Newton is often seen as the greatest of 17th-century scientists—portrayed as a lone genius relying on mathematical methods for his transformational breakthroughs: the laws of motion, universal gravitation and optics. Yet his work was not a product of sudden insight. It emerged from the broader tool revolution in science sparked by new instruments that enabled observing and measuring the world with unprecedented precision. This transformation culminated at the end of the century in Newton's Philosophiae Naturalis Principia Mathematica in 1687. Newton inherited a scientific landscape already transformed by instruments and experiments. He built on powerful new tools like the telescope and was deeply influenced by Galileo's experiments on motion, Boyle's work on pressure using the vacuum pump, and Hooke's meticulous empirical studies—all of which relied on new measurement tools and repeatable experiments. He also inherited rapidly expanding mathematical methods, including analytic geometry developed by Descartes, and early forms of calculus pioneered by Fermat and Wallis. Newton built extensively on Galileo's experimental findings on acceleration and on rich observational data of planetary motions. Recognising the telescope's extraordinary power, Newton himself developed a reflecting telescope. He also conducted prism experiments demonstrating that light consists of a spectrum of colours—with theory following experiments. This toolbox helped lay the groundwork for mathematics to describe what these instruments helped reveal: motion, force and light. It was observation and measurement that demanded better mathematics to express the motion of falling bodies and celestial objects. Newton developed calculus—as Leibniz did independently in 1675—as a means to formulate his theories and make better predictions. Remove one of these foundational elements—the telescope's observational power, the experimental data from these other new instruments, or the mathematical methods for expressing dynamic relationships—and Newton's achievements would not have been possible. Newton's ability lay in synthesising previous research, and experiments using instruments, with these mathematical methods. Newton could see further because he, in his own words, 'stood on the shoulders of giants'—and those giants had access to the right new tools. In the centuries leading up to Newton, engineers, architects, surveyors, navigators and watchmakers were using quantitative methods to solve real-world problems. Leveraging these successful mathematical methods, a small but growing group of scholars increasingly integrated the methods into science. We can trace these scientific roots even further back. In Newton's seminal Philosophiae Naturalis Principia Mathematica, we see how he applied our mind's evolved abilities to observe and experiment, he adopted the numerical system created by ancient Indian mathematicians and brought to Europe through the work of Islamic scholars, he used geometry refined by the mathematician Euclid in ancient Egypt, he wrote in Latin created by the Romans and on paper invented in China, he employed algebra developed by various cultures across millennia, and he was influenced by Ibn Al-Haytham's pioneering theory of optics. Physicists often credit mathematics—especially as embodied in Newton's work—as the central driver of the scientific revolution. But mathematics was one method. These powerful experimental tools and observations opened up entirely new realms of reality—findings that could then be described with mathematics. Many pivotal breakthroughs of the 17th century—such as biological and medical discoveries including the circulation of blood in 1628, capillaries in 1661 and cells in 1665—were derived from experiments and the new microscope. Breakthroughs relying on mathematics were mainly concentrated in physics. How modern science arose cannot be reduced to mathematical advances. New microscopes and telescopes were critical in better observing and uncovering the nature of life and the universe. (These observable scientific explanations also increasingly reduced the need for religious explanations of how the world works, though Galileo and Newton remained Christian.)
of scientific methodology As these pioneering experimental tools uncovered new layers of knowledge, scientists increasingly focused on how we apply a method or tool: scientific methodology. Researchers began combining different methodological approaches—integrating for example experimental methods, mathematical methods or causal inference— to generate more reliable results. This method integration allowed for experiments that were more quantifiable, testable and replicable, and helped establish clearer cause-and-effect relationships. We see this layered methodology in the works of Galileo, Boyle and Newton. With each new tool—microscopes, barometers, calculus—methodology evolved into an expanding toolkit that more explicitly stressed experimentation and measurement. Boyle—working with the new vacuum pump—conducted controlled experiments, and became a leading advocate T for controlled, repeatable experiments. Galileo and Newton merged instrumental data with mathematical reasoning. These developments spurred a broader metaunderstanding of the scientific process itself: not just what but how we should apply science's tools and methods. At its core, scientific methodology is about improving how we use tools. The success of the experimental breakthroughs made clear: a more systematic, more controlled methodology of studying the world could uncover truths of nature once thought unreachable. Centuries earlier, Al-Haytham in the 11th century and Grosseteste and Roger Bacon in the 13th