Framework Of Contextual Integrity Research Articles

A contextual integrity approach to genomic information: what bioethics can learn from big data ethics.

Genomic data is generated, processed and analysed at an increasingly rapid pace. This data is not limited to the medical context, but plays an important role in other contexts in society, such as commercial DNA testing, the forensic setting, archaeological research, and genetic surveillance. Genomic information also crosses the borders of these domains, e.g. forensic use of medical genetic information, insurance use of medical genomic information, or research use of commercial genomic data. This paper (1) argues that an informed consent approach for genomic information has limitations in many societal contexts, and (2) seeks to broaden the bioethical debate on genomic information by suggesting an approach that is applicable across multiple societal contexts. I argue that the contextual integrity framework, a theory rooted in information technology and big data ethics, is an effective tool to explore ethical challenges that arise from genomic information within a variety of different contexts. Rather than focusing on individual control over information, the contextual integrity approach holds that information should be shared and protected according to the norms that govern certain distinct social contexts. Several advantages of this contextual integrity approach will be discussed. The paper concludes that the contextual integrity framework helps to articulate and address a broad spectrum of ethical, social, and political factors in a variety of different societal contexts, while giving consideration to the interests of individuals, groups, and society at large.

A Roadmap for Applying the Contextual Integrity Framework in Qualitative Privacy Research

Privacy is an important topic in HCI and social computing research, and the theory of contextual integrity (CI) is increasingly used to understand how sociotechnical systems-and the new kinds of information flows they introduce-can violate privacy. In empirical research, CI can serve as a conceptual framework for explaining the contextual nature of privacy as well as an analytical framework for evaluating privacy attitudes and behaviors. Analytical applications of CI in HCI primarily employ quantitative methods to identify appropriate information flows but rarely engage with the full CI framework to evaluate such flows. In this paper, we present a roadmap to guide HCI and social computing researchers on how to apply the full CI framework to qualitative projects. To help researchers envision what such an analysis can look like, each step includes an example analysis using interview data from projects on privacy and fitness tracking. We conclude by discussing how harnessing the full CI framework can address critiques of CI and identify opportunities for further theory development.

Comprehensive evaluation of privacy policies using the contextual integrity framework

AbstractOnline privacy policies are often lengthy and difficult to understand. This may lead many users to avoid reading them despite increasing concerns about how their personal information is managed. This article presents a structured approach to evaluate the transparency and comprehensiveness of privacy policies using a comprehensive set of evaluation questions within the contextual integrity (CI) framework. We use these questions to identify policies' responses to key privacy concerns. Applying the CI framework, we analyze the clarity and context of these responses, identifying any vagueness and contextual issues that could impede a user's understanding of the privacy policy. Using the CI analysis, we quantify the quality of policies' responses, thereby enabling users to make informed decisions about online services or products. We apply our methodology to two popular messaging apps, Telegram and WhatsApp, using them as case studies to systematically uncover the strengths and weaknesses of their privacy policies. The findings demonstrate that our proposed methodology can effectively identify transparency issues and assess the comprehensiveness of privacy policies. This suggests that our approach could serve as a practical alternative to subjective evaluations typically conducted by privacy experts.

Trust TEE?: Exploring the Impact of Trusted Execution Environments on Smart Home Privacy Norms

IoT devices like smart cameras and speakers provide convenience but can collect sensitive information within private spaces. While research has investigated user perception of comfort with information flows originating from these types of devices, little focus has been given to the role of the sensing hardware in influencing these sentiments. Given the proliferation of trusted execution environments (TEEs) across commodity- and server-class devices, we surveyed 1049 American adults using the Contextual Integrity framework to understand how the inclusion of cloud-based TEEs in IoT ecosystems may influence comfort with data collection and use. We find that cloud-based TEEs significantly increase user comfort across information flows. These increases are more pronounced for devices manufactured by smaller companies and show that cloud-based TEEs can bridge the previously-documented gulfs in user trust between small and large companies. Sentiments around consent, bystander data, and indefinite retention are unaffected by the presence of TEEs, indicating the centrality of these norms.

