Good with numbers?

We have two sides to our brain. An instinctive side, that has evolved over millions of years, and a more analytical side, that is much newer.

Our instinctive side is understandably scared by COVID-19. However, it doesn’t have the ability to deal with a complex risk such as this pandemic. We need to make sure we use the newer parts of our brains to protect ourselves and our societies.

Thinking about the current COVID-19 pandemic and what policies we should ask governments to pursue is not a simple problem. It involves lots of big numbers and trade-offs over time. These are things that we are not instinctively good at.

My background is as an investment manager. Investment decisions have exactly the same problem. They involve lots of big numbers and trade-offs over time. Unsurprisingly, because getting investment decisions right can make or lose a lot of money, there has been much research done into how people make financial decisions. There is a whole field covering this – Behavioural Finance.

Looking at the current pandemic, I think we should use some of these ideas to help us make better decisions and, more importantly, avoid wrong decisions.

Please forgive me for making huge simplifications to keep this reasonably short.

One of the most important ideas is that our brains evolved over millions of years and numbers are new.

Modern humans have been around for 100,000-200,000 years. The first Mammals appeared around 200 million years ago. So, mammals have been around for something like 1,000 to 2,000 times as long as humans.

Admit it, your first thought was “a lot longer” not “1,000-2,000 times longer”. I will explain later. Trust me, we are just not naturally good with numbers.

Those early mammals were our ancestors and the brain we currently have evolved from the brain they had. When Homo Sapiens appeared we evolved, we didn’t start from scratch. Even the early mammals didn’t start from scratch.

What made us different was developing new parts of our brain that allowed us to process complex ideas.

For example, the part of your brain that keeps you breathing, even while asleep, is one of the really old parts. The part that let some clever paleontologist work out that the first mammals appeared around 200 million years ago is part of the newer bits. There are plenty of bits that evolved in between.

Daniel Kahneman won the 2002 Nobel prize for Economics for his work in this field and I think his explanation is one of the best ways to understand how our brains work. So, with many apologies to Dr Kahneman for a number of huge simplifications, I will use his framework.

His model is that our brain can be divided into system 1 and system 2. System 1 is old, very quick, but is quick because it guesses. System 2 is newer, slower, more analytical, but more accurate in complex problems. One of the reasons we often make bad decisions in complex cases is that system 1 has guessed the answer and we have committed ourselves, before the slower system 2 has come up with the right answer.

Let’s be clear, we should not criticise system 1. It kept us alive for millions of years. It just isn’t very good with complex stuff. Unfortunately, system 2 is also a bit lazy. As soon as system 1 has shouted out the answer from the back of the class, system 2 is quite happy to ignore the question unless prodded into action.

This is not about how much maths you studied at school, or how good you were at it. This is about how our brains have evolved, how they work and how they process information.

Let us look at some of the differences between system 1 and system 2. I have chosen three examples that I think are relevant to the current pandemic.

1) We aren’t very good with numbers, particularly if they are big ones.

  • Would you like one apple or two apples?

    • System 2 understands that there are twice as many apples.

    • System 1 can see than there are more apples to eat or share with social group.

  • Would you like one apple or five apples?

    • System 2 understands that there are five times as many apples.
    • System 1 can see than there are more apples to eat or share with social group.
  • Would you like one apple or one thousand apples?

    • System 2 understands that there are one thousand times as many apples.

    • System 1 can see that one thousand apples is more apples than they can ever eat, doesn’t care how may there are and is just thinking about eating apples.

System 1 isn’t stupid, it’s just lazy. Once numbers get to a size where a few more or less don’t matter, it just switches off and doesn’t waste effort thinking about it.

Once numbers become large, we lose ability to differentiate between them. Our brains don’t get that the difference between one and two is not the same as the difference between one thousand and one million. That is because we understand one and two. While we completely understand that one million is bigger than one thousand, they are just two big numbers. One bigger than the other.

Two is bigger than one. One million is bigger than one thousand. End of story for system 1.

2) We aren’t very good at comparing something today with something in the future. The further in the future, the worse we get.

  • Would you like one apple now or two apples tomorrow:

    • System 2 understands that would be twice as many apples tomorrow. It will assess current levels of hunger, availability of other food sources.

    • System 1 can see than there are more apples to eat later, if the delay is short enough will consider it. However, generally prefers getting stuff NOW. “NOW” (yes in capitals) is a really important driver of system 1.

  • Would you like one apple now or five apples a year today:

    • System 2 understands that there are five times as many apples. It will assess current levels of hunger, availability of other food sources. Over the next year.

    • System 1 has no interest at all apples in a year’s time. We need to eat NOW and will take the apple NOW.

Again, system 1 isn’t stupid. It is just working to a different set of criteria. Five apples next year, compared to one apple now, might be a pretty good deal, but has no value if I don’t survive that long. Survival means having food NOW.

3) We are naturally risk averse

  • You know when you see a sudden movement in the corner of your eye, and you jump? That’s system 1 keeping you alive.

  • For most of our evolutionary existence (even today in many places) that sudden movement could be a threat to our lives. It could be a wolf or a snake, who knows?

  • System one reacts quickly. If it was a threat, reacting quickly may have saved your life. If it wasn’t, who cares, you jumped. It makes sense to avoid that sort of risk.

  • Meanwhile system 2 is asking “I wonder what that was”

System 1 Reacting to an unknown threat is completely sensible from an evolutionary perspective.

System 1 can be very useful when faced by simple risks. However, it is useless at trading off one risk against another. All it does is jump away from the risk it sees. It doesn’t think about what other risks you might be increasing by jumping. Faced with more complex threats in the modern world, the slower answer that system 2 comes up with is often be better.

