Exploring privacy paradox in contact tracing apps adoption

Duan, Sophia Xiaoxia; Deng, Hepu

doi:10.1108/intr-03-2021-0160

Cited by 30 publications

(42 citation statements)

References 60 publications

(321 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For instance, human biases could be as severe and may lead to grave mistakes as they may opt to trust their judgements or colleagues' judgements over that of the application (Venkatesh, 2021). And for some, concerns about privacy and data security deter adoption (Duan and Deng, 2022;Huang et al, 2022). In India for example, the Arogya Setu contact tracing application was initially adopted voluntarily but subsequently became a mandated condition for returning to work notwithstanding its privacy concerns (India Today Tech, 2020).…”

Section: Implications For Researchmentioning

confidence: 99%

The role of institutional and self in the formation of trust in artificial intelligence technologies

Wong

Tan

Ooi

et al. 2023

INTR

View full text Add to dashboard Cite

PurposeThe deployment of artificial intelligence (AI) technologies in travel and tourism has received much attention in the wake of the pandemic. While societal adoption of AI has accelerated, it also raises some trust challenges. Literature on trust in AI is scant, especially regarding the vulnerabilities faced by different stakeholders to inform policy and practice. This work proposes a framework to understand the use of AI technologies from the perspectives of institutional and the self to understand the formation of trust in the mandated use of AI-based technologies in travelers.Design/methodology/approachAn empirical investigation using partial least squares-structural equation modeling was employed on responses from 209 users. This paper considered factors related to the self (perceptions of self-threat, privacy empowerment, trust propensity) and institution (regulatory protection, corporate privacy responsibility) to understand the formation of trust in AI use for travelers.FindingsResults showed that self-threat, trust propensity and regulatory protection influence trust in users on AI use. Privacy empowerment and corporate responsibility do not.Originality/valueInsights from the past studies on AI in travel and tourism are limited. This study advances current literature on affordance and reactance theories to provide a better understanding of what makes travelers trust the mandated use of AI technologies. This work also demonstrates the paradoxical effects of self and institution on technologies and their relationship to trust. For practice, this study offers insights for enhancing adoption via developing trust.

show abstract

Section: Implications For Researchmentioning

confidence: 99%

The role of institutional and self in the formation of trust in artificial intelligence technologies

Wong

Tan

Ooi

et al. 2023

INTR

View full text Add to dashboard Cite

show abstract

“… 4 Despite their usefulness, risks related to privacy infringements and surveillance have been widely discussed in recent studies. 10 – 12 , 29 – 34 Although digital contact tracing based on smartphone applications has been endorsed by many governments and organizations across the world to help limit the spread of COVID-19, 26 , 30 , 31 public concerns regarding privacy intrusions (e.g., giving away one's movement and medical information) have hindered the wider adoption of contact-tracing technologies in many countries. 9 …”

Section: Literature Reviewmentioning

confidence: 99%

“… 52 Similar results were found in studies conducted in other countries, such as Australia, India, and various European countries. 29 , 31 – 34 This suggests that achieving a balance between privacy and health data acquisition is one of the most urgent issues in the public adoption of contact tracing for technology-assisted health promotion.…”

Section: Literature Reviewmentioning

confidence: 99%

“… 54 Moreover, several studies have found that individuals’ evaluations of risk and benefits significantly influence their adoption of COVID-19 contact-tracing technologies. 29 , 32 , 33 This study explored individuals’ decision-making on the adoption of contact-tracing technologies based on perceived net equity. In this context, perceived net equity can be understood as the outcome of a cost-benefit analysis that compares potential outcomes with alternatives based on the privacy risks and the individual and social benefits of adopting contact-tracing technologies.…”

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

The role of uncertainty and affect in decision-making on the adoption of AI-based contact-tracing technology during the COVID-19 pandemic

Hong

Cho

2023

DIGITAL HEALTH

View full text Add to dashboard Cite

Objective This study explores how negative affect, perceived net equity, and uncertainty influence the public's privacy decision-making regarding the adoption of contact-tracing technology based on artificial intelligence (AI) during the COVID-19 pandemic. Methods Four hundred and eighteen adults in the US participated in the study via Amazon Mechanical Turk in August 2020. Statistical analyses were performed using the PROCESS macro. Indirect effects and their significance were estimated using bias-corrected bootstrap confidence intervals (CIs) with resampling set to n = 5000. Results Perceived net equity was positively associated with low levels of perceived uncertainty regarding a COVID-19 contact-tracing application and intention to adopt it. Low levels of perceived uncertainty were positively associated with intentions to adopt such an application, thereby suggesting that a perceived level of uncertainty mediates the association between perceived net equity and adoption intentions. Anxieties regarding AI technology and COVID-19 risks both moderate the associations among perceived net equity, perceived level of uncertainty, and intentions to adopt the contact-tracing technology. Conclusions Our findings highlight how the differing sources of emotion influence the associations among rational judgment, perceptions, and decision-making about new contact-tracing technology. Overall, the results suggest that both rational judgments and affective reactions to risks are important influencers of individuals’ perceptions and privacy-related decision-making regarding a new health technology during the pandemic.

show abstract

“…In general, whether people have trust in government exerts huge impacts on their attitudes and adoption willingness towards contact tracing apps distributed by government (Bengio et al, 2020; Hargittai et al, 2020). Specifically, trust is pivotal to mitigating people's perceived privacy risks attached to contact tracing apps, thereby leading to increase in adoption rate (Duan and Deng, 2022). This role of trust is also evident in the context of HCAs from the CI perspective.…”

Section: Contextual Integrity In the Use Of Hcasmentioning

confidence: 99%

Privacy at risk? Understanding the perceived privacy protection of health code apps in China

Huang

Chen

2022

Big Data & Society

View full text Add to dashboard Cite

As a key constituent of China's approach to fighting COVID-19, Health Code apps (HCAs) not only serve the pandemic control imperatives but also exercise the agency of digital surveillance. As such, HCAs pave a new avenue for ongoing discussions on contact tracing solutions and privacy amid the global pandemic. This article attends to the perceived privacy protection among HCA users via the lens of the contextual integrity theory. Drawing on an online survey of adult HCA users in Wuhan and Hangzhou (N = 1551), we find users’ perceived convenience, attention towards privacy policy, trust in government, and acceptance of government purposes regarding HCA data management are significant contributors to users’ perceived privacy protection in using the apps. By contrast, users’ frequency of mobile privacy protection behaviors has limited influence, and their degrees of perceived protection do not vary by sociodemographic status. These findings shed new light on China's distinctive approach to pandemic control with respect to the state's expansion of big data-driven surveillance capacity. Also, the findings foreground the heuristic value of contextual integrity theory to examine controversial digital surveillance in non-Western contexts. Put tougher, our findings contribute to the thriving scholarly conversations around digital privacy and surveillance in China, as well as contact tracing solutions and privacy amid the global pandemic.

show abstract

Exploring privacy paradox in contact tracing apps adoption

Cited by 30 publications

References 60 publications

The role of institutional and self in the formation of trust in artificial intelligence technologies

The role of institutional and self in the formation of trust in artificial intelligence technologies

The role of uncertainty and affect in decision-making on the adoption of AI-based contact-tracing technology during the COVID-19 pandemic

Privacy at risk? Understanding the perceived privacy protection of health code apps in China

Contact Info

Product

Resources

About