The public good and public attitudes toward data sharing through IoT

AbstractThe Internet of Things (IoT) has potential to deliver important benefits for IoT users, society and public good. How do citizens feel about sharing data from personal devices compared with “smart city” data collection in public spaces, with government and nongovernmental organizations, and across different situations? What predicts willingness to share their data with government? Through a nationally representative survey of over 2000 US respondents as well as interviews, we explore the willingness of citizens to share their data in various circumstances, using the contextual integrity framework, the literature on the “publicness” of organizations, and public value creation. Across different contexts, from half to 2/3 of survey respondents were willing to share data from their own IoT devices for public benefits, and 80%−93% supported the use of sensors in public places for a variety of collective purposes. Trust in government was significantly related to data sharing and support for smart city data collection. Yet government in the United States is less trusted with this data than other organizations with public purposes, such as nonprofits. Cultivating trust through transparent and responsible data stewardship will be important for future use of IoT data for public good.

Session replay scripts: A privacy analysis

Session replay scripts record a user’s actions while visiting a website or using a computer application. These recordings are typically sent to third party companies whose stated purpose is to analyze the recordings to help correct bottlenecks and illuminate problems that are difficult for users to navigate. We examine how session replay scripts are being marketed and how they are used by application developers. The extent of gathered data is intrusive, often going beyond the stated objectives, and often collected without users’ knowledge. Using Nissenbaum’s privacy as contextual integrity framework, we demonstrate how replay scripts violate the norms of both appropriateness and distribution, and hence the privacy of the user. We examine two scenarios: one where the session replay data are sent back to the application developer, and another where captured data are sent to third party companies. We compare the scenarios to two analogous situations: surveys taken at a museum and video surveillance in a brick-and-mortar store. We analyze in detail the case of FullStory, a vendor of session replay scripts. In conclusion, we offer suggestions on how to preserve private information in both scenarios.

‘A right to be forgotten’: retrospective privacy concerns in social networking services

ABSTRACT To gain a heuristic understanding of the temporal dimension of privacy, we propose the concept of retrospective privacy concerns and explore its antecedents, through the lens of contextual integrity framework. We collected 276 respondents and then conducted partial least squares to test our hypotheses. The results show life change experiences and information relevance impact retrospective impression management concerns, which, in turn, exert an effect on retrospective privacy concerns. Information dissemination regarding sharing information to only selected friends perceived higher level of control than sharing information to all friends, while perceived control could enhance retrospective privacy concerns. Also, users who feel under surveillance would be concerned about their retrospective privacy. Moreover, we verify the effect of time on retrospective privacy concerns and information relevance. This work provides new insight into the temporal dimension of privacy and offers practical implications for designing temporal privacy tools to mitigate users’ concerns.

Applying a Contextual Integrity Framework to Privacy Policies for Smart Technologies

ABSTRACT This research anticipates a future where “smart cities” rely extensively on data analytics to determine budget allocations, to manage traffic, to design infrastructure, and to advance sustainability efforts. In this study, Helen Nissenbaum's contextual integrity framework helps us understand how smart city residents consider privacy norms, and provides a structure for comparing these norms to current data privacy practices. The study findings and policy recommendations are based on focus group discussions with more than 80 residents of Long Beach, California, as well as 60 responses to an open-ended question asked in a smart city survey.

