CHS: Small: Collaborative Research: Role-Based Norm Violation Response in Human-Robot Teams

机器人可能需要仔细决定何时以及如何拒绝给他们的命令，如果执行这些命令所需的行动在道德上是不允许的。 以前关于这个主题的大多数工作都采用了基于规范的伦理方法，机器人将在一组描述哪些状态或行为在道德上是错误的规则下运行，并使用这些规则来解释其行为。相比之下，这个项目探索了一个基于角色的视角，在这个视角中，机器人会推理它与他人的关系，它在这些关系中扮演的角色，以及要求它采取的行动是否对这些角色和关系有利。具体来说，研究人员将开发一个框架，允许机器人以这种方式进行推理，并根据这种推理对其行为进行解释。 然后，研究人员将探索基于角色和基于规范的命令拒绝在如何影响人类-机器人团队合作方面的比较，并设计算法，使机器人能够根据其上下文自动决定生成什么类型的拒绝。这些算法和解释将在两个具有不同类型关系、角色和规则的非常不同的背景下进行评估：科罗拉多矿业学院的平民本科生和美国空军学院的空军学员。这项工作不仅将提高机器人的道德行为和作为良好的队友的能力，而且还将通过提供实验证据来证明基于角色的道德哲学的不同原则的相对重要性和有效性来推进道德哲学。更正式地说，这项研究的目标是调查基于规则和基于角色的反应之间的上下文敏感的权衡，以及促进基于角色的响应所需的代表和机制。 研究小组将通过确定指标来评估响应的可接受性，质量和有效性;建模基于角色的响应的生成以及基于角色和基于规则的响应之间的选择;进行实验来验证这些模型和响应;并使用结果来阐明新的道德和哲学论点。 该团队将在每个实验地点进行探索性研究，对比不同的命令拒绝措辞的有效性，这些命令拒绝措辞是通过将不同的言语行为理论沟通策略与不同的道德哲学背景配对而形成的，涉及（a）信任，可爱性，正念，工作量和规范强度的现场标准调查措施;（B）视频数据的定性分析;以及（c）来自多模态交互社区的统计语言分析。然后，研究人员将为机器人开发一个框架，以生成这些响应，这将涉及团队间关系，角色和行动的正式计算模型开发;基于机器学习的规范违反响应策略选择建模，使用任务上下文表征，角色理论提出的行动仁慈和对响应的预期响应等功能;并集成到DIARC机器人认知架构中。 在这项工作的基础上，该团队将推进传统的道德哲学论点，并开发一个新的框架，在这个框架中，道德哲学论点是基于计算模型对道德心理学的影响而合理的。 总的来说，该项目将导致基础，跨学科的知识到规范违反反应，包括算法之间的选择规范违反反应扎根于不同的伦理理论，指导方针和见解的设计道德能力的语言能力的机器人，新的计算帐户的角色为基础的机器人伦理，该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查进行评估，被认为值得支持的搜索.

Robots may need to carefully decide when and how to reject commands given to them, if the actions required to carry out those commands are not morally permissible. Most previous work on this topic takes a norm-based ethical approach, where a robot would operate under a set of rules describing what states or actions are morally wrong, and use those rules to explain its actions. In contrast, this project explores a role-based perspective, in which the robot reasons about the relationships it holds with others, the roles it plays in those relationships, and whether the actions requested of it are benevolent with respect to those roles and relationships. Specifically, the researchers will develop a framework to allow robots to reason in this way and generate explanations of its actions based on this reasoning. The researchers will then explore how role-based and norm-based command rejections compare in terms of how they affect human-robot teamwork, and design algorithms to allow robots to automatically decide what type of rejection to generate based on their context. These algorithms and explanations will be evaluated in two very different contexts with different types of relationships, roles, and rules: with civilian undergraduates at the Colorado School of Mines, and with Air Force cadets at the US Air Force Academy. This work will not only increase robots' ability to behave ethically and act as good teammates, but will also advance moral philosophy by providing experimental evidence for the relative importance and effectiveness of different tenets of role-based moral philosophy.More formally, the goals of this research are to investigate context-sensitive tradeoffs between rule-based and role-based responses, and the representations and mechanisms needed to facilitate role-based responses. The research team will do this by identifying metrics to assess response acceptability, quality, and effectiveness; modeling the generation of role-based responses and selection between role-based and rule-based responses; conducting experiments to validate those models and responses; and using the results to articulate novel moral and philosophical arguments. The team will start with exploratory studies at each experimental site contrasting the effectiveness of different command rejection phrasings formed by crossing different Speech-Act Theoretic communication strategies paired with different moral philosophical backgrounds, with respect to (a) field-standard survey measures of trust, likability, mindfulness, workload, and norm strength; (b) qualitative analysis of video data; and (c) statistical linguistic analyses from the multimodal interaction community. The researchers will then develop a framework for robots to generate these responses that will involve formal computational model development of inter-team relations, roles, and actions; machine learning-based modeling of norm violation response strategy selection using features such as task context characterization, role-theoretic proposed action benevolence, and expected responses to the responses; and integration into the DIARC robot cognitive architecture. Based on this work, the team will both advance traditional moral philosophical arguments and develop a novel framework in which moral philosophical arguments are justified based on the effects of computational models on moral psychology. Overall, the project will lead to foundational, interdisciplinary knowledge into norm violation response, consisting of algorithms for selecting between norm violation responses grounded in different ethical theories, guidelines for and insights into the design of morally competent language capable robots, novel computational accounts of role-based robot ethics, and novel empirically informed moral philosophical arguments.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.