Alle Publikationen
2018
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(2018): People are averse to machines making moral decisions. In: Cognition 181, S. 21-34. DOI: 10.1016/j.cognition.2018.08.003
DOI: https://doi.org/10.1016/j.cognition.2018.08.003 Abstract: Do people want autonomous machines making moral decisions? Nine studies suggest that that the answer is ‘no’—in part because machines lack a complete mind. Studies 1–6 find that people are averse to machines making morally-relevant driving, legal, medical, and military decisions, and that this aversion is mediated by the perception that machines can neither fully think nor feel. Studies 5–6 find that this aversion exists even when moral decisions have positive outcomes. Studies 7–9 briefly investigate three potential routes to increasing the acceptability of machine moral decision-making: limiting the machine to an advisory role (Study 7), increasing machines’ perceived experience (Study 8), and increasing machines’ perceived expertise (Study 9). Although some of these routes show promise, the aversion to machine moral decision-making is difficult to eliminate. This aversion may prove challenging for the integration of autonomous technology in moral domains including medicine, the law, the military, and self-driving vehicles. (PsycINFO Database Record (c) 2019 APA, all rights reserved)
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(2018): When different “codes” meet. Communication styles and conflict in intercultural academic meetings. In: Language & Communication 61, S. 1-14. DOI: 10.1016/j.langcom.2017.10.001
Abstract: This study focuses on conflict situations in bilingual academic meetings to investigate the communication styles used by Chinese and American university faculty. The ethnographic participant observation used as the main method was cross-checked with post-meeting interview data. The findings revealed that, due to the conflicting priorities in meeting protocol and behaviors in Taiwanese and American cultures, tension is experienced by faculty members of both cultures. What it means to have a meeting and how members address various issues does vary from culture to culture. It is suggested that conflict situations be ameliorated by more cross-cultural understanding of meeting codes, especially by those in leadership positions.
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(2018) : ETHICAL FRAMEWORK FOR MACHINE LEARNING: 2018 ITU Kaleidoscope: Machine Learning for a 5G Future (ITU K): Santa Fe, Argentina: IEEE, S. 1-8
DOI: https://doi.org/10.23919/ITU-WT.2018.8597767 Abstract: Artificial Intelligence (AI) with its core subset of Machine Learning (ML) is rapidly transforming life experiences as humans begin to grow more dependent on these ‘smart machines’ for their needs - ranging from routine mundane chores to critical personal decisions. However, these transformative technologies are at the same time proving unpredictable too as has been reported worldwide in certain cases. Therefore, several studies/reports, such as COMEST report on Robotics ethics (UNESCO, 2017) point to an obvious need for inculcating more ethical behavior in machines. The present study aims to look at the role and interplay of ML (the hard sciences) and Ethics (the soft sciences) to resolve such predicaments that are inadvertently manifested by machines not constrained or controlled by human expectations. Based on focused review of literature of both domains-ML and Ethics, the proposed paper attempts to first build on the need for introduction of an ethical algorithm in the domain of machine learning and then endeavors to provide a conceptual framework to resolve the ethical dilemmas.
