Alle Publikationen
2019
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(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) : A Computational Framework for Integrating Task Planning and Norm Aware Reasoning for Social Robots: 2018 27th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN): Nanjing, China: IEEE Robotics & Automation Society, S. 282-287
DOI: https://doi.org/10.1109/ROMAN.2018.8525577 Abstract: Autonomous robots are envisioned to increasingly become part of our lives in the house, restaurants, hospitals and offices. Additionally, self-driving cars will be soon appearing in city streets and highways and they will have to interact with cars driven by humans as well as other self-driving cars. In these settings the robots not only need to efficiently perform their tasks but also be able to interact with humans in socially appropriate ways. To accomplish this, robots must be able to reason not only on how to perform their tasks, but also incorporate societal values, social norms and legal rules so they can gain human acceptability and trust. Moreover, interactions with these robots will be long term. Long-term human interaction with robots as well as robot combined reasoning about both tasks and social norms generate multiple modeling and computational challenges. In this paper, we address one of the most important of these challenges, namely what is an appropriate and scalable computational framework that enables simultaneous task and normative reasoning. In particular, we report on our work on a novel computational framework, Modular Normative Markov Decision Processes (MNMDP) that integrates reasoning for domain tasks and normative reasoning for long-term autonomy. The MNMDP framework applies normative reasoning considering only the norms that are activated in appropriate contexts, rather than considering the full set of norms, thus significantly reducing computational complexity. The model modularity is also advantageous for long-term human-robot interaction. We present computational experiments that show significant computational improvements as compared with a base Normative Markov Decision Process (MDP) framework that includes the full set of norms.
Keywords: Angemessen(heit) (von Technik), Autonomous automobiles, autonomous robots, Cognition, Computational complexity, Decision theory, human acceptability, human-robot interaction, ieee xplore, inference mechanisms, knowledge based systems, long-term human interaction, Markov processes, MNMDP framework, Mobile robots, modular normative Markov decision processes, norm aware reasoning, normative Markov decision process framework, Normative reasoning, path planning, Planning, robot combined reasoning, self-driving cars, Social Norms, social robots, societal values, Task Analysis, task planning -
(2018) : Emotionally Adaptive Driver Voice Alert System for Advanced Driver Assistance System (ADAS) Applications: 2018 International Conference on Smart Systems and Inventive Technology (ICSSIT): Tirunelveli, India: IEEE, S. 509-512
DOI: https://doi.org/10.1109/ICSSIT.2018.8748541 Abstract: Human cognitive analysis catalyzes the innovations in Human Machine Interface (HMI) for a variety of applications. In an Automotive Advanced Driver Assistance System (ADAS), the continuous cognitive interaction of the driver with the assistance system plays a crucial role in enhancing the active safety system. Multiple ADAS functionalities uses a variety of driver alerts through visual, audio and vibrational means to provide a numerous safety alerts to the driver. The effectiveness of any alert system is measured through its success rate in mitigating the actions which are against the alert commands. The actions taken by the driver for the alerts depends heavily on the driver’s moods, which are responsible for driver’s perception in understanding the alerts. Even though the voice alerts are considered as the most effective form of human alerts, the static nature of the voice alerts makes them less effective in making the driver to understand the criticality of the alerts when his moods are abnormal or having a reduced driving concentration levels. An adaptive voice alert system with a cognitive driver synchronization makes the alert penetration successful when the driver’s moods are abnormal or having a reduced driving concentration levels. Here in this paper the adaptive voice alert system is designed using the driver’s emotional cognitive features. The emotionally adaptive voice alert system changes the voice alerts as according to the moods of the driver, which are measured by Deep Learning based Emotion Recognition System. The adaptive voice alert system makes the voice enabled HMI effective which improves the vehicle safety.
