Subthalamic nucleus detects unnatural android movement

The Neuroscience of Human and Artificial Intelligence Presence

Two decades of social neuroscience and neuroeconomics research illustrate the brain mechanisms that are engaged when people consider human beings, often in comparison to considering artificial intelligence (AI) as a nonhuman control. AI as an experimental control preserves agency and facilitates social interactions but lacks a human presence, providing insight into brain mechanisms that are engaged by human presence and the presence of AI. Here, I review this literature to determine how the brain instantiates human and AI presence across social perception and decision-making paradigms commonly used to realize a social context. People behave toward humans differently than they do toward AI. Moreover, brain regions more engaged by humans compared to AI extend beyond the social cognition brain network to all parts of the brain, and the brain sometimes is engaged more by AI than by humans. Finally, I discuss gaps in the literature, limitations in current neuroscience approaches, and how an understanding of the brain correlates of human and AI presence can inform social science in the wild.

How are emotional facial expressions detected rapidly and accurately? A diffusion model analysis

Previous psychological studies have shown that people detect emotional facial expressions more rapidly and accurately than neutral facial expressions. However, the cognitive mechanisms underlying the efficient detection of emotional facial expressions remain unclear. To investigate this issue, we used diffusion model analyses to estimate the cognitive parameters of a visual search task in which participants detected faces with normal expressions of anger and happiness and their anti-expressions within a crowd of neutral faces. The anti-expressions were artificially created to control the visual changes of facial features but were usually recognized as emotionally neutral. We tested the hypothesis that the emotional significance of the target's facial expressions modulated the non-decisional time and the drift rate. We also conducted an exploratory investigation of the effect of facial expressions on threshold separation. The results showed that the non-decisional time was shorter, and the drift rate was larger for targets with normal expressions than with anti-expressions. Subjective emotional arousal ratings of facial targets were negatively related to the non-decisional time and positively associated with the drift rate. In addition, the threshold separation was larger for normal expressions than for anti-expressions and positively associated with arousal ratings for facial targets. These results suggest that the efficient detection of emotional facial expressions is accomplished via the faster and more cautious accumulation of emotional information of facial expressions which is initiated more rapidly by enhanced attentional allocation.

Evaluation of the uncanny valley hypothesis based on declared emotional response and psychophysiological reaction

The uncanny valley (UV) hypothesis suggests that the observation of almost human-like characters causes an increase of discomfort. We conducted a study using self-report questionnaire, response time measurement, and electrodermal activity (EDA) evaluation. In the study, 12 computer-generated characters (robots, androids, animated, and human characters) were presented to 33 people (17 women) to (1) test the effect of a background context on the perception of characters, (2) establish whether there is a relation between declared feelings and physiological arousal, and (3) detect the valley of the presented stimuli. The findings provide support for reverse relation between human-likeness and the arousal (EDA). Furthermore, a positive correlation between EDA and human-likeness appraisal reaction time upholds one of the most common explanations of the UV – the categorization ambiguity. The absence of the significant relationship between declared comfort and EDA advocates the necessity of physiological measures for UV studies.