Can HR adapt to the paradoxes of artificial intelligence?

Charlwood, Andy; and Guenole, Nigel. 2022. Can HR adapt to the paradoxes of artificial intelligence? Human Resource Management Journal, 32(4), pp. 729-742. ISSN 0954-5395 [Article]
Copy

Artificial Intelligence (AI) is widely heralded as a new and revolutionary technology that will transform the world of work. While the impact of AI on HR and people management is difficult to predict, the article considers potential scenarios for how AI will affect our field. We argue that although popular accounts of AI stress the risks of bias and unfairness, these problems are eminently solvable. However, the way that the AI industry is currently constituted and wider trends in the use of technology for organising work mean that there is a significant risk that AI use will degrade the quality of work. Viewing different scenarios through a paradox lens, we argue that both positive and negative visions of the future are likely to coexist. The HR profession has a degree of agency to shape the future if it chooses to use it; HR professionals need to develop the skills to ensure that ethics and fairness are at the centre of AI development for HR and people management.

Practitioner Notes
• The use of AI for HR and people management is currently in its infancy.
• It is possible to conceive of optimistic and pessimistic accounts of how AI might affect HR and people management. A paradox lens suggests both will likely coexist in our immediate future.
• Without regulation, existing approaches to people management could lead to AI that dramatically reduces worker autonomy and ramps up effort and stress.
• The ethical values and practical insights of the HR profession are important if this ‘bad AI’ is to be contained.
• An ethical approach to AI for HR involves the full involvement of workers and stakeholders in the design and deployment of AI systems.


picture_as_pdf
Human Res Mgmt Journal - 2022 - Charlwood - Can HR adapt to the paradoxes of artificial intelligence.pdf
subject
Published Version
Available under Creative Commons: Attribution 4.0

View Download
visibility_off picture_as_pdf

Accepted Version
lock

Atom BibTeX OpenURL ContextObject in Span OpenURL ContextObject Dublin Core Dublin Core MPEG-21 DIDL Data Cite XML EndNote HTML Citation METS MODS RIOXX2 XML Reference Manager Refer ASCII Citation
Export

Downloads