The University of Southampton
University of Southampton Institutional Repository

The potential and limitations of artificial colleagues

The potential and limitations of artificial colleagues
The potential and limitations of artificial colleagues

This article assesses the potential of artificial colleagues to help us realise the goods of collegial relationships and discusses its practical implications. In speaking of artificial colleagues, it refers to AI-based agential systems in the workplace. The article proceeds in three steps. First, it develops a comprehensive account of the goods of collegial relationships. It argues that, in addition to goods at the individual level, collegial relationships can provide valuable goods at the social level. Second, it argues that artificial colleagues are limited in their capacity to realise the goods of collegial relationships: at the individual level, they can at best realise some such goods, and at the social level, they can at best support their realisation. This contradicts Nyholm and Smids’ (2020) claim that robots can be good colleagues. The article traces these limitations to particular features of artificial colleagues and discusses to what extent they would hold for radically advanced systems. Third, the article examines the policy implications of these findings. It highlights how the introduction of artificial colleagues, in addition to potentially crowding out human colleagues, will likely impact relations among human colleagues. And it proposes a governance principle that gives strict priority to human collegial relationships.

Artificial Colleagues, Collegiality, Human-robot-interaction, Relationships, Robot Ethics, Work
2210-5433
Bieber, Friedemann
245a43f9-b627-41f2-9696-37283f81cc18
Unruh, Charlotte
a13ae482-e199-48eb-afd3-27fb09d2fb9e
Bieber, Friedemann
245a43f9-b627-41f2-9696-37283f81cc18
Unruh, Charlotte
a13ae482-e199-48eb-afd3-27fb09d2fb9e

Bieber, Friedemann and Unruh, Charlotte (2025) The potential and limitations of artificial colleagues. Philosophy & Technology, 38 (2), [60]. (doi:10.1007/s13347-025-00890-9).

Record type: Article

Abstract

This article assesses the potential of artificial colleagues to help us realise the goods of collegial relationships and discusses its practical implications. In speaking of artificial colleagues, it refers to AI-based agential systems in the workplace. The article proceeds in three steps. First, it develops a comprehensive account of the goods of collegial relationships. It argues that, in addition to goods at the individual level, collegial relationships can provide valuable goods at the social level. Second, it argues that artificial colleagues are limited in their capacity to realise the goods of collegial relationships: at the individual level, they can at best realise some such goods, and at the social level, they can at best support their realisation. This contradicts Nyholm and Smids’ (2020) claim that robots can be good colleagues. The article traces these limitations to particular features of artificial colleagues and discusses to what extent they would hold for radically advanced systems. Third, the article examines the policy implications of these findings. It highlights how the introduction of artificial colleagues, in addition to potentially crowding out human colleagues, will likely impact relations among human colleagues. And it proposes a governance principle that gives strict priority to human collegial relationships.

Text
s13347-025-00890-9 - Version of Record
Available under License Creative Commons Attribution.
Download (962kB)

More information

Accepted/In Press date: 12 April 2025
Published date: 2 May 2025
Keywords: Artificial Colleagues, Collegiality, Human-robot-interaction, Relationships, Robot Ethics, Work

Identifiers

Local EPrints ID: 501509
URI: http://eprints.soton.ac.uk/id/eprint/501509
ISSN: 2210-5433
PURE UUID: bfdb4696-db7c-4352-aff7-fe6201940fc3
ORCID for Charlotte Unruh: ORCID iD orcid.org/0000-0003-3953-7617

Catalogue record

Date deposited: 03 Jun 2025 16:34
Last modified: 22 Aug 2025 02:42

Export record

Altmetrics

Contributors

Author: Friedemann Bieber
Author: Charlotte Unruh ORCID iD

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×