Trustworthy Autonomous Systems (TAS): Engaging TAS experts in curriculum design
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Abstract (arXiv)
Recent advances in artificial intelligence, specifically machine learning, contributed positively to enhancing the autonomous systems industry, along with introducing social, technical, legal and ethical challenges to make them trustworthy. Although Trustworthy Autonomous Systems (TAS) is an established and growing research direction that has been discussed in multiple disciplines, e.g., Artificial Intelligence, Human-Computer Interaction, Law, and Psychology. The impact of TAS on education curricula and required skills for future TAS engineers has rarely been discussed in the literature. This study brings together the collective insights from a number of TAS leading experts to highlight significant challenges for curriculum design and potential TAS required skills posed by the rapid emergence of TAS. Our analysis is of interest not only to the TAS education community but also to other researchers, as it offers ways to guide future research toward operationalising TAS education.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 1 of its 24 references that are in the map. First posted on arXiv 4 Feb 2022.
Builds on
1 of 24 references.
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Citing papers per year: 2022: 1; 2023: 1.
2 papers.
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- 2023Soft Gripping: Specifying for Trustworthinesscited by 0
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- 2022On Specifying for Trustworthiness22 Jun 2022