Emotional affordances for human–robot interaction

Vallverdú, Jordi; Trovato, Gabriele

doi:10.1177/1059712316668238

Cited by 37 publications

(17 citation statements)

References 88 publications

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“…When Arcimboldo originally painted his whimsical portraits in the late 16 th century, little did he know that machines today would be endowed with facial features to evoke illusory socialness -a simple, yet effective trick, corroborated by data that show that mechanical and screen-based robot faces are rated as humanlike, friendly, intelligent or in some cases, as uncanny (Chesher & Andreallo, 2020;Kalegina et al, 2018;Phillips et al, 2018;Vallverdú & Trovato, 2016). As our surroundings become increasingly populated by a variety of artificial agents (including robots and virtual agents), an important aim will be to probe how different types of faces are processed, and what we might learn about humans' intrinsic social motivation toward artificial agents' faces (Geiger & Balas, 2020).…”

Section: Human Faces Do Not Inadvertently Capture Attentionmentioning

confidence: 99%

Faces do not attract more attention than non-social distractors in the Stroop task

Henschel¹,

Bargel²,

Cross³

2020

Preprint

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As robots begin to receive citizenship, be treated as beloved pets, and are given a place at Japanese family tables, it is becoming clear that these machines are taking on increasingly social roles. While human robot interaction research relies heavily on self-report measures for assessing people’s perception of robots, a distinct lack of robust cognitive and behavioural measures to gage the scope and limits of social motivation towards artificial agents exists. Here we adapted Conty and colleagues’ (2010) social version of the classic Stroop paradigm, in which we showed four kinds of distractor images above incongruent and neutral words: human faces, robot faces, object faces (for example, a cloud with facial features) and flowers (control). We predicted that social stimuli, like human faces, would be extremely salient and draw attention away from the to-be-processed words. A repeated-measures ANOVA indicated that the task worked (the Stroop effect was observed), and a distractor-dependent enhancement of Stroop interference emerged. Planned contrasts indicated that specifically human faces presented above incongruent words significantly slowed participants’ reaction times. To investigate this small effect further, we conducted a second study (N=51) with a larger stimulus set. While the main effect of the incongruent condition slowing down the reaction time of the participants replicated, we did not observe an interaction effect of the social distractors (human faces) drawing more attention than the other distractor types. We question the suitability of this task as a robust measure for social motivation and discuss our findings in the light of the conflicting results of Hietanen and colleagues (2016).

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Section: Human Faces Do Not Inadvertently Capture Attentionmentioning

confidence: 99%

Faces do not attract more attention than non-social distractors in the Stroop task

Henschel¹,

Bargel²,

Cross³

2020

Preprint

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“…Therefore, the morphology of the robot is one among a long list of emotional affordances I've described elsewhere in previous research [19], but at the same time the morphology has an outstanding role because determines a long set of related characteristics of the agent.…”

Section: Moral Morphologies As Social Prejudices or Cognitive Bias?mentioning

confidence: 99%

(Un-)Biasing the Morphologies of Affect for HRI Purposes

Vallverdú

2017

Proceedings of the IS4SI 2017 Summit DIGITALISATION FOR a SUSTAINABLE SOCIETY, Gothenburg, Sweden, 12–16 June 2017.

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Abstract:One fundamental aspect of Human-Robot Interactions is the role of the morphologies of both humans and machines. Basically, humans are naturalistically oriented towards the social interaction with other humans. Taking into account that fact that human morphologies run a social role, and that affection or emotion are fundamental aspects of the eco-cognitive and social processes, this talk tries to relate some classic and current challenges related to HRI: moral bias, emotional role into HRI, and dynamical morphologies in transhumanist scenarios.

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“…For simplicity, we will keep out of our analysis issues of affective interaction (de Gelder, 2006 ; Duffy, 2008 ; Breazeal, 2009 ; Wiese et al, 2017 ), although empathy contributes to efficient interactions and is obviously relevant for inducing humans to eventually accept robots as social companions. On this purpose, we will focus on fundamental building blocks for allowing a robot to physically interact with a human in a symbiotic manner, at the same time amenable to further extensions in the direction of affective interaction, for example a grounded taxonomy of emotional affordances (Vallverdú and Trovato, 2016 ). We wish also to emphasize that the overall approach fully agrees with the general principles of embodied cognition (Wilson, 2002 ; Pfeifer, 2006 ; Pfeifer et al, 2008 ; Vernon et al, 2015a , b ), which link together mental processes with physical interaction processes: the motor system may indeed influence cognitive states and the latter may affect bodily actions.…”

Section: Introductionmentioning

confidence: 99%

Social Cognition for Human-Robot Symbiosis—Challenges and Building Blocks

et al. 2018

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The next generation of robot companions or robot working partners will need to satisfy social requirements somehow similar to the famous laws of robotics envisaged by Isaac Asimov time ago (Asimov, 1942). The necessary technology has almost reached the required level, including sensors and actuators, but the cognitive organization is still in its infancy and is only partially supported by the current understanding of brain cognitive processes. The brain of symbiotic robots will certainly not be a “positronic” replica of the human brain: probably, the greatest part of it will be a set of interacting computational processes running in the cloud. In this article, we review the challenges that must be met in the design of a set of interacting computational processes as building blocks of a cognitive architecture that may give symbiotic capabilities to collaborative robots of the next decades: (1) an animated body-schema; (2) an imitation machinery; (3) a motor intentions machinery; (4) a set of physical interaction mechanisms; and (5) a shared memory system for incremental symbiotic development. We would like to stress that our approach is totally un-hierarchical: the five building blocks of the shared cognitive architecture are fully bi-directionally connected. For example, imitation and intentional processes require the “services” of the animated body schema which, on the other hand, can run its simulations if appropriately prompted by imitation and/or intention, with or without physical interaction. Successful experiences can leave a trace in the shared memory system and chunks of memory fragment may compete to participate to novel cooperative actions. And so on and so forth. At the heart of the system is lifelong training and learning but, different from the conventional learning paradigms in neural networks, where learning is somehow passively imposed by an external agent, in symbiotic robots there is an element of free choice of what is worth learning, driven by the interaction between the robot and the human partner. The proposed set of building blocks is certainly a rough approximation of what is needed by symbiotic robots but we believe it is a useful starting point for building a computational framework.

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Emotional affordances for human–robot interaction

Cited by 37 publications

References 88 publications

Faces do not attract more attention than non-social distractors in the Stroop task

Faces do not attract more attention than non-social distractors in the Stroop task

(Un-)Biasing the Morphologies of Affect for HRI Purposes

Social Cognition for Human-Robot Symbiosis—Challenges and Building Blocks

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