Sophia Burnett (Université de Lorraine) & Sílvia Lima Gonçalves Araújo (Universidade do Minho)

2025-04-24

The notion of authenticity is linked to those of identity and truth. Today, it is being reconfigured in the context of hybrid productions between humans and artificial intelligence. While the general public tends to perceive artificial intelligence as a whole greater than the sum of its parts, it is important to recall that this gestalt—referring merely to the generative capacity of computational models (LLMs)—does not produce language grounded in embodied experience (Burnett, 2024), but rather draws on billions of tokens from disparate sources (Zhao et al., 2023), often collected without authorization (Baack et al., 2025). In other words, these productions are amalgams of signs, symbols, or images, resulting from statistical calculations and not from lived experiences or embodied reflections. The authenticity of hybrid productions is an issue that brings together cognitivists and generativists. Lakoff (1986) contrasted computational production and human production, rejecting the computer-brain model, and according to Chomsky et al., (2023), “we know from the science of linguistics and the philosophy of knowledge that they differ profoundly from how humans reason and use language”.

In order to apply any analysis of authenticity to the examination of hybrid productions, we must first critically interrogate the very meaning of authenticity. To do so, we draw on an epistemic framework that predates the emergence of LLMs. For a more comprehensive introduction to the notion of authenticity, we suggest Lindholm (2013). Trilling (1974) frames the evolution of authenticity as a derivation from sincerity. Handler (1986) argues that authenticity is not an innate property, but a discursive construction mobilized, for example, by nationalists to assuage anxieties around continuity and legitimation. Linnekin (1991), drawing on a Maori case-study, shows that so-called “authentic” traditions are in fact dynamic, interpreted, and politically invested: authenticity becomes a narrative rather than a reproduction of empirical reality. Lindholm (2013), addressing authenticity in the digital era—prior to the emergence of LLMs—in the context of early online banking and other official forms of digital authentication, writes: “Anxiety about the validity of experience and about the maintenance of personal identity is at the core of this computerized definition.” Drawing on linguistic and semiotic frameworks, van Leeuwen (2001) offers several responses to the question, “What is authenticity?” He observes that media tend to reproduce and reinforce the idea that authenticity is concealed behind masks, only to be revealed in order to produce an effect of realism within a saturated media landscape. This highlights the paradox of authenticity in late modernity: it must appear spontaneous, even though it is often carefully assembled.

This special issue of AI Linguistica examines how the notion of authenticity is maintained, transformed or redefined in the practice of human/AI hybrid productions. The term “hybrid” here refers to the dynamic interaction between human agents and artificial intelligence systems, in which the production, interpretation, or mediation of language results from distributed co-agency between human cognition and algorithmic computation. We invite contributions that question and analyze the notion through approaches that mobilize: language sciences (Beguš et al., 2023, De Cesare, 2023; Dynel, 2023; Meier, 2024; Weissweiler, 2024), translation studies (Li et al., 2025; Xu et al., 2025), literary/narratology studies (Beguš, 2024; Chakrabarty et al., 2024; Koivisto & Grassini, 2023), discursivity/discourse analysis (Merton, 1968; Liu et al., 2025; Lehner, 2025; Yoo et al., 2024), NLP/computational linguistics (Liu et al., 2024), didactics (Alrahabi et al., 2022; Ifelebuegu, 2023; Werdiningsih et al., 2024) and cognition (Carrasco-Farre, 2024; Grindrod, 2024; Wang et al., 2025).

This publication will address questions such as (but not limited to, as there are evidently myriad unexplored questions): How does authenticity manifest itself in the linguistic objects produced within hybrid productions? How do students negotiate the reappropriation of authorial borrowing in their academic writing? Does a fiction conceived by a human being—creative unreality—differ in value from that of a proposition generated by a computational model, and can we qualify this difference? Where does the notion of authenticity fit into a hybrid translation process, understood as transfer but also as re-enunciation? What form(s) does authenticity take in public, political or institutional discourse when it incorporates hybrid productions? (How) can hybrid corpus annotation be a site of epistemological scrutiny? We invite you to submit your reflections in one of the following axes:

I. Ideologies, intentionality, reproductions and circulations
The examination of the ideological, political, social and cultural dimensions of the notion of authenticity in hybrid productions and discourses, taking into account power dynamics as well as societal expectations or effects related to these productions. It also invites critical perspectives on linguistic diversity, performativity, and speaker positionality.

II. Cognition, Social Interaction, and the Co-construction of Meaning 

How authenticity can be approached from a human cognitive perspective within hybrid and pragmatic collaboration, through events such as social interaction, intentionality, and the co-construction of meaning, in both private and public settings.

III. Natural Language Processing and algorithms
How processes of qualification, identification, and simulation of authenticity are operationalized within algorithmically generated texts. Areas of interest include annotation practices for authenticity-related labels, treatment of non-standard linguistic features, contrastive studies of artefact retention across training paradigms, and challenges in maintaining version authenticity in multilingual alignments. Stylometric and forensic approaches to AI discourse, as well as corpus analyses of the perceptions of authenticity across model iterations, are also relevant.

Submission

Please send your proposals for articles in English or French. Maximum 500 words, and up to 5 keywords, including your name, email address, and affiliation. Send in PDF format to both sophia.burnett@univ-lorraine.fr and saraujo@elach.uminho.pt by May 31st 11h59 CET. If pertinent to your approach, please do include data source, tools, and any expected (provisional) results. Your proposition can be for two types of articles: short-length articles (between 3,000 and 6,000 words) and full-length articles (between 8,000 and 15,000 words).

Please state in your initial proposal if you intend to submit a short or a full-length article. Languages of study may include any, with a particular focus on Romance and Germanic languages. Contributions may be empirical or theoretical, provided they engage substantively with authenticity in language and discourse in the context of AI mediation.

Each proposal submitted will be peer-reviewed by two external reviewers. The reviewing process of the ensuing papers takes place in the form of a double-anonymized peer review. Based on the reviewers' reports, the editors of this special issue decide whether to accept (with minor or major revisions), to ask for revisions and resubmit for review, or reject the publication proposal submitted. Full information on the journal website: https://ai-ling.publia.org/ai_ling/about

Timeline

  • Call for Papers launched: April 24, 2025
  • Article propositions due (500 words): May 31, 2025
  • Notification of acceptance of propositions: June 10, 2025 (Does not mean acceptance of full papers).
  • Full articles due: August 30, 2025
  • Peer review period: September 1 – October 20, 2025
  • Reviewer reports returned to authors (Accepted/Rejected): October 25, 2025
  • Final revised versions due: November 20, 2025
  • Publication: Mid-December 2025

AI-Linguistica. Linguistic Studies on AI-Generated Texts and Discourses is a Diamond Open Access journal. All content is published under a Creative Commons License (CC-BY-NC-SA 4.0), at no costs for the authors.

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