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30/2 Undone Computer Science

Special issue of Philosophia Scientiæ 30/2 (June 2026)

Guest editors: Chantal Enguehard (Univ. Nantes), Guillaume Munch-Maccagnoni (INRIA), Alberto Naibo (Univ. Paris 1)

Submission deadline: April 4th April 30 2025

Acceptance notification: September 1st 2025

Revision deadline: October 31st 2025

Final version due: December 31st 2025

Submission addresses: Chantal.Enguehard@univ-nantes.fr, Guillaume.Munch-Maccagnoni@inria.fr, Alberto.Naibo@univ-paris1.fr

Description

As researchers, we are committed to advancing computer science in a way that is both epistemologically and ethically sound. With this special issue, we aim to provide a place to pause and reflect on these aspects of our scientific practices. We call for contributions from computer scientists from across the field, as well as philosophers and historians of science, social scientists, and other scholars interested in discussing ethical and epistemological dimensions of computer science.

As a structuring question, we propose to apply the concept of undone science [1] to computer science. Undone science refers to questions that are left unaddressed, ignored, or unfunded for various reasons, yet demonstrably worthy of exploration. It highlights the idea that the production and dissemination of knowledge are variously influenced, leading to biases in the choice of research that is done, and eventually in a “systematic non-production of knowledge” [2].

We might want to understand, for instance, whether the way in which computer science is established—including the various sociological and economic aspects of its development—eventually leaves out some potentially crucial questions and areas of investigation, and what makes that some questions or methods might be ignored whilst others might be favoured. The striking example of AI ethics indeed reminds us of some of the society-impacting case studies which originally motivated the analytical concept of undone science—including corporate influence denounced by critical voices [3], and the debate on requirements and evaluation criteria to improve research by acting on what is funded and published [4].

But undone science could also refer to the consequences of “theoretical commitments” [2], i.e., dominant paradigms, when they blind us collectively about what is worthy or not of exploration—all the while accounts of paradigm shifts in our young domain remain rare. It could refer as well to technical or methodological biases, such as when the availability of certain software or hardware at the right time determines which research idea “wins” [5], or when the haste towards automation in algorithm design loses valuable insights compared to alternative paths where people are involved in data exploration [6].

Undone science also refers originally to questions first recognised by actors from civil society—for computer scientists, the free software movement and civil liberties organisations come to mind.

We believe that the concept of undone science, in a broad sense, can further help bring out the epistemological and ethical aspects of research in computer science. We call for full papers exploring this theme of undone science in computer science, and encourage submissions from a wide range of perspectives.

This call for papers is related to the eponymous conference on undone science in computer science, held in Nantes, France in February 2024, organised by Guillaume Munch-Maccagnoni, Chantal Enguehard, Maël Pégny and Marc Anderson, with the support of INRIA and the university of Nantes. It is not necessary to have presented a talk at the conference to submit a full paper. In addition, authors of accepted papers can be invited to present their work at an ulterior edition of the conference.

Potential topics

It is unnecessary to be familiar with the concept of undone science in order to contribute. Potential topics include, but are not limited to:

  • Areas of research in computer science meeting challenges that will require or have required shifts in viewpoint; conditions responsible for certain kinds of research being over- or under-represented; reasons for a set of questions being neglected in an area.

  • Epistemological questions and challenges, for instance arising from the interdisciplinary nature of computer science, or dealing with the articulations between theory and practice; investigations on the values of computer science.

  • How social movements or civil society organisations (e.g. free software movement and probably others) play a role in identifying areas of research being left aside, in providing new research questions, or on the contrary in demanding that some kind of research remains undone.

  • Challenges of integrating ethical questioning regarding social, economic, and environmental consequences of our work into the process of making “good science”. Concrete examples of questions stemming from ethical consideration being introduced to a domain (why/how), are welcome.

  • How ethics codes (including for instance the ACM Code of Ethics) can be leveraged (or fail) to present some questions as being worthy of exploration; more broadly how guiding principles can be put in place to enrich the research practices in an area.

  • Explorations of the influence of publishing practices within our community, and of popular research methodology and scientific writing guides provided within our fields, on the selection, execution, and dissemination of research.

  • Examinations of biases and limitations present in commonly-used educational curricula (for instance leading to or stemming from a lack of diversity, be it social or methodological).

