Uncertainty is the cause of imperfect information about the present, the future and even the past. According to economists John Kay and Mervyn King, there are two types: resolvable and radical uncertainty.

Resolvable uncertainty is when the uncertainty can be removed, either by looking something up and gaining more information, or by representing the uncertainty as a probability distribution, as with the rolling of a dice.

In contrast, radical uncertainty can’t be resolved by either of those methods. “It is not just that we do not know what will happen,” Kay and King explain in their book Radical Uncertainty: Decision-Making Beyond the Numbers. “We often do not even know the kinds of things that might happen.” In other words, it’s what we don’t know we don’t know, or the ‘unknown unknowns’.

Where do we see radical uncertainty?

When the global financial crisis broke in 2007, the Chief Financial Officer of Goldman Sachs David Viniar famously said: “We were seeing things that were 25-standard deviation moves, several days in a row.” Multiple 25-standard deviation events are a statistical near impossibility – so improbable that our universe hasn’t existed long enough for them to occur.

But the 2008 crash wasn’t impossible. It happened.

The problem was that Goldman Sachs’ risk models weren’t fit to describe the current financial situation. Models don’t necessarily tell us truths about the world.

The financial crisis couldn’t be predicted by probability. In fact, Kay and King argue that it was our reliance on models and statistics that led to the emergency in the first place: “In the run-up to the global financial crisis […] policy advisers not only chose to express uncertainties as probability but were required to do so […] This expression of uncertainty was at best unhelpful and at worst actively misleading.”

For Kay and King, radical uncertainty encompasses everything “that lies in between the world of unlikely events which can be described with the aid of probability distributions, and the world of the unimaginable.” While it applies to financial markets, the economists argue that radical uncertainty also plays a part in everything from individual choices such as buying a house or planning for retirement, all the way up to political decisions of global significance. 

A helpful way of looking at radical uncertainty is by using the ‘known-unknowns’ matrix. Many radical uncertainties fall under the ‘unknown unknowns’ category. However, Covid is a key example of radical uncertainty that, according to the matrix, is a ‘known unknown’. This is because scientists were extremely aware that a pandemic would pose a risk to humanity in the future. What makes it a radical uncertainty is the unresolvable questions that still arise. When will it happen? What illness will it be? How will it be transmitted? And so on.

How can it help us to make decisions? 

According to Kay and King, decision-making in business in the latter half of the 20th century had been dominated by the idea that uncertainty can be broken down into probability, in order to make “rational, utility-optimising calculations.”

During the financial crisis, we saw this manifest in regulators prescribing risk models to financial institutions. In business we may see chief executives using probability to determine how to maximise shareholder value. Kay and King emphasise that “no chief executive knows what will maximise shareholder value, or after the event whether it has indeed been maximised.”

They propose that probability wields a false power. When making decisions, they instead ask us to return to the key question that probability has distracted us from: “What is going on here?”

Rather than being at the mercy of models, they recommend that we embrace uncertainty, open our mind to alternative futures when dealing with unpredictable events, seek practical knowledge and find value in leaps of the imagination.

Further reading

• Radical Uncertainty: Decision-Making Beyond the Numbers – John Kay and Mervyn King
• The Superpower of Uncertainty – The Beautiful Truth
• Decision-Making Beyond the Numbers – Financial Times
• The Decision Book: Fifty models for strategic thinking – Mikael Krogerus and Roman Tschappeler