Keywords: active safety system, adaptive driver voice alert system, Adaptive systems, Advanced Driver Assistance System (ADAS), advanced driver assistance system applications, Advanced driver assistance systems, alert commands, alert penetration successful, automotive advanced driver assistance system, Cognition, cognitive driver synchronization, Convolutional Neural Network (CNN), driver alerts, driver information systems, emotion recognition, emotion recognition system, Emotion Recognition System (ERS), emotionally adaptive voice alert system, human alerts, human cognitive analysis, Human Computer Interaction, Human Machine Interface (HMI), ieee xplore, Künstliche Intelligenz, learning (artificial intelligence), Monitoring, natural language interfaces, safety alerts, Vehicles, voice alerts -
(2018) : A Wizard of Oz Study of Human Interest Towards Robot Initiated Human-Robot Interaction: 2018 27th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN): Nanjing, China: IEEE Robotics & Automation Society, S. 515-521
DOI: https://doi.org/10.1109/ROMAN.2018.8525583 Abstract: Service robots have become a widely used tool in human-friendly assistive tasks in many aspects including social environments. Maintaining a sustainable interaction with humans is essential in performing assistive tasks in this regard. Therefore, a robot must be equipped with intelligent cognitive skills in decision making as well as in making friendly relationships with its human user. Human-like capabilities such as initiating a conversation at the right moment without distracting and maintaining an appropriate interaction are important cues in this context. This paper presents a human study conducted by means of a wizard-of-oz (WoZ) experiment to identify the behavioral features in humans that can be utilized by an assistive robot in a domestic environment to assess the situation prior to an interaction. Both verbal and nonverbal responses of participants towards an interaction initiated by a robot were recorded and analyzed to identify human behavioral changes that portray an interest towards interaction. The experiment was conducted in a simulated domestic environment and findings of the experiment are presented and discussed so that these findings could be made use of when designing human-like social robots in future. Furthermore, human behavioral changes observed during the study are analyzed and critical observations are highlighted.
Keywords: Angemessen(heit) (von Technik), assistive robot, Attitude control, Cognition, Decision Making, Emotional Intelligence, human behavioral changes, Human Factors, human interest, Human robot interaction, human user, human-friendly assistive tasks, human-like social robots, human-robot interaction, ieee xplore, intelligent cognitive skills, interaction initiation, robot initiated human-robot interaction, service robot, Social Environments, Social intelligence, Task Analysis, Tools, wizard of oz, wizard-of-oz experiment, WoZ experiment 2017
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(2017): Motivated cognition and fairness. Insights, integration, and creating a path forward. In: The Journal of applied psychology 102 (6), S. 867-889. DOI: 10.1037/apl0000204
DOI: http://www.ncbi.nlm.nih.gov/pubmed/28277729 Abstract: How do individuals form fairness perceptions? This question has been central to the fairness literature since its inception, sparking a plethora of theories and a burgeoning volume of research. To date, the answer to this question has been predicated on the assumption that fairness perceptions are subjective (i.e., "in the eye of the beholder"). This assumption is shared with motivated cognition approaches, which highlight the subjective nature of perceptions and the importance of viewing individuals arriving at those perceptions as active and motivated processors of information. Further, the motivated cognition literature has other key insights that have been less explicitly paralleled in the fairness literature, including how different goals (e.g., accuracy, directional) can influence how individuals process information and arrive at their perceptions. In this integrative conceptual review, we demonstrate how interpreting extant theory and research related to the formation of fairness perceptions through the lens of motivated cognition can deepen our understanding of fairness, including how individuals' goals and motivations can influence their subjective perceptions of fairness. We show how this approach can provide integration as well as generate new insights into fairness processes. We conclude by highlighting the implications that applying a motivated cognition perspective can have for the fairness literature and by providing a research agenda to guide the literature moving forward. (PsycINFO Database Record
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(2017): Moral learning. Psychological and philosophical perspectives. In: Cognition 167, S. 1-10. DOI: 10.1016/j.cognition.2017.06.008
DOI: http://www.ncbi.nlm.nih.gov/pubmed/28629599 Abstract: The past 15years occasioned an extraordinary blossoming of research into the cognitive and affective mechanisms that support moral judgment and behavior. This growth in our understanding of moral mechanisms overshadowed a crucial and complementary question, however: How are they learned? As this special issue of the journal Cognition attests, a new crop of research into moral learning has now firmly taken root. This new literature draws on recent advances in formal methods developed in other domains, such as Bayesian inference, reinforcement learning and other machine learning techniques. Meanwhile, it also demonstrates how learning and deciding in a social domain-and especially in the moral domain-sometimes involves specialized cognitive systems. We review the contributions to this special issue and situate them within the broader contemporary literature. Our review focuses on how we learn moral values and moral rules, how we learn about personal moral character and relationships, and the philosophical implications of these emerging models.