Keywords: Artificial intelligence, Artificial intelligence/machine learning, Big Data, COMEST report, critical personal decisions, Decision Making, design approach, domains-ML, emotional quotient, ethical algorithm, ethical aspects, ethical behavior, ethical dilemmas, ethical framework, Ethics, hard sciences, human expectations, ieee xplore, learning (artificial intelligence), machine learning, Machine learning algorithms, Moral & Ethik, Prediction algorithms, robotic ethics, Robots, routine mundane chores, smart machines, soft sciences, spiritual quotient, transformative technologies -
(2018) : Decision-Making Prediction for Human-Robot Engagement between Pedestrian and Robot Receptionist In: Cabibihan, John-Joh: IEEE RO-MAN 2018: The 27th IEEE International Symposium on Robot and Human Interactive Communication: 2018 27th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN): Nanjing: 8/27/2018 - 8/31/2018. Ro-Man; Institute of Electrical and Electronics Engineers; IEEE Robotics and Automation Society; IEEE Ro-Man; IEEE International Symposium on Robot and Human Interactive Communication: Piscataway, NJ: IEEE, S. 208-215
Abstract: Social robots have been providing a number of customer services lately. For example, they can take the place of people as receptionists. When people interact they predict each others decision-making from the others actions and take suitable actions for the sake of the other. However, taking such actions is difficult for modern social robots. Therefore, our initial aim is to solve the problem of how to predict decision-making in human-robot engagement. Choosing a reception system as a case study to approach this goal, we created a new model to predict who will use the system. The model contains a state transition function based on observation studies. We evaluated the model though a controlled experiment and a simulation experiment, using field data on prediction performance and mental effect. The experiment results lead us to believe that the model can predict the decisions of others sufficiently well. We also found that a pedestrian who will not talk with a robot receptionist suffers a negative emotion when the pedestrian is greeted by a robot, but a method we propose prevents this. We suggest that the word suitable is related to negative emotion, a part of usability. By using our model in the future we will attempt to find a method that will enable a robot to learn suitable actions by itself.
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(2018) : Care Robot Transparency Isn’t Enough for Trust: 2018 IEEE Region Ten Symposium (Tensymp): Sydney, Australia: IEEE, S. 293-297
DOI: https://doi.org/10.1109/TENCONSpring.2018.8692047 Abstract: A recent study featuring a new kind of care robot indicated that participants expect a robot’s ethical decision-making to be transparent to develop trust, even though the same type of ‘inspection of thoughts’ isn’t expected of a human carer. At first glance, this might suggest that robot transparency mechanisms are required for users to develop trust in robot-made ethical decisions. But the participants were found to desire transparency only when they didn’t know the specifics of a human-robot social interaction. Humans trust others without observing their thoughts, which implies other means of determining trustworthiness. The study reported here suggests that the method is social interaction and observation, signifying that trust is a social construct. Moreover, that ‘social determinants of trust’ are the transparent elements. This socially determined behaviour draws on notions of virtue ethics. If a caregiver (nurse or robot) consistently provides good, ethical care, then patients can trust that caregiver to do so often. The same social determinants may apply to care robots and thus it ought to be possible to trust them without the ability to see their thoughts. This study suggests why transparency mechanisms may not be effective in helping to develop trust in care robot ethical decision-making. It suggests that roboticists need to build sociable elements into care robots to help patients to develop patient trust in the care robot’s ethical decision-making.
Keywords: care robot ethical decision-making, care robot transparency, Decision Making, ethical aspects, healthcare robotics, Human robot interaction, human-robot interaction, human-robot social interaction, ieee xplore, machine transparency, medical robotics, Moral & Ethik, Patient Care, patient trust, Robot Ethics, robot-made ethical decisions, socially determined behaviour -
(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 -
(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) : Beyond Moral Dilemmas: Exploring the Ethical Landscape in HRI: 2017 12th ACM/IEEE International Conference on Human-Robot Interaction (HRI: Vienna, Austria: Association for Computing Machinery, S. 445-452
Abstract: HRI research has yielded intriguing empirical results connected to ethics and how we act in social contexts with robots, even though much of this work has focused on task-based, one-on-one interaction. In this paper, we point to the need to investigate a wider range of ethically relevant dynamics that interaction with robots carries with it - individually and in groups, with a single robot or more. We specifically examine three areas: 1) the primacy and implicit dynamics of bodily perception, 2) the competing interests at work in a single robot-human interaction, and 3) the social intricacy of multiple agents - robots and humans - communicating and making decisions. While these areas are not exhaustive by any means, we find they yield concrete directions for how HRI can contribute to a widening, intensifying set of ethical debates with critical empirical insight, starting to explore more of the ethical landscape in HRI.
