1,177 research outputs found
A Game-Theoretic Study on Non-Monetary Incentives in Data Analytics Projects with Privacy Implications
The amount of personal information contributed by individuals to digital
repositories such as social network sites has grown substantially. The
existence of this data offers unprecedented opportunities for data analytics
research in various domains of societal importance including medicine and
public policy. The results of these analyses can be considered a public good
which benefits data contributors as well as individuals who are not making
their data available. At the same time, the release of personal information
carries perceived and actual privacy risks to the contributors. Our research
addresses this problem area. In our work, we study a game-theoretic model in
which individuals take control over participation in data analytics projects in
two ways: 1) individuals can contribute data at a self-chosen level of
precision, and 2) individuals can decide whether they want to contribute at all
(or not). From the analyst's perspective, we investigate to which degree the
research analyst has flexibility to set requirements for data precision, so
that individuals are still willing to contribute to the project, and the
quality of the estimation improves. We study this tradeoff scenario for
populations of homogeneous and heterogeneous individuals, and determine Nash
equilibria that reflect the optimal level of participation and precision of
contributions. We further prove that the analyst can substantially increase the
accuracy of the analysis by imposing a lower bound on the precision of the data
that users can reveal
Privacy as a Public Good
Privacy is commonly studied as a private good: my personal data is mine to protect and control, and yours is yours. This conception of privacy misses an important component of the policy problem. An individual who is careless with data exposes not only extensive information about herself, but about others as well. The negative externalities imposed on nonconsenting outsiders by such carelessness can be productively studied in terms of welfare economics. If all relevant individuals maximize private benefit, and expect all other relevant individuals to do the same, neoclassical economic theory predicts that society will achieve a suboptimal level of privacy. This prediction holds even if all individuals cherish privacy with the same intensity. As the theoretical literature would have it, the struggle for privacy is destined to become a tragedy.
But according to the experimental public-goods literature, there is hope. Like in real life, people in experiments cooperate in groups at rates well above those predicted by neoclassical theory. Groups can be aided in their struggle to produce public goods by institutions, such as communication, framing, or sanction. With these institutions, communities can manage public goods without heavy-handed government intervention. Legal scholarship has not fully engaged this problem in these terms. In this Article, we explain why privacy has aspects of a public good, and we draw lessons from both the theoretical and the empirical literature on public goods to inform the policy discourse on privacy
A Value-sensitive Design Perspective of Cryptocurrencies: A Research Agenda
Cryptocurrencies and their underlying blockchain technology have begun to transform numerous industries. Although we have seen an uptrend in the types of created cryptocurrencies, it has not yet translated into mainstream adoption., In this paper, we use value-sensitive design principles to identify values among current and potential cryptocurrency adopters. Using Bitcoin as the context for this qualitative research study, we use grounded theory analytical techniques to discover manifested values among users and non-users. We develop a cryptocurrency value-sensitive design framework to summarize our results. As our main contribution, we offer a research agenda based on the cryptocurrency stakeholders’ underlying value system. This agenda can help information systems scholars apply this value-sensitive design perspective to their own cryptocurrency research
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