Will responsibility dissolve into algorithms? (Part 3)

Technical innovation and the adaptation of case law rarely go hand in hand. As is often the case, lawyers initially try to answer the question of breach of duty using existing case law. At some point, they reach a point where the current case law no longer clearly applies or can at least be interpreted contradictorily. Only then does the legislator react with appropriate adjustments.

The draft legislation issued by the EU Commission this week, known as the EU AI Act, is a first step in the right direction. In principle, standardised AI regulations are to be welcomed, but whether they will reduce the risks associated with the use of AI remains to be seen. It will be interesting to see whether future AI systems, such as artificial general intelligence, will have an independent legal personality.

I would not yet speak of such so-called robo-advisors becoming independent. As I already suggested in 2021, machine learning algorithms are not yet used as frequently in automated asset management as one might think (Becker, M., Beketov, M., & Wittke, M. (2021). Machine Learning in Automated Asset Management Processes 4.1. Die Unternehmung, 75(3), 411-431).

Basically, we are also moving in a highly regulated area here. According to the principles of the EU directive on the harmonisation of financial markets MIFID-II, investment advice, whether human or automated, must always comply with the "suitability" principle. This means that pensioners cannot simply be sold "junk bonds".

Without transparency algorithms (XAI), however, the algorithms simply act arbitrarily among themselves. This can sometimes even lead to "flash crashes", as the past has shown. To name just two examples: Algo Trader Softwares sometimes facilitated the stock market crash on 19 October 1987, the so-called "Black Monday".

Another example is 6 May 2010, when the Dow Jones fell by over 1000 points within eight minutes. This crash was triggered by a simple sell order from the trading house Waddell & Reed. This cannot even be described as AI, but was simply an automated sell order that was triggered when a certain threshold was reached.

My prediction is that if opaque back-box algorithms are unleashed on the financial markets without any validation, flash crashes could repeat themselves at ever shorter intervals. Fortunately, there are already laws that allow certain financial instruments to be excluded from trading (see Section 73 WpHG / Securities Trading Act). This limits the potential for price slides.

Our recommendations for the use of transparency algorithms are based on five quality criteria: Trust, associations, reliability, fairness and identity.

At best, aggrieved investors of AI-driven investment advice can assert a claim for damages for breach of duty against the financial service providers. It is debatable whether the operator of the robo-advisor can be held responsible for a programming error. Particularly in the case of black box algorithms, which no longer rely on explicit programming logic such as simple if-then relationships, it is very difficult to identify an "actual" error in the implementation. The error could merely lie in the improper control of the input parameters. If liability of the manufacturer is ruled out due to a lack of infringement of legal interests, the introduction of independent strict liability of the operator of robo-advisors in the context of product liability would be welcome.