Ethics-Based Auditing of Generative AI

The research examines how AI ethics principles can be translated into organizational audit practice, with particular attention to generative AI. Ethics-based AI auditing aims to assess whether AI systems and their surrounding organizational arrangements are consistent with relevant ethical principles or norms, making responsible AI claims assessable and reviewable. Key questions concern audit scope, criteria, evidence, organizational responsibilities, and reassessment as systems and use contexts evolve.

Research methods include: systematic and scoping literature reviews, conceptual analysis, and design science research, drawing on foundation-model documentation, an expert questionnaire, and contributions from expert informants via interviews and written responses.

  • The work has clarified the foundations of ethics-based AI auditing, examined continuous auditing and ethical concerns particularly salient in GenAI, and developed eight meta-requirements for future ethics-based GenAI audit frameworks:
  • Context and use-case specificity
  • Lifecycle integration
  • Measurability and technical verifiability
  • Risk-based ethical prioritization
  • Scalability across organizational capacity and portfolio size
  • Internal governance integration
  • Support through tooling and guidance
  • Standards alignment and external assurance
  • Together, these provide a requirements-level foundation for developing credible and repeatable ethics-based GenAI auditing practices.

Publications:

Laine, J., Minkkinen, M., Mäntymäki, M. (2024). Ethics-based AI Auditing: A Systematic Literature Review on Conceptualizations of Ethical Principles and Knowledge Contributions to Stakeholders. Information & Management, 61(5), 103969. https://doi.org/10.1016/j.im.2024.103969

Minkkinen, M., Laine, J., Mäntymäki, M. (2022). Continuous Auditing of Artificial Intelligence: a Conceptualization and Assessment of Tools and Frameworks. Digital Society, 1, Article 21. https://doi.org/10.1007/s44206-022-00022-2

Laine, J., Zimmer, M. P., Minkkinen, M., Salmela, H., Mäntymäki, M. (2022). Clustering Design Science Research Based on the Nature of the Designed Artifact. In The Role of Digital Technologies in Shaping the Post-Pandemic World (pp. 254 266). Springer. https://doi.org/10.1007/978-3-031-15342-6_20

Laine, J., Minkkinen, M., Mäntymäki, M. (2025). Understanding the Ethics of Generative AI: Established and New Ethical Principles. Communications of the Association for Information Systems, 56, 1 25. https://doi.org/10.17705/1CAIS.05601

Laine, J., Minkkinen, M., Mäntymäki, M. (Forthcoming). Meta-requirements for ethics-based auditing of generative AI: An echeloned design science research study.

The research approaches include:

  • Experimental research
  • Expert interviews
  • Expert questionnaire