Logology (science)
Logology is the study of all things related to
Origins
The early 20th century brought calls, initially from
Florian Znaniecki, who is considered to be the founder of Polish academic sociology, and who in 1954 also served as the 44th president of the American Sociological Association, opened a 1923 article:[9]
[T]hough theoretical reflection on knowledge—which arose as early as Heraclitus and the Eleatics—stretches... unbroken... through the history of human thought to the present day... we are now witnessing the creation of a new science of knowledge [author's emphasis] whose relation to the old inquiries may be compared with the relation of modern physics and chemistry to the 'natural philosophy' that preceded them, or of contemporary sociology to the 'political philosophy' of antiquity and the Renaissance. [T]here is beginning to take shape a concept of a single, general theory of knowledge... permitting of empirical study.... This theory... is coming to be distinguished clearly from epistemology, from normative logic, and from a strictly descriptive history of knowledge."[10]
A dozen years later, Polish husband-and-wife sociologists
In their 1935 paper, the Ossowscy mentioned the German philosopher Werner Schingnitz (1899–1953) who, in fragmentary 1931 remarks, had enumerated some possible types of research in the science of science and had proposed his own name for the new discipline: scientiology. The Ossowscy took issue with the name:
Those who wish to replace the expression 'science of science' by a one-word term [that] sound[s] international, in the belief that only after receiving such a name [will] a given group of [questions be] officially dubbed an autonomous discipline, [might] be reminded of the name 'mathesiology', proposed long ago for similar purposes [by the French mathematician and physicist André-Marie Ampère (1775–1836)]."[15]
Yet, before long, in Poland, the unwieldy three-word term nauka o nauce, or science of science, was replaced by the more versatile one-word term naukoznawstwo, or logology, and its natural variants: naukoznawca or logologist, naukoznawczy or logological, and naukoznawczo or logologically. And just after World War II, only 11 years after the Ossowscy's landmark 1935 paper, the year 1946 saw the founding of the Polish Academy of Sciences' quarterly Zagadnienia Naukoznawstwa (Logology) –— long before similar journals in many other countries.[16][c]
The new discipline also took root elsewhere—in English-speaking countries, without the benefit of a one-word name.
Science
The term
The word
Bod gives a historic example of scientific
Knowability
Science's search for the
The question of knowability is approached from a different perspective by physicist-astronomer Marcelo Gleiser: "What we observe is not nature itself but nature as discerned through data we collect from machines. In consequence, the scientific worldview depends on the information we can acquire through our instruments. And given that our tools are limited, our view of the world is necessarily myopic. We can see only so far into the nature of things, and our ever shifting scientific worldview reflects this fundamental limitation on how we perceive reality." Gleiser cites the condition of biology before and after the invention of the microscope or gene sequencing; of astronomy before and after the telescope; of particle physics before and after colliders or fast electronics. "[T]he theories we build and the worldviews we construct change as our tools of exploration transform. This trend is the trademark of science."[22]
Writes Gleiser: "There is nothing defeatist in understanding the limitations of the scientific approach to knowledge.... What should change is a sense of scientific triumphalism—the belief that no question is beyond the reach of scientific discourse.[22] [e]
"There are clear unknowables in science—reasonable questions that, unless currently accepted laws of nature are violated, we cannot find answers to. One example is the
Gleiser gives three further examples of unknowables, involving the origins of the universe; of life; and of mind:[24][f]
"Scientific accounts of the origin of the
"Similarly, unless we can prove that only one or very few
"For consciousness, the problem is the jump from the material to the subjective—for example, from firing neurons to the experience of pain or the color red. Perhaps some kind of rudimentary consciousness could emerge in a sufficiently complex machine. But how could we tell? How do we establish—as opposed to conjecture—that something is conscious?"[24] Paradoxically, writes Gleiser, it is through our consciousness that we make sense of the world, even if imperfectly. "Can we fully understand something of which we are a part?"[24]
Among all the sciences (i.e.,
Facts and theories
Theoretical physicist and mathematician Freeman Dyson explains that "[s]cience consists of facts and theories":
"Facts are supposed to be true or false. They are discovered by observers or experimenters. A scientist who claims to have discovered a fact that turns out to be wrong is judged harshly....