Keywords: critical empirical insight, Decision Making, ethical aspects, ethical debates, ethical landscape, ethically relevant dynamics, Ethics, Ethics in HRI, HRI research, human-robot interaction, ieee xplore, implicit dynamics, Law, Moral & Ethik, moral dilemmas, multiple agents, robot dynamics, Robot sensing systems, robot-human interaction, social contexts, social intricacy, Task Analysis -
(2017): Ethics in Robotics Research: CERNA Mission and Context. In: IEEE Robotics Automation Magazine 24 (3), S. 139-145. DOI: 10.1109/MRA.2016.2611586
DOI: https://doi.org/10.1109/MRA.2016.2611586 Abstract: This article summarizes the recommendations concerning robotics as issued by the Commission for the Ethics of Research in Information Sciences and Technologies (CERNA), the French advisory commission for the ethics of information and communication technology (ICT) research. Robotics has numerous applications in which its role can be overwhelming and may lead to unexpected consequences. In this rapidly evolving technological environment, CERNA does not set novel ethical standards but seeks to make ethical deliberation inseparable from scientific activity. Additionally, it provides tools and guidance for researchers and research institutions.
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(2017): TERESA: Socially intelligent robot as window to the world. In: Cyberpsychology, Behavior, and Social Networking 20 (5). DOI: 10.1089/cyber.2017.29072.ceu
DOI: https://doi.org/10.1089/cyber.2017.29072.ceu Abstract: This column aims to describe the characteristics of current cyberpsychology research in Europe. In particular, CyberEurope aims at describing the leading research groups and projects running on the other side of the Ocean. The researchers have developed methods that enable the robots to perform social functions automatically, so that the human controller never needs to make decisions about how the robot should move around or what postures it should adopt. TERESA robots are able to navigate semi-autonomously, maintaining face-to-face contact during conversations, and displaying appropriate body-pose behavior—in a similar way to human beings. (PsycINFO Database Record (c) 2017 APA, all rights reserved)
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(2017): Locally noisy autonomous agents improve global human coordination in network experiments. In: Nature 545 (7654), S. 370-374. DOI: 10.1038/nature22332
DOI: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5912653 Abstract: Coordination in groups faces a sub-optimization problem and theory suggests that some randomness may help to achieve global optima. Here we performed experiments involving a networked colour coordination game in which groups of humans interacted with autonomous software agents (known as bots). Subjects (n = 4,000) were embedded in networks (n = 230) of 20 nodes, to which we sometimes added 3 bots. The bots were programmed with varying levels of behavioural randomness and different geodesic locations. We show that bots acting with small levels of random noise and placed in central locations meaningfully improve the collective performance of human groups, accelerating the median solution time by 55.6%. This is especially the case when the coordination problem is hard. Behavioural randomness worked not only by making the task of humans to whom the bots were connected easier, but also by affecting the gameplay of the humans among themselves and hence creating further cascades of benefit in global coordination in these heterogeneous systems.
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(2017): Encouraging Prosocial Decisions. The Role of Fairness Salience and Uncertainty. In: Journal of Behavioral Decision Making 30 (2), S. 502-515. DOI: 10.1002/bdm.1970
DOI: https://doi.org/10.1002/bdm.1970 Abstract: Although the decision to engage in prosocial behavior has received research attention, the literature offers a limited understanding of fairness and uncertainty as antecedents. We propose that one can encourage prosocial decision making simply by invoking the notion of fairness because of its effects on the perceived trustworthiness of the invoking party. We also elucidate the complex role of uncertainty in prosocial decisions in that it has a negative effect while also serving to strengthen the positive effect of fairness salience. Our ideas are tested in two prosocial decision contexts, including participative pricing (i.e., 'pay what you want') and charitable giving. Data from an archival study of a naturally occurring event and two controlled experiments offer support for our arguments. (PsycINFO Database Record (c) 2017 APA, all rights reserved)
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(2017): Increased social distance makes people more risk-neutral. In: The Journal of Social Psychology 157 (4), S. 502-512. DOI: 10.1080/00224545.2016.1242471
