Beware the dark side: Cultural preferences for lying online

Marett, Kent; George, Joey F.; Lewis, Carmen; Gupta, Michèle; Giordano, Gabriel A.

doi:10.1016/j.chb.2017.06.021

Cited by 16 publications

(13 citation statements)

References 55 publications

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“…Prior research indicates that data collected from MTurk are of high quality and capable of producing breakthroughs in research (Lowry et al, 2016 ). More recently, IS scholars have relied on MTurk to test their study hypotheses (Maier et al, 2019 ; Marett et al, 2017 ).…”

Section: Methodsmentioning

confidence: 99%

Questioning Racial and Gender Bias in AI-based Recommendations: Do Espoused National Cultural Values Matter?

2021

Self Cite

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One realm of AI, recommender systems have attracted significant research attention due to concerns about its devastating effects to society’s most vulnerable and marginalised communities. Both media press and academic literature provide compelling evidence that AI-based recommendations help to perpetuate and exacerbate racial and gender biases. Yet, there is limited knowledge about the extent to which individuals might question AI-based recommendations when perceived as biased. To address this gap in knowledge, we investigate the effects of espoused national cultural values on AI questionability, by examining how individuals might question AI-based recommendations due to perceived racial or gender bias. Data collected from 387 survey respondents in the United States indicate that individuals with espoused national cultural values associated to collectivism, masculinity and uncertainty avoidance are more likely to question biased AI-based recommendations. This study advances understanding of how cultural values affect AI questionability due to perceived bias and it contributes to current academic discourse about the need to hold AI accountable.

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Section: Methodsmentioning

confidence: 99%

Questioning Racial and Gender Bias in AI-based Recommendations: Do Espoused National Cultural Values Matter?

2021

Self Cite

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“…76-79). Similarly, a recent global study of 461 Internet users from France, the U.S., India, and South Korea found that individuals are more likely to lie online than face-to-face (Marett, George, Lewis, Gupta, & Giordano, 2017). Caspi and Gorsky (2006) further suggest, "[n]egative emotions, like guilt, shame and fear generally associated with face-to-face deception appear to be lacking in online deception.…”

Section: Deception In Online Asynchronous Venuesmentioning

confidence: 99%

“…The deception videos and the experimental treatments were developed and administered in the United States using Qualtrics panels and other distribution methods. Current research suggests cultural elements, which were not considered, may McHaney, George, Gupta / Deception Detection -Annotated Text-Based Cues significantly influence deception detection (Marett et al, 2017). Consequently, the current study would benefit from additional data collection opportunities utilizing varied cultural backgrounds.…”

Section: Limitationsmentioning

confidence: 99%

Deception Detection: An Exploration of Annotated Text-Based Cues

McHaney¹,

George²,

Gupta³

2018

JMWAIS

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Do embedded textual cues in asynchronous communication affect deceptive message detection? The expanded use of social media and rich media applications in business make this an important issue. Prior research indicates deception commonly occurs in all forms of communication and people have difficulty detecting its use. Asynchronous online communications are no exception and offer users a variety of media choices which may complicate deception detection, particularly if the sender has strategically selected a channel intended to disguise their intentions. The current study investigated whether embedded, non-verbal cues in common media forms found in asynchronous online venues influenced deception detection. Drawing on media synchronicity theory, results suggest embedding non-verbal cues in the form of annotated text can enhance deception detection. Overall, the findings suggest managers must be wary of sender motivations, which can influence message veracity, particularly in low synchronicity environments where media is subject to edits and manipulations.

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“…We argue that social media, which freely allows people to hide their real identity behind a fake profile -a social media-related behavior commonly known as 'catfishing' (Drouin et al, 2016;Marett et al, 2017) -substantially reduces human cooperation even when communication between people is allowed. We based this prediction on several theories in psychology and economics, as well as related evidence in social media research.…”

Section: Background and Hypothesesmentioning

confidence: 99%

“…This paper proposes a new empirical test of these theories. Through a series of randomized lab and online experiments, we tested whether the ability to hide one's real identity behind a fake profile -a social media-related behavior commonly known as 'catfishing' (Drouin et al, 2016;Marett et al, 2017) -is one of the main causes of uncooperative behaviors on social media websites as well as other online venues. By randomly allowing people to misrepresent one tiny information about themselves to others, i.e., their gender, we demonstrated that the average cooperation level with real money stake for the entire group was approximately 10-14 percentage points lower compared to other groups where the random opportunity to misrepresent was not available to the participants.…”

Section: Introductionmentioning

confidence: 99%

Large Losses from Little Lies: Randomly Assigned Opportunity to Misrepresent Substantially Lowers Later Cooperation and Worsens Income Inequality

et al. 2020

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Any opinions expressed in this paper are those of the author(s) and not those of IZA. Research published in this series may include views on policy, but IZA takes no institutional policy positions. The IZA research network is committed to the IZA Guiding Principles of Research Integrity. The IZA Institute of Labor Economics is an independent economic research institute that conducts research in labor economics and offers evidence-based policy advice on labor market issues. Supported by the Deutsche Post Foundation, IZA runs the world's largest network of economists, whose research aims to provide answers to the global labor market challenges of our time. Our key objective is to build bridges between academic research, policymakers and society. IZA Discussion Papers often represent preliminary work and are circulated to encourage discussion. Citation of such a paper should account for its provisional character. A revised version may be available directly from the author.

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Beware the dark side: Cultural preferences for lying online

Cited by 16 publications

References 55 publications

Questioning Racial and Gender Bias in AI-based Recommendations: Do Espoused National Cultural Values Matter?

Questioning Racial and Gender Bias in AI-based Recommendations: Do Espoused National Cultural Values Matter?

Deception Detection: An Exploration of Annotated Text-Based Cues

Large Losses from Little Lies: Randomly Assigned Opportunity to Misrepresent Substantially Lowers Later Cooperation and Worsens Income Inequality

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