revolution in science Most people are familiar with big breakthroughs like Franklin, Crick and Watson's discovery of DNA's double-helix structure, Hubble's discovery that the universe is expanding and Einstein's theory of relativity. But who created the tools that made those surprising findings possible? Few people have heard of them: it was the Braggs' invention of x-ray crystallography that produced the extraordinary image revealing DNA's structure. It was George Hale's massive telescope—the most advanced at the time—that made possible the earth-shaking observation of galaxies moving away, transforming how we understand the nature of our vast universe. It was Albert Michelson's pioneering interferometer that allowed precisely measuring the speed of light and challenged the existing notions of absolute space and time. Tools define what we can see, measure and experiment and largely shape the very theories we can even conceive to explain the surprising findings those tools reveal. The invention of powerful new methods and tools has been the turning point behind fields across science. Better microscopes launched microbiology. Radio telescopes made radio astronomy possible. DNA sequencing methods sparked genomics. The PCR method unlocked modern genetics and virology. X-ray crystallography gave birth to structural biology. Carbon-14 dating transformed archaeology—from guesswork to precision science. Scanning tunneling microscopes laid the foundation for nanotechnology. Functional MRI powers cognitive neuroscience—giving us real-time images of the thinking brain. High-performance computing enables computational biology. Particle detectors and accelerators drive particle physics. Chromatography powers analytical chemistry. CRISPR drives genetic engineering— and so on. These tools open windows into worlds that are too small, too vast, too fast, too far beyond our mind's capacities to observe or imagine on our own. They have given birth to new fields and sparked more discoveries than a single theory—in their domains. Again and again, new methods revealed parts of the world we could not see or conceive before. The observations often came first, with theories following to explain them. Without the right tools to detect or measure, our best theories cannot be meaningfully developed or tested, but also more funding and collaboration are not enough, 292 T HE ENGINE OF SCIENTIFIC DISCOVERY and unexpected or serendipitous observations cannot be made. These other factors vary by discovery. So what unites the diverse discoveries that electron microscopes have made possible—or that telescopes, or x-ray devices, or spectrometers have made possible? It is not a shared theory, research teams, more funding or serendipity, it is using the shared powerful tool. Each unlocked findings across different fields that changed how we understand the world and sparked the need for new theoretical explanations. This is what the new methods-driven discovery theory explains: new methods and tools are a necessary condition for major discoveries, and commonly the critical driver—they are the common thread driving our biggest breakthroughs across science and history. The theory explains much, if not most, of scientific progress: from how new fields emerge, to why particular discoveries happen when they do, to why some problems resist solutions for decades, to why certain institutions become unexpected powerhouses of innovation. This discovery—that new tools drive major breakthroughs—reveals a powerful principle in science: it not only explains how our past discoveries have emerged, but it also helps anticipate future discoveries. The theory is straightforward: when we develop a new tool, we can predict where the next breakthroughs can come from, and when. Tracking the speed and direction of tool innovations gives us powerful signals that discovery is soon to follow. The signal can come from a newly invented sensor, an upgraded gene-editing technique, a combined AI-powered microscope, or an experimental method newly adopted from another field. The best way to predict the pace of new discoveries is looking at how fast, where and when we scale up our tools. But when people imagine science, they often think theories are at its heart, with methods just supporting them. But examining science's major discoveries, we reveal the opposite: methods are not just stepping stones, they enable sparking breakthrough findings that are not possible without them and often come first from inventing the method. Ultimately, the engine of discovery is inventing new ways to see, detect, measure, simulate, imagine and theorise about the world. So why are tools commonly the central driving force of discoveries? The answer lies in six fundamental ways that they transform how we explore the unknown. One, tools do not just visualise, measure and test the world. They also enable us to conceive of reality in ways unthinkable without them. From electron microscopes that reveal viruses, to radio telescopes that uncover radio waves from distant galaxies. Two, tools make discovery less driven by chance and more driven by design—making it systematic and repeatable. Three, tools accelerate the pace and scale of discovery in extraordinary ways. Think of how computational, experimental and statistical methods have vastly sped up breakthroughs. Four, tools push us beyond the boundaries of existing