The Essence of Ethical Reasoning in Robot-Emotion Processing

Abstract

As social robots become more and more intelligent and autonomous in operation, it is extremely important to ensure that such robots act in socially acceptable manner. More specifically, if such an autonomous robot is capable of generating and expressing emotions of its own, it should also have an ability to reason if it is ethical to exhibit a particular emotional state in response to a surrounding event. Most existing computational models of emotion for social robots have focused on achieving a certain level of believability of the emotions expressed. We argue that believability of a robot's emotions, although crucially necessary, is not a sufficient quality to elicit socially acceptable emotions. Thus, we stress on the need of higher level of cognition in emotion processing mechanism which empowers social robots with an ability to decide if it is socially appropriate to express a particular emotion in a given context or it is better to inhibit such an experience. In this paper, we present the detailed mathematical explanation of the ethical reasoning mechanism in our computational model, EEGS, that helps a social robot to reach to the most socially acceptable emotional state when more than one emotions are elicited by an event. Experimental results show that ethical reasoning

Identifying key ethical debates for autonomous robots in agri-food: a research agenda

“…As AI robots are often intended to interact with humans in a variety of contexts, relationships of robots with human beings or animals are an important theme in the literature [11,14,58], Sparrow et al [74]. Some of the literature focuses on the acceptance of autonomous robots that are used for various purposes (military, care, transportation etc.…”

Trust in and Ethical Design of Carebots: The Case for Ethics of Care

“…As Wallach and Allen put it, it is the "dynamic interplay" between the analysis of project structure and testing of system designed to reach goals. 55 The design process may cover aspects such as the physical form the robot takes, the way it communicates, the contents of the communication, the actions or practices it is capable of carrying out and the contexts in which they operate. To properly design carebots, the designer will have to be aware of the contexts in which the carebots will be utilised in the healthcare sector, the challenges arising from the use of robots in caregiving, and also their potential impact (in physical, mental and social terms) on humans (both care recipients and caregivers) in those specific contexts.…”

“…In this regard, artificial agents are generally more predictable than humans and hence more trustworthy. 59 Whether the technology performs its role and functions for which it is designed (such as the roles of caring for its users' health and the enhancement of human-robot interactions for users' mental well-being through, for example, displaying "socially acceptable" emotions) 60 will be important for engendering 55 Wallach and Allen [86, p. 81]. 56 Sparrow and Sparrow [68].…”

“…59 Grodzinsky et al [32, p. 26]. 60 Ojha et al [55] on the development of the Ethical Emotion Generation System (EEGS) based on data structure of emotions represented in the form of (Name, Valence, Degree, Threshold, Intensity, Decay Time), where Name denotes the name for the type of the emotion, Valence specifies whether the emotion is positive or negative, Degree represents the extent of the positivity and negativity of the emotion, Threshold represents the minimum intensity required to trigger the emotion, Intensity represents the strength of the emotional experience and Decay Time denotes the time required to drop the emotion intensity back to 0. trust in the technology. Finally, the ethical design of carebots can and should take account of potential risks arising from humans' automation bias that result in overtrust in robots.…”

“…Carebots should be designed to have the competence to carry out their tasks to fetch items for care recipients, aid their transfer from bed to wheelchair and be equipped with adequate machine learning to interact effectively with the care recipients. This may also include the development of acceptable AI models of emotions displayed by the robots in their interactions with the users [55].…”