Building trust for data-driven innovation (Data-Driven Innovation: Big Data for Growth and Well-Being)

This chapter provides an overview of emerging trust issues raised by the increasing use of data-intensive applications that impact individuals in their commercial, social and citizen interactions. Security issues are addressed first, with an examination of the traditional approach and its inherent limitations. Comparisons are then made with current digital security risk management, which views risks as the possible detrimental consequences for the objectives of, or benefits expected from, the data value cycle. The point is made that a certain level of risk has always to be accepted for the value cycle to provide some benefit – raising the question of who decides that level. The discussion then takes up privacy protection. Practical means for preventing information discovery are enumerated, and the dangers of information asymmetry, data-driven discrimination, and unanticipated uses of consumer data addressed. Attention then turns to potential policy approaches to help in addressing the issues raised.
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