When the mobile app is free, the product is your personal data

Polykalas, Spyros E.; Prezerakos, George N.

doi:10.1108/dprg-11-2018-0068

Cited by 20 publications

(22 citation statements)

References 103 publications

(158 reference statements)

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“…Transformative effects Algorithmic activities, like profiling, can lead to challenges for autonomy and informational privacy. For example, Polykalas & Prezerakos, 2019 examined the level of access required to personal data by more than 1000 apps listed in the 'most popular' free and paid for categories on the Google Play Store. They found that free apps requested significantly more data than paid-for apps, suggested that the business model of these 'free' apps is the exploitation of the personal data.…”

Section: Unfair Outcomesmentioning

confidence: 99%

From What to How: An Initial Review of Publicly Available AI Ethics Tools, Methods and Research to Translate Principles into Practices

et al. 2019

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The debate about the ethical implications of Artificial Intelligence dates from the 1960s (Wiener, 1960) (Samuel, 1960). However, in recent years symbolic AI has been complemented and sometimes replaced by (Deep) Neural Networks and Machine Learning (ML) techniques. This has vastly increased its potential utility and impact on society, with the consequence that the ethical debate has gone mainstream. Such a debate has primarily focused on principles-the 'what' of AI ethics (beneficence, non-maleficence, autonomy, justice and explicability)-rather than on practices, the 'how.' Awareness of the potential issues is increasing at a fast rate, but the AI community's ability to take action to mitigate the associated risks is still at its infancy. Therefore, our intention in presenting this research is to contribute to closing the gap between principles and practices by constructing a typology that may help practically-minded developers 'apply ethics' at each stage of the pipeline, and to signal to researchers where further work is needed. The focus is exclusively on Machine Learning, but it is hoped that the results of this research may be easily applicable to other branches of AI. The article outlines the research method for creating this typology, the initial findings, and provides a summary of future research needs.

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Section: Unfair Outcomesmentioning

confidence: 99%

From What to How: An Initial Review of Publicly Available AI Ethics Tools, Methods and Research to Translate Principles into Practices

et al. 2019

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“…The problem becomes even more difficult when there is no price for a service, as in a digital zero-price market (Newman, 2015). A well-known example of a digital zero-price market is Facebook, which leverages personal data to sell personalized ads to other external businesses (Malgieri & Custers, 2018;Polykalas & Prezerakos, 2019). However, not much is said about how these markets really work and how values are exchanged between consumers and businesses.…”

Section: The New Value Creation and Value Capturementioning

confidence: 99%

“…Previous studies therefore lack insight into how value creation and value capture by content creators from a business perspective are carried out. Also, possible value asymmetries between consumers and businesses have been studied within digital zero-price markets (Malgieri & Custers, 2018;Polykalas & Prezerakos, 2019) and other studies have investigated the monetary value (Acquisti et al, 2015). However, value created by consumers in digital zero-price markets still remains largely unclear, since it is a new phenomenon with different logic of value creation and value capture.…”

Section: Consequently the Purpose Of This Dissertation Ismentioning

confidence: 99%

“…In addition Polykalas and Prezerakos (2019) found that 84% of the free apps require access to the phone's entire file system under the mask of access to photos, media and files. More explicitly this is done without informing the users of the extent of the required access for how and why the data is being accessed.…”

Section: Valuementioning

confidence: 99%

“…Doing business within a digital zero-price market on the Internet has turned out to be successful (Lin & Sun, 2011;Newman, 2015;Yeoman, 2015). As digital apps and their services require some degree of access to personal data the associated business models are focused toward an active exploitation and disclosure of personal data (Newman, 2018;Polykalas & Prezerakos, 2019). In relation to this, scholars have been raising concerns about such business models as individuals often unreflectively agree to grant permission to private information in order to get access to the digital service (Malgieri & Custers, 2018;Montes et al, 2019;Newman, 2015).…”

Section: Digital Zero-price Marketsmentioning

confidence: 99%

See 2 more Smart Citations

Mind Your Own Business : Understanding and characterizing valuecreated by consumers in a digital economy

Mileros

2020

Linköping Studies in Science and Technology. Licentiate Thesis

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In the context of what is commonly referred to as consumer-centric digital economy, personal data has become the new currency which is utilized by consumers to be granted access to seemingly "free apps" within so-called digital zero-price markets. Simultaneously, there are consumers, known as "content creators", who can generate million-dollar revenues annually. The current understanding of how consumers create and capture value within this new digital economy is scarce and more research is needed to systematically build a basis for creating an understanding of value creation and capture in the consumer-centric digital economy, based on a consumer perspective. The purpose of this dissertation is consequently to explore how consumers create and capture value within a consumer-centric digital economy. The explorative study also serves to obtain an initial overview of the phenomenon and the widely dispersed literature which spans different research fields. The collected data constitute more than 500 articles in combination with empirical data collected from websites. Based on the current literature, central concepts related to consumer-centric digital economy are explained. These include for instance Web 2.0, user-generated content and the consumerto-business relationship. The different concepts are discussed in relation to each other and a trend analysis shows that these concepts are on the rise and have become increasingly popular. The results show that consumers within the digital economy may take different roles, and some create value as business-oriented consumers (i.e., consumers who have a commercial interest). For instance, they make a business out of their participation in the digital economy. Examples are YouTubers, bloggers or creators in virtual worlds such as Second Life. Another, probably larger category is characterized as traditional consumers, for instance they participate in the digital economy through their use of seemingly "free" apps but do not reap any direct monetary benefits. By sharing their personal data, they take part in value creation in a more passive way. The findings also indicate that the level of control, e.g. determined by whether or not value is created within the digital platform, may characterize the prerequisites for value capture. Based on this, a taxonomy for value creation and value capture by consumers in the digital economy is developed. The study also identifies different business model types for business-oriented consumers.

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Empowerment or Engagement? Digital Health Technologies for Mental Healthcare

Burr

Morley

2020

Digital Ethics Lab Yearbook

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We argue that while digital health technologies (e.g. artificial intelligence, smartphones, and virtual reality) present significant opportunities for improving the delivery of healthcare, key concepts that are used to evaluate and understand their impact can obscure significant ethical issues related to patient engagement and experience. Specifically, we focus on the concept of empowerment and ask whether it is adequate for addressing some significant ethical concerns that relate to digital health technologies for mental healthcare. We frame these concerns using five key ethical principles for AI ethics (i.e. autonomy, beneficence, non-maleficence, justice, and explicability), which have their roots in the bioethical literature, in order to critically evaluate the role that digital health technologies will have in the future of digital healthcare.

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When the mobile app is free, the product is your personal data

Cited by 20 publications

References 103 publications

From What to How: An Initial Review of Publicly Available AI Ethics Tools, Methods and Research to Translate Principles into Practices

From What to How: An Initial Review of Publicly Available AI Ethics Tools, Methods and Research to Translate Principles into Practices

Mind Your Own Business : Understanding and characterizing valuecreated by consumers in a digital economy

Empowerment or Engagement? Digital Health Technologies for Mental Healthcare

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