Enabling Morally Sensitive Robotic Clarification Requests
This addresses a problem for robotics and human-robot interaction by preventing moral miscommunication, though it is incremental as it builds on existing moral reasoning capabilities.
The paper tackles the problem of robots generating clarification requests without moral reasoning, which can miscommunicate moral dispositions and weaken human moral norms. The result shows that their method, implemented in the DIARC architecture, successfully ameliorates these concerns in a human subjects experiment.
The design of current natural language oriented robot architectures enables certain architectural components to circumvent moral reasoning capabilities. One example of this is reflexive generation of clarification requests as soon as referential ambiguity is detected in a human utterance. As shown in previous research, this can lead robots to (1) miscommunicate their moral dispositions and (2) weaken human perception or application of moral norms within their current context. We present a solution to these problems by performing moral reasoning on each potential disambiguation of an ambiguous human utterance and responding accordingly, rather than immediately and naively requesting clarification. We implement our solution in the DIARC robot architecture, which, to our knowledge, is the only current robot architecture with both moral reasoning and clarification request generation capabilities. We then evaluate our method with a human subjects experiment, the results of which indicate that our approach successfully ameliorates the two identified concerns.