Alle Publikationen
- <<
- <
- 1
2017
-
(2017) : An intervening ethical governor for a robot mediator in patient-caregiver relationship: Implementation and evaluation: 2017 IEEE International Conference on Robotics and Automation (ICRA): Marina Bay Sands, Singapore: IEEE Robotics & Automation Society, S. 2936-2942
DOI: https://doi.org/10.1109/ICRA.2017.7989340 Abstract: A robot mediator can enhance the quality of patient care in a health care context. Patients with Parkinson’s disease can experience difficulties in precisely expressing their emotions due to the loss of control of their facial musculature, leading to their stigmatization by caregivers. To remedy this challenge, a robot mediator can be inserted into a patient-caregiver relationship. In this context, it is essential to handle the ethical issues of neglect to ensure human dignity. In an earlier paper [19], we proposed an intervening ethical governor (IEG) model, which enables a robot to ethically intervene in a situation where patients or caregivers go across accepted ethical boundaries. In this paper, we show how the IEG model can be implemented and applied in a real robotics system. In addition, by conducting interviews with the target population (adults 60 years of age or older), we evaluate the current intervention rules in the model, discuss potential improvements to the model, and consider uses of the model in real clinical contexts.
Keywords: Diseases, ethical aspects, ethical boundaries, ethical governor, facial musculature, Health Care, health care context, human dignity, ieee xplore, IEG model, intervening ethical governor model, Interviews, medical robotics, Medical services, Monitoring, Moral & Ethik, Parkinson disease, Patient Care, patient-caregiver relationship, real clinical contexts, real robotics system, robot mediator, Sensors, service robot, Stigmatization, Videos 2016
-
(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.
2013
-
(2013) : Personal service: A robot that greets people individually based on observed behavior patterns: 2013 8th ACM/IEEE International Conference on Human-Robot Interaction (HRI): Tokyo, Japan: IEEE, S. 129-130
DOI: https://doi.org/10.1109/HRI.2013.6483535 Abstract: We are developing an interactive service robot which provides personal greetings to customers, using a machine-learning approach based on observations of a customer’s appearance or behavior from on-board or environmental sensors. For each visit, several features are recorded, such as “time of day” or “number of people in group.” A set of classifiers trained by human coders compare the current features with the person’s individual history, to determine an appropriate feature for a robot to speak about. This system enables the robot to make context-appropriate comments such as “good morning, you’re here very early today.” We present the design of our system and an encouraging set of preliminary prediction results based on one month of data taken from real customers at a shopping mall.
Keywords: Accuracy, Angemessen(heit) (von Technik), context-appropriate comments, customer appearance, customer behavior, environmental sensors, Feature extraction, History, human coders, human-robot interaction, ieee xplore, interactive service robot, learning (artificial intelligence), long-term interaction, machine-learning approach, observed behavior patterns, personal greetings, personal service, Robot sensing systems, Sensors, service robot, shopping mall 2007
-
(2007) : Managing Context Rules in Mobile Devices: 4th International Forum on Applied Wearable Computing 2007: Tel Aviv, Israel: IEEE, S. 1-12. Online verfügbar unter https://ieeexplore.ieee.org/document/5760482/
Abstract: Abstract: An essential aspect of Mark Weiser's vision for ubiquitous computing is that computers become "invisible", demanding very little attention of their users. For this to happen, computers should be able to establish a shared understanding of the conceptual and social settings in which they operate, i.e., they should be context aware. This paper addresses one aspect of contextawareness, namely the management of context rules in mobile and wearable devices. Context rules are employed to predict higher-level human situations (activities), and to actuate desirable operations which are suitable to these situations. Because context rules are application specific, they are defined by application developers and users. So far, little consideration is given in the literature to take the habit (experience) of users into account to dynamically generate and manage context rules. In this paper we will provide a framework to associate decision events (signifying the actions performed by a user) with numerous context types which describe a situation of interest. From an aggregate of decision-context associations we generate context rules which enable mobile devices to proactively provide useful services.
2005
-
(2005): Predicting human interruptibility with sensors. In: ACM Transactions on Computer-Human Interaction 12 (1), S. 119-146. DOI: 10.1145/1057237.1057243
DOI: https://doi.org/10.1145/1057237.1057243 Abstract: A person seeking another person’s attention is normally able to quickly assess how interruptible the other person currently is. Such assessments allow behavior that we consider natural, socially appropriate, or simply polite. This is in sharp contrast to current computer and communication systems, which are largely unaware of the social situations surrounding their usage and the impact that their actions have on these situations. If systems could model human interruptibility, they could use this information to negotiate interruptions at appropriate times, thus improving human computer interaction. This article presents a series of studies that quantitatively demonstrate that simple sensors can support the construction of models that estimate human interruptibility as well as people do. These models can be constructed without using complex sensors, such as vision-based techniques, and therefore their use in everyday office environments is both practical and affordable. Although currently based on a demographically limited sample, our results indicate a substantial opportunity for future research to validate these results over larger groups of office workers. Our results also motivate the development of systems that use these models to negotiate interruptions at socially appropriate times. (PsycINFO Database Record (c) 2016 APA, all rights reserved)
- <<
- <
- 1