Keywords: Cognition, Judgment, Kognitionswissenschaften, Lerntheorien, Moral, Morals, Philosophy, PSYCHOLOGY, science direct -
(2017): Social cognition. From brains to culture. Third edition. Los Angeles; London; New Delhi; Singapore; Washington, DC; Melbourne: Sage
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(2017): Learning a commonsense moral theory. In: Cognition 167, S. 107-123. DOI: 10.1016/j.cognition.2017.03.005
DOI: http://www.ncbi.nlm.nih.gov/pubmed/28351662 Abstract: We introduce a computational framework for understanding the structure and dynamics of moral learning, with a focus on how people learn to trade off the interests and welfare of different individuals in their social groups and the larger society. We posit a minimal set of cognitive capacities that together can solve this learning problem: (1) an abstract and recursive utility calculus to quantitatively represent welfare trade-offs; (2) hierarchical Bayesian inference to understand the actions and judgments of others; and (3) meta-values for learning by value alignment both externally to the values of others and internally to make moral theories consistent with one's own attachments and feelings. Our model explains how children can build from sparse noisy observations of how a small set of individuals make moral decisions to a broad moral competence, able to support an infinite range of judgments and decisions that generalizes even to people they have never met and situations they have not been in or observed. It also provides insight into the causes and dynamics of moral change across time, including cases when moral change can be rapidly progressive, changing values significantly in just a few generations, and cases when it is likely to move more slowly. zitiert von: 7
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(2017) : Designing technology for older adults: Augmenting usefulness and usability via cognitive support In: Kwon, Sunkyo: Gerontechnology: Research, practice, and principles in the field of technology and aging: New York, NY: Springer Publishing Company, S. 389-416
Abstract: To fully explore why age discrepancies in technology use have been observed, we describe how older adults conceptualize usefulness and how usability can be empirically measured. Because cognitive changes that co-occur with age can influence technology-related task performance, which in turn may either augment or reduce perceived usefulness and usability, we also discuss the importance of designing technology to provide cognitive and environmental support. Such supportive design is key in developing technology that older adults want to use, which furthers understanding of how age-related cognitive changes should be considered during the technology design process. Furthermore, this approach identifies research questions that should benefit from further empirical investigation. We focus on what is known about three predictor variables (i.e., usefulness, usability, and cognition) that deserve special consideration when designing technology for older adults’ use. To accomplish this goal, three approaches with examples are described in this chapter. (PsycINFO Database Record (c) 2019 APA, all rights reserved)
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(2017): Editorial. Trust: The Limits of Human Moral. In: Frontiers in psychology 8. DOI: 10.3389/fpsyg.2017.00178
DOI: https://doi.org/10.3389/fpsyg.2017.00178 Abstract: This editorial briefs the articles featured in this special issue of Frontiers in Psychology . In this special issue on trust, several studies explored how the amount and the type of contact affects trusting behavior. In the course of daily life, people routinely engage in social exchanges that involve some level of trust. Studies published as a part of the current research topic suggest that individuals do not automatically adopt trusting and moral behavior in human interactions, but that those behaviors are determined by and modulated by a plethora of cognitive, psychological, situational, and contextual factors. We believe that research published within the special topic significantly contributes to understanding of trust and we encourage further research both on the brighter and darker sides of trust. (PsycINFO Database Record (c) 2017 APA, all rights reserved)
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(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 2016
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(2016) : Towards ethical robots: Revisiting Braitenberg’s vehicles: 2016 SAI Computing Conference (SAI): London, United Kingdom: IEEE, S. 469-477
DOI: https://doi.org/10.1109/SAI.2016.7556023 Abstract: The development of software and machines capable of making ethical judgements is a topic of great interest with both the research communities and the public. Debates over the possibility and practicality of such systems have only intensified with the increased use of robotics in the military arena and the ubiquity of AI in commercial products. Modern innovations, such as the driverless car, will likely make artificial ethical agents a legal necessity. As a research field, it has received relatively little attention compared to other, more traditional, AI problems. In this paper, we propose a bottom-up reactive system that provides one possible solution. We will begin by describing the motivation to this work: the development of artificial ethical agents could both mitigate some fears about the future of autonomous AI, and providing insight into human moral reasoning. We then explore the related work, including the current attempts at simulating ethics. We describe our novel approach to ethical simulation, Vessels; a Braitenberg Vehicle inspired reactive agent approach. We, then, demonstrate how Vessels can be configured to simulate both Egoism and Altruism, comparing our simulations to the normative theory.
