Toward an Agent-Agnostic Transmission Model: Synthesizing Anthropocentric and Technocentric Paradigms in Communication

Technological and social evolutions have prompted operational, phenomenological, and ontological shifts in communication processes. These shifts, we argue, trigger the need to regard human and machine roles in communication processes in a more egalitarian fashion. Integrating anthropocentric and technocentric perspectives on communication, we propose an agent-agnostic framework for human-machine communication. This framework rejects exclusive assignment of communicative roles (sender, message, channel, receiver) to traditionally held agents and instead focuses on evaluating agents according to their functions as a means for considering what roles are held in communication processes. As a first step in advancing this agent-agnostic perspective, this theoretical paper offers three potential criteria that both humans and machines could satisfy: agency, interactivity, and influence. Future research should extend our agent-agnostic framework to ensure that communication theory will be prepared to deal with an ostensibly machine-inclusive future

The challenges of first-and second-order belief reasoning in explainable human-robot interaction

Current approaches to implement eXplainable Autonomous Robots (XAR) are dominantly based on Reinforcement Learning (RL), which are suitable for modelling and correcting people’s first-order mental state attributions to robots. Our recent findings show that people also rely on attributing second-order beliefs (i.e., beliefs about beliefs) to robots to interpret their behavior. However, robots arguably form and act primarily on first-order beliefs and desires (about things in the environment) and do not have a functional “theory of mind”. Moreover, RL models may be incapable to appropriately address second-order belief attribution errors. This paper aims to open a discussion of what our recent findings on second-order mental state attribution to robots imply for current approaches to XAR

Who Wants to Grant Robots Rights?

The robot rights debate has thus far proceeded without any reliable data concerning the public opinion about robots and the rights they should have. We have administered an online survey (n = 439) that investigates layman’s attitudes toward granting particular rights to robots. Furthermore, we have asked them the reasons for their willingness to grant them those rights. Finally, we have administered general perceptions of robots regarding appearance, capacities, and traits. Results show that rights can be divided in sociopolitical and robot dimensions. Reasons can be distinguished along cognition and compassion dimensions. People generally have a positive view about robot interaction capacities. We found that people are more willing to grant basic robot rights such as access to energy and the right to update to robots than sociopolitical rights such as voting rights and the right to own property. Attitudes toward granting rights to robots depend on the cognitive and affective capacities people believe robots possess or will possess in the future. Our results suggest that the robot rights debate stands to benefit greatly from a common understanding of the capacity potentials of future robots

Mental State Attribution to Robots: A Systematic Review of Conceptions, Methods, and Findings

The topic of mental state attribution to robots has been approached by researchers from a variety of disciplines, including psychology, neuroscience, computer science, and philosophy. As a consequence, the empirical studies that have been conducted so far exhibit considerable diversity in terms of how the phenomenon is described and how it is approached from a theoretical and methodological standpoint. This literature review addresses the need for a shared scientific understanding of mental state attribution to robots by systematically and comprehensively collating conceptions, methods, and findings from 155 empirical studies across multiple disciplines. The findings of the review include that: (1) the terminology used to describe mental state attribution to robots is diverse but largely homogenous in usage; (2) the tendency to attribute mental states to robots is determined by factors such as the age and motivation of the human as well as the behavior, appearance, and identity of the robot; (3) there is a computer < robot < human pattern in the tendency to attribute mental states that appears to be moderated by the presence of socially interactive behavior; (4) there are conflicting findings in the empirical literature that stem from different sources of evidence, including self-report and non-verbal behavioral or neurological data. The review contributes toward more cumulative research on the topic and opens up for a transdisciplinary discussion about the nature of the phenomenon and what types of research methods are appropriate for investigation

Co-designing a social robot for child health care

Social robots provide new opportunities to support general child healthcare programs. However, it is still unclear how social robots could be used in this context and how corresponding behaviours should be designed. To ensure satisfying implementations of such new technological solutions, it is essential to include the end-users in the designing process. We have conducted a co-design study at two primary schools based on three complementary, creative methods: Draw-write-and-tell and/or story-writing-and-telling, Theatre play, and Robot avatar programming. A total of 46 children aged 7–12 years old participated in four robot co-design workshops. The drawings, stories and theatre plays were analysed, resulting in evaluations of 10 scenarios as well as 21 new scenarios and 7 main user requirements for social robots providing mental support in general child healthcare. Evaluation of the activities highlight their stimulation of out-of-the-box thinking and the development of creative solutions (i.e. drawings/stories/theatre plays resulted in robot designs, scenarios and requirements), while children's reflections show them being enjoyable for participation. The inputs gathered during these co-design workshops will greatly influence future work on the design and application of social robots in the child healthcare domain

SYMPHONY consortium:Orchestrating personalized treatment for patients with bleeding disorders

Background Treatment choices for individual patients with an inborn bleeding disorder are increasingly challenging due to increasing options and rising costs for society. We have initiated an integrated interdisciplinary national research program. Objectives The SYMPHONY consortium strives to orchestrate personalized treatment in patients with an inborn bleeding disorder, by unraveling the mechanisms behind interindividual variations of bleeding phenotype. Patients The SYMPHONY consortium will investigate patients with an inborn bleeding disorder, both diagnosed and not yet diagnosed. Results Research questions are categorized under the themes: (1) diagnosis, (2) treatment, and (3) fundamental research, and consist of work packages addressing specific domains. Importantly, collaborations between patients and talented researchers from different areas of expertise promise to augment the impact of the SYMPHONY consortium, leading to unique interactions and intellectual property. Conclusions SYMPHONY will perform research on all aspects of care, treatment individualization in patients with inborn bleeding disorders, as well as diagnostic innovations and results of molecular genetics and cellular model technology with regard to the hemostatic process. We believe that these research investments will lead to health-care innovations with long-term clinical and societal impact. This consortium has been made possible by a governmental, competitive grant from the Netherlands Organization for Scientific Research (NWO) within the framework of the NWA-ORC Call grant agreement NWA.1160.18.038

Is (poly-) substance use associated with impaired inhibitory control? A mega-analysis controlling for confounders.

Many studies have reported that heavy substance use is associated with impaired response inhibition. Studies typically focused on associations with a single substance, while polysubstance use is common. Further, most studies compared heavy users with light/non-users, though substance use occurs along a continuum. The current mega-analysis accounted for these issues by aggregating individual data from 43 studies (3610 adult participants) that used the Go/No-Go (GNG) or Stop-signal task (SST) to assess inhibition among mostly "recreational" substance users (i.e., the rate of substance use disorders was low). Main and interaction effects of substance use, demographics, and task-characteristics were entered in a linear mixed model. Contrary to many studies and reviews in the field, we found that only lifetime cannabis use was associated with impaired response inhibition in the SST. An interaction effect was also observed: the relationship between tobacco use and response inhibition (in the SST) differed between cannabis users and non-users, with a negative association between tobacco use and inhibition in the cannabis non-users. In addition, participants' age, education level, and some task characteristics influenced inhibition outcomes. Overall, we found limited support for impaired inhibition among substance users when controlling for demographics and task-characteristics