Re-imaging the intentional stance

The involvement of rTPJ in intention attribution during social decision making: A TMS study

The mini-Ultimatum Game (mini-UG) is a bargaining game used to assess the reactions of a responder to unfair offers made by a proposer under different intentionality conditions. Previous studies employing this task showed the activation of responders' right temporoparietal junction (rTPJ), which could be related to its involvement in judgments of intentionality. To verify this hypothesis, in the present study we applied online transcranial magnetic stimulation (TMS) over the rTPJ in responders during the mini-UG, in which we manipulated intention attribution implicitly. A cover story was employed to induce participants to believe they were interacting with another agent. We expected that interfering with the rTPJ could affect the ability of responders to assume proposers' perspective, producing higher rates of rejections of unfair offers when offers are perceived as independent from responders' intentionality to inequality. Twenty-six healthy women voluntarily participated in the study. In the mini-UG, an unfair distribution of the proposer (8/2 offer) was pitted against one of three alternative offers: fair-alternative (5/5), no-alternative (8/2), hyperfair-alternative (2/8). During the task, a train of TMS pulses was delivered at proposers' offer presentation in blocks of active (rTPJ) or control (Vertex) stimulation according to an ABAB design. As expected, findings showed that rejection of the no-alternative offers was higher under TMS stimulation of the rTPJ compared with the control TMS. This effect was modulated by the degree of trustworthiness in the cover story. These data contribute defining the mechanisms and brain areas underpinning social decision making as assessed by bargaining tasks.

Dyadic cooperation with human and artificial agents: Event-related potentials trace dynamic role taking during an interactive game

Humans are highly co-operative and thus cognitively, affectively, and motivationally tuned to pursue shared goals. Yet, cooperative tasks typically require people to constantly take and switch individual roles. Task relevance is dictated by these roles and thereby dynamically changing. Here, we designed a dyadic game to test whether the family of P3 components can trace this dynamic allocation of task relevance. We demonstrate that late positive event-related potential (ERP) modulations not only reflect predictable asymmetries between receiving and sending information but also differentiate whether the receiver's role is related to correct decision making or action monitoring. Furthermore, similar results were observed when playing the game with a computer, suggesting that experimental games may motivate humans to similarly cooperate with an artificial agent. Overall, late positive ERP waves provide a real-time measure of how role taking dynamically shapes the meaning and relevance of stimuli within collaborative contexts. Our results, therefore, shed light on how the processes of mutual coordination unfold during dyadic cooperation.

Formalising social representation to explain psychiatric symptoms

Recent work in social cognition has moved beyond a focus on how people process social rewards to examine how healthy people represent other agents and how this is altered in psychiatric disorders. However, formal modelling of social representation has not kept pace with these changes, impeding our understanding of how core aspects of social cognition function, and fail, in psychopathology. Here, we suggest that belief-based computational models provide a basis for an integrated sociocognitive approach to psychiatry, with the potential to address important but unexamined pathologies of social representation, such as maladaptive schemas and illusory social agents.

Mind your step: social cerebellum in interactive navigation

The posterior cerebellum contributes to dynamic social cognition by building representations and predictions about sequences in which social interactions typically take place. However, the extent to which violations of prior social expectations during human interaction activate the cerebellum remains largely unknown. The present study examined inconsistent actions, which violate the expectations of desired goal outcomes, by using a social navigation paradigm in which a protagonist presented a gift to another agent that was liked or not. As an analogous non-social control condition, a pen was transported via an assembly line and filled with ink that matched the pen's cap or not. Participants (n = 25) were required to memorize and subsequently reproduce the sequence of the protagonist's or pen's trajectory. As hypothesized, expectation violations in social (vs non-social) sequencing were associated with activation in the posterior cerebellum (Crus 1/2) and other cortical mentalizing regions. In contrast, non-social (vs social) sequencing recruited cerebellar lobules IV-V, the action observation network and the navigation-related parahippocampal gyrus. There was little effect in comparison with a social non-sequencing control condition, where participants only had to observe the trajectory. The findings provide further evidence of cerebellar involvement in signaling inconsistencies in social outcomes of goal-directed navigation.

