Responsible Robotics: A Socio-Ethical Addition to Robotics Courses

Authors

  • Joshua Vekhter The University of Texas at Austin
  • Joydeep Biswas The University of Texas at Austin

DOI:

https://doi.org/10.1609/aaai.v37i13.26885

Keywords:

Ethics, Robotics Education, Responsible Robotics, Fairness

Abstract

We are witnessing a rapid increase in real-world autonomous robotic deployments in environments ranging from indoor homes and commercial establishments to large-scale urban areas, with applications ranging from domestic assistance to urban last-mile delivery. The developers of these robots inevitably have to make impactful design decisions to ensure commercially viability, but such decisions have serious real-world consequences. Unfortunately it is not uncommon for such projects to face intense bouts of social backlash, which can be attributed to a wide variety of causes, ranging from inappropriate technical design choices to transgressions of social norms and lack of community engagement. To better prepare students for the rigors of developing and deploying real-world robotics systems, we developed a Responsible Robotics teaching module, intended to be included in upper-division and graduate level robotics courses. Our module is structured as a role playing exercise which aims to equip students with a framework for navigating the conflicting goals of human actors which govern robots in the field. We report on instructor reflections and anonymous survey responses from offering our responsible robotics module in both a graduate-level, and an upper-division undergraduate robotics course at UT Austin. The responses indicate that students gained a deeper understanding of the socio-technical factors of real-world robotics deployments than they might have using self-study methods, and the students proactively suggested that such modules should be more broadly included in CS courses.

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Published

2023-09-06

How to Cite

Vekhter, J., & Biswas, J. (2023). Responsible Robotics: A Socio-Ethical Addition to Robotics Courses. Proceedings of the AAAI Conference on Artificial Intelligence, 37(13), 15877-15885. https://doi.org/10.1609/aaai.v37i13.26885