Evaluating and addressing societal externalities of big data

The BYTE-project has made a comprehensive evaluation of the societal externalities and of best practices to address these externalities within the BYTE case studies.  The evaluation findings are presented in D4.2 Evaluating and addressing positive and negative societal externalities. The report reveals a broad agenda for policy-makers to address these externalities, consisting of updating legal frameworks, the promotion of big data practices through public investments and enabling policies and an active policy to keep markets open and competitive. Regulators and stakeholders also have an important role in developing tools and approaches to mainstream societal concerns into the design process of and the implementation of big data practices.

The economic externalities are categorized into operational efficiency, innovation, new knowledge, business models, and employment. In order to diminish the negative economic impacts and to augment the positive effects, a set of best practices has been devised. Governments and public institutions can promote big data practices through public investments and enabling policies, which points to the need to develop a comprehensive big data policy. The best practices concerning corporations point mainly at a need to change the mind-set in order to perceive the opportunities of big data. These best practices are not only useful to capture positive economic externalities, but appeared useful for positive social externalities as well.

However, this also necessitates attention for adequate legal frameworks to create legal certainty and diminish negative effects, which now cause distrust and reluctance towards big data. Some general conclusions to do so can be drawn. First needs to be checked if the balance struck between different objectives and interests in the current practice or legal framework is still delivering an optimal result. If not, it will need adapting. Second, legal mechanisms based on individual transactions or individual control lead to high transaction costs in a context of a larger amount of data flows. Such mechanisms become dysfunctional or they present barriers to big data practices. They need to be substituted for collective or aggregate mechanisms of control and decision-making. Third, a specific method to reduce transaction costs is to move a large amount of the decision-making to the design phase and to create standardised solutions. Privacy-by-design has become a practical example of such approach. Similar work needs to be done to integrate other social concerns, like discrimination, and to broaden this approach to include the whole range of legal, organisational and technical safeguards.

Dealing with the political externalities entails an active policy to keep markets open and competitive, where the specific ways of how a company can acquire a dominant position need to be taken into account and addressed with adequate tools. Further it concerns efforts by states to retain their regulative capacity. These efforts have to be accompanied with adequate policies and safeguards to preserve the balance with citizens’ rights and with other states.