DOI: http://www.ncbi.nlm.nih.gov/pubmed/27685243 Abstract: Individuals are consistently observed to be risk-averse over gains and risk-seeking over losses. This study examined whether increased social distance would change these behavioral patterns. To test our hypothesis, social distance was manipulated by asking the participants to make decisions either for themselves or for another person (Experiment 1), either for a known person or for an unknown person (Experiment 2), and either for a close friend or for a distant friend (Experiment 3). The results of Experiments 1 and 3 showed that increased social distance made people more risk-neutral, and such an effect was stronger in the gain domain than in the loss domain. However, the effect of social distance was not observed in Experiment 2. These findings suggest that risk preferences are influenced by the social distance between decision makers and beneficiaries. zitiert von 4
Keywords: Adult, Decision Making, distance, Female, Humans, Male, Risk-Taking, Social Distance, Sozialpsychologie, Verhaltensforschung, Young Adult -
(2017): Harm to self outweighs benefit to others in moral decision making. In: Proceedings of the National Academy of Sciences of the United States of America 114 (30), S. 7963-7968. DOI: 10.1073/pnas.1706693114
DOI: https://doi.org/10.1073/pnas.1706693114 Abstract: How we make decisions that have direct consequences for ourselves and others forms the moral foundation of our society. Whereas economic theory contends that humans aim at maximizing their own gains, recent seminal psychological work suggests that our behavior is instead hyperaltruistic: We are more willing to sacrifice gains to spare others from harm than to spare ourselves from harm. To investigate how such egoistic and hyperaltruistic tendencies influence moral decision making, we investigated trade-off decisions combining monetary rewards and painful electric shocks, administered to the participants themselves or an anonymous other. Whereas we replicated the notion of hyperaltruism (i.e., the willingness to forego reward to spare others from harm), we observed strongly egoistic tendencies in participants' unwillingness to harm themselves for others' benefit. The moral principle guiding intersubject trade-off decision making observed in our study is best described as egoistically biased altruism, with important implications for our understanding of economic and social interactions in our society.
Keywords: Altruism, Death and Dying, Decision Making, entscheiden, Gesellschaft, Moral, Social Cognition 2016
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(2016): Outline of a sensory-motor perspective on intrinsically moral agents. In: Adaptive Behavior 24 (5), S. 306-319. DOI: 10.1177/1059712316667203
DOI: https://doi.org/10.1177/1059712316667203 Abstract: We propose that moral behaviour of artificial agents could (and should) be intrinsically grounded in their own sensory-motor experiences. Such an ability depends critically on seven types of competencies. First, intrinsic morality should be grounded in the internal values of the robot arising from its physiology and embodiment. Second, the moral principles of robots should develop through their interactions with the environment and with other agents. Third, we claim that the dynamics of moral (or social) emotions closely follows that of other non-social emotions used in valuation and decision making. Fourth, we explain how moral emotions can be learned from the observation of others. Fifth, we argue that to assess social interaction, a robot should be able to learn about and understand responsibility and causation. Sixth, we explain how mechanisms that can learn the consequences of actions are necessary for a robot to make moral decisions. Seventh, we describe how the moral evaluation mechanisms outlined can be extended to situations where a robot should understand the goals of others. Finally, we argue that these competencies lay the foundation for robots that can feel guilt, shame and pride, that have compassion and that know how to assign responsibility and blame. (PsycINFO Database Record (c) 2017 APA, all rights reserved)
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(2016): An ethics evaluation tool for automating ethical decision-making in robots and self-driving cars. In: Applied Artificial Intelligence 30 (8), S. 787-809. DOI: 10.1080/08839514.2016.1229919
DOI: https://doi.org/10.1080/08839514.2016.1229919 Abstract: As we march down the road of automation in robotics and artificial intelligence, we will need to automate an increasing amount of ethical decision-making in order for our devices to operate independently from us. But automating ethical decision- making raises novel questions for engineers and designers, who will have to make decisions about how to accomplish that task. For example, some ethical decision-making involves hard moral cases, which in turn requires user input if we are to respect established norms surrounding autonomy and informed consent. The author considers this and other ethical considerations that accompany the automation of ethical decision-making. He proposes some general ethical requirements that should be taken into account in the design room, and sketches a design tool that can be integrated into the design process to help engineers, designers, ethicists, and policymakers decide how best to automate certain forms of ethical decision-making. (PsycINFO Database Record (c) 2019 APA, all rights reserved)
