Course directory

KDDC 2EN02 - Ethics and responsibility of new digital services

KDDC 2EN02 · Fall semester 2026-2027

Language of tuition
English
Course type
Cours séminaire
Number of hours
12
Credits
2

Information

Description

This course aims to develop students' reflexive abilities on the issues raised by the integration of new digital technologies (including Artificial Intelligence and Generative AI) into products and services developed by organizations. The aim of the course is for students to master the concepts and methods to conduct ethical reflection in the management of new digital products and services. The course will address several questions: What is ethics? How to conduct ethical reflection on new technologies (tensions, dilemmas, deliberation)? How to identify controversies? What are the different ethics (normative, applied, meta-ethical)? What are the major ethical questions that managers developing new digital and AI services must ask themselves? What are the tensions and best practices of responsible management of digital technologies?

Prerequisites

No requirement.

Teaching format

Interactive courses & presentations of students’ work in group

Assessment

  • Individual essay 50%
  • Work in group 50%

Readings

Main readings 5

  1. BALAGUE Christine (2021): The challenge of responsible Artificial Intelligence, in Artificial intelligence for sustainable value creation, Edward Elgar Publishing Inc, Massachusetts, USA. https://www.e-elgar.com/shop/gbp/artificial-intelligence-for-sustainable-value-creation-9781839104381.html

  2. BALAGUE Christine (2025). Comment limiter les risques de l’intelligence artificielle en finances ? Revue d’économie Financière , n°159, 3ème trimestre 2025

  3. HAIDAR Ahmad, BALAGUE Christine (2024). A Framework to Implement Responsible Digital Innovation: Dimensions, Best Practices and Challenges, Journal of Innovation Economics & Management, p. I182 à XXXI https://shs.cairn.info/revue-journal-of-innovation-economics-2024-0-page-I182?lang=fr

  4. HAIDAR Ahmad, BALAGUE Christine (2026). Managing the Risks of Generative AI: A Framework for Enterprise Risk Management, Journal of the Operational Risk, to be published

  5. MATTHEWS Jean-Marie, CARDON Dominique, BALAGUE Christine (2022). From Reality to World. A Critical Perspective on AI Fairness. Journal of Business Ethics, DOI : 10.1007/s10551-022-05055-8

    Read online

Further readings 20

  1. BALAGUE Christine (2021). Les enjeux éthiques des objets communicants personnels, Annales des Mines, série « Enjeux Numériques »

    Read online

  2. Benamar Lamya, Balagué Christine, Zhong Zeling (2020), Internet of Things devices appropriation process: The Dynamic Interactions Value Appropriation (DIVA) framework, Technovation, Volume 89, 102082, https://doi.org/10.1016/j.technovation.2019.06.001

  3. Bertail P., Bournie D., Clemencon S., Waelbroerck P.(2019) Algorithmes : biais, discrimination et équité, Fondation Abeona

  4. Buhmann, A., & Fieseler, C. (2021). Towards a deliberative framework for responsible innovation in artificial intelligence. Technology in Society, 64, 101475. https://doi.org/10.1016/j.techsoc.2020.101475

    Read online

  5. Casilli Antonio (2019) En attendant les robots, enquête sur le travail du clic, Editions du Seuil, Paris.

    Borrow

  6. Coad, A., Nightingale, P., Stilgoe, J., & Vezzani, A. (2021). Editorial: The dark side of innovation. Industry and Innovation, 28(1), 102–112. https://doi.org/10.1080/13662716.2020.1818555

    Read online

  7. Déclaration de Montréal sur l’IA responsable (2018) :https://www.declarationmontreal-iaresponsable.com/la-declaration

  8. Eubanks Virginia (2018). Automating inequality, how high tech tools profiles, polish and punish the poor, St. Martin's Press (January 23, 2018)

  9. High-Level Expert Group on Artificial Intelligence (set up by the European Commission) (2019), Ethics guidelines for Trustworthy Artificial Intelligence

  10. Hoffmann, A. L. (2019), Where fairness fails: data, algorithms and the limits of antidiscrimination discourse, Information, Communication & Society, 22:7, pp. 900-915.

    Read online

  11. Lambrecht, A., & Tucker, C. (2019). Algorithmic bias? an empirical study of apparent gender-based discrimination in the display of stem career ads. Management Science, 65(7), 2966-2981.

  12. LOBSCHAT L., MUELLER B., EGGERS F., BRANDIMARTE L., DIEFENBACH S., KROSCHKE M., & WIRTZ J. (2021). Corporate digital responsibility. Journal of Business Research, 122, 875–888. https://doi.org/10.1016/j.jbusres.2019.10.006

    Read online

  13. Obermeyer, Z., Powers, B., Vogeli, C., & Mullainathan, S. (2019). Dissecting racial bias in an algorithm used to manage the health of populations. Science, 366(6464), 447-453.

  14. Paris B., Donovan J. (2019) Deepfakes and cheap fakes, The manipulation of audio and visual evidence, Data & Society, september.

  15. Raji, I. D., Gebru, T., Mitchell, M., Buolamwini, J., Lee, J., & Denton, E. (2020). Saving Face: Investigating the Ethical Concerns of Facial Recognition Auditing. arXiv preprint arXiv:2001.00964.

  16. Seigneurin Marion, Balagué Christine (2021). Publicité Numérique Responsable, rapport de la Chaire Good in Tech. https://www.goodintech.org/Rapports.html

  17. Seigneurin, M., Balagué, C., & Lyubareva, I. (2025). Navigating misinformation and disinformation: How definition ambiguity limits the DSA’s implementation. European Journal of Communication, 0 (0). https://doi.org/10.1177/02673231251391980

  18. Selbst, A. D., Boyd, D., Friedler, S. A., Venkatasubramanian, S., & Vertesi, J. (2019). Fairness and abstraction in sociotechnical systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency FAT2019, pp. 59-68.

  19. Strubell E., Ganesh A., McCallum A. (2019). Energy and Policy Considerations for Deep Learning in NLP, arXiv preprint arXiv:1906.02243, 2019 - arxiv.org

  20. Zhong Zeling, Balagué Christine (2023). Understanding the Role of Consumer Psychological Motives in Smart Connected Objects Appropriation: A Higher Order PLS-SEM Approach. State of the Art in Partial Least Square Structural Equation Modeling,Springer Proceeding in Business and Economics, Springer Nature Switzerland https://doi.org/10.1007/978-3-031-34589-0

Teaching units

Unit no.Unit type Teaching unitsTeachers Number of hoursCredits
17398Cours séminaire Ethics and responsibility of new digital services Christine BALAGUÉ122

Teachers

  • Christine BALAGUÉ

In the curricula

Contacts and resources

Contact
JEROME Amélie