Notice and consent in a world of Big Data

Cate, Fred H.; Mayer-Schönberger, Viktor

doi:10.1093/idpl/ipt005

Cited by 125 publications

(67 citation statements)

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“…Dit alles is gemakkelijker gezegd dan gedaan. Microsoft heeft een initiatief gesponsord om dit probleem van de bescherming van gegevens wereldwijd te bespreken (Cate & Mayer-Schönberger, 2013). Uit deze discussie komt naar voren dat licentieovereenkomsten waarschijnlijk de beste manier zijn om bescherming te bieden.…”

Section: Zeggenschap En Het Recht Te Vergetenunclassified

Het verband tussen publiek belang en ontwerp bij het internet der dingen

Butter¹,

Butter²

2016

Beleid en Maatschappij

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Section: Zeggenschap En Het Recht Te Vergetenunclassified

Het verband tussen publiek belang en ontwerp bij het internet der dingen

Butter¹,

Butter²

2016

Beleid en Maatschappij

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“…The most common privacy preservation method for web services is notice and consent [6]. Every time an individual accesses a new application or service, a notice stating privacy concerns is displayed.…”

Section: Notice and Consentmentioning

confidence: 99%

“…This method empowers an individual to ensure his privacy rights. It puts the burden of privacy preservation on the individual [6].…”

Section: Notice and Consentmentioning

confidence: 99%

“…When applied to big data, this method poses numerous challenges [6]. In most of the cases uses of big data are unexpected or unknown at the time when notice and consent is given.…”

Section: Notice and Consentmentioning

confidence: 99%

“…Another method used for ensuring consumer privacy is Notice and Consent [6]. By this method consumer information is shared only after obtaining consent from the user using a notice.…”

Section: Introductionmentioning

confidence: 99%

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Privacy Preservation in Big Data

Gosain¹,

Chugh²

2014

IJCA

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Big data has brought a revolution in the world of data analytics. Data that was discarded a few years back is now considered a powerful asset. Big data is now being extensively used for knowledge discovery by all sectors of society. It is produced by almost all digital processes and is stored, shared on web. This reliance of big data on web model poses serious security concerns. Traditional security methods cannot be applied to big data due to its large volume, variety and volume. Also since big data contains person specific information, privacy is a major security concern. The three important privacy preservation methods are: data anonymization, notice and consent and differential privacy. In this paper we discuss these privacy preservation methods for big data and how differential privacy is a better solution for big data privacy.

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Consumer Views on Privacy Protections and Sharing of Personal Digital Health Information

et al. 2023

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ImportanceDigital health information has many potential health applications, but privacy is a growing concern among consumers and policy makers. Consent alone is increasingly seen as inadequate to safeguard privacy.ObjectiveTo determine whether different privacy protections are associated with consumers’ willingness to share their digital health information for research, marketing, or clinical uses.Design, Setting, and ParticipantsThis 2020 national survey with an embedded conjoint experiment recruited US adults from a nationally representative sample with oversampling of Black and Hispanic individuals. Willingness to share digital information across 192 different scenarios reflecting the product of 4 possible privacy protections, 3 uses of information, 2 users of information, and 2 sources of digital information was evaluated. Each participant was randomly assigned 9 scenarios. The survey was administrated between July 10 and July 31, 2020, in Spanish and English. Analysis for this study was conducted between May 2021 and July 2022.Main Outcomes and MeasuresParticipants rated each conjoint profile on a 5-point Likert scale measuring their willingness to share their personal digital information (with 5 indicating the most willingness to share). Results are reported as adjusted mean differences.ResultsOf the 6284 potential participants, 3539 (56%) responded to the conjoint scenarios. A total of 1858 participants (53%) were female, 758 (21%) identified as Black, 833 (24%) identified as Hispanic, 1149 (33%) had an annual income less than $50 000, and 1274 (36%) were 60 years or older. Participants were more willing to share health information with the presence of each individual privacy protection, including consent (difference, 0.32; 95% CI, 0.29-0.35; P &lt; .001), followed by data deletion (difference, 0.16; 95% CI, 0.13-0.18; P &lt; .001), oversight (difference, 0.13; 95% CI, 0.10-0.15; P &lt; .001), and transparency of data collected (difference, 0.08; 95% CI, 0.05-0.10; P &lt; .001). The relative importance (importance weight on a 0%-100% scale) was greatest for the purpose of use (29.9%) but when considered collectively, the 4 privacy protections together were the most important (51.5%) factor in the conjoint experiment. When the 4 privacy protections were considered separately, consent was the most important (23.9%).Conclusions and RelevanceIn this survey study of a nationally representative sample of US adults, consumers’ willingness to share personal digital health information for health purposes was associated with the presence of specific privacy protections beyond consent alone. Additional protections, including data transparency, oversight, and data deletion may strengthen consumer confidence in sharing their personal digital health information.

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Notice and consent in a world of Big Data

Cited by 125 publications

References 0 publications

Het verband tussen publiek belang en ontwerp bij het internet der dingen

Het verband tussen publiek belang en ontwerp bij het internet der dingen

Privacy Preservation in Big Data

Consumer Views on Privacy Protections and Sharing of Personal Digital Health Information

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