Enabling Morally Sensitive Robotic Clarification Requests

Abstract

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 Distributed Integrated Cognition Affect and Reflection 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.

Document Details

Document Type
Pub Defense Publication
Publication Date
Mar 04, 2022
Source ID
10.1145/3503795

Entities

People

  • Ryan Blake Jackson
  • Tom Williams

Organizations

  • Air Force Office of Scientific Research
  • Colorado School of Mines

Tags

Fields of Study

  • Computer science

Readers

  • Computational Linguistics
  • Strategic Security Studies
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • Autonomy
  • Autonomy - Human-Robot Interaction