What are the major ethical legal and security aspects associated with big data?

The societal acceptability of Big Data solutions crucially depends on the proper handling of the ethical, legal, and social issues (ELSI) those technologies raise. Consequently, several projects within NRP 75 explicitly deal with ELSI topics and members of these projects formed an ELSI Task Force. The white paper “Ethical, Legal and Social Issues of Big Data – a Comprehensive Overview” aims to bring together the expertise of the ELSI Task Force members.

The white paper consists of two parts: a total of six main articles, divided into three sections corresponding to the ELSI analysis levels of ethics, law and social affairs, and three commentaries that either expand on topics already covered or highlight new ones. The most important findings and recommendations of the six main articles are summarised here.

Ethical issues: Big Data and healthcare

Author: Marcello Ienca

Big Data trends have pervaded even healthcare and hold the promise of exerting a positive impact on the delivery of healthcare services. However, considering their methodological novelty, reliance on large data repositories and computational complexity, Big Data may challenge existing oversight mechanisms such as independent review by an Ethics Review Committee (ERC).

Recommendations: The requirements for approval of Big Data studies by Ethics Review Committee (ERC) should be better clarified. This is with the aim of creating a culture of stewardship and responsibility among researchers who engage in health-related Big Data activities. Among other things, this requires an increase in the level of competence of ERCs (e.g. expanding their expertise in data science) so that they can better assess Big Data studies. Where appropriate, the establishment of complementary oversight entities such as data ethics boards should be considered.

Ethical issues: Big Data and informed consent

Author: Bernice Elger

Fulfilling the requirement of true informed consent for data use is challenging in today’s digitalized world. It might be necessary, more transparent, and more honest to abandon, at least in part, the concept of informed consent to Big Data processing and use and complement it with mechanisms that ensure protection from harm or guarantee appropriate compensation in the case of harm.

Recommendations: Experts and procedures should ensure that data protection through anonymisation is sufficient; that people receive short, understandable information about the most significant ways their data will be used; and that data abuse will be either unlikely or detected early enough to prevent significant harm, independently of the choices people make about the use of their data.

Legal issues: Data protection laws and Big Data

Author: Christophe Schneble

Ensuring the protection of data subjects has become central to both the research and commercial use of big data. Current data protection regulations play an important role in providing safeguards, mitigating risk, and mandate rights for data subjects.

Recommendations: As data protection laws cannot follow the dynamics of Big Data development, the provision of guidelines is a better way forward. The context of obtaining consent is a field where for example the use of up-to-date mechanisms such as dynamic consent could be beneficial for individuals, their engagement, and protection of their right by maintaining their autonomy.

Legal issues: Big Data and digital sovereignty

Author: Eleonora Viganò

Digital sovereignty refers, on the one hand, to a state’s autonomy in regulation and protection of its citizens’ data and, on the other hand, the users’ self-determination in the use of their personal data. The two meanings can conflict in the case of Big Data because personal data is a good on which both individuals and states aim to exercise their autonomy.

Recommendations: As Big Data is intangible, it cannot be regulated in ways that are based on the sovereignty of the state over a finite physical space. Therefore, states should coordinate and cooperate with each other to regulate the collection, storage, sharing, and transmission of Big Data. In doing so, the state’s aim to protect the security of its digital infrastructure has to be weighed against its citizens’ autonomy in order to avoid unjustified intrusions of the state into its citizens’ private life.

Social issues: Big Data Divide

Author: Markus Christen

The term “Big Data Divide” describes the asymmetric relationship between those who collect, store, and mine large quantities of data (usually companies), and those who are the target of data collection (e.g., customers).

Recommendations: Big Data divide is an inevitable consequence of a society that values freedom and diversity; eliminating this divide is a wrong political goal. Instead, legislation should identify realistic harms that could result from Big Data divide and develop legal safeguards for those who are disadvantaged by the divide. In doing so, values such as nonmaleficence and fairness may be more relevant than autonomy and privacy.

Social issues: Discrimination and Big Data

Author: Michele Loi

So-called data bias can potentially lead to discrimination and unfairness in machine learning. However, the definition of what counts as bias is not only a technical matter, but a normative choice.

Recommendations: Policy makers should include fairness as a requirement for the design of high-stake algorithmic systems. Discrimination is not avoided by avoiding the processing of group information. This must be collectible for the sake of checking the fairness of algorithms. Anti-discrimination policies must be flexible enough to legitimate different statistical standard for different use cases.

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