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(2016) : The ethical risk of attachment how to identify, investigate and predict potential ethical risks in the development of social companion robots: 2016 11th ACM/IEEE International Conference on Human-Robot Interaction (HRI): Christchurch, New Zealand: IEEE Press, S. 367-374
DOI: https://doi.org/10.1109/HRI.2016.7451774 Abstract: In this paper we present the Triple-A Model intended as a framework for researchers and developers to incorporate ethics in the user-and robot-centered design of social companion robots. The purpose of the model is to help identifying potential ethical risks in the implementation of Human-Robot Interaction (HRI) scenarios. We base our model on three interaction levels, which companion robots can offer: Assistance, Adaptation, and Attachment (Triple-A). Every single interaction level has its specific potential ethical risks, which can be addressed during the robot development phase. However, we especially focus on the prominent ethical risks of long-term human-robot attachment and its implications on human-robot relationships. We discuss the practical use and the theoretical foundation of the Triple-A model which is well-grounded in the social role theory from sociology and the human cognitive-mnestic structure from cognitive science.
Keywords: assistance adaptation, Attachment, bonding, Cognition, Cognitive Science, ethical aspects, ethical risk, Ethics, HRI, human cognitive-mnestic structure, human-robot attachment, human-robot interaction, human-robot interaction scenarios, human-robot relationships, ieee xplore, Moral & Ethik, robot companions, robot development phase, robot-centered design, social companion robots, Social role, social role theory, socially assistive robots, triple-A model, user centred design, user-centered design -
(2016): Intuition and Moral Decision-Making - The Effect of Time Pressure and Cognitive Load on Moral Judgment and Altruistic Behavior. In: PLoS one 11 (10). DOI: 10.1371/journal.pone.0164012
DOI: https://doi.org/10.1371/journal.pone.0164012 Abstract: Do individuals intuitively favor certain moral actions over others? This study explores the role of intuitive thinking-induced by time pressure and cognitive load-in moral judgment and behavior. We conduct experiments in three different countries (Sweden, Austria, and the United States) involving over 1,400 subjects. All subjects responded to four trolley type dilemmas and four dictator games involving different charitable causes. Decisions were made under time pressure/time delay or while experiencing cognitive load or control. Overall we find converging evidence that intuitive states do not influence moral decisions. Neither time-pressure nor cognitive load had any effect on moral judgments or altruistic behavior. Thus we find no supporting evidence for the claim that intuitive moral judgments and dictator game giving differ from more reflectively taken decisions. Across all samples and decision tasks men were more likely to make utilitarian moral judgments and act selfishly compared to women, providing further evidence that there are robust gender differences in moral decision-making. However, there were no significant interactions between gender and the treatment manipulations of intuitive versus reflective decision-making. zitiert von 19
2015
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(2015): Measuring social complexity. In: Animal Behaviour 103, S. 203-209. DOI: 10.1016/j.anbehav.2015.02.018
DOI: https://doi.org/10.1016/j.anbehav.2015.02.018 Abstract: In one of the first formulations of the social complexity hypothesis, Humphrey (1976, page 316, Growing Points in Ethology, Cambridge University Press) predicts ‘that there should be a positive correlation across species between social complexity and individual intelligence’. However, in the many ensuing tests of the hypothesis, surprisingly little consideration has been given to measures of the independent variable in this evolutionary relationship, that is, social complexity. Here, we seek to encourage more rigorous measures of social complexity. We first review previous definitions of this variable and point to two common flaws; a lack of objectivity and a failure to directly connect sociality to the use of cognition. We argue that, rather than creating circularity, including cognition in the definition of social complexity is necessary for accurately testing the social complexity hypothesis. We propose a new definition of social complexity that is based on the number of differentiated relationships that individuals have. We then demonstrate that the definition is both broadly applicable and flexible, allowing researchers to include more detailed information about the degree of differentiation among individuals when the data are available. While we see this definition of social complexity as one possible way forward, our larger goal is to encourage researchers examining the social complexity hypothesis to carefully consider their measurement of social complexity.
