Towards a seamful ethics of Covid-19 contact tracing apps?

Hoffman, Andrew S.; Jacobs, Bart; Gastel, Bernard van; Schraffenberger, Hanna; Sharon, Tamar; Pas, Berber

doi:10.1007/s10676-020-09559-7

Cited by 25 publications

(20 citation statements)

References 12 publications

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“…When a user indicates a positive test result, all users within 3 traversals of the time series graph are notified. A few more research papers have used the QR code approach [16][17][18]. Moreover, the smartphones' GPS can be used to track users in the outdoor environments [19].…”

Section: Contact Tracingmentioning

confidence: 99%

Wi-Fi and Bluetooth Contact Tracing Without User Intervention

Yuen¹,

Bie²,

Cairns³

et al. 2022

Preprint

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A custom Wi-Fi and Bluetooth indoor contact tracing system is created to find detailed paths of infected individuals without any user intervention. The system tracks smartphones, but it does not require smartphone applications, connecting to the routers, or any other extraneous devices on the users. A custom Turtlebot3 is used for site surveying, where it simulates mobile device movement and packet transmission. Transmit power, receive power, and round trip time are collected by a custom ESP32C3 router. MAC randomization is defeated to identify unique smartphones. Subsequently, the wireless parameters above are converted to signal path loss and time of flight. Bidirectional long short term memory takes the wireless parameters and predicts the detailed paths of the users within 1 m. Public health authorities can use the contact tracing website to find the detailed paths of the suspected cases using the smartphone models and initial positions of confirm cases. The system can also track indirect contact transmissions originating from surfaces and droplets due to having absolute positions of users.

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Section: Contact Tracingmentioning

confidence: 99%

Wi-Fi and Bluetooth Contact Tracing Without User Intervention

Yuen¹,

Bie²,

Cairns³

et al. 2022

Preprint

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“…While a definition of what can be considered contact in the context of COVID-19 is still evolving [57], active algorithmic contact tracing commonly uses physical proximity and duration of exposure [58] as an approximation. Data gathered for algorithmic contact tracing commonly takes one of three forms: (1) proactively reported data (ie, manual digital check-ins that require participants' compliance [59]), (2) active sensor data (ie, information about an encounter with a different device utilizing the same tracing app), and (3) passive sensor data (ie, information about the geographic position of the device). These are commonly generated by devices using Bluetooth, including Bluetooth Low Energy; GPS; and Wi-Fi signal strength information [60].…”

Section: Overview Of Conventional and Algorithmic Contact Tracing Approachesmentioning

confidence: 99%

Test, Trace, and Put on the Blockchain?: A Viewpoint Evaluating the Use of Decentralized Systems for Algorithmic Contact Tracing to Combat a Global Pandemic

Platt

Hasselgren

Román-Belmonte

et al. 2021

JMIR Public Health Surveill

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The enormous pressure of the increasing case numbers experienced during the COVID-19 pandemic has given rise to a variety of novel digital systems designed to provide solutions to unprecedented challenges in public health. The field of algorithmic contact tracing, in particular, an area of research that had previously received limited attention, has moved into the spotlight as a crucial factor in containing the pandemic. The use of digital tools to enable more robust and expedited contact tracing and notification, while maintaining privacy and trust in the data generated, is viewed as key to identifying chains of transmission and close contacts, and, consequently, to enabling effective case investigations. Scaling these tools has never been more critical, as global case numbers have exceeded 100 million, as many asymptomatic patients remain undetected, and as COVID-19 variants begin to emerge around the world. In this context, there is increasing attention on blockchain technology as a part of systems for enhanced digital algorithmic contact tracing and reporting. By analyzing the literature that has emerged from this trend, the common characteristics of the designs proposed become apparent. An archetypal system architecture can be derived, taking these characteristics into consideration. However, assessing the utility of this architecture using a recognized evaluation framework shows that the added benefits and features of blockchain technology do not provide significant advantages over conventional centralized systems for algorithmic contact tracing and reporting. From our study, it, therefore, seems that blockchain technology may provide a more significant benefit in other areas of public health beyond contact tracing.

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“…Alongside this, the development of contact tracing apps raised heated debate about possible intrusions of privacy and concerns about increased surveillance (Sharon 2020 ; Wienroth et al 2020 ), including concerns about who would have access to the data collected via these apps and the re-purposing of the data for other uses (Anderson 2020 ). Concerns were also raised that app usage could reinforce digital divides, exacerbate inequalities, and/or discriminate against certain groups (AdaLovelace Institute 2020a , b ; Gasser et al 2020 ; Kahn et al 2020 ; Morley et al 2020 ; NHSX app Ethics Advisory Board 2020 ).…”

Section: Introductionmentioning

confidence: 99%

Ecologies of Public Trust: The NHS COVID-19 Contact Tracing App

et al. 2021

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In April 2020, close to the start of the first U.K. COVID-19 lockdown, the U.K. government announced the development of a COVID-19 contact tracing app, which was later trialled on the U.K. island, the Isle of Wight, in May/June 2020. United Kingdom surveys found general support for the development of such an app, which seemed strongly influenced by public trust. Institutions developing the app were called upon to fulfil the commitment to public trust by acting with trustworthiness. Such calls presuppose that public trust associated with the app can emerge if the conditions for trustworthiness are met and that public trust is simplistic, i.e., linearly the sum of each member of the publics’ individual – U.K. government trust relationship. Drawing on a synthesis of the trust literature and fifteen interviews with members of the public trialling the app on the Isle of Wight, this paper aims to explore what trust mechanisms and relationships are at play when thinking about public trust in the context of the U.K. COVID-19 app. We argue that public trust is a complex social phenomenon and not linearly correlated with institutional trustworthiness. As such, attention needs to widen from calls for trustworthy infrastructures as a way to build public trust, to a deeper understanding of those doing the trusting; in particular, what or whom do people place their trust in (or not) when considering whether using the app and why. An understanding of this will help when trying to secure public trust during the implementation of necessary public health measures.

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Towards a seamful ethics of Covid-19 contact tracing apps?

Cited by 25 publications

References 12 publications

Wi-Fi and Bluetooth Contact Tracing Without User Intervention

Wi-Fi and Bluetooth Contact Tracing Without User Intervention

Test, Trace, and Put on the Blockchain?: A Viewpoint Evaluating the Use of Decentralized Systems for Algorithmic Contact Tracing to Combat a Global Pandemic

Ecologies of Public Trust: The NHS COVID-19 Contact Tracing App

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