Precuneus brain response changes differently during human-robot and human-human dyadic social interaction

Human–human interactions (HHI) and human–robot interactions (HRI) are compared to identify differences between cognitive processes reflecting bonding in social interactions with natural and artificial agents. We capitalize on a unique corpus of neuroimaging data (fMRI) recorded while participants freely discussed with another human or a conversational robotic head, in order to study a crucial parameter of human social cognition, namely that social interactions are adaptive bidirectional processes that evolve over time. We used linear statistics to identify regions of the brain where activity changes differently when participants carry out twelve one-minute conversations, alternating between a human and a robotic interlocutor. Results show that activity in the posterior cingulate cortex, a key region associated with social cognition, increases over time in HHI but not in HRI. These results are interpreted as reflecting a process of strengthening social bonding during repeated exchanges when the interacting agent is a human, but not a robot.

Different models of anthropomorphism across cultures and ontological limits in current frameworks the integrative framework of anthropomorphism

Anthropomorphism describes the tendency to ascribe human characteristics to nonhuman agents. Due to the increased interest in social robotics, anthropomorphism has become a core concept of human-robot interaction (HRI) studies. However, the wide use of this concept resulted in an interchangeability of its definition. In the present study, we propose an integrative framework of anthropomorphism (IFA) encompassing three levels: cultural, individual general tendencies, and direct attributions of human-like characteristics to robots. We also acknowledge the Western bias of the state-of-the-art view of anthropomorphism and develop a cross-cultural approach. In two studies, participants from various cultures completed tasks and questionnaires assessing their animism beliefs, individual tendencies to endow robots with mental properties, spirit, and consider them as more or less human. We also evaluated their attributions of mental anthropomorphic characteristics towards robots (i.e., cognition, emotion, intention). Our results demonstrate, in both experiments, that a three-level model (as hypothesized in the IFA) reliably explains the collected data. We found an overall influence of animism (cultural level) on the two lower levels, and an influence of the individual tendencies to mentalize, spiritualize and humanize (individual level) on the attribution of cognition, emotion and intention. In addition, in Experiment 2, the analyses show a more anthropocentric view of the mind for Western than East-Asian participants. As such, Western perception of robots depends more on humanization while East-Asian on mentalization. We further discuss these results in relation to the anthropomorphism literature and argue for the use of integrative cross-cultural model in HRI research.

A Pragmatic Approach to the Intentional Stance Semantic, Empirical and Ethical Considerations for the Design of Artificial Agents

Artificial agents are progressively becoming more present in everyday-life situations and more sophisticated in their interaction affordances. In some specific cases, like Google Duplex, GPT-3 bots or Deep Mind’s AlphaGo Zero, their capabilities reach or exceed human levels. The use contexts of everyday life necessitate making such agents understandable by laypeople. At the same time, displaying human levels of social behavior has kindled the debate over the adoption of Dennett’s ‘intentional stance’. By means of a comparative analysis of the literature on robots and virtual agents, we defend the thesis that approaching these artificial agents ‘as if’ they had intentions and forms of social, goal-oriented rationality is the only way to deal with their complexity on a daily base. Specifically, we claim that this is the only viable strategy for non-expert users to understand, predict and perhaps learn from artificial agents’ behavior in everyday social contexts. Furthermore, we argue that as long as agents are transparent about their design principles and functionality, attributing intentions to their actions is not only essential, but also ethical. Additionally, we propose design guidelines inspired by the debate over the adoption of the intentional stance.

I Am Looking for Your Mind: Pupil Dilation Predicts Individual Differences in Sensitivity to Hints of Human-Likeness in Robot Behavior

The presence of artificial agents in our everyday lives is continuously increasing. Hence, the question of how human social cognition mechanisms are activated in interactions with artificial agents, such as humanoid robots, is frequently being asked. One interesting question is whether humans perceive humanoid robots as mere artifacts (interpreting their behavior with reference to their function, thereby adopting the design stance) or as intentional agents (interpreting their behavior with reference to mental states, thereby adopting the intentional stance). Due to their humanlike appearance, humanoid robots might be capable of evoking the intentional stance. On the other hand, the knowledge that humanoid robots are only artifacts should call for adopting the design stance. Thus, observing a humanoid robot might evoke a cognitive conflict between the natural tendency of adopting the intentional stance and the knowledge about the actual nature of robots, which should elicit the design stance. In the present study, we investigated the cognitive conflict hypothesis by measuring participants’ pupil dilation during the completion of the InStance Test. Prior to each pupillary recording, participants were instructed to observe the humanoid robot iCub behaving in two different ways (either machine-like or humanlike behavior). Results showed that pupil dilation and response time patterns were predictive of individual biases in the adoption of the intentional or design stance in the IST. These results may suggest individual differences in mental effort and cognitive flexibility in reading and interpreting the behavior of an artificial agent.