Business models in the digital economy are increasingly based on the collection, analysis and use of data. The data-driven economy and its corresponding innovations impact almost all areas of the economy and life. This raises numerous questions in the fields of competition, intellectual property and data protection law. In public discourse, such questions are often discussed under the heading of vague buzzwords, such as “Big Data”, the “Internet of Things” and “Industry 4.0”. In particular, scientific research addresses the legal framework for ensuring access to data and its potential allocation. Further, the field of “artificial Intelligence” bears massive legal and societal implications and highlights the need for research of various kinds. Most notably, self-learning algorithms that make decisions autonomously and realise their goals independently shed a new light on traditional legal issues.
The rapidly developing possibilities for the collection and processing of huge amounts of data fundamentally characterise the economic cycle and affect more and more areas of life. Numerous technological developments based on digitisation go hand in hand with a range of economic effects. The resulting phenomena are discussed under the heading of vague buzzwords, such as “Big Data”, “Industry 4.0”, “data-driven innovation” and the “Internet of Things”. Data-driven business models already characterise the value creation in many sectors which go far beyond the traditional Internet economy (e.g. the automotive and insurance industries, the healthcare sector).
“Artificial intelligence” (AI) is a particular aspect of the data-driven economy. In particular, AI deals with self-learning algorithms that make decisions autonomously and realise their goals independently. Autonomous driving serves as an oft-cited example, yet, revolutionary and disruptive effects stemming from AI are expected in almost all economic sectors and areas of life (smart homes, smart cities, etc.).
For the design of the law and its application, the data-driven economy in general and AI in particular raise a large number of substantive and methodological questions which relate to both private and public law. Apart from competition and intellectual property law, which aim to foster innovation, the focus lies on the laws concerning the protection of personality rights, data, and consumers (keyword: “information self-determination”), as well as on the general civil law. In particular, research needs to consider the connections between the affected legal regimes and the interactions resulting from that.
Contouring the term “data” and delineating “personal” from “non-personal” data are key challenges. These legal terms determine – apart from other demarcation criteria, such as the temporal relevance of data – the applicability of different legal regimes. At the same time, treating data as economic assets inevitably leads to the question whether rights in data (be they rights of use or rights of access) should be attributed. Conversely, one can ask how the voluntary provision of data (in line with open-data approaches) can be promoted. Should AI create something novel, questions regarding the allocation of rights are presented in a new light.
Control over data can strengthen economic power. Furthermore, so-called “deep learning algorithms” which address models of pricing and terms can restrict competitive diversity. Competition law discourse takes up the corresponding effects. Complex questions concern the definition of markets in the data-driven economy. In addition, it is necessary to assess the link between data or algorithms and market power as well as the abuse of a dominant position. The development of robust approaches in the field of competition policy is crucial as this strongly relates to the question of how to regulate in order to correct market failure by allocating corresponding resources. Finally, the mechanisms for the enforcement of competition law in data-related markets also need to be reconceived.
From a European perspective, the typical cross-border, instant transferability of data leads to questions regarding the realisation of the “free flow of data” within the internal market. At the same time, technical and economic questions arise concerning the transfer of data to and from third countries. The effectivness of possible regulation significantly depends on sector-specific mechanisms and on institutions for the legal enforcement.