Two ways of thinking. But it was a person who approached the problem using scientific thinking who got it right.
Step 1: Start with an open mind
When thinking about a problem or debate, scientists always start with an open mind.
If you already think you know the answer, how receptive are you going to be to new information? And really, unless you are an expert, how likely is it that you really do know the right answer?
“The vast majority of ideas,” wrote astronomer Carl Sagan, “are simply wrong.”
“Science invites us to let the facts in”.
This is surprisingly difficult. Everyone likes to think they know what they are talking about.
When we are asked a question, scientific thinking requires us to admit that we often simply don’t know the answer.
A lot of people ask me for my predictions about COVID-19. I’d like to give out answers – because it makes me look like an expert. But I’m not an expert. Unless it’s something I’ve specifically reported on, I try to say ‘I don’t know’.
Scientists tend to be more willing to trust the judgement of experts in other fields – like mechanics – because they start with an open mind. They accept they don’t know best.
“It’s crazy. Why would you not trust the guy who repairs your car to do a good job?” says Associate Professor Peter Bragge, a specialist in reviewing and evaluating research and Director of Monash Sustainable Development Institute’s Evidence Review Service.
Being open-minded also means not holding on to a belief when the evidence changes. This is even harder!
If you’ve argued passionately for something, it can feel like you’re backflipping if you change your mind.
But if the evidence changes and you don’t change your mind, that’s not a good spot to be in.
Step 2: Be sceptical
The counter-balance to having an open mind: scepticism. Prove it. When a big company makes a claim about its new apple sauce, or a government makes a claim about a health policy, we should say: prove it. Want us to wear masks? Prove it. Want us to be vaccinated? Prove it. (In both cases, thankfully, they have – but we should remain sceptical about new COVID-19 drugs until they prove their benefits).
“People with agendas are always a flag for my scepticism,” says cancer biologist Associate Professor Darren Saunders.
Step 3: Accept uncertainty
Scientists always accept that there are things they do not know, and things they simply cannot know for sure.
Accepting you don’t know things isn’t a sign of ignorance – it allows you to make better decisions because you’re taking the uncertainty into account.
“You have to embrace uncertainty. I reckon probably the single most important thing I learnt from my PhD is how to be comfortable with grey areas and uncertainty. Because that’s at the heart of scientific understanding,” says Professor Saunders.
Equally – and I as a journalist have learnt a lot from this – science says it is OK to wait for evidence before coming to a conclusion, rather than coming to a gut decision and risk getting it wrong.
I’ve been trying to apply this thinking to new COVID-19 outbreaks. Everyone wants to know if an outbreak is going to turn into a cluster or a large outbreak – but the reality is, at the start of the outbreak, we simply don’t know.
Step 4: Assemble your data
Go and do your research. Pull together all the data – stuff that agrees with your argument and stuff that refutes it. Consider everything, rather than fixating on a single point.
Then, for each piece of data, consider the quality of the evidence.
Professor Bragge found himself purchasing a webcam recently. He started by accepting he knew nothing about webcams. Then he gathered data, reading reviews from across the web. Each review he categorised by quality, marking down reviews that were clearly sponsored.
“You want to find a good, independent source. Like Choice – you can see how they’ve tested it, they’re not funded by industry.”
Step 5: Develop a hypothesis
A hypothesis is a theory about the world – a guess.
Ask yourself: which of my theories best explains the data I have gathered? Start with the most likely explanation, and then test it. If you can prove it wrong, move on to the next most likely.
Apply Occam’s razor. If you have two theories that explain the facts equally well, pick the simpler one.
Good hypotheses are ‘falsifiable’. There’s no point, scientists say, in having a theory about the world that can’t be proven false.
Consider the Wuhan ‘lab leak’ hypothesis. Much of the strength of this hypothesis rests on the idea that someone – the Chinese in this case – are lying. Sure, that’s plausible. But if you use the claim that someone is lying to knock down every key pillar of an opposing argument while being unable to provide evidence showing a lie is being told … well, you’re not left with much of an argument beyond ‘fake news’, are you?
“Claims that cannot be tested, assertions immune to disproof, are veridically worthless,” writes Sagan.
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