"Theories have an entirely different status. They are free creations of the human mind, intended to describe our understanding of nature. Since our understanding is incomplete, theories are provisional. Theories are tools of understanding, and a tool does not need to be precisely true in order to be useful. Theories are supposed to be more-or-less true... A scientist who invents a theory that turns out to be wrong is judged leniently."[26]
Dyson cites a psychologist's description of how theories are born: "We can't live in a state of perpetual doubt, so we make up the best story possible and we live as if the story were true." Dyson writes: "The inventor of a brilliant idea cannot tell whether it is right or wrong." The passionate pursuit of wrong theories is a normal part of the development of science.[27] Dyson cites, after Mario Livio, five famous scientists who made major contributions to the understanding of nature but also believed firmly in a theory that proved wrong.[27]
Linus Pauling discovered the chemical structure of protein and proposed a completely wrong structure for DNA, which carries hereditary information from parent to offspring. Pauling guessed a wrong structure for DNA because he assumed that a pattern that worked for protein would also work for DNA. He overlooked the gross chemical differences between protein and DNA. Francis Crick and James Watson paid attention to the differences and found the correct structure for DNA that Pauling had missed a year earlier.[27]
Astronomer
Albert Einstein discovered the theory of space, time, and gravitation known as general relativity, and then added a cosmological constant, later known as dark energy. Subsequently, Einstein withdrew his proposal of dark energy, believing it unnecessary. Long after his death, observations suggested that dark energy really exists, so that Einstein's addition to the theory may have been right; and his withdrawal, wrong.[27]
To Mario Livio's five examples of scientists who blundered, Dyson adds a sixth: himself. Dyson had concluded, on theoretical principles, that what was to become known as the
Truth
Science, writes Oreskes, is not a fixed, immutable set of discoveries but "a process of learning and discovery [...]. Science can also be understood as an institution (or better, a set of institutions) that facilitates this work.[30]
It is often asserted that scientific findings are true because scientists use "the
In fact, writes Oreskes, the methods of science have varied between disciplines and across time. "Many scientific practices, particularly statistical tests of significance, have been developed with the idea of avoiding wishful thinking and self-deception, but that hardly constitutes 'the scientific method.'"[30]
Science, writes Oreskes, "is not simple, and neither is the natural world; therein lies the challenge of science communication. [...] Our efforts to understand and characterize the natural world are just that: efforts. Because we're human, we often fall flat."[30]
"Scientific theories", according to Oreskes, "are not perfect replicas of reality, but we have good reason to believe that they capture significant elements of it."[30]
Empiricism
Weinberg draws parallels between past and present science, as when a scientific theory is "fine-tuned" (adjusted) to make certain quantities equal, without any understanding of why they should be equal. Such adjusting vitiated the celestial models of Plato's followers, in which different spheres carrying the
Ancient science has been described as having gotten off to a good start, then faltered. The doctrine of
Weinberg believes that science faltered early on due to Plato's suggestion that scientific truth could be attained by reason alone, disregarding
A scientific field in which the
The challenge was to make sense of the apparently irregular wanderings of the planets on the assumption that all heavenly motion is actually circular and uniform in speed. Circular, because Plato held the circle to be the most perfect and symmetrical form; and therefore circular motion, at uniform speed, was most fitting for celestial bodies. Aristotle agreed with Plato. In Aristotle's cosmos, everything had a "natural" tendency to motion that fulfilled its inner potential. For the cosmos' sublunary part (the region below the Moon), the natural tendency was to move in a straight line: downward, for earthen things (such as rocks) and water; upward, for air and fiery things (such as sparks). But in the celestial realm things were not composed of earth, water, air, or fire, but of a "fifth element", or "quintessence," which was perfect and eternal. And its natural motion was uniformly circular. The stars, the Sun, the Moon, and the planets were carried in their orbits by a complicated arrangement of crystalline spheres, all centered around an immobile Earth.[34]
The Platonic-Aristotelian conviction that celestial motions must be circular persisted stubbornly. It was fundamental to the astronomer