century had also stressed the need to unify observation, experiments and methods with theory. What they lacked were the powerful tools for observing and experimenting that 17th-century scholars finally had in their hands— ultimately enabling scientific methodology and testable science to reach its greater potential. Scientific methodology added a meta layer to science—making how we applied our toolbox more systematic and robust. The concept of scientific methodology, in its explicit form, spread. With better methods came the hope that we could finally solve the great puzzles of stars, planets, human biology and the causes of diseases. The spark of the scientific revolution was not a new hypothesis or new experiment—it was a new way of seeing that led to entirely new types of hypotheses and experiments and to realising their importance. After the invention of these two tools, Francis Bacon, in Novum Organum in 1620, then reiterated the importance of methodology. He highlighted that knowledge should not come from speculation but from inductive reasoning grounded in carefully collected evidence. And this is precisely what these new tools had been generating at the time. They provided a systematic, unifying framework for cross-disciplinary inquiry, from astronomy to biology—moving beyond philosophical speculation. The core insight here remains unchanged today: great tools and methods not only make discoveries possible but also make them reliable, repeatable and robust. Science keeps refining its methodology—for example through more rigorous experimental controls, randomisation and robust statistical inference to draw clearer conclusions. These methodological features were largely developed in the 19th and 20th centuries within medicine and public health. It is here where the stakes are at times life and death and the demand for methodological rigour is especially high. A powerful new method emerged in the mid-1800s: the natural experiment. It was pioneered by the British epidemiologist John Snow in his groundbreaking study in 1855 of a deadly cholera epidemic in London. Snow studied a 'natural' separation in the water supply across different neighbourhoods, comparing disease rates between areas served by different pumps. By linking the prevalence of cholera to contaminated water drawn from a single public pump, compared to other public pumps that were not contaminated, he provided an effective method of using data to infer causality in public health. This offered compelling evidence of the cause of cholera: water contaminated by sewage. His findings convinced local authorities to take action— and the outbreak stopped. It was a turning point in public health: an excellent example of how combining observational data with thoughtful methodology saves many lives. Nearly a century later, in 1948, another major method breakthrough transformed medicine and public health: the first randomised controlled trial. Developed by epidemiologist and statistician Bradford Hill, the method was applied in a landmark study testing a treatment (streptomycin) for tuberculosis in London—one of the most deadly diseases of the time. By randomly assigning patients to treatment or control groups, the RCT introduced an entirely new methodological rigor: it vastly reduced bias, clarified cause and effect and set a new methodological benchmark for future studies. Then came the invention of computers—since the mid-20th century—that sparked a deep transformation in how we conduct science: making it far more systematic, scalable and replicable than ever before. Where scientists once relied on slow data collection and manual calculations, they can now rapidly process vast datasets, run complex statistical analyses automatically, replicate experiments with striking precision and even run many experiments at the same time—all of which were unimaginable before. From basic data analysis to running millions of simulations, digital technology has made scientific methodology much faster, more methodical and infinitely more scalable. New computational methods—powered by big data, largescale statistical simulations, machine learning and AI—have transformed entire fields, uncovering patterns and layers of complexity we never saw. The internet has also reshaped the speed and openness of science: research can now be quickly published, reviewed, replicated and improved by scientists across the globe. These developments are spurring a digital and AI revolution—one that can redefine how efficiently and quickly we do science.
and systematic observational methods took off after, not before, the microscope and telescope Modern science was seeded in 1590 with the microscope and truly ignited in 1608 with the telescope—triggering the first large-scale surge of public and scholarly interest in science. These tools laid the critical foundation and catalysed science's instrumental, demographic, institutional and conceptual development in the decades that followed. Here we synthesise the key insights. Modern science followed—not preceded—the invention of these first groundbreaking instruments: • These optical breakthroughs were the first tools in history to fundamentally extend human perception— breaking with millennia of inherited instruments from antiquity. In contrast to ancient tools—from quadrants to geometry— used to study the world in the 1500s and earlier, the microscope and telescope revealed phenomena previously unimaginable, both at very small and very distant scales. • They fundamentally transformed our relationship with nature and how we interacted with it—shifting us from observers using our evolved naked eye to active discoverers. These tools transferred authority from