Alle Publikationen
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2019
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(2019): On Proactive, Transparent, and Verifiable Ethical Reasoning for Robots. In: Proceedings of the IEEE 107 (3), S. 541-561. DOI: 10.1109/JPROC.2019.2898267
DOI: https://doi.org/10.1109/JPROC.2019.2898267 Abstract: Previous work on ethical machine reasoning has largely been theoretical, and where such systems have been implemented, it has, in general, been only initial proofs of principle. Here, we address the question of desirable attributes for such systems to improve their real world utility, and how controllers with these attributes might be implemented. We propose that ethically critical machine reasoning should be proactive, transparent, and verifiable. We describe an architecture where the ethical reasoning is handled by a separate layer, augmenting a typical layered control architecture, ethically moderating the robot actions. It makes use of a simulation-based internal model and supports proactive, transparent, and verifiable ethical reasoning. To do so, the reasoning component of the ethical layer uses our Python-based belief-desire-intention (BDI) implementation. The declarative logic structure of BDI facilitates both transparency, through logging of the reasoning cycle, and formal verification methods. To prove the principles of our approach, we use a case study implementation to experimentally demonstrate its operation. Importantly, it is the first such robot controller where the ethical machine reasoning has been formally verified.
Keywords: BDI implementation, belief desire intention implementation, control engineering computing, Design methodology, ethical machine reasoning, ethical reasoning, Ethics, formal verification, ieee xplore, intelligent robots, layered control architecture, learning (artificial intelligence), machine learning, Moral & Ethik, Predictive models, Python, robot controller, robot programming, Robots, safety, simulation-based internal model, Social implications of technology, software architecture, transparency -
(2019) : Beyond Programming: Can Robots’ Norm-Violating Actions Elicit Mental State Attributions?: 2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI): Daegu, Korea: IEEE, S. 530-531
DOI: https://doi.org/10.1109/HRI.2019.8673293 Abstract: Social perceivers often view a human agent’s norm-violating behavior as diagnostic of that person’s mental states, while behaviors that conform to norms are viewed as less informative. We developed a series of stimulus videos depicting a DRC-HUBO robot engaging in norm-violating and norm-conforming behaviors. We explored the hypothesis that robots’ norm-violating actions may invite social perceivers to increase their mental state attributions in a similar manner as they do in humans. Surprisingly, we found that norm-conforming behaviors appear to be at least as conducive as norm-violating behaviors, and perhaps even moreso, to mental state attribution to robotic agents.
Keywords: action explanation, actions elicit mental state attributions, agency, Artificial intelligence, behavioural sciences computing, Cognition, control engineering computing, DRC-HUBO, DRC-HUBO robot, human agent norm-violating behavior, Humanoid Robots, human-robot interaction, ieee xplore, Künstliche Intelligenz, Mobile robots, multi-agent systems, norms, PSYCHOLOGY, robot programming, robotic agents, social perceivers, theory of mind, Videos 2018
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(2018) : From social interaction to ethical AI: a developmental roadmap: 2018 Joint IEEE 8th International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob): Tokyo, Japan: IEEE, S. 204-211
DOI: https://doi.org/10.1109/DEVLRN.2018.8761023 Abstract: AI and robot ethics have recently gained a lot of attention because adaptive machines are increasingly involved in ethically sensitive scenarios and cause incidents of public outcry. Much of the debate has been focused on achieving highest moral standards in handling ethical dilemmas on which not even humans can agree, which indicates that the wrong questions are being asked. We suggest to address this ethics debate strictly through the lens of what behavior seems socially acceptable, rather than idealistically ethical. Learning such behavior puts the debate into the very heart of developmental robotics. This paper poses a roadmap of computational and experimental questions to address the development of socially acceptable machines. We emphasize the need for social reward mechanisms and learning architectures that integrate these while reaching beyond limitations of plain reinforcement-learning agents. We suggest to use the metaphor of “needs” to bridge rewards and higher level abstractions such as goals for both communication and action generation in a social context. We then suggest a series of experimental questions and possible platforms and paradigms to guide future research in the area.
Keywords: adaptive machines, Artificial intelligence, control engineering computing, Decision Making, developmental roadmap, developmental robotics, ethical AI, ethical aspects, ethically sensitive scenarios, Ethics, Face, ieee xplore, Künstliche Intelligenz, learning (artificial intelligence), plain reinforcement-learning agents, Robot Ethics, robot programming, Robot sensing systems, social interaction, social reward mechanisms, socially acceptable machines, standards 2015
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(2015) : May I help you? - Design of Human-like Polite Approaching Behavior-: 2015 10th ACM/IEEE International Conference on Human-Robot Interaction (HRI): Portland, Oregon, USA: Association for Computing Machinery, S. 35-42
Abstract: When should service staff initiate interaction with a visitor? Neither simply-proactive (e.g. talk to everyone in a sight) nor passive (e.g. wait until being talked to) strategies are desired. This paper reports our modeling of polite approaching behavior. In a shopping mall, there are service staff members who politely approach visitors who need help. Our analysis revealed that staff members are sensitive to ‘intentions’ of nearby visitors. That is, when a visitor intends to talk to a staff member and starts to approach, the staff member also walks a few steps toward the visitors in advance to being talked. Further, even when not being approached, staff members exhibit ”availability” behavior in the case that a visitor’s intention seems uncertain. We modeled these behaviors that are adaptive to pedestrians’ intentions, occurred prior to initiation of conversation. The model was implemented into a robot and tested in a real shopping mall. The experiment confirmed that the proposed method is less intrusive to pedestrians, and that our robot successfully initiated interaction with pedestrians.
Keywords: Adaptation models, availability behavior, Behavior Design, Collaboration, Estimation, ieee xplore, initiation of interaction, Intention estimation, Künstliche Intelligenz, learning (artificial intelligence), Micromechanical devices, nearby visitors, polite approaching behavior, robot programming, Robot sensing systems, service staff members, shopping mall, Task Analysis 2014
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(2014) : Acting vs. being moral: The limits of technological moral actors: 2014 IEEE International Symposium on Ethics in Science, Technology and Engineering: Chicago, IL, USA: IEEE, S. 1-4
DOI: https://doi.org/10.1109/ETHICS.2014.6893396 Abstract: An autonomous robot (physical or digital artificial being) may be capable of producing actions that if performed by a human could be considered moral, by mimicking its creators actions or following their programmed instructions, but it cannot be moral. Morality cannot be fully judged by any behavioral test, as the answer to moral questions is less important than the process followed in arriving at the answer (as evidenced by disagreement among ethicists on the correct answer to many such questions based on the individual’s moral style). The distinction between acting and being moral was recently considered for lethal autonomous military robots [1], and in this paper is further clarified in the context of more broad applications. In addition such a distinction has implications for what types of tasks autonomous robots should not be allowed to do, based on what must be moral decisions. Here we draw a distinction between what might be illegal for an agent to do (which relates more to the agreed upon laws of the current political leadership), and what actions are so innately moral decisions that we cannot delegate them to a machine, no matter how advanced it appears.
Keywords: behavioral test, Buildings, Computers, Decision Making, digital artificial being, Educational institutions, Ethics, Humanoid Robots, ieee xplore, lethal autonomous military robots, military systems, Moral & Ethik, moral decisions, Morality, physical being, political leadership, programmed instructions, robot programming, Robot sensing systems, technological moral actors, Weapons
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