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Embedding ethics up front in AI and robotics: evidence from future engineers

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2026-03-13

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2730-5953

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Oostveen A-M, Eimontaite I. (2026) Embedding ethics up front in AI and robotics: evidence from future engineers. AI and Ethics, Volume 6, Issue 1, February 2026, Article number 128

Abstract

As artificial intelligence and robotics increasingly shape societies, ensuring that these technologies align with ethical and societal values is a pressing challenge. This paper presents survey findings from 98 MSc Robotics and Applied AI students at Cranfield University, offering rare empirical evidence of how future AI and robotics professionals perceive their ethical responsibilities. While students demonstrate strong awareness of key risks such as autonomous decision-making in warfare, surveillance, labour displacement, and emotional manipulation, they show limited engagement with professional codes of ethics or structured training. Instead, ethical reflection often occurs informally, through peer discussions or media exposure. These findings highlight a consistent gap between ethical awareness and institutionalised engagement, raising questions about how future engineers will navigate the ethical challenges of AI. To address this, the paper proposes an “ethics up front” model for ethics integration that embeds reflection early in the development lifecycle, supported by participatory design, professional education, and regulatory alignment. This paper provides empirical evidence on future AI engineers’ ethical orientations and proposes a practical model for early-stage ethics integration into the practice of AI and robotics engineering.

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35 Commerce, Management, Tourism and Services, 50 Philosophy and Religious Studies, 5001 Applied Ethics, 3507 Strategy, Management and Organisational Behaviour, Bioengineering, Machine Learning and Artificial Intelligence

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Attribution 4.0 International

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This research was funded by EPSRC (Engineering and Physical Sciences Research Council) and ISCF (Industry Strategy Challenge Fund) under the Made Smarter scheme No EP/V062158/1 and by the Horizon Europe project AI-PRISM, grant number 101058589.

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