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In a novel experimental setting, we augmented a variation of traditional compassion meditation with our custom-built VR environment for multiple concurrent users. The presence of another user’s avatar in shared virtual space supports social interactions and provides an active target for evoked compassion. The system incorporates respiration and brainwave-based biofeedback to enable closed-loop interaction of users based on their shared physiological state. Specifically, we enhanced interoception and the deep empathetic processes involved in compassion meditation with real-time visualizations of: breathing rate, level of approach motivation assessed from EEG frontal asymmetry, and dyadic synchrony of those signals between two users. We manipulated these interventions across eight separate conditions (dyadic or solo meditation; brainwave, breathing, both or no biofeedback) in an experiment with 39 dyads (N=8), observing the effect of conditions on self-reported experience and physiological synchrony. We found that each different shared biofeedback type increased users’ self-reported empathy and social presence, compared to no-biofeedback or solo conditions. Our study illustrates how dyadic synchrony biofeedback can expand the possibilities of biofeedback in affective computing and VR solutions for health and wellness.

The ongoing conversation on AI ethics and politics is in full swing and has spread to the general public. Rather than contributing by engaging with the issues and views discussed, we want to step back and comment on the widening conversation itself. We consider evolved human cognitive tendencies and biases, and how they frame and hinder the conversation on AI ethics. Primarily, we describe our innate human capacities known as folk theories and how we apply them to phenomena of different implicit categories. Through examples and empirical findings, we show that such tendencies specifically affect the key issues discussed in AI ethics. The central claim is that much of our mostly opaque intuitive thinking has not evolved to match the nature of AI, and this causes problems in democratizing AI ethics and politics. Developing awareness of how our intuitive thinking affects our more explicit views will add to the quality of the conversation.

A Correction to this article was published on 25 March 2021, DOI: 10.1007/s12369-020-00738-6. Artificial intelligence and robotics are rapidly advancing. Humans are increasingly often affected by autonomous machines making choices with moral repercussions. At the same time, classical research in robotics shows that people are adverse to robots that appear eerily human – a phenomenon commonly referred to as the uncanny valley effect. Yet, little is known about how machines’ appearances influence how human evaluate their moral choices. Here we integrate the uncanny valley effect into moral psychology. In two experiments we test whether humans evaluate identical moral choices made by robots differently depending on the robots’ appearance. Participants evaluated either deontological (“rule based”) or utilitarian (“consequence based”) moral decisions made by different robots. The results provide first indication that people evaluate moral choices by robots that resemble humans as less moral compared to the same moral choices made by humans or non-human robots: a moral uncanny valley effect. We discuss the implications of our findings for moral psychology, social robotics and AI-safety policy.

Traumatic brain injury (TBI) is characterized by a complex pattern of abnormalities in resting-state functional connectivity (rsFC) and network dysfunction, which can potentially be ameliorated by rehabilitation. In our previous randomized controlled trial, we found that a 3-month neurological music therapy intervention enhanced executive function (EF) and increased grey matter volume in the right inferior frontal gyrus (IFG) in patients with moderate-to-severe TBI (N=40). Extending this study, we performed longitudinal rsFC analyses of resting-state fMRI data using a ROI-to-ROI approach assessing within-network and between-network rsFC in the frontoparietal (FPN), dorsal attention (DAN), default mode (DMN), and salience (SAL) networks, which all have been associated with cognitive impairment after TBI. We also performed a seed-based connectivity analysis between the right IFG and whole-brain rsFC. The results showed that neurological music therapy increased the coupling between the FPN and DAN as well as between these networks and primary sensory networks. By contrast, the DMN was less connected with sensory networks after the intervention. Similarly, there was a shift towards a less connected state within the FPN and SAL networks, which are typically hyperconnected following TBI. Improvements in EF were correlated with rsFC within the FPN and between the DMN and sensorimotor networks. Finally, in the seed-based connectivity analysis, the right IFG showed increased rsFC with the right inferior parietal and left frontoparietal (Rolandic operculum) regions. Together, these results indicate that the rehabilitative effects of neurological music therapy after TBI are underpinned by a pattern of within- and between-network connectivity changes in cognitive networks as well as increased connectivity between frontal and parietal regions associated with music processing.

Part 1 concluded by introducing the concept of the new ontological category – explaining how our cognitive machinery does not have natural and intuitive understanding of robots and AIs, unlike we have for animals, tools, and plants. Here the authors review findings in the moral psychology of robotics and transhumanism. They show that many peculiarities arise from the interaction of human cognition with robots, AIs, and human enhancement technologies. Robots are treated similarly, but not completely, like humans. Some such peculiarities are explained by mind perception mechanisms. On the other hand, it seems that transhumanistic technologies like brain implants and mind uploading are condemned, and the condemnation is motivated by our innate sexual disgust sensitivity mechanisms.

The idea of sex with robots seems to fascinate the general public, raising both enthusiasm and revulsion. We ran two experimental studies (Ns = 172 and 260) where we compared people’s reactions to variants of stories about a person visiting a bordello. Our results show that paying for the services of a sex robot is condemned less harshly than paying for the services of a human sex worker, especially if the payer is married. We have for the first time experimentally confirmed that people are somewhat unsure about whether using a sex robot while in a committed monogamous relationship should be considered as infidelity. We also shed light on the psychological factors influencing attitudes toward sex robots, including disgust sensitivity and interest in science fiction. Our results indicate that sex with a robot is indeed genuinely considered as sex, and a sex robot is genuinely seen as a robot; thus, we show that standard research methods on sexuality and robotics are also applicable in research on sex robotics.