Hossein Jorjani
First publication: 2026 – 07 – 19
Science is often associated with certainty. Popular accounts frequently portray scientific knowledge as the discovery of universal laws that establish facts beyond reasonable doubt. Historically, however, the development of modern science has followed a different trajectory. Rather than moving toward absolute certainty, many scientific disciplines have become increasingly probabilistic, explicitly incorporating uncertainty into both their theories and their methods.
This transformation reflects not a weakening of scientific knowledge but an increase in methodological sophistication. Statistical inference, stochastic models, confidence intervals, Bayesian methods, risk estimation, and probabilistic prediction have become indispensable in disciplines as diverse as genetics, epidemiology, climatology, economics, and particle physics. Instead of eliminating uncertainty, modern science increasingly seeks to measure, quantify, and manage it.
Evolutionary biology illustrates this development. Darwin explained evolution primarily through qualitative reasoning supported by extensive empirical observations. Subsequent generations of biologists, however, introduced probability theory into the study of inheritance, mutation, natural selection, genetic drift, and population dynamics. Modern evolutionary theory therefore relies heavily upon statistical models that estimate the likelihood of evolutionary outcomes rather than predicting individual events with certainty.
This shift represents a fundamental change in scientific reasoning. Classical science often sought deterministic explanations in which identical causes invariably produced identical effects. Contemporary science recognizes that many natural processes are inherently stochastic or too complex to permit exact prediction. Scientific explanations therefore increasingly concern distributions, probabilities, and expected outcomes rather than absolute certainties.
The increasing role of probability should not be interpreted as a retreat from scientific objectivity. On the contrary, explicitly acknowledging uncertainty often produces more reliable knowledge than unwarranted claims of precision. A confidence interval, a probability distribution, or a quantified margin of error expresses both what is known and what remains uncertain. Such transparency strengthens rather than weakens scientific inference. Modern science should therefore be understood not as the pursuit of certainty but as the continual refinement of reliable knowledge under conditions of uncertainty. The transition from deterministic to probabilistic reasoning constitutes one of the most significant methodological transformations in the history of science.
Hossein Jorjani 