On Making Ethical Choices in Ethnographic Research into (Young) People’s Mediated Intimacy: A Research Note

ABSTRACT People’s intimate life-worlds are increasingly taking place in networked media spaces such as social media, smartphone applications and virtual reality environments. For (digital) ethnographers, it becomes crucial to understand people’s intense intimate attachments to mediated spaces. Many researchers are already exploring networked media spaces’ affects; what opportunities they offer for people’s intimacies as well as the, albeit hidden, damage they may bring. However, there are many challenges for qualitative researchers to operate ethically when inquiring into people’s intimate life-worlds in networked media spaces. A framework of contextual integrity needs to consider what it means to live a personal life in deeply mediatised contexts. For an ethnographic researcher, being present in the intimate networked media spaces of research subjects, means tapping into affective networks. Responsible researchers should therefore understand the contextual affective dynamics and affordances of these networked media spaces; this implies understanding what it means to be present as a researcher and what the implications are of this presence.

Applying contextual integrity to digital contact tracing and automated triage for hospitals during COVID-19

To control and minimise the spread of COVID-19, various technological solutions have been proposed. In this research, we focus on digital contact tracing and automated triage for hospitals. We conducted an online survey in Flanders (N = 1708) to investigate the perceived appropriateness of these systems based on the Contextual Integrity framework, as developed by Nissenbaum [1]. For digital contact tracing, significant differences were found between the appropriateness of using various types of data for different goals. Precise individual location data (i.e. GPS) was considered to be least appropriate and much less appropriate than proximity data (i.e. Bluetooth) or coarser location data (i.e. GSM). Goals for digital contact tracing with a high individual impact were considered to be less appropriate than goals with a low individual or societal impact. In addition, the data showed that respondents would find the usage of digital contact tracing to be less appropriate after the pandemic, underlining the temporality of this technological solution. For automated triage, the results indicated that gender is perceived to be significantly less appropriate than the other types of data, including age, to determine the priority of treatment.

Surveillance and privacy – Beyond the panopticon. An exploration of 720-degree observation in level 3 and 4 vehicle automation

On the path to high-level vehicle automation, the degree of surveillance both inside and outside the car increases significantly. Consequently, ethical considerations are becoming central to questions around surveillance regimes and data privacy implicit in level 3 and 4 vehicle automation. In this paper, we focus on outputs from the EU Horizon 2020 project Vision Inspired Driver Assistance Systems (VI-DAS). In particular, we assess the VI-DAS 720-degree observation technology, critical to ensuring a safe Human Machine Interaction (HMI), from multiple theoretical perspectives to contribute to a better understanding of the phenomena of privacy. As a synonym for surveillance, we started our evaluation with Bentham's ideation of the panopticon. From there, it is a relatively short step to radical Foucauldian critiques that offered more dystopian technologies of power. However, both theorems demonstrate a limited understanding of the issue of data privacy in the context of safe transportation along the evolution of highly automated vehicles. Thus, to allow the debate to move beyond more binary discussions on privacy versus control/power and to a certain degree escape the shadow of the panopticon, we applied the Nissenbaum four theses framework of Contextual Integrity (CI). Her decision heuristic allowed us to introduce structure and a degree of precision in our thinking on the matter of privacy that represents a step forward to phenomena of privacy in a specific context. Our approach concludes that the VI-DAS 720-degree observation technology can respect the user's privacy through an appropriate flow of personal information. However, the flows of personal data must be strongly regulated to ensure that data is seen as a value in terms of a commodity to protect human life and not seen as an asset that needs to be turned into value in terms of capital or the facilitation of asymmetric power-relations.

Investigating privacy concerns related to mobile augmented reality Apps – A vignette based online experiment

Augmented reality (AR) gained much public attention after the success of Pokémon Go in 2016, and has found application in online games, social media, interior design, and other services since then. AR is highly dependent on various different sensors gathering real time context-specific personal information about the users causing more severe and new privacy threats compared to other technologies. These threats have to be investigated as long as AR is still shapeable in order to ensure users’ privacy and foster market adoption of privacy-friendly AR systems.To provide viable recommendations regarding the design of privacy-friendly AR systems, we follow a user-centric approach and investigate the role and causes of privacy concerns within the context of mobile AR (MAR) apps. We design a vignette-based online experiment adapting ideas from the framework of contextual integrity to analyze drivers of privacy concerns related to MAR apps, such as characteristics of permissions, trust-evoking signals, and AR-related contextual factors. The results of the large-scale experiment with 1,100 participants indicate that privacy concerns are mainly determined by the sensitivity of app permissions (i.e., whether sensitive resources on the smartphone are accessed) and the number of prior app downloads. Furthermore, we devise detailed practical and theoretical implications for developers, regulatory authorities and future research.