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(2015): The rise of moral cognition. In: Cognition 135, S. 39-42. DOI: 10.1016/j.cognition.2014.11.018
DOI: http://www.ncbi.nlm.nih.gov/pubmed/25498900 Abstract: The field of moral cognition has grown rapidly in recent years thanks in no small part to Cognition. Consistent with its interdisciplinary tradition, Cognition encouraged the growth of this field by supporting empirical research conducted by philosophers as well as research native to neighboring fields such as social psychology, evolutionary game theory, and behavioral economics. This research has been exceptionally diverse both in its content and methodology. I argue that this is because morality is unified at the functional level, but not at the cognitive level, much as vehicles are unified by shared function rather than shared mechanics. Research in moral cognition, then, has progressed by explaining the phenomena that we identify as "moral" (for high-level functional reasons) in terms of diverse cognitive components that are not specific to morality. In light of this, research on moral cognition may continue to flourish, not as the identification and characterization of distinctive moral processes, but as a testing ground for theories of high-level, integrative cognitive function. zitiert von: 43
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(2015) : Robot Form and Motion Influences Social Attention: 2015 10th ACM/IEEE International Conference on Human-Robot Interaction (HRI): Portland, Oregon, USA: Association for Computing Machinery, S. 43-50
Abstract: For social robots to be successful, they need to be accepted by humans. Human-robot interaction (HRI) researchers are aware of the need to develop the right kinds of robots with appropriate, natural ways for them to interact with humans. However, much of human perception and cognition occurs outside of conscious awareness, and how robotic agents engage these processes is currently unknown. Here, we explored automatic, reflexive social attention, which operates outside of conscious control within a fraction of a second to discover whether and how these processes generalize to agents with varying humanlikeness in their form and motion. Using a social variant of a well-established spatial attention paradigm, we tested whether robotic or human appearance and/or motion influenced an agent’s ability to capture or direct implicit social attention. In each trial, either images or videos of agents looking to one side of space (a head turn) were presented to human observers. We measured reaction time to a peripheral target as an index of attentional capture and direction. We found that all agents, regardless of humanlike form or motion, were able to direct spatial attention in the cued direction. However, differences in the form of the agent affected attentional capture, i.e., how quickly the observers could disengage attention from the agent and respond to the target. This effect further interacted with whether the spatial cue (head turn) was presented through static images or videos. Overall whereas reflexive social attention operated in the same manner for human and robot social agents for spatial attentional cueing, robotic appearance, as well as whether the agent was static or moving significantly influenced unconscious attentional capture processes. These studies reveal how unconscious social attentional processes operate when the agent is a human vs. a robot, add novel manipulations to the literature such as the role of visual motion, and provide a link between attention studies in HRI, and decades of research on unconscious social attention in experimental psychology and vision science.Categories and Subject Descriptors H.1.2 [Models and Principles]: User/Machine Systems -Human factors. H.5.2 [Information Interfaces and Presentation]: User Interfaces - Evaluation/methodology, User-Centered DesignGeneral TermsDesign, Human Factors.
