John Kay joined us today to discuss the difference between risk and uncertainty, what this means for finance and how societies can collectively deal with the unknown by ensuring systems build in resilience.
As John explained to series host Kaisie Rayner FRSA, risk can be estimated, while uncertainty is truly unknowable, a distinction forged in the wake of the Great Depression.
Over the last half century, finance and economics have gradually merged these two concepts. The economist Milton Friedman explicitly stated, in his quest to model society as a collection of perfectly informed utility maximiser.
This reflects a general bias towards quantifying phenomena among policymakers, a fear of the unknown and the unknowable. Models should be treated not as quantitative answers to these intractable problem, but rather tools to be used to organise thinking.
Sir John Kay argued that this is reflected in the paradox of the perfect map; if a map were to represent reality perfectly, it would be a 1:1 copy of it, and therefore no map at all.
What a map or model should do is simplify information in a way that retains what is useful while cutting out other information. London’s Tube map is a great way of navigating the city by train, but much less helpful on foot.
By treating models as gospel, rather than helpful simplifications, we risk ignoring that which has been left out. Resilience and robustness – which are key to dealing with uncertainty – will be viewed as inefficiency.
An example of this is the global financial crisis, where sophisticated risk modelling and the unrelenting pursuit of profit sidelined experienced professional judgement. Another is that of privatisation of public services, where resilience and robustness can be cut to make profit, with the state ready to step in if the unexpected does happen.
John Kay joined us today to discuss the difference between risk and uncertainty, what this means for finance and how societies can collectively deal with the unknown by ensuring systems build in resilience.
As John explained to series host Kaisie Rayner FRSA, risk can be estimated, while uncertainty is truly unknowable, a distinction forged in the wake of the Great Depression.
Over the last half century, finance and economics have gradually merged these two concepts. The economist Milton Friedman explicitly stated, in his quest to model society as a collection of perfectly informed utility maximiser.
This reflects a general bias towards quantifying phenomena among policymakers, a fear of the unknown and the unknowable. Models should be treated not as quantitative answers to these intractable problem, but rather tools to be used to organise thinking.
Sir John Kay argued that this is reflected in the paradox of the perfect map; if a map were to represent reality perfectly, it would be a 1:1 copy of it, and therefore no map at all.
What a map or model should do is simplify information in a way that retains what is useful while cutting out other information. London’s Tube map is a great way of navigating the city by train, but much less helpful on foot.
By treating models as gospel, rather than helpful simplifications, we risk ignoring that which has been left out. Resilience and robustness – which are key to dealing with uncertainty – will be viewed as inefficiency.
An example of this is the global financial crisis, where sophisticated risk modelling and the unrelenting pursuit of profit sidelined experienced professional judgement. Another is that of privatisation of public services, where resilience and robustness can be cut to make profit, with the state ready to step in if the unexpected does happen.
Purchase Radical Uncertainty: https://lnkd.in/epTk7ujb or https://lnkd.in/gHD4h5P3
Find out more about our Radical Old Idea series https://lnkd.in/eKYu2uny
Watch the full webinar on our YouTube page.