It even survived the Copernican Revolution. Copernicus was conservative in his Platonic reverence for the circle as the heavenly pattern. According to Weinberg, Copernicus was motivated to dethrone the Earth in favor of the Sun as the immobile center of the cosmos largely by aesthetic considerations: he objected to the fact that Ptolemy, though faithful to Plato's requirement that heavenly motion be circular, had departed from Plato's other requirement that it be of uniform speed. By putting the sun at the center—actually, somewhat off-center—Copernicus sought to honor circularity while restoring uniformity. But to make his system fit the observations as well as Ptolemy's system, Copernicus had to introduce still more epicycles. That was a mistake that, writes Weinberg, illustrates a recurrent theme in the history of science: "A simple and beautiful theory that agrees pretty well with observation is often closer to the truth than a complicated ugly theory that agrees better with observation."[34]
The planets, however, do not move in perfect circles but in ellipses. It was Johannes Kepler, about a century after Copernicus, who reluctantly (for he too had Platonic affinities) realized this. Thanks to his examination of the meticulous observations compiled by astronomer Tycho Brahe, Kepler "was the first to understand the nature of the departures from uniform circular motion that had puzzled astronomers since the time of Plato."[34]
The replacement of circles by supposedly ugly ellipses overthrew Plato's notion of perfection as the celestial explanatory principle. It also destroyed Aristotle's model of the planets carried in their orbits by crystalline spheres; writes Weinberg, "there is no solid body whose rotation can produce an ellipse." Even if a planet were attached to an ellipsoid crystal, that crystal's rotation would still trace a circle. And if the planets were pursuing their elliptical motion through empty space, then what was holding them in their orbits?[34]
Science had reached the threshold of explaining the world not geometrically, according to shape, but dynamically, according to force. It was Isaac Newton who finally crossed that threshold. He was the first to formulate, in his "laws of motion", the concept of force. He demonstrated that Kepler's ellipses were the very orbits the planets would take if they were attracted toward the Sun by a force that decreased as the square of the planet's distance from the Sun. And by comparing the Moon's motion in its orbit around the Earth to the motion of, perhaps, an apple as it falls to the ground, Newton deduced that the forces governing them were quantitatively the same. "This," writes Weinberg, "was the climactic step in the unification of the celestial and terrestrial in science."[34]
By formulating a unified explanation of the behavior of planets, comets, moons, tides, and apples, writes Weinberg, Newton "provided an irresistible model for what a
About two centuries later, in 1915, a deeper explanation for Newton's law of gravitation was found in
Absence of evidence
Naomi Oreskes cautions against making "the classic error of conflating absence of evidence with evidence of absence [emphases added]." She cites two examples of this error that were perpetrated in 2016 and 2023.[36]
In 2016 the
Oreskes explains that "
In 2023 Cochrane published a report determining that wearing surgical masks "probably makes little or no difference" in slowing the spread of respiratory illnesses such as COVID-19. Mass media reduced this to the claim that masks did not work. The Cochrane Library's editor-in-chief objected to such characterizations of the review; she said the report had not concluded that "masks don't work", but rather that the "results were inconclusive." The report had made clear that its conclusions were about the quality and capaciousness of available evidence, which the authors felt were insufficient to prove that masking was effective. The report's authors were "uncertain whether wearing [surgical] masks or N95/P2 respirators helps to slow the spread of respiratory viruses." Still, they were also uncertain about that uncertainty [emphasis added], stating that their confidence in their conclusion was "low to moderate."[39]
Subsequently the report's lead author confused the public by stating that mask-wearing "Makes no difference – none of it", and that Covid policies were "evidence-free": he thus perpetrated what Oreskes calls "the [...] error of conflating absence of evidence with evidence of absence." Studies have in fact shown that U.S. states with mask mandates saw a substantial decline in Covid spread within days of mandate orders being signed; in the period from 31 March to 22 May 2020, more than 200,000 cases were avoided.[40]
Oreskes calls the Cochrane report's neglect of the
Artificial intelligence
The term "
As machines have become increasingly capable, specific tasks considered to require "intelligence", such as optical character recognition, have often been removed from the definition of AI, a phenomenon known as the "AI effect". It has been quipped that "AI is whatever hasn't been done yet."[44]