Keywords: Angemessen(heit) (von Technik), automatic attention, Biology, Cognition, conscious awareness, conscious control, cued direction, Experimental Psychology, head turn, HRI, human appearance, Human Factors, human observers, human perception, humanlike form, Humanlikeness, human-robot interaction, Human-robot interaction researchers, ieee xplore, implicit social attention, Kinematics, Mobile robots, motion influences social attention, PSYCHOLOGY, reflexive social attention, robot design, robot form, Robot sensing systems, robotic agents, robotic appearance, Social Attention, social robots, social variant, Spatial Attention, spatial attention paradigm, spatial attentional cueing, spatial cue, static images, Time measurement, unconscious attentional capture processes, unconscious social attention, unconscious social attentional processes, user interfaces, User/Machine Systems-Human factors, varying humanlikeness, Videos, visual motion, Visual Perception -
(2015) : When will people regard robots as morally competent social partners?: 2015 24th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN): Kobe, Japan: IEEE Robotics & Automation Society, S. 486-491
DOI: https://doi.org/10.1109/ROMAN.2015.7333667 Abstract: We propose that moral competence consists of five distinct but related elements: (1) having a system of norms; (2) mastering a moral vocabulary; (3) exhibiting moral cognition and affect; (4) exhibiting moral decision making and action; and (5) engaging in moral communication. We identify some of the likely triggers that may convince people to (justifiably) ascribe each of these elements of moral competence to robots. We suggest that humans will treat robots as moral agents (who have some rights, obligations, and are targets of blame) if they perceive them to have at least elements (1) and (2) and one or more of elements (3)-(5).
Keywords: Cognition, Context, Decision Making, Ethics, Human Factors, human-robot interaction, ieee xplore, Moral & Ethik, Moral action, Moral cognition, moral communication, moral competence, moral decision making, moral vocabulary, morally competent social partners, PSYCHOLOGY, Robots, social aspects of automation, Vocabulary -
(2015) : A model of empathy to shape trolley problem moral judgements: 2015 International Conference on Affective Computing and Intelligent Interaction (ACII): Xian, China: IEEE, S. 112-118
DOI: https://doi.org/10.1109/ACII.2015.7344559 Abstract: Moral judgements are a complex phenomenon that have gained a renewed interest in the research community. Many have proposed explanations for moral judgements, including utilitarian accounts and the Principle of Double Effect. Some also advocate for the critical role of emotional processes like empathy. However, developing a computational model of moral judgements is rare perhaps due in part to the numerous influences on it. We present here a computational model of moral judgements based on moral expectation and the Principle of Double Effect. We then extend this model to provide a plausible explanation for the effect of empathy on these judgements. We evaluate these models using results from recent studies with human participants.
Keywords: Cognition, Complexity theory, computational model, Computational modeling, Decision Making, Decision theory, double effect principle, Empathy, empathy model, Ethics, ieee xplore, Moral & Ethik, moral expectation, Moral judgment, PSYCHOLOGY, shape trolley problem moral judgements, Trajectory, utility 2014
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(2014): Making fingers and words count in a cognitive robot. In: Frontiers in behavioral neuroscience 8
Abstract: Evidence from developmental as well as neuroscientific studies suggest that finger counting activity plays an important role in the acquisition of numerical skills in children. It has been claimed that this skill helps in building motor-based representations of number that continue to influence number processing well into adulthood, facilitating the emergence of number concepts from sensorimotor experience through a bottom-up process. The act of counting also involves the acquisition and use of a verbal number system of which number words are the basic building blocks. Using a Cognitive Developmental Robotics paradigm we present results of a modeling experiment on whether finger counting and the association of number words (or tags) to fingers, could serve to bootstrap the representation of number in a cognitive robot, enabling it to perform basic numerical operations such as addition. The cognitive architecture of the robot is based on artificial neural networks, which enable the robot to learn both sensorimotor skills (finger counting) and linguistic skills (using number words). The results obtained in our experiments show that learning the number words in sequence along with finger configurations helps the fast building of the initial representation of number in the robot. Number knowledge, is instead, not as efficiently developed when number words are learned out of sequence without finger counting. Furthermore, the internal representations of the finger configurations themselves, developed by the robot as a result of the experiments, sustain the execution of basic arithmetic operations, something consistent with evidence coming from developmental research with children. The model and experiments demonstrate the importance of sensorimotor skill learning in robots for the acquisition of abstract knowledge such as numbers. (PsycINFO Database Record (c) 2016 APA, all rights reserved)
