Be More Transparent and Users Will Like You

Vitale, Jonathan; Tonkin, Meg; Herse, Sarita; Ojha, Suman; Clark, Jesse N.; Williams, Mary-Anne; Wang, Xun; Judge, William Q.

doi:10.1145/3171221.3171269

Cited by 32 publications

(6 citation statements)

References 18 publications

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“…Meanwhile, the display of finer grained information embedded in data requests lowered users' likelihood to share personal information [63]. Aiming to compare the effects of different interfaces, Vitale et al [64] found no significant differences in the amount of personal information disclosed when a kiosk or a robot were employed, while Zhu, Carpenter and Kulkarni [65] observed that an interface providing privacy suggestions to users helped them in limiting unnecessary disclosures.…”

Section: Plos Onementioning

confidence: 99%

Privacy nudges for disclosure of personal information: A systematic literature review and meta-analysis

et al. 2021

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Objective Digital nudging has been mooted as a tool to alter user privacy behavior. However, empirical studies on digital nudging have yielded divergent results: while some studies found nudging to be highly effective, other studies found no such effects. Furthermore, previous studies employed a wide range of digital nudges, making it difficult to discern the effectiveness of digital nudging. To address these issues, we performed a systematic review of empirical studies on digital nudging and information disclosure as a specific privacy behavior. Method The search was conducted in five digital libraries and databases: Scopus, Google Scholar, ACM Digital Library, Web of Science, and Science Direct for peer-reviewed papers published in English after 2006, examining the effects of various nudging strategies on disclosure of personal information online. Results The review unveiled 78 papers that employed four categories of nudge interventions: presentation, information, defaults, and incentives, either individually or in combination. A meta-analysis on a subset of papers with available data (n = 54) revealed a significant small-to-medium sized effect of the nudge interventions on disclosure (Hedges’ g = 0.32). There was significant variation in the effectiveness of nudging (I2 = 89%), which was partially accounted for by interventions to increase disclosure being more effective than interventions to reduce disclosure. No evidence was found for differences in the effectiveness of nudging with presentation, information, defaults, and incentives interventions. Conclusion Identifying ways to nudge users into making more informed and desirable privacy decisions is of significant practical and policy value. There is a growing interest in digital privacy nudges for disclosure of personal information, with most empirical papers focusing on nudging with presentation. Further research is needed to elucidate the relative effectiveness of different intervention strategies and how nudges can confound one another.

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Section: Plos Onementioning

confidence: 99%

Privacy nudges for disclosure of personal information: A systematic literature review and meta-analysis

et al. 2021

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“…The defined guidelines serve to improve acceptance and benefits of the use of technology for companies and their employees. To provide one example, previous research showed a significant positive effect of transparent information representation via the user interface on the user experience [32]. A concept for transparent data recording would be advantageous.…”

Section: Discussionmentioning

confidence: 99%

On the Intention to Use the Pepper Robot as Communication Channel in a Business Context

Schmidbauer

Umele

Zigart

et al. 2020

Proceedings of the 8th International Conference on Human-Agent Interaction

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This paper presents the results of a user acceptance survey (based on the Technology Acceptance Model-TAM) of the humanoid social robot Pepper as a communication channel in different information retrieval scenarios in a business context. In total, 239 passers-by participated in the survey, which had a specific focus on the impact of perceived safety and security aspects. The results revealed a positive assessment of its perceived ease of use and perceived usefulness. It also showed how safety, data protection, and privacy concerns impact the intention to use the robot. The study findings are supported by the outcomes of eight expert interviews.

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“…Fourth, in terms of transparency, the literature yields mixed results. On the one hand, more openness about the algorithm is essential for building trust in AI systems (Neuhaus et al, 2019), involving the users (Kizilcec, 2016), reducing anxiety (Jhaver et al, 2018), and increasing user experience (Vitale et al, 2018). On the other hand, studies show that too much transparency can impair user experience (Lim and Dey, 2011) and confuse users, complicating the interaction between humans and AI systems (Eslami et al, 2018).…”

Section: Public Preferences For Ai Ethics Guidelinesmentioning

confidence: 99%

Artificial intelligence ethics by design. Evaluating public perception on the importance of ethical design principles of artificial intelligence

2022

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Despite the immense societal importance of ethically designing artificial intelligence, little research on the public perceptions of ethical artificial intelligence principles exists. This becomes even more striking when considering that ethical artificial intelligence development has the aim to be human-centric and of benefit for the whole society. In this study, we investigate how ethical principles (explainability, fairness, security, accountability, accuracy, privacy, and machine autonomy) are weighted in comparison to each other. This is especially important, since simultaneously considering ethical principles is not only costly, but sometimes even impossible, as developers must make specific trade-off decisions. In this paper, we give first answers on the relative importance of ethical principles given a specific use case—the use of artificial intelligence in tax fraud detection. The results of a large conjoint survey ([Formula: see text]) suggest that, by and large, German respondents evaluate the ethical principles as equally important. However, subsequent cluster analysis shows that different preference models for ethically designed systems exist among the German population. These clusters substantially differ not only in the preferred ethical principles but also in the importance levels of the principles themselves. We further describe how these groups are constituted in terms of sociodemographics as well as opinions on artificial intelligence. Societal implications, as well as design challenges, are discussed.

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Be More Transparent and Users Will Like You

Cited by 32 publications

References 18 publications

Privacy nudges for disclosure of personal information: A systematic literature review and meta-analysis

Privacy nudges for disclosure of personal information: A systematic literature review and meta-analysis

On the Intention to Use the Pepper Robot as Communication Channel in a Business Context

Artificial intelligence ethics by design. Evaluating public perception on the importance of ethical design principles of artificial intelligence

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