theories by revealing unexpected phenomena current understanding cannot explain—from uncovering superconductivity to x-rays. Five, tools spark cascading breakthroughs across unrelated fields—with the laser, originally developed in physics, triggering discoveries in medicine (laser surgery) and communications (fibre optics). Six, tools make science scalable, precise and reproducible. Tools often transcend theories and what theoretical explanations can do (Chapters 1 and 6). In fact, new major tools are themselves the big discoveries. And discovering what drives discovery can mark a key advance for scientific progress. P The key to advancing science is inventing, upgrading, combining and adopting new methods and tools of discovery. It is how we break and redefine the current limits of science. If we do not place our tools at the heart of science, we cannot understand how we trigger major discoveries. But current explanations of science—whether from scientometricians, historians, psychologists, computer scientists or philosophers—do not recognise tools as the key driver. What we have uncovered in this book is the missing principle overlooked up to now: tool innovation is commonly the primary driver of discovery—and once recognised, we are much better able to spark new advances faster (Chapters 1–6).(346,350 –353,355,358 ) Expanding our toolbox is the thread connecting science—from the present, back to its origins, and forward to the cutting-edge frontier. It provides answers to the big questions about science: how we trigger new discoveries (Chapter 1), what sparks serendipity in science (Chapter 2), whether scientific progress is cumulative and even how we define the scientific method itself (Chapter 3), how our powerful tools interact with discoverers' demographics, institutions and resources (Chapter 4), how we actually create new scientific fields (Chapter5), how we invent new methods and tools (Chapter 6), what the origins of science and our methods are (Chapters7–8), what the common force driving science is (Chapter 9), what the current limits of science are and how we can break them (Chapters 10–11). At the centre of answers to these big puzzles is a common principle: method innovations. They provide a unified answer to many unsolved questions about science. The efforts of millions of people using their eyes, minds and hands to explore the world are rarely as transformative as creating a new tool—like an advanced spectrometer or electron microscope—that can trigger multiple major breakthroughs by enabling us to see further and think deeper. In this book, we have adopted a new approach: examining science's over 750 major discoveries, the methods and tools they used and the traits and conditions of the discoverers to systematically assess what exactly sparks them. A striking finding emerged: it is new tools themselves that consistently trigger new breakthroughs—experimental, methodological and theoretical—by providing a new needed lens. The inspiration for this approach came from recognising a pattern across breakthroughs—that they rely on new methods, from randomised controlled trials to new statistical techniques. Testing the pattern here revealed that it surprisingly applies across scientific fields and history—leading to this new method-to-discovery principle. This key driver of discoveries has been overlooked because researchers had not yet reviewed science's over 750 discoverymaking studies—one by one—to identify the underlying pattern and extract the data from each study and multiple other sources. It has been a meticulous and very time-consuming task that culminated in this book. This method-to-discovery principle could also be applicable across other domains—from technology to business and even policy. Designing new methods could solve our large challenges across domains. The impact of new methods can be much greater than their initial intention as we can use them for different purposes in different fields. Just like the first microscopes and telescopes were not invented for scientific purposes but were then leveraged across science, the internet was created for improving communication but we now use it worldwide for gaining knowledge—it is our global library. 294 T HE ENGINE OF SCIENTIFIC DISCOVERY Discovering this methods-driven principle has vast implications: scientists need to begin focusing on spotting the gaps and blind spots in their own tools and finding ways to tackle them. We mapped out the crucial pathways we take to invent new tools—the discovery engine. We also created a scientific table of discovery methods—a map of explored and unexplored method options that can help identify and predict untapped combinations of tools and where the next breakthroughs can emerge. This method map can coordinate efforts across scientists to create databases of methods and tools—cataloguing combinations, blind spots and unexplored regions. It can also guide resources and strategic investment. We also laid out seven major reforms that could drastically speed up scientific progress and develop the Methodology of Science (at the end of Chapter 6). Here we summarise those critical reforms. One, we need far more researchers dedicated to tackling method bottlenecks across the scientific community. Two, we should make testing and expanding our best methods a regular part of what we all do. Three, we need to redefine research