Alle Publikationen
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2018
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(2018) : Artificial Empathy in Social Robots: An analysis of Emotions in Speech: 2018 27th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN): Nanjing, China: IEEE Robotics & Automation Society, S. 632-637
DOI: https://doi.org/10.1109/ROMAN.2018.8525652 Abstract: Artificial speech developed using speech synthesizers has been used as the voice for robots in Human Robot Interaction (HRI). As humans anthropomorphize robots, an empathetically interacting robot is expected to increase the level of acceptance of social robots. Here, a human perception experiment evaluates whether human subjects perceive empathy in robot speech. For this experiment, empathy is expressed only by adding appropriate emotions to the words in speech. Also, humans’ preferences for a robot interacting with empathetic speech versus a standard robotic voice are also assessed. The results show that humans are able to perceive empathy and emotions in robot speech, and prefer it over the standard robotic voice. It is important for the emotions in empathetic speech to be consistent with the language content of what is being said, and with the human users’ emotional state. Analyzing emotions in empathetic speech using valence-arousal model has revealed the importance of secondary emotions in developing empathetically speaking social robots.
Keywords: Angemessen(heit) (von Technik), Anthropomorphism, appropriate emotions, artificial empathy, artificial speech, control engineering computing, emotion recognition, empathetic speech, empathetically interacting robot, human perception experiment, Human robot interaction, human subjects, human users, human-robot interaction, Humans, ieee xplore, Medical services, robot interacting, Robot sensing systems, robot speech, Robots, service robot, social robots, speech synthesis, speech synthesizers, standard robotic voice, standards, Task Analysis -
(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 2017
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(2017): Value-Based Standards Guide Sexism Inferences for Self and Others. In: Journal of Experimental Social Psychology 72, S. 101-117. DOI: 10.1016/j.jesp.2017.04.006
DOI: http://www.ncbi.nlm.nih.gov/pubmed/29230069 Abstract: People often disagree about what constitutes sexism, and these disagreements can be both socially and legally consequential. It is unclear, however, why or how people come to different conclusions about whether something or someone is sexist. Previous research on judgments about sexism has focused on the perceiver's gender and attitudes, but neither of these variables identifies comparative standards that people use to determine whether any given behavior (or person) is sexist. Extending Devine and colleagues' values framework (Devine, Monteith, Zuwerink, & Elliot, 1991; Plant & Devine, 1998), we argue that, when evaluating others' behavior, perceivers rely on the morally-prescriptive values that guide their own behavior toward women. In a series of 3 studies we demonstrate that (1) people's personal standards for sexism in their own and others' behavior are each related to their values regarding sexism, (2) these values predict how much behavioral evidence people need to infer sexism, and (3) people with stringent, but not lenient, value-based standards get angry and try to regulate a sexist perpetrator's behavior to reduce sexism. Furthermore, these personal values are related to all outcomes in the present work above and beyond other person characteristics previously used to predict sexism inferences. We discuss the implications of differing value-based standards for explaining and reconciling disputes over what constitutes sexist behavior.
Keywords: FRAMEWORK, Geschlechterforschung, Inferences, science direct, Sexism, Sozialpsychologie, standards, VALUES 2016
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(2016): Quality of Life for Diverse Older Adults in Assisted Living: The Centrality of Control. In: Journal of gerontological social work 59 (7-8), S. 512-536. DOI: 10.1080/01634372.2016.1254699
DOI: http://www.ncbi.nlm.nih.gov/pubmed/27824306 Abstract: This pilot project asked: How do ethnically diverse older adult residents of assisted living (AL) facilities in British Columbia (BC) experience quality of life? And, what role, if any, do organizational and physical environmental features play in influencing how quality of life is experienced? The study was conducted at three AL sites in BC: two ethnoculturally targeted and one nontargeted. Environmental audits at each site captured descriptive data on policies, fees, rules, staffing, meals, and activities, and the built environment of the AL building and neighborhood. Using a framework that understands the quality of life of older adults to be contingent on their capability to pursue 5 conceptual attributes-attachment, role, enjoyment, security, and control-we conducted 3 focus groups with residents (1 per site) and 6 interviews with staff (2 per site). Attributes were linked to the environmental features captured in the audits. All dimensions of the environment, especially organizational, influence tenants' capability to attain the attributes of quality of life, most importantly control. Although many tenants accept the trade-off between increased safety and diminished control that accompanies a move into AL, more could be done to minimize that loss. Social workers can advocate for the necessary multi-sectoral changes.