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(2016): Third-party punishment. Altruistic and anti-social behaviours in in-group and out-group settings. In: Journal of Cognitive Psychology 28 (4), S. 486-495. DOI: 10.1080/20445911.2016.1138961
Abstract: Explored the decision-making process involved in third-party punishment (TPP) within an economic frame, using the TPP game. Specifically, altruistic punishment (i.e., the behavior of spending one's own money, with no personal gain, to punish those who violate the norms of cooperation) was investigated. This behavior was analyzed in an ingroup and outgroup game setting to compare how individuals behave with members of their own group (ingroup) and with members of another group (outgroup). In particular, groups were defined on a real nationality basis (Chinese or Italian). Results showed altruistic punishment behavior in both experimental groups, and this tendency emerged as more prominent when faced with unfair play towards a member of one's own group. Furthermore, both groups exhibited a propensity for antisocial punishment behavior: Many participants spent small amounts of money to punish fair behavior, regardless of national group membership. zitiert von 5
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(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): Higher incentives can impair performance. Neural evidence on reinforcement and rationality. In: Social cognitive and affective neuroscience 10 (11), S. 1477-1483
Abstract: Examined the assumption that monetary incentives always result in increased performance. Human decision makers frequently focus on past performance, a form of reinforcement learning occasionally at odds with rational decision making. An incentivized belief-updating task from economics was employed to investigate this conflict through measurements of neural correlates of reward processing. 85 healthy college students (aged 19-29 years) participated in 2 experiments while electroencephalography (EEG) was recorded. Results showed that higher incentives fail to improve performance when immediate feedback on decision outcomes is provided. Subsequent analysis of the feedback-related negativity, an early event-related potential following feedback, revealed the mechanism behind this paradoxical effect. As incentives increase, the win/lose feedback becomes more prominent, leading to an increased reliance on reinforcement and more errors. This mechanism is relevant for economic decision making and the debate on performance-based payment. zitiert von 15
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(2015): Has the World Changed?. My Neighbor Might Know: Effects of Social Context on Routine Deviation. In: Journal of Behavioral Decision Making 28 (1), S. 50-66. DOI: 10.1002/bdm.1828
Abstract: Investigated the effects of social context on deviations from routines. 94 students (mean age 21 years) were asked to repeatedly choose among four gambles that were represented by four decks of cards. After the routine acquisition phase, unbeknownst to the participants, the underlying payoff structure of the game was altered so that the routine choice no longer yielded a profit. In addition, a confederate served as a behavioral model who made the normative choice most of the time in the acquisition phase, the test phase, in both phases, or in no phase at all (baseline). Results showed that participants were influenced by prior success of a routine; however, they were not immune to new counterevidence. The new evidence had to compensate prior knowledge before individuals decided to abandon their routine. Participants were most likely to adapt if the confederate served as a behavioral model in both the acquisition and test phases. It is concluded that participants could detect a lasting change in the environment and trustworthy behavioral models helped participants overcome a previously adaptive routine. zitiert von 5
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(2015) : Psychological aspects of technology interacting with humans In: Sundar, S. S.: The handbook of the psychology of communication technology: Hoboken, NJ: Wiley-Blackwell (Handbooks in communication and media), S. 176-201
DOI: https://doi.org/10.1002/9781118426456.ch8 Abstract: This chapter describes a large number of sometimes complex studies that in unison have led to the production of a reliable, serviceable sometimes stern but fair care robot. The initial summary of studies is necessary to understand what the smart, sensitive, creative, and moral humanoid that interacts with its human user is actually based upon: Its core is driven by the model called Perceiving and Experiencing Fictional Characters (PEFiC), the interactive variant of which (I-PEFiC) received a module to make affective decisions (ADM). An integration of I-PEFICADM with prevailing emotion models led to the Silicon Coppélia model. Silicon Coppélia, then, was extended by a system for moral reasoning (Moral Coppélia) and is now in the process to become creative (ACASIA) and have an understanding of reality in contrast to fiction (Epistemics of the Virtual). (PsycINFO Database Record (c) 2019 APA, all rights reserved)
