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Digital technologies: tensions in privacy and data.

ABSTRACT: Driven by data proliferation, digital technologies have transformed the marketing landscape. In parallel, significant privacy concerns have shaken consumer-firm relationships, prompting changes in both regulatory interventions and people's own privacy-protective behaviors. With a comprehensive analysis of digital technologies and data strategy informed by structuration theory and privacy literature, the authors consider privacy tensions as the product of firm-consumer interactions, facilitated by digital technologies. This perspective in turn implies distinct consumer, regulatory, and firm responses related to data protection. By consolidating various perspectives, the authors propose three tenets and seven propositions, supported by interview insights from senior managers and consumer informants, that create a foundation for understanding the digital technology implications for firm performance in contexts marked by growing privacy worries and legal ramifications. On the basis of this conceptual framework, they also propose a data strategy typology across two main strategic functions of digital technologies: data monetization and data sharing. The result is four distinct types of firms, which engage in disparate behaviors in the broader ecosystem pertaining to privacy issues. This article also provides directions for research, according to a synthesis of findings from both academic and practical perspectives.

SUBMITTER: Quach S

PROVIDER: S-EPMC8897618 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:ObjectivesTo survey international regulatory frameworks that serve to protect privacy of personal data as a human right as well as to review the literature regarding privacy protections and data ownership in mobile health (mHealth) technologies between January 1, 2016 and June 1, 2019 in order to identify common themes.MethodsWe performed a review of relevant literature available in English published between January 1, 2016 and June 1, 2019 from databases including PubMed, Google Scholar, and Web of Science, as well as relevant legislative background material. Articles out of scope (as detailed below) were eliminated. We categorized the remaining pool of articles and discrete themes were identified, specifically: concerns around data transmission and storage, including data ownership and the ability to re-identify previously de-identified data; issues with user consent (including the availability of appropriate privacy policies) and access control; and the changing culture and variable global attitudes toward privacy of health data.ResultsRecent literature demonstrates that the security of mHealth data storage and transmission remains of wide concern, and aggregated data that were previously considered "de-identified" have now been demonstrated to be re-identifiable. Consumer-informed consent may be lacking with regard to mHealth applications due to the absence of a privacy policy and/or to text that is too complex and lengthy for most users to comprehend. The literature surveyed emphasizes improved access control strategies. This survey also illustrates a wide variety of global user perceptions regarding health data privacy.ConclusionThe international regulatory framework that serves to protect privacy of personal data as a human right is diverse. Given the challenges legislators face to keep up with rapidly advancing technology, we introduce the concept of a "healthcare fiduciary" to serve the best interest of data subjects in the current environment.

Project description:BackgroundThe collection, storage, and analysis of large data sets are relevant in many sectors. Especially in the medical field, the processing of patient data promises great progress in personalized health care. However, it is strictly regulated, such as by the General Data Protection Regulation (GDPR). These regulations mandate strict data security and data protection and, thus, create major challenges for collecting and using large data sets. Technologies such as federated learning (FL), especially paired with differential privacy (DP) and secure multiparty computation (SMPC), aim to solve these challenges.ObjectiveThis scoping review aimed to summarize the current discussion on the legal questions and concerns related to FL systems in medical research. We were particularly interested in whether and to what extent FL applications and training processes are compliant with the GDPR data protection law and whether the use of the aforementioned privacy-enhancing technologies (DP and SMPC) affects this legal compliance. We placed special emphasis on the consequences for medical research and development.MethodsWe performed a scoping review according to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews). We reviewed articles on Beck-Online, SSRN, ScienceDirect, arXiv, and Google Scholar published in German or English between 2016 and 2022. We examined 4 questions: whether local and global models are "personal data" as per the GDPR; what the "roles" as defined by the GDPR of various parties in FL are; who controls the data at various stages of the training process; and how, if at all, the use of privacy-enhancing technologies affects these findings.ResultsWe identified and summarized the findings of 56 relevant publications on FL. Local and likely also global models constitute personal data according to the GDPR. FL strengthens data protection but is still vulnerable to a number of attacks and the possibility of data leakage. These concerns can be successfully addressed through the privacy-enhancing technologies SMPC and DP.ConclusionsCombining FL with SMPC and DP is necessary to fulfill the legal data protection requirements (GDPR) in medical research dealing with personal data. Even though some technical and legal challenges remain, for example, the possibility of successful attacks on the system, combining FL with SMPC and DP creates enough security to satisfy the legal requirements of the GDPR. This combination thereby provides an attractive technical solution for health institutions willing to collaborate without exposing their data to risk. From a legal perspective, the combination provides enough built-in security measures to satisfy data protection requirements, and from a technical perspective, the combination provides secure systems with comparable performance with centralized machine learning applications.