Keywords: 80 and over, Aged, Assistenz, Assisting Living Facilities, Attitude of Health Personnel, British Columbia, Community Networks, Female, Focus Groups, Gerontologie, Humans, Male, Personal Autonomy, Personal Satisfaction, Pilot Projects, PSYCHOLOGY, Quality of Life, Safety Management, standards -
(2016): Bridging the Ethical Gap: From Human Principles to Robot Instructions. In: IEEE Intelligent Systems 31 (5), S. 76-82. DOI: 10.1109/MIS.2016.87
DOI: https://doi.org/10.1109/MIS.2016.87 Abstract: Asimov’s three laws of robotics and the Murphy-Woods alternative laws assume that a robot has the cognitive ability to make moral decisions, and fail to escape the myth of self-sufficiency. But ethical decision making on the part of robots in human-robot interaction is grounded on the interdependence of human and machine. Furthermore, the proposed laws are high-level principles that cannot easily be translated into machine instructions because there is an immense gap between the architecture, implementation, and activity of humans and robots in addressing ethical situations. The characterization of the ethical gap, particularly with reference to the Murphy-Woods laws, leads to a proposal for a shift in focus away from the autonomous behavior of the robot to human-robot communication at the interface, and the development of interdependence rules to underpin the process of ethical decision-making.
Keywords: autonomous behavior, cognitive ability, Context modeling, control engineering computing, ethical decision making, ethical gap, ethical interdependence, Ethics, human principle, human-robot interaction, human-robot interface, ieee xplore, Intelligent Systems, Law, laws of robotics, Moral & Ethik, Murphy-Woods alternative laws, Robot Ethics, robot instruction, Robot kinematics, Robot sensing systems, Robotics, standards 2008
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(2008) : Learning polite behavior with situation models: 3rd ACM/IEEE International Conference on Human-Robot Interaction (HRI): New York, NY, US: Association for Computing Machinery, S. 209-216
DOI: https://doi.org/10.1145/1349822.1349850 Abstract: In this paper, we describe experiments with methods for learning the appropriateness of behaviors based on a model of the current social situation. We first review different approaches for social robotics, and present a new approach based on situation modeling. We then review algorithms for social learning and propose three modifications to the classical Q-Learning algorithm. We describe five experiments with progressively complex algorithms for learning the appropriateness of behaviors. The first three experiments illustrate how social factors can be used to improve learning by controlling learning rate. In the fourth experiment we demonstrate that proper credit assignment improves the effectiveness of reinforcement learning for social interaction. In our fifth experiment we show that analogy can be used to accelerate learning rates in contexts composed of many situations.
Keywords: Angemessen(heit) (von Technik), Convergence, credit assignment, Humans, ieee xplore, Learning, learning (artificial intelligence), Learning by Analogy, machine learning, polite behavior, Q-Learning, Q-learning algorithm, Reinforcement learning, Robot sensing systems, Robots, situation modeling, social aspects of automation, Social factors, social interaction, social learning, Social robotic, social situation, standards 2006
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(2006) : Learning polite behavior with situation models: 3rd International Forum on Applied Wearable Computing 2006: Bremen, Germany: IEEE, S. 209-216
DOI: https://doi.org/10.1145/1349822.1349850 Abstract: In this paper, we describe experiments with methods for learning the appropriateness of behaviors based on a model of the current social situation. We first review different approaches for social robotics, and present a new approach based on situation modeling. We then review algorithms for social learning and propose three modifications to the classical Q-Learning algorithm. We describe five experiments with progressively complex algorithms for learning the appropriateness of behaviors. The first three experiments illustrate how social factors can be used to improve learning by controlling learning rate. In the fourth experiment we demonstrate that proper credit assignment improves the effectiveness of reinforcement learning for social interaction. In our fifth experiment we show that analogy can be used to accelerate learning rates in contexts composed of many situations.
Keywords: Convergence, credit assignment, Humans, ieee xplore, Künstliche Intelligenz, Learning, learning (artificial intelligence), Learning by Analogy, machine learning, polite behavior, Q-Learning, Q-learning algorithm, Reinforcement learning, Robot sensing systems, Robots, situation modeling, social aspects of automation, Social factors, social interaction, social learning, Social robotic, social situation, standards 2002
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(2002): Beurteilerübereinstimmung und Beurteilerreliabilität. Methoden zur Bestimmung und Verbesserung der Zuverlässigkeit von Einschätzungen mittels Kategoriensystemen und Ratingskalen. Göttingen: Hogrefe Verl. für Psychologie
Abstract: Einschätzungen durch Beurteiler stellen in der angewandten psychologischen und sozialwissenschaftlichen Forschung eines der wichtigsten Datenerhebungsverfahren dar. Das Buch liefert erstmalig einen vollständigen Überblick über Methoden zur Bestimmung der Übereinstimmung und der Reliabilität zwischen Beurteilern. Es zeigt auf, welche Entscheidungskriterien für die Wahl der geeigneten Kenngrößen maßgebend sind. Ausgehend von typischen Problemstellungen werden verschiedene Lösungsansätze verglichen und spezifische Vor- und Nachteile herausgearbeitet. Die genaue Berechnung der empfohlenen Maßzahlen wird an praktischen Beispielen demonstriert. Ferner wird eine Anleitung zur Berechnung mit SPSS dargestellt, die auch für mit dem Programmsystem wenig vertrauten Anwendern verständlich ist. Zusätzlich werden wichtige Hinweise gegeben, wie durch ein systematisches Beurteilertraining die Qualität und Aussagekraft empirischer Studien verbessert werden kann.
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