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(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): Trust me (or not). Regret and disappointment in experimental economic games. In: Decision 2 (2), S. 118-126. DOI: 10.1037/dec0000025
DOI: https://doi.org/10.1037/dec0000025 Abstract: Emotional states exert an influence on trust and the reciprocation of trust. The current research found that regret and disappointment, though both negatively valenced, have distinct effects on trust (and trustworthiness). Three experiments showed that regret decreased trust and trustworthiness, whereas disappointment increased them. Regret elicited both lower initial transfers and returns in a trust game. Conversely, disappointment gave rise to both higher initial transfers and returns in the same game. The implications of our results are discussed. The findings once again demonstrate that emotions play a crucial role on decision-making. (PsycINFO Database Record (c) 2016 APA, all rights reserved) zitiert von 19
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(2015): Reconsidering Respect for Persons in a Globalizing World. In: Developing world bioethics 15 (2), S. 98-106. DOI: 10.1111/dewb.12045
DOI: http://www.ncbi.nlm.nih.gov/pubmed/24720355 Abstract: Contemporary clinical ethics was founded on principlism, and the four principles: respect for autonomy, nonmaleficence, beneficence and justice, remain dominant in medical ethics discourse and practice. These principles are held to be expansive enough to provide the basis for the ethical practice of medicine across cultures. Although principlism remains subject to critique and revision, the four-principle model continues to be taught and applied across the world. As the practice of medicine globalizes, it remains critical to examine the extent to which both the four-principle framework, and individual principles among the four, suffice patients and practitioners in different social and cultural contexts. Using the four-principle model we analyze two accounts of surrogate decision making - one from the developed and one from the developing world - in which the clinician undertakes medical decision-making with apparently little input from the patient and/or family. The purpose of this analysis is to highlight challenges in assessing ethical behaviour according to the principlist model. We next describe cultural expectations and mores that inform both patient and clinician behaviors in these scenarios in order to argue that the principle of respect for persons informed by culture-specific ideas of personhood may offer an improved ethical construct for analyzing and guiding medical practice in a globalized and plural world.
Keywords: Beneficence, Bewertung von sozialem Verhalten (/sozialer Angemessenheit), Clinical Decision-Making/ethics, Cultural Characteristics, culture specific, Decision Making, Developed Countries, Developing Countries, Ethical Analysis, Ethics, Medical, Family/ethnology/psychology, Humans, Internationality, Interviews as Topic, Islam, kulturspezifisch, Medizin, Observablen/Kriterien für sozial angemessenes Verhalten und dessen Bewertung, Pakistan, Personal Autonomy, Personhood, Physician-Patient Relations/ethics, Principle-Based Ethics, respect, Respekt, Transcultural Nursing, United States -
(2015): Intra and inter-individual differences in social intelligence of Portuguese students. In: Paidéia 25 (61), S. 153-161. DOI: 10.1590/1982-43272561201503
DOI: https://doi.org/10.1590/1982-43272561201503 Abstract: Social intelligence is a favorable condition for career decision-making and development. The social intelligence indices of Portuguese students in school years prior to a career transition are characterized and intra and interindividual differences are analyzed. Participants were 1095 students (552, 50.4% women) with a mean age of 14.78 years (SD = 1.86), in the 8th (542, 49.5%), 10th (295, 26.9%) and 11th (258, 23.6%) grades. The Cognitive Test of Social Intelligence (PCIS) was administered at two moments, six months apart. Results indicate that the 8th grade obtained higher average scores in Problem Solving, Motivation and Self-confidence (time 1), while the 10th grade obtained better results in Problem Solving, Motivation and Familiarity (time 2). Between the assessment moments, all school years register an increase in Problem Solving and Self-confidence in social situations. These results constitute favorable psychological conditions for the promotion of ethical questioning in career guidance interventions. (PsycINFO Database Record (c) 2016 APA, all rights reserved)