Abstract
In this paper, we present the methodology we used in the European Horizon 2020 AI-PROFICIENT project, to evaluate the implementation of the ethical component of the project. The project is a 3-year collaboration between a university partner and industrial and tech partners, which aims to research the integration of AI services in heavy industry work settings. An AI ethics approach developed for the project has involved embedded ethical analysis of work contexts and design solutions and the generation of specific and evolving ethical recommendations for partners. We have performed an ongoing evaluation and monitoring of the implementation of recommendations. We describe the quantitative results of these implementations: overall, broken down by category, and broken down by category and responsible project partner (anonymized). In parallel, we discuss the results in light of our approach and offer insights for future research into the ground-level application of ethical recommendations for AI in heavy industry.
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Notes
Hereafter tech companies, or tech company partners in case we refer specifically to the technology company partners collaborating within our project. Software engineers, in contrast, refer to the individuals working within these tech companies.
N/A recommendations have not been included in the calculation of percentages for implementation.
The categories that were merged are not presented in the table above.
For those interested, more detailed information and more expansive discussion, including our orientation with regard to the HLEG, can be found in the AI-PROFICIENT Public Deliverable 6.4: AI-PROFICIENT Ethical Recommendations at https://ai-proficient.eu/public-deliverables/
Note that the overall results as assessed by the Project Partners are based on 108 recommendations kept and 22 rendered N/A (as opposed to 121 kept and 9 N/A for the ethics team). This difference is due to project partners deciding to formally abandon one UC fairly late in the project, thus rendering all of its recommendations N/A for the project partner assessment. The ethics team, however, decided to retain their assessment of the 13 recommendations of the UC, since that assessment had been completed before the formal abandonment occurred.
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Acknowledgements
This research was funded by AI-PROFICIENT which has received funding from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No. 957391. The authors would like to thank the anonymous reviewer for their suggestions on improving the paper. The authors would also like to thank Bertrand Remy at LORIA for generating the heat maps of Figs. 7 and 8.
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Anderson, M.M., Fort, K. Evaluating the acceptability of ethical recommendations in industry 4.0: an ethics by design approach. AI & Soc 39, 2989–3003 (2024). https://doi.org/10.1007/s00146-023-01834-7
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DOI: https://doi.org/10.1007/s00146-023-01834-7