Causes of Psychological Reactance in Human-Computer Interaction

Ehrenbrink, Patrick; Prezenski, Sabine

doi:10.1145/3121283.3121304

Cited by 5 publications

(4 citation statements)

References 13 publications

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“…In the context of everyday interactions, factors such as intelligibility, control over a system, trust, likeability, or acceptance and expectations of the system are also shown to influence people's perception of autonomy or reactance (Sankaran and Markopoulos, 2021). An extensive literature review and survey in human-computer interaction showed that factors like undesirable behavior of agents, restricting choice, and control would lead to psychological reactance among users (Ehrenbrink and Prezenski, 2017). However, it is not clear how these factors influence people's perception of autonomy and reactance vary in different contexts.…”

Section: Motivationmentioning

confidence: 99%

“…Recent research states reactance as negative motivational arousal which is experienced by people when they experience a threat to or loss of free behavior and independent actions (Steindl et al, 2015 ). In human–computer interaction, factors such as reduced freedom of choice and behavior restriction cause psychological reactance when interacting with systems in real-life situations (Ehrenbrink and Prezenski, 2017 ). Furthermore, studies have shown that digital assistants influence users' perceived control during an interaction, often resulting in disappointment with the online recommendation (André et al, 2018 ) and experience a psychological reactance when they perceive that their freedom is reduced (Lee and Lee, 2009 ).…”

Section: Introductionmentioning

confidence: 99%

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Exploring Peoples' Perception of Autonomy and Reactance in Everyday AI Interactions

et al. 2021

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Applications using Artificial Intelligence (AI) have become commonplace and embedded in our daily lives. Much of our communication has transitioned from human–human interaction to human–technology or technology-mediated interaction. As technology is handed over control and streamlines choices and decision-making in different contexts, people are increasingly concerned about a potential threat to their autonomy. In this paper, we explore autonomy perception when interacting with AI-based applications in everyday contexts using a design fiction-based survey with 328 participants. We probed if providing users with explanations on “why” an application made certain choices or decisions influenced their perception of autonomy or reactance regarding the interaction with the applications. We also looked at changes in perception when users are aware of AI's presence in an application. In the social media context, we found that people perceived a greater reactance and lower sense of autonomy perhaps owing to the personal and identity-sensitive nature of the application context. Providing explanations on “why” in the navigation context, contributed to enhancing their autonomy perception, and reducing reactance since it influenced the users' subsequent actions based on the recommendation. We discuss our findings and the implications it has for the future development of everyday AI applications that respect human autonomy.

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Section: Motivationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Exploring Peoples' Perception of Autonomy and Reactance in Everyday AI Interactions

et al. 2021

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“…However, when humans are subjected to persuasive attempts, they can respond to these attempts by showing both positive responses (liking, compliance) and negative responses (tantrum, reactance). Positive experiences include conformity to the robots by children [14], trustworthy to the robots with dissimilar gender with users [15] and increment of human performance facilitated by robot touch [16]. Indeed, powerful persuasive attempts can lead to psychological reactance [17] as highlighted earlier [18].…”

Section: Introductionmentioning

confidence: 99%

Assessing the effect of persuasive robots interactive social cues on users’ psychological reactance, liking, trusting beliefs and compliance

Ghazali

Ham²,

Barakova

et al. 2019

Advanced Robotics

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Research in the field of social robotics suggests that enhancing social cues in robots can elicit more social responses in users. It is however not clear how users respond socially to persuasive social robots and whether such reactions will be more pronounced when the robots feature more interactive social cues. In the current research, we examine social responses towards persuasive attempts provided by a robot featuring different numbers of interactive social cues. A laboratory experiment assessed participants' psychological reactance, liking, trusting beliefs and compliance toward a persuasive robot that either presented users with: no interactive social cues (random head movements and random social praises), low number of interactive social cues (head mimicry), or high number of interactive social cues (head mimicry and proper timing for social praise). Results show that a persuasive robot with the highest number of interactive social cues invoked lower reactance and was liked more than the robots in the other two conditions. Furthermore, results suggest that trusting beliefs towards persuasive robots can be enhanced by utilizing praise as presented by social robots in no interactive social cues and high number of interactive social cues conditions. However, interactive social cues did not contribute to higher compliance. ARTICLE HISTORY

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“…The weight of advice captures the distance to advice, but not reactance. Reactance to AI is a prevalent problem (Ehrenbrink and Prezenski, 2017;Sheng and Chen, 2020), and a mere assessment of the mean weight of advice may prove insufficient in effectively capturing these complex response patterns. Furthermore, various explanation strategies may elicit distinct levels of reactance.…”

Section: Accurate Information Strategiesmentioning

confidence: 99%

Humans in XAI: increased reliance in decision-making under uncertainty by using explanation strategies

Lammert,

Richter,

Schütze

et al. 2024

Front. Behav. Econ.

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IntroductionAlthough decision support systems (DSS) that rely on artificial intelligence (AI) increasingly provide explanations to computer and data scientists about opaque features of the decision process, especially when it involves uncertainty, there is still only limited attention to making the process transparent to end users.MethodsThis paper compares four distinct explanation strategies employed by a DSS, represented by the social agent Floka, designed to assist end users in making decisions under uncertainty. Using an economic experiment with 742 participants who make lottery choices according to the Holt and Laury paradigm, we contrast two explanation strategies offering accurate information (transparent vs. guided) with two strategies prioritizing human-centered explanations (emotional vs. authoritarian) and a baseline (no explanation).Results and discussionOur findings indicate that a guided explanation strategy results in higher user reliance than a transparent strategy. Furthermore, our results suggest that user reliance is contingent on the chosen explanation strategy, and, in some instances, the absence of an explanation can also lead to increased user reliance.

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Causes of Psychological Reactance in Human-Computer Interaction

Cited by 5 publications

References 13 publications

Exploring Peoples' Perception of Autonomy and Reactance in Everyday AI Interactions

Exploring Peoples' Perception of Autonomy and Reactance in Everyday AI Interactions

Assessing the effect of persuasive robots interactive social cues on users’ psychological reactance, liking, trusting beliefs and compliance

Humans in XAI: increased reliance in decision-making under uncertainty by using explanation strategies

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