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(2014): Don't do it again! Directed forgetting of habits. In: Psychological science 25 (6), S. 1242-1248. DOI: 10.1177/0956797614526063
DOI: http://www.ncbi.nlm.nih.gov/pubmed/24714574 Abstract: Most daily routines are determined by habits. However, the experienced ease and automaticity of habit formation and execution come at a cost when habits that are no longer appropriate must be overcome. So far, proactive and reactive control strategies that prevent inappropriate habit execution either by preparation or "on the fly" have been identified. Here, we present evidence for a third, retroactive control strategy. In two experiments using the list method of directed forgetting, the accessibility of newly learned and practiced stimulus-response rules was significantly reduced when participants were cued to forget the rules rather than to remember them. The results thus show that directed forgetting, so far observed and investigated only for episodic memory traces, can also be applied to habits. The findings further emphasize the adaptive value of forgetting and can be taken as evidence of a retroactive strategy of habit control. zitiert von 12
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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 -
(2014): Making Sense of Culture. In: Annual Review of Sociology 40 (1), S. 1-30. DOI: 10.1146/annurev-soc-071913-043123
2013
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(2013) : Making a moral decision: A proposition for an integrated model of cognition, emotion, and social interaction.: The handbook of educational theories.: Charlotte, NC, US: IAP Information Age Publishing, S. 629-642
Abstract: This chapter will address the moral decision-making processes that lead to moral behaviors and actions in adolescents and children. An integrated model of cognition, emotions, and social interaction is proposed which may be applied to elucidate the developmental processes that contribute to moral judgment. The chapter will begin with a review of major theories of moral development, focusing on the cognitive-structural models of Piaget and Kohlberg, the affective model of Hoffman, and theories associated with socialization. The review will be followed by a proposed theoretical model that outlines the processes involved in making a moral decision. The model integrates cognitive, affective, and social interaction domains. Finally, the chapter will present empirical research to preliminarily validate and support the proposed model. (PsycINFO Database Record (c) 2017 APA, all rights reserved)
Keywords: age differences, Cognition, Decision Making, Emotions, entscheiden, MODELS, Moral, Moral Development, Morality, Review, social interaction, Theories 2012
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(2012): Between Homo Sociologicus and Homo Biologicus. The Reflexive Self in the Age of Social Neuroscience. In: Science & Education 21 (10), S. 1507-1526. DOI: 10.1007/s11191-012-9447-7
Abstract: The social sciences rely on assumptions of a unified self for their explanatory logics. Recent work in the new multidisciplinary field of social neuroscience challenges precisely this unproblematic character of the subjective self as basic, well-defined entity. If disciplinary self-insulation is deemed unacceptable, the philosophical challenge arises of systematically bringing together neurological, psychological, sociological, and anthropological dimensions of analysis in one framework such as dynamic systems theory; and of finding bridging concepts such as memory, social cognition, and cultural scripts that can facilitate the cross disciplinary study of the reflexive self. Relying on the systemic philosophy of science developed by Mario Bunge, this paper takes some steps in this direction.
Keywords: Cognition, cultural scripts, Culture, dynamic systems theory, History and Philosophy of Science, Kognitionswissenschaft/Social Sciences/Humanities, Konstruktion des Selbst, Mario Bunge, MEMORY, Modelle/Theorien, SCIENCE, PSYCHOLOGY, script, SELVES, Social Cognition, soziale Kognition, STRANGE BEDFELLOWS, subjective self