What if you were walking alongside a road with heavy traffic? That jump to the side could put you under a bus and be fatal.

So, what does any of that have to do with Covid-19?

We are not good with numbers. When thinking about this pandemic, we need to take a deep breath. Pause. Tell system 1 to shut up, and prod system 2 until it starts working and gives us some sensible answers. Let’s think about how those three traits, discussed above, might get us into trouble with this pandemic.

1) We aren’t very good with numbers, particularly if they are big ones.

  • The current UK population is about 68,000,000. That is 68 million people. System 1 thinks that is a lot of people.

  • As of Easter 2020 current UK deaths from Covid 19 are about 10,000. System 1 thinks that is a lot of people.

  • System 1 is telling you that Covid-19 is the end of the world and people are dropping like flies. TELL SYSTEM 1 TO SHUT UP AND STOP GUESSING.

  • With system 2 (and possibly your calculator), divide 10,000 by 68. The answer is 147 (and a bit). This is the number of deaths from Covid-19, so far, per million people in the UK.

  • In the UK by the 10^th^ April 2018 there had been around 187,000 deaths from all sorts of causes (everything from flu to that guy - remember him - who thought he saw a tiger and jumped off the pavement into the path of a bus). 2018 was a pretty typical year.

  • Doing the same sum as before, 187,000 divided by 68 gives us 2,750. So, by this point in the year we should have expected about 2,750 people to have died for every million people we started with.

  • About 495 people of those 2,750 people in 2018 died of flu / pneumonia.

  • If we assume that 2020 is pretty much like 2018 for all the “other stuff”, for every person that has died from Covid-19 in the UK this year, about 18 will have died from “other stuff”. That includes somewhere between 3 and 4 people who died from “normal” flu.

  • Covid-19 is a nasty disease. However, it is killing many less people than all the “other stuff”.

  • A question for you:

    • If we could half the number of deaths from Covid-19 but that means the deaths from other stuff would rise by 5%, should we?
    • Your System 1 said that we should half the Covid-19 deaths. Didn’t it? But let system 2 think about it.
    • Halving Covid-19 deaths saves 74 lives per million. A 5% increase in “other stuff” kills another 137 per million.
    • It sounded good didn’t it?

    • If you said yes, with 68 million people in the UK, your system 1 just killed over 4,200 people. Well done.

SYSTEM 1 IS SCARED. SYSTEM 1 IS GUESSING. SYSTEM 1 IS WRONG.

2) We aren’t very good at comparing something today with something in the future.

  • A large number of people are going to die from Covid-19.

  • However, a much larger number of people are going to die from “other stuff”. We need to think about the long term effects of any policy on both Covid-19 and on the “other stuff”.

  • Deaths from “other stuff” will almost certainly be increased by poverty caused by the current economic lockdown. Some here in the UK, but many in other poorer countries.

  • Another question for you. What is better:

    a). 1,000 people die tomorrow; or

b). 2 people die every day for the next 5 years

  • System 1 is screaming out to you to pick (b). 2 is small, 1,000 is huge.

  • However, two deaths per day for five years is 3,650 deaths.

  • Be honest with yourself. When you saw the question, did you choose (a) or (b)?

  • If you chose (b), your system 1 just killed 2,650 more people.

  • We need to be really careful that by saving 1,000 people today, we don’t condemn 2 people a day to death for years.

SYSTEM 1 IS SCARED. SYSTEM 1 IS GUESSING. SYSTEM 1 IS WRONG.

3) We are naturally risk averse.

  • System 1 hates risk, and Covid-19 is an unknown risk. System 1 is saying jump away from the risk it sees today. System 1 is saying jump off the pavement and into the road, even if there is a bus coming. System 1 says that we will deal with the approaching bus later.

  • Our current policy of shutting down our lives and the economy is jumping away from Covid-19, but introducing a whole range of other risks.

  • Some are risks to us now.

    • Example – people with chest pains not going to hospital because they are afraid – The numbers at A&E departments are down by around half.
  • Some are risks to us in the future.

    • Example – a smaller economy in the future means less money for healthcare (and everything else) in the future.
  • Some are risks to others.

    • What is happening to the garment workers in Bangladesh who are now out of work because we have shut our shops? Do they have welfare and the NHS?
  • System 1 is wrong because there isn’t just one risk. Not jumping has risk but jumping has different risks. In order to work out which risks are bigger, we need to tell System 1 to shut up and engage system 2.

SYSTEM 1 IS SCARED. SYSTEM 1 IS GUESSING. SYSTEM 1 IS WRONG.

What do we need to we do?

As with any complex problem that needs us to trade off one risk against another, we need to pause, tell System 1 to shut up, and engage system 2.

System 2 is what will help us navigate this disease. System 1 will guess and get it wrong. System 2 is our best hope to get it right.

I am very worried that in the UK, and most other countries, System 1 is currently in charge.

SYSTEM 1 IS SCARED. SYSTEM 1 IS GUESSING. SYSTEM 1 IS WRONG.

About the Author:

Dr Glyn Jones – not a medical Doctor, but a PhD in mathematical modelling.

Studied Engineering at Cambridge followed by a PhD form Sheffield University in mathematical modelling.>

Then went for the money and had a successful career in the finance industry. Firstly, as a derivatives trader. Secondly, as an investment advisor and investment manager for pension schemes.

Retired as Chief Investment Officer of River & Mercantile Group PLC in January 2018.

Believes that a major contribution to the success of his career was understanding the limitations of complex mathematical models used in the finance and trading industry.

One of his favourite sayings when discussing the results from financial models was, and still is, “Here are some numbers we made up earlier”.