Charles Capaday
Why humans do science
Humans possess a truly uncanny ability, understanding. Consequently, it logically follows that we naturally seek to understand. As Prof. Roger Penrose [1, 2] made it clear, understanding is not an algorithm. This, on its own, is a very good reason to think that artificial intelligence will never have understanding and science will thus always be a human enterprise. I add that understanding entails consciousness, id este self-awareness and self-dialogue.
When human understanding is focused on nature, it is called science. First and foremost, science is experimental, a fundamental that is often obviated in our epoch of sensationalism and untestable theoretical speculations. In science, we confront nature by forcing it to reveal something of itself, either by observation or experimentation. The later involves confronting nature with a question of the sort ‘is it’, or ‘is it not’. Pasteur’s demonstration that spontaneous generation of life does not occur is an excellent example of forcing nature to reveal something of itself by a well-designed experiment. Measurement accuracy is highly important in science and repetition is necessary to reach a high level of certainty. Additionally, in experimental work, a well thought out control is needed. This too increases certainty of the results. There is no rule that says that only one control is needed, the more well thought out controls and repetitions of the experiment with different controls the better. Regrettably, there are currently too many published scientific studies lacking proper controls. The reasons for this are many, lack of scientific culture is among them. Indeed, one of the motivations of the organizers of this forum is to increase scientific culture. Poor studies are unreproducible, they lead to confusion and a waste of effort and funds. Do and redo your work, re-examine your assumptions and verify the logic and veracity of everything you claim. High quality data once obtained need to be interpreted. This requires acumen, i.e. understanding. Great science comes from great acumen.
Doing science is pleasurable. Designing and building apparatuses for experiments is one source of pleasure. The careful execution of a difficult experiment, or a novel theoretical insight are pleasurable. In a word, there is a pleasure factor in science, and it is linked to understanding. Who should do science? If you are curious and experience pleasure in doing science and understanding, then try your hand at science.
What is science vs. non-science? Asking if drug X is more efficient that drug Y is not science, because we are not asking nature to reveal something of itself. This type of work is simply testing and currently strongly relies on statistics, which is not a branch of mathematics. The premises of the statistical methods used may not apply to the real world and statistics cannot palliate poor experimental design or execution. Statistical inference is not scientific proof, and the latter can never reach the level of mathematical proof, the only type of proof that is certain, forever. If you rely solely on statistics to claim a novel finding, it will never stand on firm ground. What will, are findings of direct causal relations or better, the elucidation of mechanisms. And, if the endeavor culminates in a mathematical model that captures the main operations of the system studied, that is beautiful science. Outstanding science we know, say Einstein’s special and general relativity, or Maxwell’ s theoretical synthesis of Faraday’s seminal discoveries. Such works express universal laws.
Epilogue
There is no proof in science in the mathematical sense of the term. Hence, there always exists some uncertainty, ambiguity, and incompleteness. The best we can do is to corroborate or falsify hypotheses by careful experiments. Scientific knowledge is thus not to be praised but questioned. There is otherwise no progress. Insightful questioning presumes understanding. My answer to the question ‘why do we research?’ is simply, to satisfy our curiosity. Curiosity is inherent to understanding and the latter is pleasurable and thus motivating.
References
[1] Penrose, Roger (1989). The Emperor's New Mind: Concerning Computers, Minds, and the Laws of Physics. Oxford University Press. ISBN 978-0-19-255007-1.
[2] Penrose R., Shimony A., Cartwright N., Hawking S. (1997). The Large, the Small and the Human Mind. Cambridge University Press. ISBN 978-0-521-78572-3.
At the time of writing, Charles Capaday is Adjunct Professor in the Dept. of Bioengineering at McGill University (Montreal, Canada) and Visiting Professor in the Department of Health and Human Physiology at the University of Iowa.