Human-Likeness of Feedback Gestures Affects Decision Processes and Subjective Trust

Parenti, Lorenzo; Lukomski, Adam W.; Tommaso, Davide De; Belkaid, Marwen; Wykowska, Agnieszka

doi:10.1007/s12369-022-00927-5

Cited by 5 publications

(6 citation statements)

References 32 publications

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“…The “cups‐and‐balls” experiment, while sharing similarities with the task used in Parenti et al. (2023), represents a more engaging adaptation of a simple gambling task previously employed in HRI studies (e.g., see Abubshait et al., 2021). We selected this task, as it addresses decision‐making processes in ambiguous situations, where one needs to “bet” on an option.…”

Section: Methodsmentioning

confidence: 99%

“…Robot verbal feedback has been shown to influence participants’ choices (Ham & Midden, 2014). Nevertheless, robot feedback could also be provided through non‐verbal behavior, like facial expressions, gaze behavior, and gestures (Ciardo & Wykowska, 2022; Gonsior et al., 2011; Parenti, Lukomski, De Tommaso, Belkaid, & Wykowska, 2023). Post‐decision feedback is likely to influence upcoming decisions, and thus interact with pre‐decision signals.…”

Section: Introductionmentioning

confidence: 99%

“…Indeed, extensive research in social psychology highlighted the importance of prior expectations based on experiences and social norms in anticipating others’ behavior (Burgoon, 1993). Concurrently, it has been suggested that people tend to interact with machines using the same interaction patterns they developed to interact with other humans (Edwards et al., 2019) and similar cognitive mechanisms that have developed for interacting with other humans (Parenti et al., 2023; Wykowska, 2020). On the other hand, people's social expectations about robots’ behavior (Kahn et al., 2011) might to some extent differ from expectations regarding human behavior.…”

Section: Introductionmentioning

confidence: 99%

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Differences in Social Expectations About Robot Signals and Human Signals

Parenti,

Belkaid,

Wykowska

2023

Cognitive Science

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In our daily lives, we are continually involved in decision‐making situations, many of which take place in the context of social interaction. Despite the ubiquity of such situations, there remains a gap in our understanding of how decision‐making unfolds in social contexts, and how communicative signals, such as social cues and feedback, impact the choices we make. Interestingly, there is a new social context to which humans are recently increasingly more frequently exposed—social interaction with not only other humans but also artificial agents, such as robots or avatars. Given these new technological developments, it is of great interest to address the question of whether—and in what way—social signals exhibited by non‐human agents influence decision‐making. The present study aimed to examine whether robot non‐verbal communicative behavior has an effect on human decision‐making. To this end, we implemented a two‐alternative‐choice task where participants were to guess which of two presented cups was covering a ball. This game was an adaptation of a “Shell Game.” A robot avatar acted as a game partner producing social cues and feedback. We manipulated robot's cues (pointing toward one of the cups) before the participant's decision and the robot's feedback (“thumb up” or no feedback) after the decision. We found that participants were slower (compared to other conditions) when cues were mostly invalid and the robot reacted positively to wins. We argue that this was due to the incongruence of the signals (cue vs. feedback), and thus violation of expectations. In sum, our findings show that incongruence in pre‐ and post‐decision social signals from a robot significantly influences task performance, highlighting the importance of understanding expectations toward social robots for effective human–robot interactions.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Differences in Social Expectations About Robot Signals and Human Signals

Parenti,

Belkaid,

Wykowska

2023

Cognitive Science

Self Cite

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“…Robot verbal feedback has been shown to influence participants' choices (Ham and Midden, 2014). However, robot feedback could also be provided through the non-verbal behavior, like facial expressions, gaze behavior and gestures for instance (Gonsior et al, 2011;Ciardo & Wykowska, 2022;Parenti et al, 2022). Yet, the effects of nonverbal feedback from the robot remain relatively understudied.…”

Section: Introductionmentioning

confidence: 99%

“…These differing expectations about robot behavior can also influence the degree to which people rely in robots in decision-making scenario. For instance, robots may be expected to exhibit mechanistic movements rather than smooth motion trajectories and not meeting these expectations could lead to lack of trust or affect participants' performance (Parenti et al, 2021;Parenti et al 2022). As suggested by previous studies, robots' anticipated behavior can be influenced by a variety of factors such as their appearance, social setting, and prior experience and familiarity (Kahn et al, 2011;Kwon et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Differences in social expectations about robot signals and human signals

Parenti¹,

Belkaid²,

Wykowska³

2023

Preprint

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Decision-making processes are involved in a large portion of humans’ everyday life and often occur in social situations. Although social decision-making has received increasing interest in literature, the influence of communicative signals, like social cues and feedback, on social decision-making is still poorly understood. In particular, the issue of whether social signals exhibited by non-human agents influence decision making has not yet been addressed. This question is of great importance today, in the new era in which artificial agents, such as robots or avatars start interacting with humans on a daily basis. This study aimed to examine whether robot non-verbal communicative behavior has an effect on human decision-making and can be perceived as a social signal. To this end, we implemented a 2-alternative-choice task with a between-subjects design where a robot acted as a game partner. We manipulated robot’s cues before participant’s decision and robot’s feedback after the decision. We found that manipulating robot signals affected participants’ performance. In particular, participants were slower in the condition where cues were mostly invalid and the robot reacted positively to wins. We show that this effect could not be attributed to attentional mechanisms, feedback expectation, or cognitive control. Instead, our results suggest that the effect is rather due to the violation of expectations about the incongruence between social signals. Our findings also indicate differences in these social expectations when they are about robot signals compared to human signals.

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A Psychological Need-Fulfillment Perspective for Designing Social Robots that Support Well-Being

Janssen,

Schadenberg

2024

Int J of Soc Robotics

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This conceptual paper presents a novel framework for the design and study of social robots that support well-being. Building upon the self-determination theory and the associated Motivation, Engagement, and Thriving in User Experience (METUX) model, this paper argues that users’ psychological basic needs for autonomy, competence, and relatedness should be put at the center of social robot design. These basic needs are essential to people’s psychological well-being, engagement, and self-motivation. However, current literature offers limited insights into how human–robot interactions are related to users’ experiences of the satisfaction of their basic psychological needs and thus, to their well-being and flourishing. We propose that a need-fulfillment perspective could be an inspiring lens for the design of social robots, including socially assistive robots. We conceptualize various ways in which a psychological need-fulfillment perspective may be incorporated into future human–robot interaction research and design, ranging from the interface level to the specific tasks performed by a robot or the user’s behavior supported by the robot. The paper discusses the implications of the framework for designing social robots that promote well-being, as well as the implications for future research.

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Human-Likeness of Feedback Gestures Affects Decision Processes and Subjective Trust

Cited by 5 publications

References 32 publications

Differences in Social Expectations About Robot Signals and Human Signals

Differences in Social Expectations About Robot Signals and Human Signals

Differences in social expectations about robot signals and human signals

A Psychological Need-Fulfillment Perspective for Designing Social Robots that Support Well-Being

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