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Responsible AI and action learning

Craig Johnson & Emad Mohamed

Action Learning Research and Practice2025https://doi.org/10.1080/14767333.2025.2458900article
AJG 1ABDC C
Weight
0.37

What the paper says

This paper proposes action learning has a role to play in advancing responsible AI. Despite the recent surge in attention towards artificial intelligence, predominantly focusing on its technological and commercial aspects, the social dimensions have often been overlooked. Action learning, known for fostering interdisciplinary discourse, is proposed as a collaborative learning approach to foster responsible AI. The paper explores three potential avenues: facilitating multidisciplinary dialogue, reshaping the workforce, and promoting ethical AI practices. Emphasising the importance of cultivating critical questioning skills, we suggest an action learning approach can cultivate the innovative potential of AI, whilst mitigating its potential risks.

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https://doi.org/https://doi.org/10.1080/14767333.2025.2458900

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@article{craig2025,
  title        = {{Responsible AI and action learning}},
  author       = {Craig Johnson & Emad Mohamed},
  journal      = {Action Learning Research and Practice},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1080/14767333.2025.2458900},
}

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Responsible AI and action learning

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.