Everyday Philosophy: Bad at Probability? That might be a blessing.
Everyday Philosophy: Bad at Probability? That might be a blessing.
By Jonny Thomson | Published: 2024-12-20 17:21:00 | Source: Thinking – Big Think
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Very few of my friends understand the basic possibilities of life. They only see things in black and white, often through intuition. Can you tell me why so many humans are so bad at odds, and why it’s important to be better?
– Pratyush, IndiA
I used to work with a guy who used to call me “Hopscotch Johnny.” Hopscotch is a popular game where you jump from one square to another: one leg, two legs, one leg, two legs. Hop, hop, hop. The reason I’m called Hopscotch Jonny is because I’ve spent a lot of my life busy with fads. I live in stages. I’ll become obsessed with a topic, but five books on it, and then I talk about it to anyone who will listen, makes the whole book boring. A new obsession consumes my life for a few months before I move on to something new — before I jump into the next box. My study is a jungle thanks to a potting phase, my closet is full of swim gear from my most famous triathlon, and now, as I write this, my phone is almost full of downloaded podcasts about data analysis. (Here’s an unpaid subscription, but “The Studies Show” is my all-time favorite.)
So Pratyush’s question is timely for me, because I’ve realized that I’m one of those humans who is ‘bad at probabilities’. My father, a psychologist, used to say, “Half people are below average in intelligence, you know,” trying to educate me. But everything your father says is worthless until you are twenty. So, let’s dive into why I, and many people, are so bad at probability.
To do this, I will do my best to explain Bayes’ Theorem and how it relates to “intuition” and “black and white.” Then, we can explore the extent to which humans actually fit the mold of the ideal of enlightenment. Are humans really that rational? Are we meant to be?
Bayes’ Theorem: Rational Idealism
Bayes’ Theorem is arguably the most important thing any rational person can learn. A lot of our arguments and disagreements that we shout about are because we don’t understand Bayes’ theorem, or how human rationality often works.
Named after 18th-century mathematician Thomas Bayes, Bayes’ Theorem is essentially an equation that asks the question: When you’re presented with all the evidence for something, how much should you believe it?
Bayes’ theorem teaches us that our beliefs are not fixed; It’s possibilities. Our beliefs change when we compare new evidence with our assumptions, or our “ancestors.” In other words, we all carry with us certain ideas about how the world works and new evidence will challenge us. For example, someone might believe that “smoking is safe,” or that “vitamin C prevents disease,” or that “human activity has nothing to do with climate change.” These are their ancestors: their current beliefs, shaped by the culture, biases, and information they have encountered.
Now, imagine a new study that challenges one of your predecessors. Well, one study may not carry enough weight to overturn your current beliefs, but imagine the studies piling up and eventually the scales start to tip. At some point, your ex’s message will become less acceptable.
Bayes’ theorem says that being rational is not black and white, as Pratyush points out. It’s not even about right or wrong. It’s about what makes the most sense based on the best available evidence. But for this to work, we need as much high-quality data as possible. Without evidence, without belief-forming data, we only have our own prejudices and biases.
Primacy and biases: Why we’re not all that rational
This column is called Everyday philosophyno Scientific method 101. The task here is to look at human beliefs, the human condition, and how societies function more broadly. When we look at it from this position, Bayes’s theorem definitely hits a wall. After all, although Bayes’ theorem is a great—perhaps the greatest—way to interpret data and drive scientific results, it is not the only way to explain human beliefs.
In our daily lives, “new evidence” is rarely a double-blind, peer-reviewed study published in a prestigious academic journal. It’s an indefinable blur of personal experience, reliable testimony, background intuition, and what that guy wrote on social media last week. We could and did provide a heavy notebook full of “cognitive biases” or “logical fallacies.” For example, authority bias, where we believe that the opinions of certain authority figures have more influence (even on topics beyond their authority). But these biases are not unwelcome shortcomings, and we must always purge them. They are there for a reason.
One of the best and most famous examples is found in the works of Daniel Kahneman, e.g Thinking, fast and slow. The human mind has evolved over hundreds of thousands of years in response to a specific environment that requires specific cognitive abilities. Over the time scale required for evolution, very little is “meaningless.” Survival of the fittest leaves little room for repetition. These biases – “bad probability” mentalities – serve a purpose. For example, take the “optimism bias,” which makes us believe that we are less likely to experience negative events such as illness or accidents than others. This can enhance motivation and resilience, encouraging people to take risks and pursue goals they might otherwise avoid. If every new entrepreneur fully understood the statistical probability of failure, he or she would probably never get started. Human agency, especially human boldness, requires a high degree of ignorance of risks.
Bad but good
So, I agree with you, Pratyush. I think a lot of people are bad at odds. We often don’t understand how things like Bayesian statistics work, and we don’t appreciate how uncertain a lot of things are. But while “misfortune” can sometimes lead to flawed decisions, it is also closely linked to how we navigate an uncertain and chaotic world.
Rationality, like Bayes’ theorem, gives us an ideal to strive for, perhaps, but our evolutionary quirks remind us that we are still very much human.
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