Thoughts on uncertainty and COVID-19

27th March 2020
Many have described the impact on COVID-19 across the world, and we are all living through the disruption of everyday life. As it is testing our economic, health and social systems, it reveals how our current global decision-making frameworks react to uncertainty.

The current happening is for many seen as a “Black Swan” Scenario, an unpredictable outlier event, from its inventor Nassim Nicholas Taleb, Lebanese economist ex-trader known for his studies in uncertainty, risk and anti-fragility. Others argue that this event was a “highly probable, yet neglected threat” and better described as a “grey rhino”, a term coined by Michele Wucker. Indeed, Imperial Tech Foresight created a deck of “Disruption Cards” in 2015, where we referenced the potential disruption that related to a pandemic on society. In foresight, the current epidemic has been imagined by countless scenario planners and by governments. Even though we played out this scenario, we had not understood how deeply it could impact us and the real probability of this happening. Now we as we are seeing governments and organisations struggling with decision-making, as the outcomes are highly uncertain.

Decisions-making in risk and uncertainty ‘are two different things in the field of risk management, as Gerd Gigerenzer from the Max Planck Institute describes in his research. The difference is fundamental and depends on the quantity of information that is known and unknown, and that can be predicted about the event. Risk is described where alternatives and prior probabilities are known and when future patterns are projections of the past data – a case of high information and certainty. On the other hand, uncertainty is a situation of the unknown, where inadequate information on the novel current state and it lacks known statistic distributions. In these situations, Gigerenzer explains that heuristics, intuition and “fast and frugal” solutions to problems ahead, are the norm, and tend to work better than optimization methods. Novel actions emerge out of the system under pressure, providing novel and unexpected solutions, we have seen graduation ceremonies on Minecraft in Japan and hacked decathlon snorkelling masks that become into ventilators in Italy—showing the potential of quick reactions to the outbreak.


Dealing with complexity requires an understanding of multiple futures and disruptions, exploring a variety of options that might create more adaptive systems. Another area to examine is the reactions of the scientific body within policy systems and the society to respond to the crisis. A story to highlight is one of Didier Raoult, a French micro-biologist, who shocked the world announcing a cure for the coronavirus. According to him, this could end the pandemic, and it was unexpectedly endorsed by Trump on Twitter, that caused people to believe in his home-made cure solutions. The proposed cure based on a mix of existing medicines – malaria drugs with antibiotics – is claimed to have killed the virus in dozens of patients in his research centre in France. The discovery of the French scientist was received in the media as a quasi-alchemical discovery, whose result, methods and safety can’t be measured nor readily validated, tested or accepted by the scientific community in such a short time. What if this might be the cure for the outbreak? This raises a question; how can the academic community react efficiently and quickly to new pandemics and outbreaks? In an economic and psychological framework, in conditions of uncertainty and low information, heuristics and ingenuity provide new, faster and often better solutions to problems than classic risk planning scenarios with dense and long “calculations”. The case of Didier Raoult maps as a scientific metaphor onto this concept, representing the emergence of a heuristic method, a creative discovery that comes as a response to this highly uncertain scenario that stresses the whole scientific and medical body. Far from taking sides, it’s a relevant signal to explore. What might we learn from this quick and adaptive scientific discovery? And might outlier discoveries become a solution to outlier events?

There are dangerous precedents of rushing vaccines into service without the usual testing, as the 2009 case with the swine-flu vaccine, that was given to dozen of NHS staff and younger teenagers that lately developed narcolepsy as a side-effect. We find ourselves in the space of dealing with the complexity of risk-reward situations, in which smaller short-term consequences are accepted when taking risks in actions that could bring higher benefits in the long-term for society but raise moral and ethical questions on the sacrifices of the process.

As a foresight practice, we like to be positive and consider weak signals and future ideas that might positively speed these discoveries. We have mentioned two below:


Automated discovery and AI systems

AI systems that in the near future can be harnessed to automate and speed up these processes of test, validation and discovery of new vaccines. As Imperial College London President Alice Gast recently declared at WEF (World Economic Forum):

“AI is changing fundamental basic research. It’s enhancing our ability to design molecules in chemistry, making it possible to understand our microbiome, develop technologies for people to use in medicine, health, surgeries and tackle climate change. We need to make sure we are pursuing fundamental research that benefits society and at the same time educate our students and the population.”


Professor Mimi Hii is working on the Dial-a-Molecule institute that is rapidly creating and testing new molecules. She and her team are hoping to create systems that could personalise medicine and quickly respond to medical needs.


The potential of RNA vaccines

Professor Robin Shattock leads the Future Vaccine Manufacturing Network, their teamwork on developing RNA vaccines. As explained in this article, “Synthetic RNA vaccines – which harness the body’s cell machinery to make an antigen rather than injecting the antigen directly – take only weeks to produce and may offer the easiest route for global product consistency. This approach is already being successfully used in cancer and the technology provides the ability to manufacture anywhere in the world”. This team are already responding to the COVID-19 challenge, where they developed a candidate vaccine within 14 days of getting the sequence from China, this process often takes years. They have already tested the vaccine on animals since 10 February and plan to move to clinical trials in the summer. Professor Robin Shattock told The Telegraph: “We have the kind of technology to be able to generate a vaccine with a speed that’s never been realised before. Most vaccines are five years in the discovery phase, and at least one or two years to manufacture and get into trials.”


This pandemic has shown us that there is a need to embrace novel ways of exploring, developing and reacting to threats. We need to find ways to decrease the reaction time against future pandemics. So perhaps, what we see future opportunities where AI can discover new medicines and unveil undetected patterns? What we could also wish for, is an AI system that could advise us on planetary-scale decision making? It could be able to predict the future’s critical uncertainties and to help us act on them in a better way, taking into account also to the heuristics that work and that we often forget to possess.


In conclusion, leaving AI aside, from a more human perspective, maybe what science and society can learn is to adopt a flexible mindset to speed up its reaction to uncertainty and disruptive events. Developing approaches that encourage adaptive thinking and considerations helping the community and governs to be more resilient and anti-fragile.

Note: These are initial thoughts on uncertainty and COVID-19, we will be writing a short foresight piece every Friday on this topic.