What is the problem
The enormous quantities of data that is collected, stored and processed may considerably improve the speed, effectiveness and quality of decision-making and innovation for companies, governments and researchers. Data-driven innovation (DDI) is a catalyst for growth, competitiveness and productivity gains and is an essential ingredient of the digital transformation process occurring in all sectors of the economy, including low-tech industries and manufacturing (such as the evolution towards industry 4.0). However, emerging social challenges include the potential loss of autonomy and freedom because of mass surveillance and discrimination enabled by data analytics; the risk of new types of market concentration and dominance in data value chains, due to “winner takes all” phenomena (think of the dominance of platforms such as Booking.com); risk of greater information inequalities leading to market power imbalances (between organizations, between citizens and governments, between consumers and suppliers).
Why is this important for Society?
Processing vast amounts of data may lead to situations in which data controllers may know many of the characteristics, behaviours and whereabouts of people. In some cases, data controllers may even know more about people than these people know about themselves, such as life expectancies and happiness levels. Also they may be able to predict characteristics of people that these people may prefer not to disclose, including criminal records, sexual preferences and substance abuse. This may raise privacy issues, but also (other) ethical and societal issues, such as issues regarding discrimination, human dignity, justice, fairness and trust. In view of such privacy (and other ethical, legal and societal) considerations, businesses and governments are often unsure about how to deal with the data collected through their operations. On the one hand, the data is of particularly high value to companies and governments for offering personalised services or developing new business models, but, on the other hand, ethical and societal issues may result in lack of confidence, undermining efficient and legitimate data sharing and value creation for agreed purposes.
Objectives of the project
The central objective of the e-SIDES coordination and support action is to complement the research on privacy-preserving big data technologies, by analysing, mapping and clearly identifying the main societal and ethical challenges emerging from the adoption of big data technologies, conforming to the principles of responsible research and innovation; setting up and organizing a sustainable dialogue between industry, research and social actors, as well as networking with the main Research and Innovation Actions and Large Scale Pilots as well as other framework programme projects interested in these issues.
This central objective has been broken down into the following detailed objectives of the project:
Objective I. Identify and validate ethical and societal implications of privacy-preserving big data Technologies
Objective II. Examine, discuss and validate privacy-preserving big data technologies
Objective III. Liaise with researchers, business leaders, policy makers and civil society through community events
Objective IV. Provide an open-access Internet-based meeting place for discussion, learning and networking regarding privacy-preserving technologies
Objective V. Provide ethical-legal and societal-economic advice to facilitate responsible research and innovation in the field of big data technologies
Objective VI. Observe, map and report on ethical and societal issues related to big data technologies, research, markets and education
Objective VII. Provide an agreed-upon and collective community position paper presenting recommendations for each of the issues addressed in the community events to foster societally compatible and ethically valid big data research and innovation
