Each financial crisis has been human-made, not an outcome of a metaphysical invisible hand, and this fact will not disappear even if one relies on artificial interpretations of Homo oeconomicus. Just as current developments in Artificial Intelligence and their interoperability with other technologies have left behind the parameters set by the famous Moore’s Law, we are witnessing an increasing offer of proposals that aim to predict financial crises, improve central banking and develop algorithmic trading, among others, building upon this potential. Certainly, this technological potential could influence the speed of financial innovation and, accordingly, within these proposals, one can find rather interesting ideas that will be materialised in the near future. However, the systemic implications of these black boxes raises several concerns, especially considering the underlying assumption that financial black boxes are human financial intelligences. The talk aims to highlight the risks behind financial black boxes that could give form to the next generation of financial infrastructures and their systemic relevance, and propose a set of standards to uniform these structures to coordinate actions and avoid contagion in Machine-to-Machine interactions.

Israel is a Full-Time Lecturer/Researcher in Banking and IP/IT Law at Universidad de las Américas Puebla (UDLAP), Mexico. He obtained his PhD in Law at the University of Edinburgh in 2020. Professionally, he has worked as Intellectual Property Advisor and Personal Data Protection for different institutions and editor on Intellectual Property for SCRIPTed. (Twitter: @IsraelCL)

Jiahong is a Lecturer in Law at University of Sheffield. His research interests include data protection law, cybersecurity law, law and AI, data ethics and internet regulation.