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There is a lack of access to critical knowledge on machine ethics and the impacts of technology on individuals and communities in everyday life. This project pioneers an inclusive curriculum design process to broaden accessibility to machine ethics education. Our approach uses a ''source'' course to develop materials for seven "target" courses. The source course is a machine ethics curriculum development course in which students and faculty collaboratively build curricular materials for integration into non-computer science courses. Here we describe the development of the ''source'' course using a curriculum co-creation process that leverages student and faculty expertise. The process emphasizes an inclusive design approach, rooted in continuous stakeholder feedback and consistent, transparent communication. The products of this process include course materials that incorporate underrepresented ethical frameworks. Additionally, it features peer-reviewed journal assignments that promote reflective learning and sharing of diverse perspectives, as well as a final module project in which students collaborate with faculty to co-create curricular materials. Our approach aims to broaden a culturally relevant understanding of ethical challenges in technology while ensuring that the curriculum resonates with diverse student backgrounds. Our presentation will describe key insights about the process and products of our curriculum design.
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An Experimental Ethics Approach to Robot Ethics Education
We propose an experimental ethics-based curricular module for an undergraduate course on Robot Ethics. The proposed module aims to teach students how human subjects research methods can be used to investigate potential ethical concerns arising in human-robot interaction, by engaging those students in real experimental ethics research. In this paper we describe the proposed curricular module, describe our implementation of that module within a Robot Ethics course offered at a medium-sized engineering university, and statistically evaluate the effectiveness of the proposed curricular module in achieving desired learning objectives. While our results do not provide clear evidence of a quantifiable benefit to undergraduate achievement of the described learning objectives, we note that the module did provide additional learning opportunities for graduate students in the course, as they helped to supervise, analyze, and write up the results of this undergraduate-performed research experiment.
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- Award ID(s):
- 1849348
- PAR ID:
- 10125972
- Date Published:
- Journal Name:
- Proceedings of the AAAI Conference on Artificial Intelligence
- ISSN:
- 2159-5399
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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