ancient Aristotelian texts to nature itself—to what we could actually see through these fascinating lenses. At its core, modern scientific consciousness lies in transcending our natural sensory limits through technological innovations. T • These two optical instruments turned, for the first time, isolated insights into a sustained engine of discovery, unexpectedly sparking most of the major discoveries of the 17th century. The tools did not just uncover unknown phenomena about life and the universe—but they forced us to redefine how we understood nature, and triggered modern observational and experimental science. • These fascinating tools of discovery sparked widespread curiosity and attracted a growing community of scholars. Works like Galileo's Starry Messenger and Hooke's Micrographia showcased these new instrument-driven discoveries, quickly becoming widely read and influential—and catalysing the scientific community. Before this optical revolution, natural philosophy was a fragmented and minor pursuit. In 1600, fewer than an estimated hundred individuals, mostly in Italy, engaged in regular inquiry; by the end of the century, a community began to emerge that spread to England, France and Germany. • The exciting telescopic and microscopic breakthroughs motivated the establishment of the first major national scientific societies—beginning with the Royal Society in 1660, whose early members used these tools including Hooke, Boyle and Newton. The French Academy of Sciences followed in 1666 and then the Berlin Academy of Sciences in 1700. These institutions—and the first scientific journals that soon followed—mark how science had transformed into a tool-enhanced, observation-led system and demanded debate about the surge of these new breakthroughs. • These powerful tools made systematic observation the gold standard, redefined what counted as valid evidence and enabled science to truly become replicable. They gave science its first universal language of evidence: scholars across countries—for the first time—could observe the same phenomena, apply consistent tools and methods and validate each other's findings. The success of these instruments catalysed how to use them better. Indeed, the tools themselves embody methodology: systematic observation, inductive evidence and experimentation. In 1620, about a decade later, Bacon emphasised these features again in describing how science should be conducted. These better instruments enabled better observations and demanded better hypotheses. In summary, before the invention of the microscope and telescope, science had not yet surpassed the limits of ancient tools or transcended our evolved sensory limits—but their arrival marked the moment we finally did. With their invention, we gained direct access to entirely new realms of reality at microscopic and astronomical scales that were previously unimaginable. And after their invention, we observe three large scientific developments: these instruments did not emerge from scientific institutions, or from a large scientific community, or from a formal scientific methodology, but they preceded and inspired them. Their transformative impact forced science to evolve and grow, to create new institutions that could share and publish these breakthroughs and to apply more systematic methods for observation and confirmation. More so than other factors, the transformative power of these new instruments better explains the rise of modern science by enabling these very breakthroughs. And what is key is that they did not arise from science at all, but unexpectedly from two eyeglass makers—Janssen and Lippershey—experimenting with lenses; yet they ultimately made modern science possible. These two instruments did not help science, but fundamentally redefined it: forcing natural philosophy to transform into modern science. They illustrated what science was and could become. They completely changed the sophistication of science's major tools before and after this decisive point. In short, science did not take off because we asked better questions, but because these tools finally offered what natural philosophy had lacked: reliable access to new evidence of unimaginable phenomena—triggering new explanations and theories like nothing before. And this same dynamic powers science today, driven by modern instruments that build on that first, transformative leap in sensory enhancement that supercharged discovery. From scanning electron microscopes that reveal the nanoworld, to deep-space telescopes that peer across the universe, from particle accelerators that probe into matter, to quantum sensors that detect what was once undetectable, each new instrument keeps pushing the boundaries of what we can observe and think. Each forces science to rethink, rewrite and evolve. With each major leap in observation comes a major leap in understanding what is revealed.
