Mathematician and epidemiologist Adam Kucharski in Proof: The Uncertain Science of Certainty sets out for readers “why it is crucial to find better ways to trust the things we cannot explain…and…explain the things we do not trust.”
There’s little that’s self-evident truth. People need, crave proof. A lack of explainability bothers them. Many things are difficult to explain, simply because there may be no straight answer to the ‘why’ of it. That’s why, as more and more scenarios turn complex – scientific modelling to politics to Covid to AI – predictions are replacing explanations.
Many explanations to the ‘why’ of things only explain the ‘how’ of it. Take general anesthesia. Or heart defibrillation. Or Lincoln setting out equality as a goal for a country to be created. Or vaccines for Covid. We know what anesthesia or heart defibrillation does, but why a combination of drugs makes a person unconscious or why an electric current restores a heartbeat is not all clear.
Lincoln framed equality as a goal , when slavery was still in vogue. Instead of framing equality as a self-evident truth, Lincoln framed it as a proposition proved in building the nation. Equality remains a notion that’s flexible, wrought through amendments to laws that are proof of equality. So Lincoln taught himself from Euclid’s The Elements : The idea that mathematics has absolute answers, even if an illusion, made for powerful rhetoric.
In the vacuum of things unexplained, conspiracy theories take shape. When the science is patchy or complex, conspiracy theorists are driven to extremes, believing there is “no such thing as a coincidence”. The danger, in Henri Poincaré’s words, is “to doubt everything or to believe everything are two equally convenient solutions; both dispense with the necessity of reflection.”
Kucharski fears people are disengaging with truth in today’s climate of almost excessive doubt, argues that the gap between what’s happening and why it’s happening has to be bridged. What can be done to speed up the process of proof in a world of noisy data and noisier opinions? Making a plea for the value of rigour and logic, Kucharski says much of modern science is stuck in rote learning, whereas scientific evidence should be about tools, not rules. The toolkit is contradiction, construction, contraposition.
Science is dynamic, and proof ever evolving. “Even mathematical notions of proof” are “not always as robust and politics-free as they might seem.” That’s why it’s essential to embrace uncertainty, balancerebalance beliefs. To understand how ‘proof’ works, and the concept of it, it’s important to understand errors and biases. The need for total proof can be dangerous in a crisis – some level of scientific evidence may demand certain action but the inaction in waiting for more ‘proof’ can prove costly.
Probability quantifies uncertainty. Covid highlighted the need to understand such ‘uncertainty’. Were lockdowns effective? Did vaccines work? How to prove what Delta’s rise may mean in coming months? Kucharski says Covid showed how politicised science was – search for scientific truth collided with the urgency of decision-making. Questions arrived quickly, answers weren’t instant, and the evidence wasn’t deemed enough for policy tweaks. Was Delta more transmissible? What was the extent of the link between social contacts and transmission? What was the proof ? The book argues that in navigating the noise of data, it’s essential to keep the questions open. Leave room for, and learn to be comfortable with, uncertainty, doubt.
There’s little that’s self-evident truth. People need, crave proof. A lack of explainability bothers them. Many things are difficult to explain, simply because there may be no straight answer to the ‘why’ of it. That’s why, as more and more scenarios turn complex – scientific modelling to politics to Covid to AI – predictions are replacing explanations.
Many explanations to the ‘why’ of things only explain the ‘how’ of it. Take general anesthesia. Or heart defibrillation. Or Lincoln setting out equality as a goal for a country to be created. Or vaccines for Covid. We know what anesthesia or heart defibrillation does, but why a combination of drugs makes a person unconscious or why an electric current restores a heartbeat is not all clear.
Lincoln framed equality as a goal , when slavery was still in vogue. Instead of framing equality as a self-evident truth, Lincoln framed it as a proposition proved in building the nation. Equality remains a notion that’s flexible, wrought through amendments to laws that are proof of equality. So Lincoln taught himself from Euclid’s The Elements : The idea that mathematics has absolute answers, even if an illusion, made for powerful rhetoric.
In the vacuum of things unexplained, conspiracy theories take shape. When the science is patchy or complex, conspiracy theorists are driven to extremes, believing there is “no such thing as a coincidence”. The danger, in Henri Poincaré’s words, is “to doubt everything or to believe everything are two equally convenient solutions; both dispense with the necessity of reflection.”
Kucharski fears people are disengaging with truth in today’s climate of almost excessive doubt, argues that the gap between what’s happening and why it’s happening has to be bridged. What can be done to speed up the process of proof in a world of noisy data and noisier opinions? Making a plea for the value of rigour and logic, Kucharski says much of modern science is stuck in rote learning, whereas scientific evidence should be about tools, not rules. The toolkit is contradiction, construction, contraposition.
Science is dynamic, and proof ever evolving. “Even mathematical notions of proof” are “not always as robust and politics-free as they might seem.” That’s why it’s essential to embrace uncertainty, balancerebalance beliefs. To understand how ‘proof’ works, and the concept of it, it’s important to understand errors and biases. The need for total proof can be dangerous in a crisis – some level of scientific evidence may demand certain action but the inaction in waiting for more ‘proof’ can prove costly.
Probability quantifies uncertainty. Covid highlighted the need to understand such ‘uncertainty’. Were lockdowns effective? Did vaccines work? How to prove what Delta’s rise may mean in coming months? Kucharski says Covid showed how politicised science was – search for scientific truth collided with the urgency of decision-making. Questions arrived quickly, answers weren’t instant, and the evidence wasn’t deemed enough for policy tweaks. Was Delta more transmissible? What was the extent of the link between social contacts and transmission? What was the proof ? The book argues that in navigating the noise of data, it’s essential to keep the questions open. Leave room for, and learn to be comfortable with, uncertainty, doubt.
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Why 100% Proof Is An Illusion