Project description:BackgroundAlong with the proliferation of health information technologies (HITs), there is a growing need to understand the potential privacy risks associated with using such tools. Although privacy policies are designed to inform consumers, such policies have consistently been found to be confusing and lack transparency.ObjectiveThis study aims to present consumer preferences for accessing privacy information; develop and apply a privacy policy risk assessment tool to assess whether existing HITs meet the recommended privacy policy standards; and propose guidelines to assist health professionals and service providers with understanding the privacy risks associated with HITs, so that they can confidently promote their safe use as a part of care.MethodsIn phase 1, participatory design workshops were conducted with young people who were attending a participating headspace center, their supportive others, and health professionals and service providers from the centers. The findings were knowledge translated to determine participant preferences for the presentation and availability of privacy information and the functionality required to support its delivery. Phase 2 included the development of the 23-item privacy policy risk assessment tool, which incorporated material from international privacy literature and standards. This tool was then used to assess the privacy policies of 34 apps and e-tools. In phase 3, privacy guidelines, which were derived from learnings from a collaborative consultation process with key stakeholders, were developed to assist health professionals and service providers with understanding the privacy risks associated with incorporating HITs as a part of clinical care.ResultsWhen considering the use of HITs, the participatory design workshop participants indicated that they wanted privacy information to be easily accessible, transparent, and user-friendly to enable them to clearly understand what personal and health information will be collected and how these data will be shared and stored. The privacy policy review revealed consistently poor readability and transparency, which limited the utility of these documents as a source of information. Therefore, to enable informed consent, the privacy guidelines provided ensure that health professionals and consumers are fully aware of the potential for privacy risks in using HITs to support health and well-being.ConclusionsA lack of transparency in privacy policies has the potential to undermine consumers' ability to trust that the necessary measures are in place to secure and protect the privacy of their personal and health information, thus precluding their willingness to engage with HITs. The application of the privacy guidelines will improve the confidence of health professionals and service providers in the privacy of consumer data, thus enabling them to recommend HITs to provide or support care.

Project description:BackgroundIn 2020, the number of internet users surpassed 4.6 billion. Individuals who create and share digital data can leave a trail of information about their habits and preferences that collectively generate a digital footprint. Studies have shown that digital footprints can reveal important information regarding an individual's health status, ranging from diet and exercise to depression. Uses of digital applications have accelerated during the COVID-19 pandemic where public health organizations have utilized technology to reduce the burden of transmission, ultimately leading to policy discussions about digital health privacy. Though US consumers report feeling concerned about the way their personal data is used, they continue to use digital technologies.ObjectiveThis study aimed to understand the extent to which consumers recognize possible health applications of their digital data and identify their most salient concerns around digital health privacy.MethodsWe conducted semistructured interviews with a diverse national sample of US adults from November 2018 to January 2019. Participants were recruited from the Ipsos KnowledgePanel, a nationally representative panel. Participants were asked to reflect on their own use of digital technology, rate various sources of digital information, and consider several hypothetical scenarios with varying sources and health-related applications of personal digital information.ResultsThe final cohort included a diverse national sample of 45 US consumers. Participants were generally unaware what consumer digital data might reveal about their health. They also revealed limited knowledge of current data collection and aggregation practices. When responding to specific scenarios with health-related applications of data, they had difficulty weighing the benefits and harms but expressed a desire for privacy protection. They saw benefits in using digital data to improve health, but wanted limits to health programs' use of consumer digital data.ConclusionsCurrent privacy restrictions on health-related data are premised on the notion that these data are derived only from medical encounters. Given that an increasing amount of health-related data is derived from digital footprints in consumer settings, our findings suggest the need for greater transparency of data collection and uses, and broader health privacy protections.

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Digital technologies: tensions in privacy and data.

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