05-28, 11:00–11:25 (CET), Root
There is now a great temptation for us all to start building blockchain technologies which do good things.
But what is a "good technology", what does it mean to "do good", and how closely do these two match? It might seem extremely beneficial to convert or export a problem into something that can be worked with on a blockchain, and then "optimise" what that blockchain object does against some notion of good. Unfortunately, this can sometimes lead to important factors being overlooked or lost, and moreover could cause harm in completely unintended ways. In this talk I will discuss some of the experiences I have had working with blockchain startups, as part of the work I do in the Ethics in Mathematics Project. I will explore how, even with the very best of intentions, mathematically-powered work (such as blockchain tech) that aims to do good and help society might still have undesired, and possibly even harmful, consequences.
Maurice addresses the ethical challenges and risks posed by mathematics, mathematicians, and mathematically-powered technologies. His research looks at the ethical issues arising in all types of mathematical work, including AI, finance, modelling, surveillance, and statistics. He set up the Ethics in Mathematics Project in 2016 and has been its principal investigator since then, delivering seminar series, giving invited talks, and producing scholarly articles in the area. Maurice has direct industry experience with over 30 startups, having been a member of the Ethics Advisory Group at Machine Intelligence Garage UK for over 2 years. He comes from a background in research mathematics, holding two PhDs in mathematics, from the University of Cambridge and the University of Melbourne, and has over a decade of experience working as an academic mathematician on problems in algebra and computability theory.