Since 1950, when Alan Turing proposed what has come to be called the "Turing test," there has been speculation whether machines such as computers can possess intelligence; and, if so, whether intelligent machines could become a threat to human intellectual and scientific ascendancy—or even an existential threat to humanity.[45] John Searle points out common confusion about the correct interpretation of computation and information technology. "For example, one routinely reads that in exactly the same sense in which Garry Kasparov… beat Anatoly Karpov in chess, the computer called Deep Blue played and beat Kasparov.... [T]his claim is [obviously] suspect. In order for Kasparov to play and win, he has to be conscious that he is playing chess, and conscious of a thousand other things... Deep Blue is conscious of none of these things because it is not conscious of anything at all. Why is consciousness so important? You cannot literally play chess or do much of anything else cognitive if you are totally disassociated from consciousness."[45]
Searle explains that, "in the literal, real, observer-independent sense in which humans compute, mechanical computers do not compute. They go through a set of transitions in electronic states that we can interpret computationally. The transitions in those electronic states are absolute or observer-independent, but the computation is observer-relative. The transitions in physical states are just electrical sequences unless some conscious agent can give them a computational interpretation.... There is no psychological reality at all to what is happening in the [computer]."[46]
"[A] digital computer", writes Searle, "is a syntactical machine. It manipulates symbols and does nothing else. For this reason, the project of creating human intelligence by designing a computer program that will pass the
Like Searle,
Professor of psychology and neural science
"Artificial intelligence" is synonymous with "
Humankind may not be able to outsource, to machines, its creative efforts in the sciences, technology, and culture.
Gary Marcus cautions against being taken in by deceptive claims about artificial general intelligence capabilities that are put out in press releases by self-interested companies which tell the press and public "only what the companies want us to know."[60] Marcus writes:
Although
Uncertainty
A central concern for science and scholarship is the
In 1925 British geneticist and statistician
The use of p values, ever since, to determine the statistical significance of experimental results has contributed to an illusion of
Every statistical model relies on a set of assumptions about how data are collected and analyzed and about how researchers decide to present their results. These results almost always center on null-hypothesis significance testing, which produces a p value. Such testing does not address the truth head-on but obliquely: significance testing is meant to indicate only whether a given line of research is worth pursuing further. It does not say how likely the hypothesis is to be true, but instead addresses an alternative question: if the hypothesis were false, how unlikely would the data be? The importance of "statistical significance", reflected in the p value, can be exaggerated or overemphasized – something that readily occurs with small samples. That has caused replication crises.[62]
Some scientists have advocated "redefining statistical significance", shifting its threshold from 0.05 to 0.005 for claims of new discoveries. Others say such redefining does no good because the real problem is the very existence of a threshold.[66]
Some scientists prefer to use
When Ronald Fisher embraced the concept of "significance" in the early 20th century, it meant "signifying" but not "important". Statistical "significance" has, since, acquired am excessive connotation of confidence in the validity of the experimental results. Statistician Andrew Gelman says, "The original sin is people wanting certainty when it's not appropriate." "Ultimately", writes Lydia Denworth, "a successful theory is one that stands up repeatedly to decades of scrutiny."[66]
Increasingly, attention is being given to the principles of open science, such as publishing more detailed research protocols and requiring authors to follow prespecified analysis plans and to report when they deviate from them.[66]
Discovery
Discoveries and inventions
Fifty years before Florian Znaniecki published his 1923 paper proposing the creation of an empirical field of study to study the field of science, Aleksander Głowacki (better known by his pen name, Bolesław Prus) had made the same proposal. In an 1873 public lecture "On Discoveries and Inventions",[67] Prus said:
Until now there has been no science that describes the means for making discoveries and inventions, and the generality of people, as well as many men of learning, believe that there never will be. This is an error. Someday a science of making discoveries and inventions will exist and will render services. It will arise not all at once; first only its general outline will appear, which subsequent researchers will correct and elaborate, and which still later researchers will apply to individual branches of knowledge.[68]
Prus defines "discovery" as "the finding out of a thing that has existed and exists in nature, but which was previously unknown to people";[69] and "invention" as "the making of a thing that has not previously existed, and which nature itself cannot make."[70]
He illustrates the concept of "discovery":