Applying a Contextual Integrity Framework to Privacy Policies for Smart Technologies

This research anticipates a future where “smart cities” rely extensively on data analytics to determine budget allocations, to manage traffic, to design infrastructure and to advance sustainability efforts. In this study, Helen Nissenbaum's contextual integrity framework helps us understand how smart city residents consider privacy norms, and provides a structure for comparing these norms to current data privacy practices. The study findings and policy recommendations are based on focus group discussions with more than 80 residents of Long Beach, Calif., as well as responses to open-ended questions in a survey completed by about 200 survey respondents.

Strengthening Children’s Privacy Literacy through Contextual Integrity

Researchers and policymakers advocate teaching children about digital privacy, but privacy literacy has not been theorized for children. Drawing on interviews with 30 families, including 40 children, we analyze children’s perspectives on password management in three contexts—family life, friendship, and education—and develop a new approach to privacy literacy grounded in Nissenbaum’s contextual integrity framework. Contextual integrity equates privacy with appropriate flows of information, and we show how children’s perceptions of the appropriateness of disclosing a password varied across contexts. We explain why privacy literacy should focus on norms rather than rules and discuss how adults can use learning moments to strengthen children’s privacy literacy. We argue that equipping children to make privacy-related decisions serves them better than instructing them to follow privacy-related rules.

Context-Relative Norms Determine the Appropriate Type of Consent in Clinical Biobanks: Towards a Potential Solution for the Discrepancy between the General Data Protection Regulation and the European Data Protection Board on Requirements for Consent

Clinical biobanks processing data of participants in the European Union (EU) fall under the scope of the General Data Protection Regulation (GDPR), which among others includes requirements for consent. These requirements are further specified by the Article 29 Working Party (WP29)—an EU advisory body currently known as the European Data Protection Board (EDPB). Unfortunately, their guidance is cause for some confusion. While the GDPR allows participants to give broad consent for research when specific research purposes are still unknown, the WP29 guidelines suggest that additional consent for specific uses should be obtained in addition to broad consent when this becomes applicable. This discrepancy elicits the question whether clinical biobanks can fail the requirement of consent if they obtain broad consent, but not a specific consent for each biomedical study. We analysed this discrepancy within the framework of contextual integrity, in order to describe the context-relative informational norms that govern information flows in clinical biobanks. However, our analysis demonstrates that there is no uniform set of norms that can be applied to all clinical biobanks. As such, neither the GDPR nor the WP29 guidance can act as a “one size fits all” approach to all clinical biobanks. Rather, differences between clinical biobanks—especially regarding the scientific aims and patient populations—make the case for context-relative norms that determine the appropriate type of consent.

School Surveillance in Context: High School Students’ Perspectives on CCTV, Privacy, and Security

This study examines high school students’ perceptions of school closed-circuit television systems (CCTVs). It draws on interviews conducted with 83 adolescents recruited from 10th- to 12th-grade classes at 39 Israeli schools. The findings indicate that students’ perceptions of CCTVs are embedded in their overall opinions about their school, particularly concerning relationships and trust between students and educators. The various metaphors that students used to describe their relational position regarding school CCTVs highlight that surveillance has become part of the organizational–educational experience. The findings also show that students’ scrutiny of school CCTVs reflects a conflict between privacy and security concerns. Students resolve this conflict by resorting to various balances, which echo general constitutional principles but were also anchored in the students’ personal schooling experiences. While building on Nissenbaum’s framework of contextual integrity for assessing privacy violations, we challenge its assumption of a uniform set of informational norms within a given context.

