In his sequel to Ignorance (Oxford University Press, 2012), Stuart Firestein shows us that the scientific enterprise is riddled with mistakes and errors - and that this is a good thing! Failure: Why Science Is So Successful delves into the origins of scientific research as a process that relies upon trial and error, one which inevitably results in a hefty dose of failure.
Philosophers and scientists discuss how failure has influenced the development of science, and how current failures might influence its course in the future. Among the modern examples are nonequilibrium statistical physics, and neoclassical consumer theory; early examples include Aristotelian psychology and molecular biology. Some of the eight articles were presented at an April 1988 workshop at the University of Pittsburgh. No index. Annotation copyright by Book News, Inc., Portland, OR
Contrary to the popular view of science as a mountainous accumulation of facts and data, Stuart Firestein takes the novel perspective that ignorance is the main product and driving force of science, and that this is the best way to understand the process of scientific discovery.
Most failure or accident investigations begin at the end of the story: after the explosion, after the fire has been extinguished, or after the collapse. In many instances, information about the last event and the starting event is known reasonably well. Information about what occurred between these endpoints, however, is often unclear, confusing, and perhaps contradictory. Scientific Method: Applications in Failure Investigation and Forensic Science explains how scientific investigative methods can best be used to determine why and how a particular event occurred. While employing examples from forensic engineering, the book uses principles and ideas applicable to most of the forensic sciences. The author examines the role of the failure investigator, describes the fundamental method for investigation, discusses the optimal way to organize evidence, and explores the four most common reasons why some investigations fail. The book provides three case studies that exemplify proper report writing, contains a special chapter profiling a criminal case by noted forensic specialist Jon J. Nordby, and offers a reading list of resources for further study. Concise and illustrative, this volume demonstrates how the scientific method can be applied to failure investigation in ways that avoid flawed reasoning while delivering convincing reconstruction scenarios. Investigators can pinpoint where things went wrong, providing valuable information that can prevent another catastrophe.
One of the pathways by which the scientific community confirms the validity of a new scientific discovery is by repeating the research that produced it. When a scientific effort fails to independently confirm the computations or results of a previous study, some fear that it may be a symptom of a lack of rigor in science, while others argue that such an observed inconsistency can be an important precursor to new discovery. Concerns about reproducibility and replicability have been expressed in both scientific and popular media. As these concerns came to light, Congress requested that the National Academies of Sciences, Engineering, and Medicine conduct a study to assess the extent of issues related to reproducibility and replicability and to offer recommendations for improving rigor and transparency in scientific research. Reproducibility and Replicability in Science defines reproducibility and replicability and examines the factors that may lead to non-reproducibility and non-replicability in research. Unlike the typical expectation of reproducibility between two computations, expectations about replicability are more nuanced, and in some cases a lack of replicability can aid the process of scientific discovery. This report provides recommendations to researchers, academic institutions, journals, and funders on steps they can take to improve reproducibility and replicability in science.
The Economics of Scientific Misconduct explores episodes of misconduct in the natural and biomedical sciences and replication failure in economics and psychology over the past half-century. Here scientific misconduct is considered from the perspective of a single discipline such as economics likely for the first time in intellectual history. Research misconduct has become an important concern across many natural, medical, and social sciences, including economics, over the past half-century. Initially, a mainstream economic approach to science and scientific misconduct draws from conventional microeconomics and the theories of Becker, Ehrlich, and C. S. Peirce’s "economy of research." Then the works of Peirce and Thorstein Veblen from the 19th century point toward contemporary debates over statistical inference in econometrics and the failure of recent macroeconomic models. In more contemporary economics, clashes regarding discrimination and harassment have led to a Code of Professional Conduct from the American Economic Association and a Code of Ethics from one of its members. The last chapter considers research ethics matters related to the COVID-19 pandemic. There has been an explosion of research and some retractions. More generally, a concern with research ethics contributes to scientific progress by making some of its most difficult problems more transparent and understandable and thus possibly more surmountable. This book offers valuable insights for students and scholars of research ethics across the sciences, philosophy of science and social science, and economic theory.
