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Open AccessJournal ArticleDOI

Pricing privacy – the right to know the value of your personal data

TLDR
If individuals are shown the “price” of their personal data, they can acquire higher awareness about their power in the digital market and thus be effectively empowered for the protection of their information privacy.
About
This article is published in Computer Law & Security Review.The article was published on 2017-09-21 and is currently open access. It has received 86 citations till now. The article focuses on the topics: Privacy policy & Personally identifiable information.

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Citations
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From user-generated data to data-driven innovation: A research agenda to understand user privacy in digital markets

TL;DR: The present study aims to provide a comprehensive understanding of the main challenges related to user privacy that affect DDI, and identifies 14 topics related to the study of DDI and UGD strategies.
Journal ArticleDOI

Competitive Data Trading Model With Privacy Valuation for Multiple Stakeholders in IoT Data Markets

TL;DR: A competitive data trading model that consists of data providers who weigh the value between privacy protection and valuation as well as other business stakeholders is proposed that maximizes the profits of business stakeholders while satisfying all market participants.
Journal ArticleDOI

Personal Data Trading Scheme for Data Brokers in IoT Data Marketplaces

TL;DR: An optimized trading model for data brokers who buy personal data with proper incentives based on the WTS, and they sell valuable information from the refined dataset by considering the WTB and the dataset quality is proposed.
Journal ArticleDOI

Blockchain: The operating system of smart cities

TL;DR: The potential of Blockchain as a technology for enabling sustainable future cities and empowering citizen co-creation and participation, promoting civic engagement and achieving Smart Cities' efficiency and transparency objectives is explored.
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Governing online platforms: Competition policy in times of platformization

TL;DR: In this article, the authors argue that a paradigmatic change in competition policy is needed and empirically under way to cope with the challenges posed by economically strong online platforms and their big-data-based business models.
References
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Journal ArticleDOI

Private traits and attributes are predictable from digital records of human behavior

TL;DR: It is shown that easily accessible digital records of behavior, Facebook Likes, can be used to automatically and accurately predict a range of highly sensitive personal attributes including: sexual orientation, ethnicity, religious and political views, personality traits, intelligence, happiness, use of addictive substances, parental separation, age, and gender.
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Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy

TL;DR: Cathy O’Neil’s Weapons of Math Destruction is a timely reminder of the power and perils of predictive algorithms and model-driven decision processes and speaks forcefully to the cultural moment the authors share.
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Why a Right to Explanation of Automated Decision-Making Does Not Exist in the General Data Protection Regulation

TL;DR: The problems show that the GDPR lacks precise language as well as explicit and well-defined rights and safeguards against automated decision-making, and therefore runs the risk of being toothless.
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What Is Privacy Worth

TL;DR: In this article, the authors use a field experiment informed by behavioral economics and decision research to investigate individual privacy valuations and find evidence of endowment and order effects, which highlight the sensitivity of privacy valuation to contextual, nonnormative factors.
Journal ArticleDOI

Why a right to explanation of automated decision-making does not exist in the General Data Protection Regulation

TL;DR: In this paper, the authors propose a number of legislative and policy steps that, if taken, may improve the transparency and accountability of automated decision-making when the GDPR comes into force in 2018.
Related Papers (5)
Frequently Asked Questions (9)
Q1. How much would a personalised advertisement cost?

According to industry sources, 1000 personalised advertisements on Facebook mobile would cost approximately 50 cents and about one dollar for the desktop version of Facebook. 

Informing consumers about prices is a very effective way to increase attention of consumers while reading pre-contractual information papers and so to increase consumers’ awareness. 

By answering questions on demographics, family & health, property, activities and consumer characteristics, a person can calculate the value of his or her personal data. 

The impact assessment of the proposed directive clarifies that the extended scope is consistent with the existing personal data protection framework, which recognises the high importance and value of personal data and that “it does not overlap with data protection rules”. 

It is obvious that this proposed right to know the value of your personal data also entails several practical problems (such as choosing a pricing method, issues regarding control and consent and issues regarding governance and enforcement) and moral problems (such as the commodification of inalienable and non-negotiable human rights and the potential reinforcement of existing disparities in society). 

Checking whether pricing information was provided correctly is something that can be checked by comparing prices with similar organisations and that can be realised with the investigative and corrective powers that Data Protection Authorities have under articles 31 and 58 of the GDPR. 

For instance, several sensitive characteristics, such as those referring to ethnicity, religion, health, union membership, politics, criminal records, substance abuse and sexual preferences, are more ‘telling’ about people. 

people may change their interests over time, sometimes gradually (for instance, when they grow older), sometimes immediately (for instance, when they have big life events, like getting married, getting children, facing serious diseases, etc.). 

A typical example of the second type of use cases are music platforms, like Spotify, where users can access nearly all kind of songs or music pieces at high quality, even if protected by copyright, for free.