“… scientific evidence should be about tools, not rules”
Adam Kucharski made this statement toward the end of his 2025 book, Proof: The Art and Science of Certainty (p.302). This was a fitting phrase to represent what I found to be one of the most important points of this book aimed at exploring what we consider to be proof and how we reach it. Specifically, Kucharski spoke to the importance of being equipped to not only evaluate the quality of proof one is presented with but also to identify gaps in said proof.
The above statement was sandwiched between two ideas that are critical to consider in this moment. The first, that “much of modern science is still mired in rote learning, from ‘significant’ p-values to simplistic evidence pyramids.” The second, a quote from mathematician Maryam Mirzakhani, “‘…It’s the reason why doing research is challenging as well as attractive. It is like being lost in a jungle and trying to use all the knowledge that you can gather to come up with some new tricks, and with some luck, you might find a way out.’” Taken together, these ideas speak to the divide between scientists and the people who use their science and how that can, and has, complicate communication of, and actions based on, information gleaned from scientific inquiry. Scientists are enthralled with navigating Mirzakhani’s “jungle” to learn something new and push the boundaries of our collective knowledge; however, they don’t always consider the social factors that determine whether or how new information will be received and used. On the other hand, non-scientists often aren’t versed in how science works, so necessary considerations, like expansive time, relative permanence and non-definitive answers, can leave people unsettled and looking for clearer, simpler statements — like those offered by rote learning or social media influencers.
While Kucharski drew on a topic of great divide — COVID-19 — as a central example, the main theme of this book was not the differences in focus between scientists and non-scientists, but rather the limitations of proof — even within the practice of science. Kucharski started with a historical look at mathematical proofs and some of the individuals who identified important gaps within them before moving on to consider more current examples, including discussions related to p-values and significance, publication biases, and strengths and weaknesses inherent in the various scientific approaches to evaluating hypotheses. In terms of the latter, he discussed scientific understanding gained by methods other than randomized-controlled trials and the benefits of triangulation through both understanding and approach. The former, relating to gaps from things we can’t measure, and the latter to overcoming approach-based biases.
Using examples across science, politics and law, Kucharski weaved concepts of statistics and math into real-world examples that demonstrated not only our reliance on proof but also the importance of understanding its gaps. One example was Abraham Lincoln’s penchant for using proof in arguments against slavery. Another was COVID-19 where we didn’t have the luxury of “expansive time” to build a complete understanding before making decisions that would affect entire populations. Kucharski also addressed the human limitations of large datasets, the increasing need for machines in doing this work (e.g., artificial intelligence), and the related implications and considerations.
Kucharski concluded by reminding readers that other elements factor into how proof is used within a society. “A simplistic view of scientific evidence risks a path of too much faith followed by too much disillusionment. From researchers to journalists, societies must get better at communicating how the process works, monsters and all” (p. 304).
At the end, I found myself back at the divide between scientists and the people who use their science. Scientists surely know the path through the jungle is not perfect, but are those who use the evidence prepared to embrace the process and its monsters, or will the proof be dismissed out of hand because it’s unsettled — or unsettling?
Check out Adam Kucharski’s book, Proof: The Art and Science of Certainty.
Contributed by: Charlotte A. Moser, MS
“… scientific evidence should be about tools, not rules”
Adam Kucharski made this statement toward the end of his 2025 book, Proof: The Art and Science of Certainty (p.302). This was a fitting phrase to represent what I found to be one of the most important points of this book aimed at exploring what we consider to be proof and how we reach it. Specifically, Kucharski spoke to the importance of being equipped to not only evaluate the quality of proof one is presented with but also to identify gaps in said proof.
The above statement was sandwiched between two ideas that are critical to consider in this moment. The first, that “much of modern science is still mired in rote learning, from ‘significant’ p-values to simplistic evidence pyramids.” The second, a quote from mathematician Maryam Mirzakhani, “‘…It’s the reason why doing research is challenging as well as attractive. It is like being lost in a jungle and trying to use all the knowledge that you can gather to come up with some new tricks, and with some luck, you might find a way out.’” Taken together, these ideas speak to the divide between scientists and the people who use their science and how that can, and has, complicate communication of, and actions based on, information gleaned from scientific inquiry. Scientists are enthralled with navigating Mirzakhani’s “jungle” to learn something new and push the boundaries of our collective knowledge; however, they don’t always consider the social factors that determine whether or how new information will be received and used. On the other hand, non-scientists often aren’t versed in how science works, so necessary considerations, like expansive time, relative permanence and non-definitive answers, can leave people unsettled and looking for clearer, simpler statements — like those offered by rote learning or social media influencers.
While Kucharski drew on a topic of great divide — COVID-19 — as a central example, the main theme of this book was not the differences in focus between scientists and non-scientists, but rather the limitations of proof — even within the practice of science. Kucharski started with a historical look at mathematical proofs and some of the individuals who identified important gaps within them before moving on to consider more current examples, including discussions related to p-values and significance, publication biases, and strengths and weaknesses inherent in the various scientific approaches to evaluating hypotheses. In terms of the latter, he discussed scientific understanding gained by methods other than randomized-controlled trials and the benefits of triangulation through both understanding and approach. The former, relating to gaps from things we can’t measure, and the latter to overcoming approach-based biases.
Using examples across science, politics and law, Kucharski weaved concepts of statistics and math into real-world examples that demonstrated not only our reliance on proof but also the importance of understanding its gaps. One example was Abraham Lincoln’s penchant for using proof in arguments against slavery. Another was COVID-19 where we didn’t have the luxury of “expansive time” to build a complete understanding before making decisions that would affect entire populations. Kucharski also addressed the human limitations of large datasets, the increasing need for machines in doing this work (e.g., artificial intelligence), and the related implications and considerations.
Kucharski concluded by reminding readers that other elements factor into how proof is used within a society. “A simplistic view of scientific evidence risks a path of too much faith followed by too much disillusionment. From researchers to journalists, societies must get better at communicating how the process works, monsters and all” (p. 304).
At the end, I found myself back at the divide between scientists and the people who use their science. Scientists surely know the path through the jungle is not perfect, but are those who use the evidence prepared to embrace the process and its monsters, or will the proof be dismissed out of hand because it’s unsettled — or unsettling?
Check out Adam Kucharski’s book, Proof: The Art and Science of Certainty.
Contributed by: Charlotte A. Moser, MS