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5 result(s) for "Finkel, Marcel"
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Humanoid Robots – Artificial. Human-like. Credible? Empirical Comparisons of Source Credibility Attributions Between Humans, Humanoid Robots, and Non-human-like Devices
Source credibility is known as an important prerequisite to ensure effective communication (Pornpitakpan, 2004). Nowadays not only humans but also technological devices such as humanoid robots can communicate with people and can likewise be rated credible or not as reported by Fogg and Tseng (1999). While research related to the machine heuristic suggests that machines are rated more credible than humans (Sundar, 2008), an opposite effect in favor of humans’ information is supposed to occur when algorithmically produced information is wrong (Dietvorst, Simmons, and Massey, 2015). However, humanoid robots may be attributed more in line with humans because of their anthropomorphically embodied exterior compared to non-human-like technological devices. To examine these differences in credibility attributions a 3 (source-type) x 2 (information’s correctness) online experiment was conducted in which 338 participants were asked to either rate a human’s, humanoid robot’s, or non-human-like device’s credibility based on either correct or false communicated information. This between-subjects approach revealed that humans were rated more credible than social robots and smart speakers in terms of trustworthiness and goodwill. Additionally, results show that people’s attributions of theory of mind abilities were lower for robots and smart speakers on the one side and higher for humans on the other side and in part influence the attribution of credibility next to people’s reliance on technology, attributed anthropomorphism, and morality. Furthermore, no main or moderation effect of the information’s correctness was found. In sum, these insights offer hints for a human superiority effect and present relevant insights into the process of attributing credibility to humanoid robots.
Prioritized Research for the Prevention, Treatment, and Reversal of Chronic Disease: Recommendations From the Lifestyle Medicine Research Summit
Declining life expectancy and increasing all-cause mortality in the United States have been associated with unhealthy behaviors, socioecological factors, and preventable disease. A growing body of basic science, clinical research, and population health evidence points to the benefits of healthy behaviors, environments and policies to maintain health and prevent, treat, and reverse the root causes of common chronic diseases. Similarly, innovations in research methodologies, standards of evidence, emergence of unique study cohorts, and breakthroughs in data analytics and modeling create new possibilities for producing biomedical knowledge and clinical translation. To understand these advances and inform future directions research, The Lifestyle Medicine Research Summit was convened at the University of Pittsburgh on December 4–5, 2019. The Summit's goal was to review current status and define research priorities in the six core areas of lifestyle medicine: plant-predominant nutrition, physical activity, sleep, stress, addictive behaviors, and positive psychology/social connection. Forty invited subject matter experts (1) reviewed existing knowledge and gaps relating lifestyle behaviors to common chronic diseases, such as cardiovascular disease, diabetes, many cancers, inflammatory- and immune-related disorders and other conditions; and (2) discussed the potential for applying cutting-edge molecular, cellular, epigenetic and emerging science knowledge and computational methodologies, research designs, and study cohorts to accelerate clinical applications across all six domains of lifestyle medicine. Notably, federal health agencies, such as the Department of Defense and Veterans Administration have begun to adopt “whole-person health and performance” models that address these lifestyle and environmental root causes of chronic disease and associated morbidity, mortality, and cost. Recommendations strongly support leveraging emerging research methodologies, systems biology, and computational modeling in order to accelerate effective clinical and population solutions to improve health and reduce societal costs. New and alternative hierarchies of evidence are also be needed in order to assess the quality of evidence and develop evidence-based guidelines on lifestyle medicine. Children and underserved populations were identified as prioritized groups to study. The COVID-19 pandemic, which disproportionately impacts people with chronic diseases that are amenable to effective lifestyle medicine interventions, makes the Summit's findings and recommendations for future research particularly timely and relevant.
Quantum Sensing for High Energy Physics
Report of the first workshop to identify approaches and techniques in the domain of quantum sensing that can be utilized by future High Energy Physics applications to further the scientific goals of High Energy Physics.