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1. Role-based Morality, Ethical Pluralism, and Morally Capable Robots1

   Zhu, Qin; Williams, Tom; Wen, Ruchen (January 2021, Journal of contemporary Eastern Asia)

   Ess, Charles (Ed.)

   Dominant approaches to designing morally capable robots have been mainly based on rule-based ethical frameworks such as deontology and consequentialism. These approaches have encountered both philosophical and computational limitations. They often struggle to accommodate remarkably diverse, unstable, and complex contexts of human-robot interaction. Roboticists and philosophers have recently been exploring underrepresented ethical traditions such as virtuous, role-based, and relational ethical frameworks for designing morally capable robots. This paper employs the lens of ethical pluralism to examine the notion of role-based morality in the global context and discuss how such cross-cultural analysis of role ethics can inform the design of morally competent robots. In doing so, it first provides a concise introduction to ethical pluralism and how it has been employed as a method to interpret issues in computer and information ethics. Second, it reviews specific schools of thought in Western ethics that derive morality from role-based obligations. Third, it presents a more recent effort in Confucianism to reconceptualize Confucian ethics as a role-based ethic. This paper then compares the shared norms and irreducible differences between Western and Eastern approaches to role ethics. Finally, it discusses how such examination of pluralist views of role ethics across cultures can be conducive to the design of morally capable robots sensitive to diverse value systems in the global context. 

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2. Robo-Identity: Exploring Artificial Identity and Multi-Embodiment

   https://doi.org/10.1145/3434074.3444878  

   Lee, Minha; Kontogiorgos, Dimosthenis; Torre, Ilaria; Luria, Michal; Tejwani, Ravi; Dennis, Matthew J.; Pereira, Andre (March 2021, HRI '21 Companion: Companion of the 2021 ACM/IEEE International Conference on Human-Robot Interaction)

   null (Ed.)

   Interactive robots are becoming more commonplace and complex, but their identity has not yet been a key point of investigation. Identity is an overarching concept that combines traits like personality or a backstory (among other aspects) that people readily attribute to a robot to individuate it as a unique entity. Given people's tendency to anthropomorphize social robots, "who is a robot?" should be a guiding question above and beyond "what is a robot?" Hence, we open up a discussion on artificial identity through this workshop in a multi-disciplinary manner; we welcome perspectives on challenges and opportunities from fields of ethics, design, and engineering. For instance, dynamic embodiment, e.g., an agent that dynamically moves across one's smartwatch, smart speaker, and laptop, is a technical and theoretical problem, with ethical ramifications. Another consideration is whether multiple bodies may warrant multiple identities instead of an "all-in-one" identity. Who "lives" in which devices or bodies? Should their identity travel across different forms, and how can that be achieved in an ethically mindful manner? We bring together philosophical, ethical, technical, and designerly perspectives on exploring artificial identity. 

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3. Investigating Robot Moral Advice to Deter Cheating Behavior

   Kim, Boyoung; Wen, Ruchen; de Visser, Ewart J.; Zhu, Qin; Williams, Tom; Phillips, Elizabeth (January 2021, TSAR Workshop at ROMAN 2021)

   null (Ed.)

   We examined whether a robot that proactively offers moral advice promoting the norm of honesty can discourage people from cheating. Participants were presented with an opportunity to cheat in a die-rolling game. Prior to playing the game, participants received from either a NAO robot or a human, a piece of moral advice grounded in either deontological, virtue, or Confucian role ethics, or did not receive any advice. We found that moral advice grounded in Confucian role ethics could reduce cheating when the advice was delivered by a human. No advice was effective when a robot delivered moral advice. These findings highlight challenges in building robots that can possibly guide people to follow moral norms. 

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4. A survey of communicating robot learning during human-robot interaction

   https://doi.org/10.1177/02783649241281369  

   Habibian, Soheil; Alvarez_Valdivia, Antonio; Blumenschein, Laura_H; Losey, Dylan_P (October 2024, The International Journal of Robotics Research)

   For robots to seamlessly interact with humans, we first need to make sure that humans and robots understand one another. Diverse algorithms have been developed to enable robots to learn from humans (i.e., transferring information from humans to robots). In parallel, visual, haptic, and auditory communication interfaces have been designed to convey the robot’s internal state to the human (i.e., transferring information from robots to humans). Prior research often separates these two directions of information transfer, and focuses primarily on either learning algorithms or communication interfaces. By contrast, in this survey we take an interdisciplinary approach to identify common themes and emerging trends that close the loop between learning and communication. Specifically, we survey state-of-the-art methods and outcomes for communicating a robot’s learning back to the human teacher during human-robot interaction. This discussion connects human-in-the-loop learning methods and explainable robot learning with multimodal feedback systems and measures of human-robot interaction. We find that—when learning and communication are developed together—the resulting closed-loop system can lead to improved human teaching, increased human trust, and human-robot co-adaptation. The paper includes a perspective on several of the interdisciplinary research themes and open questions that could advance how future robots communicate their learning to everyday operators. Finally, we implement a selection of the reviewed methods in a case study where participants kinesthetically teach a robot arm. This case study documents and tests an integrated approach for learning in ways that can be communicated, conveying this learning across multimodal interfaces, and measuring the resulting changes in human and robot behavior. 

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5. Wastewater Monitoring Raises Privacy and Ethical Considerations

   https://doi.org/10.1109/TTS.2021.3073886  

   Jacobs, Danielle; McDaniel, Troy; Varsani, Arvind; Halden, Rolf U.; Forrest, Stephanie; Lee, Heewook (January 2021, IEEE transactions on technology and society)

   null (Ed.)

   Analysis of municipal wastewater, or sewage for public health applications is a rapidly expanding field aimed at understanding emerging epidemiological trends, including human and disease migration. The newly gained ability to extract and analyze genetic material from wastewater poses important societal and ethical questions, including: How to safeguard data? Who owns genetic data recovered from wastewater? What are the ethical and legal issues surrounding its use? In the U.S., both corporate and legal policies regarding privacy have been historically reactive instead of proactive. In wastewater-based epidemiology (WBE), the pace of innovation has outpaced the ability of social and legal mechanisms to keep up. To address this discrepancy, early and robust discussions of the research, policies, and ethics surrounding WBE analysis and genetics is needed. This paper contributes to this discussion by examining ownership issues for human genetic data recovered from wastewater and the uses to which it may be put. We focus particularly on the risks associated with personally identifiable data, highlighting potential risks, relevant privacy-enhancing technologies, and appropriate ethics. The paper proposes an approach for people conducting WBE studies to help them systematically consider the ethical and privacy implications of their work. 

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