Augmenting aesthetic chills using a wearable prosthesis improves their downstream effects on reward and social cognition

Haar, Adam; Jain, Abhinandan; Schoeller, Félix; Maes, Pattie

doi:10.1038/s41598-020-77951-w

Cited by 20 publications

(29 citation statements)

References 60 publications

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“…Recent studies have demonstrated that affective states can be elicited by triggering psychogenic shivering (PS) (Haar et al, 2020;Schoeller, et al, 2019a), using a device that controls the temperature in the upper back of the participants. Additional research indicates that the ability to be empathetic with others' emotions can be influenced by delivering electrical stimulation in the vagus nerve (Colzato et al, 2017), and by inducing affective states in the observer through videos (Pinilla et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

Affective Visualization in Virtual Reality: An Integrative Review

Pinilla

García

Raffe

et al. 2021

Front. Virtual Real.

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A cluster of research in Affective Computing suggests that it is possible to infer some characteristics of users’ affective states by analyzing their electrophysiological activity in real-time. However, it is not clear how to use the information extracted from electrophysiological signals to create visual representations of the affective states of Virtual Reality (VR) users. Visualization of users’ affective states in VR can lead to biofeedback therapies for mental health care. Understanding how to visualize affective states in VR requires an interdisciplinary approach that integrates psychology, electrophysiology, and audio-visual design. Therefore, this review aims to integrate previous studies from these fields to understand how to develop virtual environments that can automatically create visual representations of users’ affective states. The manuscript addresses this challenge in four sections: First, theories related to emotion and affect are summarized. Second, evidence suggesting that visual and sound cues tend to be associated with affective states are discussed. Third, some of the available methods for assessing affect are described. The fourth and final section contains five practical considerations for the development of virtual reality environments for affect visualization.

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Section: Discussionmentioning

confidence: 99%

Affective Visualization in Virtual Reality: An Integrative Review

Pinilla

García

Raffe

et al. 2021

Front. Virtual Real.

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“…Moreover, preliminary evidence on a small sample recently indicated that augmenting sensory signals that mimics the physical experience of aesthetic chills can enhance individual social-affective cognition (e.g., empathy and pleasure; 56 ).…”

Section: Discussionmentioning

confidence: 99%

“…Yet, how can one reinterpret such results in light of our present findings? Is it environmental exposure over one's own lifetime to art and poetry that is causally shaping the connectivity as seen in Williams et al 34 or is it more a priori predisposition that makes individuals better at integrating sensory information with their internal states, or alternatively more sensitive to sensory signals such as the ones seen in Haar et al 56 , that makes them more likely to reach such peaks of emotional-hedonic experiences? Clearly, further studies are needed to answer these questions.…”

Section: Discussionmentioning

confidence: 99%

On the Etiology of Aesthetic Chills: a Behavioral Genetic Study

Bignardi

Chamberlain

et al. 2021

Preprint

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Aesthetic chills, broadly defined as a somatic marker of peak emotional-hedonic responses, are experienced by individuals across a variety of human cultures. Yet individuals vary widely in the propensity of feeling them. These individual differences have been studied in relation to demographics, personality, and neurobiological and physiological factors, but no study to date has explored the genetic etiological sources of variation. To partition genetic and environmental sources of variation in the propensity of feeling aesthetic chills, we fitted a biometrical genetic model to data from 14127 twins (from 8995 pairs), collected by the Netherlands Twin Register. Both genetic and unique environmental factors accounted for variance in aesthetic chills, with heritability estimated at .36 ([.33, .39] 95% CI). We found females more prone than males to report feeling aesthetic chills. However, a test for genotype x sex interaction did not show evidence that heritability differs between sexes. We thus show that the propensity of feeling aesthetic chills is not shaped by nurture alone, but it also reflects underlying genetic propensities.

