Speaker: Norman Fenton, PhD
Misunderstandings about risk, statistics and probability often lead to flawed decision-making in many critical areas such as medicine, finance, law, defence, and transport. The ‘big data’ revolution was intended to at least partly address these concerns but, even where (relevant) big data are available, there are fundamental limitations to what can be achieved through pure machine learning techniques. This talk will explain how causal probabilistic models of risk (Bayesian networks) can provide powerful decision-support and accurate predictions by a ‘smart data’, rather than ‘big data’ approach.
Norman Fenton is Professor of Risk Information Management at Queen Mary University of London and a Director of Agena, a company that specialises in risk management for critical systems. He is a mathematician by training with current focus on critical decision-making and, in particular, on quantifying uncertainty using causal, probabilistic models that combine data and knowledge (Bayesian networks). The approach can be summarized as 'smart data rather than big data'. Applications include law and forensics (he has been an expert witness in major criminal and civil cases), health, security, software reliability, transport safety and reliability, finance, and football prediction.