School Surveillance in Context: High School Students’ Perspectives on CCTV, Privacy, and Security

This study examines high school students’ perceptions of school closed-circuit television systems (CCTVs). It draws on interviews conducted with 83 adolescents recruited from 10th to 12th-grade classes at 39 Israeli schools. The findings indicate that students’ perceptions of CCTVs are embedded in their overall opinions about their school, particularly concerning relationships and trust between students and educators. The various metaphors that students used to describe their relational position regarding school CCTVs highlight that surveillance has become part of the organizational-educational experience. The findings also show that students’ scrutiny of school CCTVs reflects a conflict between privacy and security concerns. Students resolve this conflict by resorting to various balances, which echo general constitutional principles, but were also anchored in the students’ personal schooling experiences. While building on Helen Nissenbaum’s framework of Contextual Integrity for assessing privacy violations, we challenge its assumption of a uniform set of informational norms within a given context. Final version available (Open Access) at https://journals.sagepub.com/doi/full/10.1177/0044118X20916617

Disaster privacy/privacy disaster

AbstractPrivacy expectations during disasters differ significantly from nonemergency situations. This paper explores the actual privacy practices of popular disaster apps, highlighting location information flows. Our empirical study compares content analysis of privacy policies and government agency policies, structured by the contextual integrity framework, with static and dynamic app analysis documenting the personal data sent by 15 apps. We identify substantive gaps between regulation and guidance, privacy policies, and information flows, resulting from ambiguities and exploitation of exemptions. Results also indicate gaps between governance and practice, including the following: (a) Many apps ignore self‐defined policies; (b) while some policies state they “might” access location data under certain conditions, those conditions are not met as 12 apps included in our study capture location immediately upon initial launch under default settings; and (c) not all third‐party data recipients are identified in policy, including instances that violate expectations of trusted third parties.

Going against the (Appropriate) Flow: A Contextual Integrity Approach to Privacy Policy Analysis

We present a method for analyzing privacy policies using the framework of contextual integrity (CI). This method allows for the systematized detection of issues with privacy policy statements that hinder readers’ ability to understand and evaluate company data collection practices. These issues include missing contextual details, vague language, and overwhelming possible interpretations of described information transfers. We demonstrate this method in two different settings. First, we compare versions of Facebook’s privacy policy from before and after the Cambridge Analytica scandal. Our analysis indicates that the updated policy still contains fundamental ambiguities that limit readers’ comprehension of Facebook’s data collection practices. Second, we successfully crowdsourced CI annotations of 48 excerpts of privacy policies from 17 companies with 141 crowdworkers. This indicates that regular users are able to reliably identify contextual information in privacy policy statements and that crowdsourcing can help scale our CI analysis method to a larger number of privacy policy statements.

Closed Circuit Television Systems on University Campuses: Unexamined Implications for the Expectation of Privacy and Academic Freedom

Since 9/11 and particularly since the massacre at Virginia Tech University in 2007, many universities in the United States have begun installation of Closed Circuit Television (CCTV) systems on their campuses. What sorts of claims are being made about the use of these systems and what justifications are there for installing them? How might the pervasive use of monitoring technology affect traditional values associated with university life such as freedom of speech, freedom of assembly, privacy, and the freedom to explore? What policies are in place to ensure that whatever benefits associated with these systems justify both tangible and intangible costs?Our analysis is partially derived from a study of university policies in the United States concerning the installation and operation of CCTV systems with the aim of gaining insight into these questions. In addition, we used a coding instrument for analyzing the corpus of policies in order to understand how the policies addressed such issues as: rationale or justification for CCTV usage, relevant personnel roles, public awareness, accountability measures, information security and data handling, routine operations of usage, and any relevant limiting measures. One aspect of our study is to interpret the corpus of policies through the lens of Nissenbaum’s contextual integrity framework which is concerned with examining the effects of new technological practices (such as the installation of CCTV systems) on one’s expectation of privacy.