TIM-7070 v1

Mišić, J., van Est, R. & Kool, L. Good governance of public sector AI: a combined value framework for good order and a good society. AI Ethics (2025). https://doi.org/10.1007/s43681-025-00751-3.
This study proposes a value framework for governing public sector AI, balancing democratic order and societal well-being through seven core values and supporting operational interpretations.

Bikkasani, D.C. Navigating artificial general intelligence (AGI): societal implications, ethical considerations, and governance strategies. AI Ethics (2024). https://doi.org/10.1007/s43681-024-00642-z
This paper explores AGI's transformative, ethical, legal, economic, and political implications, proposing a multidisciplinary governance framework to ensure alignment with human values and societal interests.

Maiti, M., Kayal, P. & Vujko, A. A study on ethical implications of artificial intelligence adoption in business: challenges and best practices. Future Business Journal 11, 34 (2025). https://doi.org/10.1186/s43093-025-00462-5
This study examines ethical challenges in business AI adoption—such as privacy, bias, and accountability—and offers best practices for responsible implementation across diverse organizational contexts.

Josifović, S. Legal and administrative frameworks as foundations for AI alignment with human volition. AI Ethics (2024). https://doi.org/10.1007/s43681-024-00640-1
This paper advocates a legal-centric framework for AGI regulation, emphasizing law-informed self-governance over moral alignment, using legal history to embed coherent human values.

Esmaili, A., Rahmani, A., Alijanpour, A. et al. Challenges for Ethics Review Committees in Regulating Medical Artificial Intelligence Research. Indian J Surg Oncol (2025). https://doi.org/10.1007/s13193-025-02229-4
This review highlights 23 challenges Ethics Review Committees face in regulating medical AI, urging interdisciplinary collaboration and updated ethical frameworks to address consent, bias, and innovation risks.

Lund, B., Orhan, Z., Mannuru, N.R. et al. Standards, frameworks, and legislation for artificial intelligence (AI) transparency. AI Ethics (2025). https://doi.org/10.1007/s43681-025-00661-4
This paper compares global AI transparency frameworks, highlighting shared principles, challenges, and the need for adaptable, sector-specific regulations to build trust while supporting innovation and accountability.

Ajmal, C.S., Yerram, S., Abishek, V. et al. Innovative Approaches in Regulatory Affairs: Leveraging Artificial Intelligence and Machine Learning for Efficient Compliance and Decision-Making. AAPS J 27, 22 (2025). https://doi.org/10.1208/s12248-024-01006-5
AI and ML are revolutionizing pharmaceutical regulatory affairs by streamlining compliance processes, though challenges in validation, ethics, and evolving regulatory standards still require active management.

Nwebonyi, N., McKay, F. Exploring bias risks in artificial intelligence and targeted medicines manufacturing. BMC Med Ethics 25, 113 (2024). https://doi.org/10.1186/s12910-024-01112-1
This paper explores how AI-driven targeted medicine manufacturing may introduce bias, potentially worsening health inequalities, especially given the novelty and complexity of emerging digital systems.