Alle Publikationen
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2017
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(2017): Artificial agents among us. Should we recognize them as agents proper?. In: Ethics and Information Technology 19 (1), S. 1-17. DOI: 10.1007/s10676-016-9411-3
Abstract: Abstract In this paper, I discuss whether in a society where the use of artificial agents is pervasive, these agents should be recognized as having rights like those we accord to group agents. This kind of recognition I understand to be at once social and legal, and I argue that in order for an artificial agent to be so recognized, it will need to meet the same basic conditions in light of which group agents are granted such recognition. I then explore the implications of granting recognition in this manner. The thesis I will be defending is that artificial agents that do meet the conditions of agency in light of which we ascribe rights to group agents should thereby be recognized as having similar rights. The reason for bringing group agents into the picture is that, like artificial agents, they are not self-evidently agents of the sort to which we would naturally ascribe rights, or at least that is what the historical record suggests if we look, for example, at what it took for corporations to gain legal status in the law as group agents entitled to rights and, consequently, as entities subject to responsibilities. This is an example of agency ascribed to a nonhuman agent, and just as a group agent can be described as nonhuman, so can an artificial agent. Therefore, if these two kinds of nonhuman agents can be shown to be sufficiently similar in relevant ways, the agency ascribed to one can also be ascribed to the other-this despite the fact that neither is human, a major impediment when it comes to recognizing an entity as an agent proper, and hence as a bearer of rights.
Keywords: agency, Anerkennung, Anerkennung technischer Systeme, Anerkennung und technische Systeme, Artificial agent, artificial agents, doppelter Treffer, Favoriten, Group agent, Mensch-Technik-Relationen (MTR), Modelle/Theorien, Personhood, RATIONALITY, Realtechnik, recognition and self, responsibility, Rights, Serviceroboter, Soziale Angemessenheit, Soziale Robotik, Technik -
(2017) : Learning behavioral norms in uncertain and changing contexts: 2017 8th IEEE International Conference on Cognitive Infocommunications (CogInfoCom): Debrecen, Hungary: IEEE, S. 000301-000306
DOI: https://doi.org/10.1109/CogInfoCom.2017.8268261 Abstract: Human behavior is often guided by social and moral norms. Robots that enter human societies must therefore behave in norm-conforming ways as well to increase coordination, predictability, and safety in human-robot interactions. However, human norms are context-specific and laced with uncertainty, making the representation, learning, and communication of norms challenging. We provide a formal representation of norms using deontic logic, Dempster-Shafer Theory, and a machine learning algorithm that allows an artificial agent to learn norms under uncertainty from human data. We demonstrate a novel cognitive capability with which an agent can dynamically learn norms while being exposed to distinct contexts, recognizing the unique identity of each context and the norms that apply in it.
Keywords: Artificial agent, behavioral norms, behavioural sciences computing, Cognition, Conferences, Dempster-Shafer Theory, deontic logic, Ethics, formal logic, Human behavior, human societies, human-robot interaction, human-robot interactions, ieee xplore, inference mechanisms, learning (artificial intelligence), Libraries, machine learning algorithm, Moral & Ethik, moral norms, norm-conforming ways, Robot kinematics, Social Norms, uncertainty, uncertainty handling 2015
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(2015): Empathy for Artificial Agents. In: Int J of Soc Robotics 7 (1), S. 111-116. DOI: 10.1007/s12369-014-0260-0
DOI: https://doi.org/10.1007/s12369-014-0260-0 Abstract: The paper has three goals. First, it introduces into different notions of empathy and related capacities such as emotional contagion, affective empathy, cognitive empathy, and sympathy. Second, it presents a case in point of an intelligent tutoring system, Affective AutoTutor, whose affect-sensitive behavior seems to further and enhance the outcome of its interactions with its students. Affective AutoTutor appears to behave empathically within a well defined learning environment. Third, attention is directed towards the requirements to be met by artificial empathizers to be judged as empathizers tout court by their social interactants, even when acting in unspecified social situations. To be a convincing empathizer, the artificial agent would not only need to grasp the emotional states of its interaction partners and understand their situation with respect to an adequate world model, but also communicate its own affective states. Eventually, an artificial empathizer should be ready to react appropriately to its interaction partner’s reciprocal empathy.
2014
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(2014) : Moral competence in social robots: 2014 IEEE International Symposium on Ethics in Science, Technology and Engineering: Chicago, IL, USA: IEEE, S. 1-6
DOI: https://doi.org/10.1109/ETHICS.2014.6893446 Abstract: We propose that any robots that collaborate with, look after, or help humans-in short, social robots-must have moral competence. But what does moral competence consist of? We offer a framework for moral competence that attempts to be comprehensive in capturing capacities that make humans morally competent and that therefore represent candidates for a morally competent robot. We posit that human moral competence consists of four broad components: (1) A system of norms and the language and concepts needed to communicate about these norms; (2) moral cognition and affect; (3) moral decision making and action; and (4) moral communication. We sketch what we know and don’t know about these four elements of moral competence in humans and, for each component, ask how we could equip an artificial agent with these capacities.
Keywords: Affect, Artificial agent, Cognition, Communities, Context, Decision Making, ethical aspects, Ethics, Human Factors, human moral competence, human-robot interaction, ieee xplore, intentionality, Mobile robots, Moral & Ethik, Moral action, moral affect, Moral agency, Moral cognition, moral communication, moral decision making, moral language, norms system, PSYCHOLOGY, Robots, Social Cognition, social robots 2008
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(2008) : Typification-based ethics for artificial agents: 2008 2nd IEEE International Conference on Digital Ecosystems and Technologies: Phitsanulok, Thailand: IEEE, S. 482-491
DOI: https://doi.org/10.1109/DEST.2008.4635149 Abstract: A digital ecosystem has to deal with the notion of responsibility with respect to some of its entities, including artefacts. Autonomous artificial agents have given rise to the study of the possibility that these agents have ethical aspects. This paper introduces a conceptual framework for ethical situations that involve artificial agents such as robots. Specifically, we focus on how ethical rules should be applied in reference to artificial agents in order for them to act correctly when facing ethical situations. We typify these situations in order to facilitate ethical evaluations. This typification involves classifications of ethical agents and patients according to whether they are human beings, human-based organizations, or non-human beings, and in reference to ethical evaluations of each of these entities. The resultant methodology is applied to Asimovpsilas ldquoLaws of Robotics.
Keywords: Artificial agent, artificial agents, Asimov’s Laws, Biological system modeling, control engineering computing, digital ecosystem, Ecosystems, ethical agent, ethical aspect, ethical aspects, ethical evaluation, ethical rule, Ethics, Humans, ieee xplore, Moral & Ethik, ORGANIZATIONS, Robot, Robot sensing systems, Robots, Software agents, typification-based ethics
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