Data-Driven Innovation

Big Data for Growth and Well-Being

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Today, the generation and use of huge volumes of data are redefining our “intelligence” capacity and our social and economic landscapes, spurring new industries, processes and products, and creating significant competitive advantages. In this sense, data-driven innovation (DDI) has become a key pillar of 21st-century growth, with the potential to significantly enhance productivity, resource efficiency, economic competitiveness, and social well-being.

Greater access to and use of data create a wide array of impacts and policy challenges, ranging from privacy and consumer protection to open access issues and measurement concerns, across public and private health, legal and science domains. This report aims to improve the evidence base on the role of DDI for promoting growth and well-being, and provide policy guidance on how to maximise the benefits of DDI and mitigate the associated economic and societal risks.



Building trust for data-driven innovation

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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