Honesty in the Digital Age

Maréchal, Michel André; Cohn, Alain; Gesche, Tobias

doi:10.2139/ssrn.3198158

Cited by 3 publications

(3 citation statements)

References 71 publications

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“…Both tested hypotheses were confirmed by our data: Participants were more likely to evade taxes when dealing with AAs compared to a human (Hypothesis 1), and they were more likely to evade taxes when interacting with an agent described to be simpler compared to a complex one (Hypothesis 2). These findings align with previous research (De Melo et al, 2016;Maréchal et al, 2020), suggesting that individuals are more likely to exploit machines in strategic exchanges. The fact that the complex treatment converged with the human treatment over the course of the experiment indicates the potential of participants evaluating humans and complex agents similarly.…”

Section: Discussionsupporting

confidence: 92%

“…This tendency was reproduced in other studies, where participants did show trust in AAs, but were more likely to exploit them (Karpus et al, 2021). In addition, people were more dishonest toward AAs, compared to humans in a coin-toss task (Maréchal et al, 2020). Therefore, while people go against theoretical expectations of rationality and selfishness and treat AA's socially, they still tend to be less prosocial and less honest with computers and exploit them more compared to interactions with humans.…”

Section: Human-computer Interactionsupporting

confidence: 59%

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Evading the algorithm: increased propensity for tax evasion and norm violations in human-computer interactions

Mutzner,

Oberhauser,

Winter

et al. 2023

Front. Behav. Econ.

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Today's modern world is characterized by an increasing shift from human-to-human interaction toward human-computer-interaction (HCI). With the implementation of artificial agents as inspectors, as can be seen in today's airports, supermarkets, or, most recently, within the context of the COVID-19 pandemic, our everyday life is progressively shaped around interacting with automated agents. While our understanding of HCI is evolving, it is still in nascent stages. This is particularly true in the sphere of non-cooperative strategic interactions between humans and automated agents, which remains largely unexplored and calls for further investigation. A deeper understanding of the factors influencing strategic decision-making processes within HCI situations, and how perceptions of automated agents' capabilities might influence these decisions, is required. This gap is addressed by extending a non-cooperative inspection-game experiment with a tax-evasion frame, implementing automated agents as inspectors. Here, a within-subject design is used to investigate (1) how HCI differs from human-to-human interactions in this context and (2) how the complexity and perceived capabilities of automated agents affect human decision-making. The results indicate significant differences in decisions to evade taxes, with participants more likely to evade taxes when they are inspected by automated agents rather than by humans. These results may also be transferred to norm violations more generally, which may become more likely when participants are controlled by computers rather than by humans. Our results further show that participants were less likely to evade taxes when playing against an automated agent described as a complex AI, compared to an automated agent described as a simple algorithm, once they had experienced different agents.

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Section: Discussionsupporting

confidence: 92%

Section: Human-computer Interactionsupporting

confidence: 59%

Evading the algorithm: increased propensity for tax evasion and norm violations in human-computer interactions

Mutzner,

Oberhauser,

Winter

et al. 2023

Front. Behav. Econ.

View full text Add to dashboard Cite

show abstract

“…Previous research has demonstrated that deception rates tend to be higher in text-based formats or over the phone, as opposed to video or face-to-face interactions (Hancock et al , 2004; Rockmann and Northcraft, 2008; Van Swol et al , 2015; George et al , 2014, for an exception), because removing the need to stare someone in the eyes creates a buffer of its own (Barry and Fulmer, 2004). The less human the other side feels, the easier it is to lie in self-serving ways, including engaging in more cheating behavior when reporting information to a machine rather than a person (Maréchal et al , 2018). But even when comparing text-only channels sent to real people, differences emerge, with people showing more self-serving behavior via electronic means than when making decisions via hard-copy documents (Naquin et al , 2010).…”

Section: Introductionmentioning

confidence: 99%

Deception by device: are we more self-serving on laptops or cell phones?

Kurtzberg

Naquin

Ameri

2022

IJCMA

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Purpose As both workplace and personal interactions increasingly move into online discussions, the impact of various technological devices (such as cell phones and laptops) on behaviors and decisions must be better understood. This study aims to assess whether tasks done on cell phones or laptops prompt more deception for the sake of personal gain in decisions and negotiations, based on the associations held about each device. Design/methodology/approach Four empirical studies plus a single-study meta-analysis explore the rates of self-serving deceptive behavior based on the type of device used in decision-making tasks (ultimatum-game bargaining and negotiations). Findings Results show that using a laptop prompted more self-serving behavior than using a cell phone. Follow-up studies suggest that the dominant associations that people hold with each device – professional ones for the laptop and personal ones for cell phone – may help drive this effect. Originality/value To the best of the authors’ knowledge, this study is among the first to establish a link between technological device and behavioral outcomes in negotiations, even when the exact format of the information sent and received is identical (i.e. text-only format). The findings have implications for selecting devices for important negotiations and decisions, as some may promote more ethical behavior than others.

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Group Effect Aspects in Digitalisation Production Contexts

Carvalho

Reichel

Martin

et al. 2022

Proc. ACM Hum.-Comput. Interact.

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Across the years, production systems have recurrently turned to new digital technologies in the search for enhanced productivity and competitiveness. More recently, a prelude to a Fourth Industrial Revolution has been heard, announcing Industry 4.0 as the future of production and manufacture. It has been claimed that cyber-physical production systems would bring drastic changes in the way that people go about engaging in work. It is therefore sensible to think that the way that cooperation is accomplished within production contexts will be also affected. Based on an in-depth interview study featuring 21 participants from different companies, we go on to discuss which challenges have been emerging from recent digitalisation of production work in regard to the way that workers cooperate in accomplishing their productive activities. Our results suggest that there are associated group effects - e.g., group polarisation, hidden profiles, and exclusion - that pose relevant challenges for cooperation within these settings. In this contribution, we go on to present and discuss these results and to propose articulation spaces, which conceptually bring together aspects of coordination mechanisms and common information spaces, as a potential solution for some of those challenges.

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Honesty in the Digital Age

Cited by 3 publications

References 71 publications

Evading the algorithm: increased propensity for tax evasion and norm violations in human-computer interactions

Evading the algorithm: increased propensity for tax evasion and norm violations in human-computer interactions

Deception by device: are we more self-serving on laptops or cell phones?

Group Effect Aspects in Digitalisation Production Contexts

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