At this stage, we can pull together the bigger picture and synthesise the insights: nine main conditions enabled modern science—and six of them also formed the foundation for civilisation. Here we step back and trace how scientific thinking has evolved over time: comparing the conditions and methodological abilities that make it possible—across time, species and human cultures. From early hunter-gatherers to Newton and Marie Curie, all humans have drawn from the same evolved capacities. These are what allow us to observe, experiment, create methods, develop technologies and unlock knowledge about the world. The capacity for methodological reasoning can be seen on a spectrum: from smart chimpanzees using sticks to extract termites, to early humans experimenting with farming techniques, to Egyptian engineers designing pyramids with remarkable geometric precision, and ultimately to discover new planets with the telescope, and then new protein structures and cancer drug candidates with AI-powered tools. Science is a deeply-rooted evolutionary, historical and cross-cultural enterprise embedded in our expanding ability to think methodically—embedded in our method advances. About 11,000 years ago, many of the ingredients for civilisation were in place: the necessary biological, cognitive and social abilities, as well as favourable ecological and demographic conditions. These made it possible to domesticate plants and animals, build permanent settlements and eventually develop complex cities. With civilisation came the necessary external systems that made it possible to accumulate vast tools and knowledge and pass them across generations: written language, mathematics and social stability embodied in institutions. By the time the first civilisations emerged in Mesopotamia and Egypt, we had already built the basic scaffolding for long-term scientific development. Yet researchers studying the origins of science focus on a particular broad factor (like culture or geography) or a few particular scholars (like T Galileo and Newton)—not the extraordinary new tools these scholars inherited. And extending our toolbox in innovative ways enables us to continue unlocking new, unknown frontiers. So how can we explain the big shifts in how we have come to understand the world so deeply? The answer lies in our capacity to extend our universal toolbox. What ultimately distinguished our species from other animals is expanding our universal toolbox to better combine our cognitive abilities—from trial and error to pattern recognition—and increasingly use logical reasoning and develop diverse tools. What separated ancient Greeks from our earlier ancestors is broadening our toolbox to include theoretical thinking and formalising abstract reasoning. What set 17th-century discoverers apart from their predecessors is an upgraded toolbox with perception-enhancing tools that made science vastly more powerful, systematic and reliable. The prominent scholars at the time did not invent our mind's evolved methodological abilities or create these needed external conditions for science. But these scholars—from Galileo to Hooke—did have access to the new and unexpected powerful tools that made the key difference by accelerating scientific progress in ways unimaginable before. Early pioneering scientists such as Al-Haytham and their methods were equally on the right path as European scholars at the turn of the 17th century, but without perception-enhancing tools in their hands, modern science could not take off—the counterfactual. In fact, the conditions in Al-Haytham's time in the 11th century were arguably as favourable—if not more—than in Copernicus's time in the mid-1500s and up to 1600. Al-Haytham worked within a larger, more established community of scholars supported by the institutional infrastructure of the Islamic Golden Age, while the Prussian-Polish Copernicus worked in greater isolation among fewer, more fragmented scholars in Europe. The Islamic world at the time arguably had more developed academic institutions, more extensive libraries, translation centres and scholarly networks than 16th-century Europe. But neither Al‑Haytham nor Copernicus had access to the instrumental power of the microscope or telescope. And introducing these two unanticipated inventions is what ultimately changed the game entirely. Our methodological abilities are made possible by our deeply evolved biological, basic cognitive and social abilities. These are the three enabling conditions that allow us to do science. But these traits alone are not enough to create modern science. Let us describe these conditions: our core methodological capacities including logical reasoning (conditions 1–4) evolved—throughout much of our species' history—mainly beyond our control. Favourable environmental conditions also emerged out of our control . Yet over time, we have gained increasing (if still limited) influence over these abilities. And we do have greater control in shaping demographic and social conditions. Although we may be able—in principle—to do science without complex division of labour , complex systems of written language and mathematics and long-term social stability , science has not ever been and would not be sustainable in the long run without them. That is why individuals throughout history—who had the needed cognitive capacities and at times created sophisticated methods and knowledge—did not develop powerful precision tools, vast discoveries and bodies of knowledge that characterise modern science. To go from intelligent individuals to civilisation, we required the first six conditions—and to launch modern science we needed all nine conditions. These building blocks are so foundational for science that most people take them for granted. And they are not tied to one culture or continent. Just as civilisations emerged independently across the world, so did parts of scientific reasoning—at different times, in different forms. What we call modern science could have developed elsewhere—and in some places, it nearly did. Islamic civilisation came impressively close with the remarkable work and methods of pioneering scholars like Al-Haytham. So what if contemporary science were to be lost in the future—lost to environmental devastation or war (which led to the decline of past civilisations)? To rebuild science from scratch in the future, we would not have to wait for a Christian worldview to emerge, a particular capitalistic system or a renaissance of Aristotelian thought. What we would need