On Thursday, May 26th 2022, Prof. Stefan Thomas and Prof. Michèle Finck invited to an hybrid interactive talk led by Prof. Wolf-Georg Ringe, director of the institute Law & Economics at the University of Hamburg.
Ringe, being a specialist at the intersection of AI (artificial intelligence) and law, presented his research on “Machine Learning, Market Manipulation and Collusion on Capital Markets: Why the “Black Box” matters” which has been realized in cooperation with Alessio Azzutti and Siegfried Stiehl.
The paper basically treats the implication of machine learning on competitive market processes, emerging issues and possible solutions.
Ringe explained that due to the rapid evolution of artificial intelligence and their use on the global financial markets, strong evidence exists that eventually fully autonomous AI trading agents could act independently on the markets. They would benefit from a combination of already existing technologies such as deep learning and try and error. As a consequence, one could set a specific goal such as profit maximalisation by the end of the week and the algorithm would invest by itself, finding the best way to reach the goal.
This prospect implies various legal and ethical issues on liability for AI wrongdoing and/or crimes and therefore attracts the attention of lawyers such as Ringe. “When things go wrong, we are interested”, he pointed out aptly during his talk.
Autonomously acting algorithms could learn how to cheat and commit market abuse in terms of market manipulation (e.g. “spoofing” or “pinging”) and “tacit” collusion without human interference. Since algorithms’ decision making is not fully understandable for human beings and therefore pictured as “black box”, the current legal system faces various issues emerging from AI use in the specialist’s point of view.
So far, it strongly relied on a human subject and criteria as intent, causation and negligence that could not be applied on AI’s actions, Ringe stated. Moreover, he unveiled the lack of explainability of an AI’s decision making as a fundamental problem for compliance systems and enforcement.