as not just question-driven but equally methods-driven. Four, we have to fix science's reward system, so journals, prizes and funding bodies equally incentivise method innovations. Five, we need to establish new Methods Labs, Methods Hubs and Departments of Methodology of Science—as incubators of innovation. Six, we have to shift our main measure of success from just outputs (especially article citations) to focus equally on inputs—method innovations. Seven, we need to train the next generation of tool innovators—and integrate deep methodological training into university degrees across science. These reforms would help us much better spot when even our best tools of discovery are holding us back—and how to overcome those barriers. If we adopt these seven reforms, we could kick-start a tool revolution across science. It would break from the status quo: the era before the tool revolution, where we until now commonly made new methods and tools in a surprisingly improvised and scattered way. It would mark a shift towards the tool revolution, where we would design and develop new methods and tools in a deliberate, planned and strategic way. It would cut down the time it takes to identify new possible tools but also to create them. Until now, without yet a general theory of scientific progress and dedicated research programmes for tool development, each discoverer has had to improvise, test and work out on their own how to best make a breakthrough—and which new tools we need. The tool revolution would be driven by a shared understanding—across scientists, science policymakers and funders—of the incredible power of designing and engineering the very methods that generate new discoveries. Researchers lose much time and fields stall because we did not yet have a systematic roadmap for building better tools. So what if we stopped waiting for the next discovery tools to arise by chance? How many breakthroughs do we overlook simply because we have not yet made tool development a clear priority? What if science labs start competing to invent discovery tools, not just to use them? Indeed, when most researchers stick with familiar tools just because that is what they know best, breakthroughs are slowed—or even missed (Chapter 1). That common comfort zone holds fields back. Yet science would then move from more unplanned insights to designing better ways to see, detect and think—to better engineering discoveries. If researchers everywhere recognised that the tools and methods we use shape what we can discover with them, it will push us to extend them and invent better ones—far more systematically. It may be the most powerful, untapped frontier in science. Ultimately, when we hit the limits of our tools, we know exactly where to innovate next. Each limitation we uncover is one step closer to unknown terrain and findings. Because the biggest leaps in science do not generally come from re-examining existing blurry data or re-measuring existing data samples. They come from building sharper lenses, more precise sensors and more accurate computer simulations. A tool-centric science opens whole new lines of research and countless questions that hold large potential. How can we incentivise researchers to develop new methods that may not yield a paper, but could change a field in a few years? What are actually the best strategies to reward not just for solving scientific questions, but for inventing better ways to solve them? How could scientists best see their role not just as answering questions, but also as engineering better ways to answer them? How can we create a culture that values method design and toolmaking as the foundation of discovery? Can we develop models to help guide tool design and bootstrap innovation? Can we develop models to predict which new methods could enable bigger advances before they are developed? Could fields forecast their own growth by investing in the methods they will need in coming years (just like engineers plan major infrastructure in advance)? What ethical frameworks do we need to ensure responsible tool innovation, especially in fields like genetics and climate science? Ultimately, new methods and tools are the engine of discovery—our keys to unlocking the mysteries of life, matter and the universe. As we invent more powerful tools, our capacity to reveal what is beyond our imagination today only grows. Each time we invent a better tool to see, measure or simulate the world, we expand what is possible—and what we can discover. The frontiers of science largely lie in uncovering underdeveloped and undeveloped tools. Designing better tools is set to become science's next frontier of competitive advantage. The logic of science and discovery is simple: conventional methods produce conventional research; new tools make new breakthroughs possible. If a science-wide awareness of this principle emerged and the scientific community made it a priority, it could begin a tool revolution in science. One that transforms how we understand, create and accelerate new scientific advances. One that changes how science is organised, practiced and funded. By recognising tool innovation as the key driver of science, we could make discoveries faster and more predictable over time. So there is a science of discovery: those who develop and use new methods and tools today are generally the ones who spark tomorrow's new breakthroughs.