Algorithmic business and EU law on fair trading

This thesis studies how commercial practice is developing with artificial in- telligence technologies and discusses some normative concepts of EU law on fair trading. The author argues that the mainstream normative debate concerning artificial intelligence has underestimated the importance of un- derstanding the socio-technical context behind its adoption, and therefore aims at amending this gap by studying artificial intelligence in the context of business-consumer marketing relationships. The "algorithmic business" phe- nomenon refers to the increased deployment of artificial intelligence tools in marketing organisations which - based on large quantities of consumer data - allow companies to optimise a number of tasks related to consumer relation- ships. The phenomenon is orienting relations with consumers towards some general observable trends that are critically affecting the power relations be- tween business and consumers. These developments do not take place in a legal vacuum but in the background of a system of norms and rules aimed at maintaining fairness and balance in market transactions. Thus, the author assesses current developments in business practice in the context of EU con- sumer law specifically aimed at regulating business practice. The analysis is critical by design and without neglecting concrete practices attempts to look at the general picture.
The thesis consists of nine chapters divided in three thematic parts. The first part discusses the integration of artificial intelligence technologies in marketing organisations, a brief history, the technical foundations, and their modes of integration in business organisations. In the second part, a se- lected number of socio-technological developments in commercial practice are analysed and the main implications from the perspective of consumers discussed. In particular, the following are addressed: the monitoring and analysis of consumer behaviour based on data; the personalisation of offers and customer experience; the capture of information on consumers’ psychol- ogy and emotions, the mediation through algorithmic assistants. The third part assesses these socio-technical transformations in the context of EU fair trading law and of the broader policy debate concerning consumer protection in the algorithmic society. In particular, two normative concepts underlying the EU fairness standard are critically analysed: manipulation, as a substan- tive regulatory concept that limits commercial behaviours in order to protect consumers’ informed and free choices and vulnerability, as a concept of social policy that portrays people who are more exposed to marketing practices.