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“…Numerous studies attest to the complex, dynamic, and continuous interaction between cognitive and affective empathy, such as during passive observation of emotions or pain (Christov-Moore and Iacoboni, 2016), passive observation of films depicting personal loss (Raz et al, 2014), reciprocal imitation (Sperduti et al, 2014), tests of empathic accuracy (Zaki et al, 2009), and comprehension of others' emotions (Spunt and Lieberman, 2012), at the level of transcranial magnetic stimulation (TMS)--induced motor evoked potentials (MEPs), a functional readout of motor excitability (Gordon et al, 2018), and even in their neural substrates at rest (Christov-Moore et al, 2020). Indeed, recent studies using emotion prosthetics or interoceptive technologies have shown the importance of bodily signals in that process of identification (Schoeller et al, 2020;Haar et al, 2021). By stimulating the somatic markers of the emotion, Schoeller, Haar and Jain were able to enhance the prosocial effects of aesthetic chills (psychogenic shivers felt down the spine) during a film Haar et al, 2020).…”

Section: Alignment Feeling and Empathy In Aimentioning

confidence: 99%

How to Prevent Robotic Sociopaths: A Neuroscience Approach to Artificial Ethics

Moore¹,

Reggente²,

Vaccaro³

et al. 2022

Preprint

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Artificial intelligence (AI) is expanding into every niche of human life, organizing our activity, expanding our agency and interacting with us to an exponentially increasing extent. At the same time, AI’s efficiency, complexity and refinement are growing at an accelerating speed. An expanding, ubiquitous intelligence that does not have a means to care about us poses a species-level risk. Justifiably, there is a growing concern with the immediate problem of how to engineer an AI that is aligned with human interests. Computational approaches to the alignment problem currently focus on engineering AI systems to (i) parameterize human values such as harm and flourishing, and (ii) avoid overly drastic solutions, even if these are seemingly optimal. In parallel, ongoing work in applied AI (caregiving, consumer care) is concerned with developing artificial empathy, teaching AI’s to decode human feelings and behavior, and evince appropriate emotional responses.We propose that in the absence of affective empathy (which allows us to share in the states of others), existing approaches to artificial empathy may fail to reliably produce the pro-social, caring component of empathy, potentially resulting in increasingly cognitively complex sociopaths. We adopt the colloquial usage of the term “sociopath” to signify an intelligence possessing cognitive empathy (i.e., the ability to decode, infer, and model the mental and affective states of others), but crucially lacking pro-social, empathic concern arising from shared affect and embodiment. It is widely acknowledged that aversion to causing harm is foundational to the formation of empathy and moral behavior. However, harm aversion is itself predicated on the experience of harm, within the context of the preservation of physical integrity. Following from this, we argue that a “top-down” rule-based approach to achieving caring AI may be inherently unable to anticipate and adapt to the inevitable novel moral/logistical dilemmas faced by an expanding AI. Crucially, it may be more effective to coax caring to emerge from the bottom up, baked into an embodied, vulnerable artificial intelligence with an incentive to preserve its physical integrity. This may be achieved via iterative optimization within a series of tailored environments with incentives and contingencies inspired by the development of empathic concern in humans. Here we attempt an outline of what these training steps might look like. We speculate that work of this kind may allow for AI that surpasses empathic fatigue and the idiosyncrasies, biases, and computational limits that restrict human empathy. While for us, “a single death is a tragedy, a million deaths are a statistic”, the scaleable complexity of AI may allow it to deal proportionately with complex, large-scale ethical dilemmas. Hopefully, by addressing this problem seriously in the early stages of AI’s integration with society, we may one day be accompanied by AI that plans and behaves with a deeply ingrained weight placed on the welfare of others, coupled with the cognitive complexity necessary to understand and solve extraordinary problems.

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Augmenting aesthetic chills using a wearable prosthesis improves their downstream effects on reward and social cognition

Cited by 20 publications

References 60 publications

Affective Visualization in Virtual Reality: An Integrative Review

Affective Visualization in Virtual Reality: An Integrative Review

On the Etiology of Aesthetic Chills: a Behavioral Genetic Study

How to Prevent Robotic Sociopaths: A Neuroscience Approach to Artificial Ethics

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