is to recreate these nine general conditions once again. When we view our methods as the main trigger enabling us to directly develop scientific and technological knowledge—and so science and civilisation—we unlock a powerful new lens for understanding science and the history of science. And the conditions offer a roadmap—not just to explain the past, but to enable us to predict the development of science in the future. If another intelligent species evolved in the future (on Earth or beyond) and met these nine criteria, science—systematic, cumulative and transformative—would be expected to follow. Understanding these conditions can help us think about how to strengthen science today and how to futureproof it for the challenges to come—for example when specific governments put social stability and science in danger. So we can trace a continuity in human reasoning and problem-solving—from our evolutionary past to today's leading scientists—revealing how our methodological capacities have scaled with our tools. Our early ancestors observed patterns in nature—tracking animal migrations, adapting to seasonal cycles and navigating using the stars—to solve survival challenges; today's scientists also observe patterns in nature but using powerful instruments like microscopes and mass spectrometers. Where our early ancestors relied on trial and error, controlled fire, invented basic notation, made early tools and explored hypotheses, today's scientists build on that logic by designing controlled experiments, inventing advanced calculus and testing systematic hypotheses. Similarly, our early ancestors used causal reasoning— 'if x, then y'—which we have developed into today's formalised causal modelling and advanced statistical inference, revealing hidden relationships in everything from climate systems to brain networks. Our early tools—spears, fire, notation systems— extended our physical tools and basic cognitive abilities, while our contemporary tools—microscopes, supercomputers, CRISPR, particle accelerators, AI—vastly amplify not only our cognitive power but also our sensory reach. Our cognitive architecture— pattern recognition, abstraction, inductive reasoning—remains fundamentally the same. What has changed is the range, scale and precision of these capacities through systematic scientific tools—tools with which we can now explore quantum, genomic, cosmic realms once unimaginable. This illustrates the cumulative nature of our method evolution: ever more complex abilities, methods and tools over time have sparked ever more complex discoveries. History is a chain of extraordinary method revolutions over time. Smart animals Chimpanzees use stone and wood hammers to crack nuts, sticks to extract termites, leaf sponges to collect water Our universal toolbox Our adaptive toolbox (…used to develop more sophisticated methods and tools) Early humans Controlled fire, hand axes, fire-hardened spears, inferential animal tracking Homo Sapiens Plant-based medicines, notation systems, lunar calendars,boats and eventually domesticating animals and plants, early architecture Ancient Greeks Mathematical system, early experiments on weight loss, principles for levers and buoyancy, water mills, complex architecture Imperial Chinese Mechanical clocks, long ironchain suspension bridges, hydraulic engineering, pesticides, the Yongle Encyclopedia, pharmaceutical experiments on animals 18/19th century Pasteurisation, x-rays, light bulb, combustion engines, trains, chemical manufacturing, encyclopaedias 17th century Kepler's laws of planetary motions, Copernican revolution, Newtonian mechanics and gravity, calculus, barometer, microscope Ancient Chinese Magnetic compass, negative numbers, the 'Pascal' triangle, algebra, seismographs, papermaking, immunisation, steel technology, cartography, records of supernovae Our toolbox (our mind's evolved methodological abilities…) observing problem solving trial and error sense of quantity causal reasoning testing hypotheses abstraction methodical problem solving observing systematically computational and statistical microscopes and telescopes problem solving more controlled experiments pre-registering studies, replication blinded, randomised experiments multivariate causal inference quantum statisticsstatistics Time Millions of years ago – present Millions of years ago – 9000 BCE 300,000 years ago – 9000 BCE 4000 BCE – 500 BCE 600 BCE – 200 BCE 1050 BCE – 50 BCE 100s – 1500s 1600s 1700s – 1800s 1900s –2000s Future Technologies and discoveries made (using our methods) Large-scale simulationslogic/abstract modelling elaborate theories concept of cause and effect mathematical theories using multiple methods arithmetic, geometry and algebra 20/21st century Computers, antibiotics, DNA, vitamins, insulin, cancer therapies, airplanes, mobile phones, internet, AI, quantum computing, CRISPR Early civilisation Written language and mathematics systems, medical knowledge of injuries, fractures and basic surgeries, immunisation, pyramids, early experimentson diets Can the answer to the question of how we understood the world for most of history—and how we do today—be as straightforward as pointing to the incredible new tools we develop that stretch our senses and sharpen our minds? Can inventing the microscope and telescope, and then the barometer, vacuum pump, statistics and calculus, explain the first major surge of discoveries in the 1600s? Can developing cutting-edge tools like electron microscopes, statistical methods, supercomputers and particle accelerators largely explain the accelerated pace of discoveries that followed them? The answer is yes—based on examining over 750 major discoveries that define scientific history.