  • More generally, any discussion of systematic non-production and non-dissemination of knowledge, whether in a specific area or in computer science in general, whether past or present; whether due to limitations of available methodologies, blind spots of dominant paradigms, institutional and industrial biases, lack of social representation, or other factors.

Acceptance criteria

Submissions will be evaluated according to standard reviewing criteria, including correctness, significance and originality. They will be evaluated for scope according to two criteria:

  • Computer science—we seek contributions pertaining to computer science in a broad sense. For instance, a reflexion on computer science by a computer scientist can be rooted in their research practice; a contribution by a social scientist can be rooted in the study of an example or through field work; a contribution by a philosopher or historian of science can be rooted in the study of computer science as a specific domain of production of knowledge and scientific practice.

  • Undone science—we seek contributions within the theme of undone science in a broad sense (see above); the link with undone science can be explored in the manuscript or left implicit. We expect that the question of undone science will serve as an inspiration for contributions leading to meaningful reflections on computer science (for instance ethical or epistemological aspects thereof), without necessarily requiring expertise in epistemology and ethics. For instance, a submission from a computer scientist could outline a potential ethical question derived from a detailed examination of the practices in their area without delving into the ethical aspects in detail.

Interested authors should feel free to inquire in advance with the guest editors for scope.

Instructions

Manuscripts must:

  • be original, and may not be in the process of being submitted for another publication;

  • be written in English or French;

  • be prepared for anonymous double-blind evaluation;

  • contain an abstract in English (200-300 words), and space must be reserved for an additional abstract in French (or conversely);

  • be prepared in LaTeX in the standard article class with A4 paper size and Latin Modern 12 pt font (i.e., using \documentclass[a4paper,12pt]{article}), with the bibliography style of the journal (see below);

  • not exceed 13 11-15 pages including the bibliography with this page formatting (corresponding to roughly to 34 000 characters including spaces);

  • be sent by April 4th 30 2025 in PDF to the following addresses: Chantal.Enguehard@univ-nantes.fr, Guillaume.Munch-Maccagnoni@inria.fr, Alberto.Naibo@univ-paris1.fr.

For more details on the article format, notably the citation and bibliography style, please consult the instructions for authors: https://journals.openedition.org/philosophiascientiae/633

Bibliographie

[1] D. J. Hess (2016). Undone Science: Social Movements, Mobilized Publics, and Industrial Transitions. MIT Press. ISBN 9780262529495.

[2] Frickel, S., Gibbon, S., Howard, J., Kempner, J., Ottinger, G., & Hess, D. J. (2010). Undone Science: Charting Social Movement and Civil Society Challenges to Research Agenda Setting. Science, Technology, & Human Values, 35(4), 444–473. doi :10.1177/0162243909345836. https://pubmed.ncbi.nlm.nih.gov/32099268/

[3] According to Green, tech ethics increasingly tends to be “subsumed into corporate logics and incentives”; according to Abdalla and Abdalla, actions of “Big Tech” to influence academic and public discourse are reminiscent of the tactics of Big Tobacco:

B. Green (2021). The Contestation of Tech Ethics: A Sociotechnical Approach to Technology Ethics in Practice, Journal of Social Computing, 2 (3), pp. 209-225, September 2021. https://doi.org/10.23919/JSC.2021.0018

M. Abdalla & M. Abdalla (2021). The Grey Hoodie Project: Big Tobacco, Big Tech, and the Threat on Academic Integrity. In Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society (AIES ’21). Association for Computing Machinery, New York, NY, USA, 287–297. https://doi.org/10.1145/3461702.3462563

[4] C.E.A. Prunkl, C. Ashurst, M. Anderljung et al. Institutionalizing ethics in AI through broader impact requirements. Nature Machine Intelligence, 3, 104–110 (2021). https ://doi.org/10.1038/s42256-021-00298-y

[5] Sara Hooker. 2021. The hardware lottery. Communications of the ACM, 64, 12 (December 2021), 58–65. https://dl.acm.org/doi/10.1145/3467017

[6] Dawn Nafus. 2018. “Exploration or Algorithm? The Undone Science Before the Algorithms.” Cultural Anthropology, 33 (3) : 368–374. https://journal.culanth.org/index.php/ca/article/view/ca33.3.03

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