Drawing on the lives of five great scientists, this “scholarly, insightful, and beautifully written book” (Martin Rees, author of From Here to Infinity) illuminates the path to scientific discovery. Charles Darwin, William Thomson (Lord Kelvin), Linus Pauling, Fred Hoyle, and Albert Einstein all made groundbreaking contributions to their fields—but each also stumbled badly. Darwin’s theory of natural selection shouldn’t have worked, according to the prevailing beliefs of his time. Lord Kelvin gravely miscalculated the age of the earth. Linus Pauling, the world’s premier chemist, constructed an erroneous model for DNA in his haste to beat the competition to publication. Astrophysicist Fred Hoyle dismissed the idea of a “Big Bang” origin to the universe (ironically, the caustic name he gave to this event endured long after his erroneous objections were disproven). And Albert Einstein speculated incorrectly about the forces of the universe—and that speculation opened the door to brilliant conceptual leaps. As Mario Livio luminously explains in this “thoughtful meditation on the course of science itself” (The New York Times Book Review), these five scientists expanded our knowledge of life on earth, the evolution of the earth, and the evolution of the universe, despite and because of their errors. “Thoughtful, well-researched, and beautifully written” (The Washington Post), Brilliant Blunders is a wonderfully insightful examination of the psychology of five fascinating scientists—and the mistakes as well as the achievements that made them famous.
The integrity of knowledge that emerges from research is based on individual and collective adherence to core values of objectivity, honesty, openness, fairness, accountability, and stewardship. Integrity in science means that the organizations in which research is conducted encourage those involved to exemplify these values in every step of the research process. Understanding the dynamics that support â€" or distort â€" practices that uphold the integrity of research by all participants ensures that the research enterprise advances knowledge. The 1992 report Responsible Science: Ensuring the Integrity of the Research Process evaluated issues related to scientific responsibility and the conduct of research. It provided a valuable service in describing and analyzing a very complicated set of issues, and has served as a crucial basis for thinking about research integrity for more than two decades. However, as experience has accumulated with various forms of research misconduct, detrimental research practices, and other forms of misconduct, as subsequent empirical research has revealed more about the nature of scientific misconduct, and because technological and social changes have altered the environment in which science is conducted, it is clear that the framework established more than two decades ago needs to be updated. Responsible Science served as a valuable benchmark to set the context for this most recent analysis and to help guide the committee's thought process. Fostering Integrity in Research identifies best practices in research and recommends practical options for discouraging and addressing research misconduct and detrimental research practices.
This book develops a systematic approach to the role of failure in innovation, using the laboratory notebooks of America's most successful inventor, Thomas Edison. It argues that Edison's active pursuit of failure and innovative uses of failure as a tool were crucial to his success. From this the author argues that not only should we expect innovations to fail but that there are good reasons to want them to fail. Using Edison's laboratory notebooks, written as he worked and before he knew the outcome we see the many false starts, wrong directions and failures that he worked through on his way to producing revolutionary inventions. While Edison's strengths in exploiting failure made him the icon of American inventors, they could also be liabilities when he moved from one field to another. Not only is this book of value to readers with an interest in the history of technology and American invention, its insights are important to those who seek to innovate and to those who employ and finance them.
“The Knowledge Machine is the most stunningly illuminating book of the last several decades regarding the all-important scientific enterprise.” —Rebecca Newberger Goldstein, author of Plato at the Googleplex A paradigm-shifting work, The Knowledge Machine revolutionizes our understanding of the origins and structure of science. • Why is science so powerful? • Why did it take so long—two thousand years after the invention of philosophy and mathematics—for the human race to start using science to learn the secrets of the universe? In a groundbreaking work that blends science, philosophy, and history, leading philosopher of science Michael Strevens answers these challenging questions, showing how science came about only once thinkers stumbled upon the astonishing idea that scientific breakthroughs could be accomplished by breaking the rules of logical argument. Like such classic works as Karl Popper’s The Logic of Scientific Discovery and Thomas Kuhn’s The Structure of Scientific Revolutions, The Knowledge Machine grapples with the meaning and origins of science, using a plethora of vivid historical examples to demonstrate that scientists willfully ignore religion, theoretical beauty, and even philosophy to embrace a constricted code of argument whose very narrowness channels unprecedented energy into empirical observation and experimentation. Strevens calls this scientific code the iron rule of explanation, and reveals the way in which the rule, precisely because it is unreasonably close-minded, overcomes individual prejudices to lead humanity inexorably toward the secrets of nature. “With a mixture of philosophical and historical argument, and written in an engrossing style” (Alan Ryan), The Knowledge Machine provides captivating portraits of some of the greatest luminaries in science’s history, including Isaac Newton, the chief architect of modern science and its foundational theories of motion and gravitation; William Whewell, perhaps the greatest philosopher-scientist of the early nineteenth century; and Murray Gell-Mann, discoverer of the quark. Today, Strevens argues, in the face of threats from a changing climate and global pandemics, the idiosyncratic but highly effective scientific knowledge machine must be protected from politicians, commercial interests, and even scientists themselves who seek to open it up, to make it less narrow and more rational—and thus to undermine its devotedly empirical search for truth. Rich with illuminating and often delightfully quirky illustrations, The Knowledge Machine, written in a winningly accessible style that belies the import of its revisionist and groundbreaking concepts, radically reframes much of what we thought we knew about the origins of the modern world.
