Towards an experiential ethics of AI and robots: A review of empirical research on human encounters

Björn Fischer and Susanne Frennert

Technological Forecasting and Social Change, 2025, vol. 219, issue C

Abstract: The past few years have seen a profound re-acceleration of interest in artificial intelligence (AI) and robotics, accompanied by intensifying debates about ethical regulation. Yet, less attention has been paid to how people experience AI and robots in practice. This paper explores the potential of an experiential approach to AI and robot ethics. Specifically, we review empirical studies on human experiences with AI and robots and argue for the value of assembling and analysing findings from studies that inquire into the everyday encounters with AI and robots. Following a hybrid approach that combines systematic review with narrative social inquiry, we identify six key dimensions of human experiences with AI and robots: appreciation of imperfection, formation of affective relationships, discomfort with lack of transparency, addition of invisible work, shifting responsibilities, and readiness to trade off privacy for other benefits. By placing these dimensions into dialogue with ethical AI governance, pragmatist philosophy and Science and Technology Studies, we argue for an experiential approach to ethics, i.e. an approach that grounds ethical reflection in lived encounters, where abstract principles often take new, context-specific meanings. Thereby, we invite attentiveness to ethical concerns that might otherwise become sidelined in extant AI and robotics policy frameworks.

Keywords: Artificial intelligence; Robots; Machine learning algorithms; Science and Technology Studies (STS); Experiential philosophy; Ethical principles (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0040162525002951
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:219:y:2025:i:c:s0040162525002951

DOI: 10.1016/j.techfore.2025.124264

Access Statistics for this article

Technological Forecasting and Social Change is currently edited by Fred Phillips

More articles in Technological Forecasting and Social Change from Elsevier
Bibliographic data for series maintained by Catherine Liu ().