Algorithm control in the Internet of Things
In the Internet of Things, everyday devices are connected to each other digitally and are thus able to be controlled from both sides. Self-learning algorithms interlink the networked devices over a communication platform and make them operable for their users. The fact that the legal system classifies the algorithms as a trade secret causes a regulatory conflict situation between Germany's demands and that of the European Union to establish a space with higher data and consumer protection standards. Algorithms quickly turn out to be a "black box", which harbours substantial risk potential to the basic rights of consumers. In the Internet of Things, this finding pertains in a particular manner: a lack of transparency combines here with a mass of data and patterns of interaction that is hardly manageable for the individual. Without technical tools (like visualisation or search screens), people cannot understand the unstructured mass of information. Without the possibility of state influence, they cannot control it. The realization of the basic right to informational self-determination, the principle of transparency in sovereign decisions, and the principle of data sovereignty put an obstacle in the path. Research is all the more called upon to keep a lookout for suitable regulatory approaches in order to keep the lurking threats in the Internet of Things at bay and to make the technical innovations beneficial for the common good.
A consumer protection-friendly Internet of Things is inconceivable without a discrimination-free infrastructure focused on the common good, especially without normative provisions for managing interfaces. From this perspective, the research projects initially analysed the general risk potential of self-learning algorithms and worked out the sensitivity to fundamental rights. It seeks - with particular consideration of the characteristics of the Internet of Things - regulatory starting points, structural options in organisation law and normative innovative potentials to anchor the parameters of data sovereignty, data security and transparency in the infrastructural architecture. A further goal is to counteract against risks of discrimination by self-learning algorithms.
The research project developed a legal basis for state algorithm control. The insights from it are then broken down into an application scenario in the Internet of Things.
The research project is a third-party funded project within the scope of the programme "Promoting Innovation in Consumer Protection in the Law and the Economy - Consumer-Based Research on the 'Internet of Things'" of the German Federal Ministry for Justice and for Consumer Protection.
Note: The text on this home page is copyrighted. It is taken verbatim or based on Martini, "Digitalisierung als Herausforderung und Chance für Staat und Verwaltung" (Digitalisation as Challenge and Chance for State and Administration), FÖV Discussion Paper No. 85, 2016, in particular p. 42 ff.