Table 15a The Robots for Social Justice (Zhu et al., 2024)
| The Robots for Social Justice | ||||
|---|---|---|---|---|
| Item | Factor 1 | Factor 2 | ||
| 1. | Recommendation 1: HRI Researchers should clearly specify the communities their research is intended to benefit. Even for highly theoretical research, we argue that researchers should be able to identify some community that would ultimately benefit. | |||
| 2. | Recommendation 2: HRI Researchers should clearly specify the human capabilities their research is intended to en- hance for those communities. Even for highly theoretical research, we argue that researchers should be able to identify some human capabilities their research would enhance. | |||
| 3. | Recommendation 3: HRI Researchers should provide clear justification, grounded in close, contextual listening (by them- selves or others), for claims regarding the value and prioritization placed on those capabilities by those communities. | |||
| 4. | Recommendation 4: HRI Researchers should clearly specify the relevant structural conditions that motivate, constrain, and shape those values and priorities. | |||
| 5 | Recommendation 5: HRI Researchers should map out the power structures within the communities they wish to serve; between the community and the other stakeholders with which they interact; and between the engineers themselves and these communities and other stakeholders. | |||
Zhu, Y., Wen, R., & Williams, T. (2024). Robots for Social Justice (R4SJ): Toward a More Equitable Practice of Human-Robot Interaction. 2024 19th ACM/IEEE International Conference on Human-Robot Interaction (HRI), 850–859. https://doi.org/10.1145/3610977.3634944
Grounded in the Engineering for Social Justice (E4SJ) framework for Engineering Education
“A community-engaging approach has been shown to be effective in helping engineering students shift their mindset from charity to thinking for the community, to advocate for social justice, and to develop meaningful empathy for specific communities
We have discussed the ways in which the axiology of HRI research papers have aligned with Nussbaum’s capabilities, let’s consider the axiology of the remaining papers. Virtually all of the remaining 417 papers had concrete motivations not captured by the E4SJ framework. These motivations include: (1) an abstract desire for explainability and understanding of a robotic system (i.e., Leutert et al. [31]) (2) better understanding of trustworthiness (i.e., Sebo et al. [54]) (3) improving the efficiency of an existing system (i.e., Milliez et al. [38]) (4) improving robot perception, cognition, and behavior model- ing (i.e., Murakami et al. [41] (5) development of novel algorithmic capabilities (i.e., Mohseni- Kabir et al. [40]) (6) better understanding of robots’ role in our society and how we perceive robots in social contexts(i.e., Paepcke and Takayama[44])”