Abstract
The ELSI White Paper is the final achievement of the ELSI Task Force for the National Research Programme “Big Data” (NRP 75). It is an informational document that provides an overview of the key ethical, legal, and social challenges of big data and provides guidance for the collection, use, and sharing of big data. The document aims to bring together the expertise of the ELSI Task Force members rather than exhaustively covering all topics in big data relating to ethical, legal, and social issues (ELSI).
The white paper comprises two parts: main articles and commentaries on it. The main articles give an overview of the major concerns associated with the use of big data, based on the assessment of the participating researchers. The commentary articles either examine in depth one or more of the issues that are presented in the main articles or highlight other issues that are considered relevant by their authors but are not covered in the main articles.
The main articles are divided into three sections corresponding to the three ELSI levels of analysis. In the section on ethics, Marcello Ienca explores the threat of big data to ethics commissions, privacy rights, personal autonomy, and equality in the healthcare sector and biomedical research. Bernice Elger focuses on the need to address informed consent differently and complement it with additional mechanisms in the big data context. In the legal section, Christophe Schneble explores whether current Swiss data protection laws adequately regulate and protect individuals’ data. Eleonora Viganò analyses the threat of big data to state sovereignty and explore the two contrasting acceptations of the term “digital sovereignty” in the context of big data. In the section on social issues, Markus Christen addresses the big data divide, namely, the uneven distribution of benefits and harms from big data and the connected issue of the transparency asymmetry between data givers and data owners. Michele Loi delves into the debate on fair algorithms, presenting the risks of discriminating against certain groups when adopting big data-based predictive algorithms, such as those for predicting inmates’ recidivism.
The second part of the ELSI White Paper contains three commentaries. In the first, Mira Burri focuses on the viability of new approaches to global trade governance that seek to address big data issues and makes recommendations for a better informed and more proactive Swiss approach. In the second commentary, David Shaw explores the lack of protection for vulnerable groups in big data research and the temporospatial and moral distance between researchers and participants that increases the risk of exploitation. In the third commentary, Christian Hauser tackles big data from the perspective of business ethics and provides guidance to companies employing big data.