Are we going towards "no-brainer" risk management? A case study on climate hazards

The overall risk management domain is stepping into its 4.0 phase by implementing and increasingly relaying on cyber-technological systems. Enhanced computational power provides the capability of processing collected databases for prediction and preparation purposes. In fact, early warnings can lead to suggestion for proactive strategies, or directly initiate the action of autonomous actuators ensuring the required level of system safety. But have we reached the promises of digital risk management yet, or will we ever reach them? A traditional view on safety defines it as the absence of accidents and incidents. A forward-looking perspective on safety affirms that it involves ensuring that "as many things as possible go right". However, in both the views there is an element of uncertainty associated to the prediction of future risks and, more subtle, to the capability of possessing all the necessary information for such prediction. This uncertainty does not simply disappear once we apply advanced Machine Learning (ML) techniques to the infinite series of possible accident scenarios, but it can be found behind modelling choices and parameters setting. In a nutshell, "there ain't no such thing as a free lunch", i.e., any model claiming superior flexibility usually introduces extra assumptions. This contribution will illustrate a case on climate-driven disaster data extracted from the Emergency Events Database (EM-DAT) where ML techniques are used to understand natural disaster mortality and unravel underlying causes and influential factors that can inform decision-making and be relevant for risk reduction efforts. This manuscript may allow to affirm with certain confidence that present risk management systems are not even close to a "no-brainer" condition in which the responsibility for human and system safety is entirely moved to the machine. However, this shows that such advanced techniques are progressively providing a reliable support for critical decision making and guiding society towards more risk-informed and safety-responsible planning.