Algorithm exploitation: Humans are keen to exploit benevolent AI

Karpus, Jurgis; Krüger, Adrian; Verba, Júlia Tovar; Bahrami, Bahador; Deroy, Ophelia

doi:10.1016/j.isci.2021.102679

Cited by 28 publications

(38 citation statements)

References 48 publications

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“…Despite their concerns about algorithms, people often choose automatically taken decisions rather than decisions by human experts or they are indifferent (Araujo et al, 2020). Moreover, they appear to trust algorithms to be as cooperative as human interaction partners (Karpus et al, 2021).…”

Section: Studymentioning

confidence: 99%

Zombies in the Loop? Humans Trust Untrustworthy AI-Advisors for Ethical Decisions

2022

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Departing from the claim that AI needs to be trustworthy, we find that ethical advice from an AI-powered algorithm is trusted even when its users know nothing about its training data and when they learn information about it that warrants distrust. We conducted online experiments where the subjects took the role of decision-makers who received advice from an algorithm on how to deal with an ethical dilemma. We manipulated the information about the algorithm and studied its influence. Our findings suggest that AI is overtrusted rather than distrusted. We suggest digital literacy as a potential remedy to ensure the responsible use of AI.

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Section: Studymentioning

confidence: 99%

Zombies in the Loop? Humans Trust Untrustworthy AI-Advisors for Ethical Decisions

2022

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“…Together with the participant statements, this suggests that the AI is seen as a tool rather than an independent co-author (H4). In line with the tendency of humans to more readily exploit AI than a human [62], the human ghostwriter was also credited more often than the AI ghostwriter (H5). Study 2 provided participants with a multiple-choice list of possible options to choose from, rather than an open author declaration.…”

Section: Discussionmentioning

confidence: 92%

“…org/RKV_ZXX 13 ), comparing AI-supported writing to the case of a human author supporting the writing task. Based on the finding that algorithms/AI models are more likely to be exploited than humans [62], we posit the following hypotheses:…”

Section: The Ai Ghostwriter Effectmentioning

confidence: 99%

“…This is in line with recent studies of algorithm exploitation. Karpus et al [62] have found that while users of automated vehicles are well aware of traffic rules and the role of automated vehicles on the road, drivers are keen on exploiting automated cars as compared to cars driven by human drivers. Thus, we find that algorithm exploitation also holds for text production with AI concerning ghost-authorship.…”

Section: Implications For Cognition and Behavior In Writingmentioning

confidence: 99%

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The AI Ghostwriter Effect: Users Do Not Perceive Ownership of AI-Generated Text But Self-Declare as Authors

Draxler¹,

Werner²,

Lehmann³

et al. 2023

Preprint

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Human-AI interaction in text production increases complexity in authorship. In two empirical studies (n1 = 30 & n2 = 96), we investigate authorship and ownership in human-AI collaboration for personalized language generation models. We show an AI Ghostwriter Effect:Users do not consider themselves the owners and authors of AI-generated text but refrain from publicly declaring AI authorship.The degree of personalization did not impact the AI Ghostwriter Effect, and control over the model increased participants' sense of ownership. We also found that the discrepancy between the sense of ownership and the authorship declaration is stronger in interactions with a human ghostwriter and that people use similar rationalizations for authorship in AI ghostwriters and human ghostwriters. We discuss how our findings relate to psychological ownership and human-AI interaction to lay the foundations for adapting authorship frameworks and user interfaces in AI in text-generation tasks.

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“…High acceptance of artificial agents has been observed when the task involves analytical skills (March, 2021; Tulli et al, 2019). Conversely, people are less willing to accept artificial agents as cooperation partners in social contexts (Dietvorst et al, 2015; Ishowo‐Oloko et al, 2019; Karpus et al, 2021; Rovatsos, 2019). Neural activity in mentalizing and empathy networks is reduced when interacting with a computer or robot as compared to a true or alleged human (Chaminade et al, 2012; Rilling et al, 2004), and ERP components sensitive to affective stimulus significance are attenuated when participants receive personality feedback from a computer (Schindler & Kissler, 2016, 2018).…”

Section: Introductionmentioning

confidence: 99%

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

Flösch,

Flaisch,

Imhof

et al. 2023

Psychophysiology

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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.

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Algorithm exploitation: Humans are keen to exploit benevolent AI

Cited by 28 publications

References 48 publications

Zombies in the Loop? Humans Trust Untrustworthy AI-Advisors for Ethical Decisions

Zombies in the Loop? Humans Trust Untrustworthy AI-Advisors for Ethical Decisions

The AI Ghostwriter Effect: Users Do Not Perceive Ownership of AI-Generated Text But Self-Declare as Authors

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

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