If I had more time to study, I would’ve passed this test; if I had more money, she would’ve stayed; if Goodluck Jonathan had won the elections, Nigeria would have been fine.
We ask ourselves these sort of questions every day. Also known as counterfactuals, these are alternate scenarios we draw on that give us an idea of how things would have turned out if we made a different decision or took a different path. They are the constant "What if?" scenarios that keep us restlessly awake at night.
Counterfactuals are great. By discovering a different way things could have been, they show us what to do differently and serve as a valuable learning experience. For example, if you had a bad interview experience and then realise it would have gone better if you had been more confident, you'd probably respond more confidently in the future.
But counterfactuals also trip us up. They do so when we take our counterfactual outcomes as facts and not just assumptions. Are you sure you would have passed that exam if you had more time to study? Did your girlfriend really leave you just because you weren't wealthy? We can never be sure about the answer to these questions.
Counterfactuals let us assume that every other factor is left constant; but in reality, things are never constant. When you imagine if you had more time to study, you naively assume that is the only thing that would change in the alternative scenario.
This illusion worsens when we think we can project simple conditional cause and effect to much larger policy decisions. With more complex issues, counterfactuals become less certain. When a decision is made, three possibilities exist: things remain the same, things get better, or things get worse. When we make a different decision, any of these three possibilities could have become a reality – and it is often very hard to tell which would occur.
Here come the RCTs
Hypothetically, we could go to an alternate universe or back to the past and make a different decision, but well…. we can’t. So how do we determine what really could have been? Data-serious non-profits, drug companies, and social scientists use a tool called the Randomised Controlled Trial (RCT). Through the process of randomisation, RCTs let policy makers or non-profits figure out the effect of their policy by comparing two random groups – one that was affected by the policy and one that was not. The beauty of RCTs is that the randomness of the groups means they are directly comparable – any individual differences are likely to cancel out. So any observed difference must be as a result of the policy!
Companies also employ this concept of randomisation and testing through the use of A/B tests to determine the most optimal choice in marketing or product design. For example, if you've ever used Facebook, you're likely to have been one of the subjects in its A/B tests. Companies present two options of the same site to two groups of people, so while your friend sees a green button, you could be seeing a blue button. This helps them figure out which option works better.
When Counterfactuals Meet Politics
RCTs and A/B tests are great, but how can we use them in everyday situations? They don't help us understand complex events any better, and these are the ones where we usually mistake correlation for causation. We’re especially vulnerable to the counterfactual fallacy in cases where multiple factors play a role in the determining an outcome. Politics is a particularly fertile breeding ground for this fallacy.
One great example? The ‘Why Hillary Lost’ pieces that try to break down what conspired to get President Trump to The White House. Though such theories seek to use counterfactuals to figure out what exactly went wrong, they usually end up finding correlation, not causation. Was it because Hillary was a woman? Or because she didn’t campaign hard enough in swing states? Did the American people vote based on bigotry and racism? Or did she lose because they were losing their jobs? Honestly, it is very hard to tell, and all these factors probably played a role. Any attempt to pinpoint a single cause – or even the suggestion that Bernie Sanders would have swept the floor with President Trump – is unlikely to be true.
Never one to be left out of the fun, Nigerians are undergoing a similar case of the counterfactual fallacy. As the economy takes a nosedive under the leadership of President Buhari, ardent fans of the former president, Goodluck Jonathan, frequently gloat that the economic situation would be different if their man had been re-elected into office. They seem to have history on their side as well – Nigeria's economy grew by more than 6% in President Jonathan's last full year in office.
A closer inspection reveals the ruse. This counterfactual is lazily based on a number of assumptions. The first is that Nigeria's economy does not move with global oil prices – and the latter crashed in 2014. Another assumption is that CBN Governor Godwin Emefiele – appointed by President Jonathan – would act more independently and pragmatically. And this is barely scratching the surface. This does not excuse President Buhari's uninspiring economic management during his much-hyped second rule, but it does point out the fallacy in attempting to create an alternative reality that perfectly conforms to what we'd prefer.
Instead, counterfactuals should teach us to demand more than vague promises from politicians – irrespective of party. Wishful thinking does not reality make. Next time you’re tempted to create scenarios of what could have been, ask yourself if you’re thinking up what you wish could have been or if you’re accounting for what truly could have been. Anything can be good or bad; it is our thinking that makes it so.