TIM-7074 v1

Obrenovic, B., Gu, X., Wang, G., Godinic, D., & Jakhongirov, I. (2025). Generative AI and human–robot interaction: implications and future agenda for business, society and ethics. AI & SOCIETY: Journal of Knowledge, Culture and Communication, 40 (2), 677–690. https://doi.org/10.1007/s00146-024-01889-0

• This paper explores the implications of generative AI on human–robot interactions, discussing the ethical, societal, and business considerations.

Zimmerman, A., Janhonen, J., & Beer, E. (2024). Human/AI relationships: challenges, downsides, and impacts on human/human relationships. AI and Ethics, 4 (4), 1555–1567. https://doi.org/10.1007/s43681-023-00348-8

• This paper discusses the evolving nature of human-AI relationships and highlights the psychological and societal challenges that can result from close human interaction with AI systems.

Giest, S. N., & Klievink, B. (2024). More than a digital system: how AI is changing the role of bureaucrats in different organizational contexts. Public Management Review, 26 (2), 379–398. https://doi.org/10.1080/14719037.2022.2095001

• This study examines how AI technologies are changing the roles and responsibilities of bureaucrats in public service, raising questions about transparency and decision-making.

Russo, F., Schliesser, E., & Wagemans, J. (2024). Connecting ethics and epistemology of AI. AI & SOCIETY: Journal of Knowledge, Culture and Communication, 39 (4), 1585–1603. https://doi.org/10.1007/s00146-022-01617-6

• This article connects ethics with how AI systems produce knowledge, arguing that trust and transparency are key to responsible AI use.

Zhou, J., & Chen, F. (2023). AI ethics: from principles to practice. AI & Society, 38 (6), 2693–2703. https://doi.org/10.1007/s00146-022-01602-z

• This paper discusses the difficulties in turning ethical AI principles into real-world tools and systems, and offers practical ways to close the gap.