The 'Rigor of Mathematics' in Medicine
Taleb criticizes mathematical models of medicine and social science that focus on known quantities while ignoring important unknowns. He favors using probability to expose uncertainty and inconsistencies in decisions.
THE IDEA
For those of us who laugh at the charlatanism hidden behind fictional mathematics in social science, one may wonder why this did not happen to medicine.
And indeed the cemetery of bad ideas (and hidden ideas) shows that mathematics fooled us there. There have been many forgotten attempts to mathematize medicine. There was a period during which medicine derived its explanatory models from the physical sciences. Giovanni Borelli, in De motu animalium, compared the body to a machine consisting of animal levers—hence we could apply the rules of linear physics.
Let me repeat: I am not against rationalized learned discourse, provided it is not fragile to error; I am first and last a decision maker hybrid and will never separate the philosopher-probabilist from the decision maker, so I am that joint person all the time, in the morning when I drink the ancient liquid called coffee, at noon when I eat with my friends, and at night when I go to bed clutching a book. What I am against is naive rationalized, pseudolearned discourse, with green lumber problems—one that focuses solely on the known and ignores the unknown. Nor am I against the use of mathematics when it comes to gauging the importance of the unknown—this is the robust application of mathematics. Actually the arguments in this chapter and the next are all based on the mathematics of probability—but it is not a rationalistic use of mathematics and much of it allows the detection of blatant inconsistencies between statements about severity of disease and intensity of treatment. On the other hand, the use of mathematics in social science is like interventionism. Those who practice it professionally tend to use it everywhere except where it can be useful.
The only condition for such brand of more sophisticated rationalism: to believe and act as if one does not have the full story—to be sophisticated you need to accept that you are not so.
When to use it
Evaluating medical research that over-relies on statistical models without considering real-world complexity and rare events
Assessing economic predictions that use mathematical models ignoring black swan events and unknown unknowns
Using probability to detect inconsistencies between disease severity and treatment intensity in clinical decision making
FROM THEORY TO EVERYDAY LIFE
In practice
Borelli's mechanical model of the body
Giovanni Borelli, in De motu animalium, compared the body to a machine consisting of animal levers. Taleb uses this mechanical model to illustrate his criticism of applying a narrow physical model to biological complexity.
Detection of inconsistencies in treatment severity
The author notes that a robust use of probability mathematics can reveal inconsistencies between stated disease severity and actual treatment intensity, illustrating a practical application that accounts for unknowns.
A MOMENT TO REFLECT
Put it to work.
Where in your field do you see naive mathematization that ignores unknown unknowns?
How can you distinguish between robust and fragile uses of mathematics in decision-making?
Think of a claim in social science that used mathematical models poorly—what were the missing elements?
Often confused with
References
- De motu animalium — Giovanni Borelli
CONTINUE THE CONVERSATION
Source texts
- Antifragile (Nassim Nicholas Taleb)