Until 400 years ago, people thought that the Earth comprised just three parts: Europe, Asia, and Africa; it was only in 1492 that the Genoese, Christopher Columbus, sailed out from Europe into the Atlantic Ocean and, proceeding ever westward, after [10 weeks] reached a part of the world that Europeans had never known. In that new land he found copper-colored people who went about naked, and he found plants and animals different from those in Europe; in short, he had discovered a new part of the world that others would later name "America." We say that Columbus had discovered America, because America had already long existed on Earth.[71]
Prus illustrates the concept of "invention":
[As late as] 50 years ago, locomotives were unknown, and no one knew how to build one; it was only in 1828 that the English engineer Stephenson built the first locomotive and set it in motion. So we say that Stephenson invented the locomotive, because this machine had not previously existed and could not by itself have come into being in nature; it could only have been made by man.[70]
According to Prus, "inventions and discoveries are natural phenomena and, as such, are subject to certain laws." Those are the laws of "gradualness", "dependence", and "combination".[72]
1. The law of gradualness. No discovery or invention arises at once perfected, but is perfected gradually; likewise, no invention or discovery is the work of a single individual but of many individuals, each adding his little contribution.[73]
2. The law of dependence. An invention or discovery is conditional on the prior existence of certain known discoveries and inventions. ...If the rings of Saturn can [only] be seen through telescopes, then the telescope had to have been invented before the rings could have been seen. [...][74]
3. The law of combination. Any new discovery or invention is a combination of earlier discoveries and inventions, or rests on them. When I study a new mineral, I inspect it, I smell it, I taste it ... I combine the mineral with a balance and with fire...in this way I learn ever more of its properties.[75][j]
Each of Prus' three "laws" entails important corollaries. The law of gradualness implies the following:[77]
a) Since every discovery and invention requires perfecting, let us not pride ourselves only on discovering or inventing something completely new, but let us also work to improve or get to know more exactly things that are already known and already exist. [...][77] b) The same law of gradualness demonstrates the necessity of expert training. Who can perfect a watch, if not a watchmaker with a good comprehensive knowledge of his métier? Who can discover new characteristics of an animal, if not a naturalist?[77]
From the law of dependence flow the following corollaries:[77]
a) No invention or discovery, even one seemingly without value, should be dismissed, because that particular trifle may later prove very useful. There would seem to be no simpler invention than the needle, yet the clothing of millions of people, and the livelihoods of millions of seamstresses, depend on the needle's existence. Even today's beautiful sewing machine would not exist, had the needle not long ago been invented.[78] b) The law of dependence teaches us that what cannot be done today, might be done later. People give much thought to the construction of a flying machine that could carry many persons and parcels. The inventing of such a machine will depend, among other things, on inventing a material that is, say, as light as paper and as sturdy and fire-resistant as steel.[79]
Finally, Prus' corollaries to his law of combination:[79]
a) Anyone who wants to be a successful inventor, needs to know a great many things—in the most diverse fields. For if a new invention is a combination of earlier inventions, then the inventor's mind is the ground on which, for the first time, various seemingly unrelated things combine. Example: The steam engine combines the kettle for cooking Rumford's Soup, the pump, and the spinning wheel.[79]
[...] What is the connection among zinc, copper, sulfuric acid, a magnet, a clock mechanism, and an urgent message? All these had to come together in the mind of the inventor of the telegraph... [...][80]
The greater the number of inventions that come into being, the more things a new inventor must know; the first, earliest and simplest inventions were made by completely uneducated people—but today's inventions, particularly scientific ones, are products of the most highly educated minds. [...][81]
b) A second corollary concerns societies that wish to have inventors. I said that a new invention is created by combining the most diverse objects; let us see where this takes us.[81]
Suppose I want to make an invention, and someone tells me: Take 100 different objects and bring them into contact with one another, first two at a time, then three at a time, finally four at a time, and you will arrive at a new invention. Imagine that I take a burning candle, charcoal, water, paper, zinc, sugar, sulfuric acid, and so on, 100 objects in all, and combine them with one another, that is, bring into contact first two at a time: charcoal with flame, water with flame, sugar with flame, zinc with flame, sugar with water, etc. Each time, I shall see a phenomenon: thus, in fire, sugar will melt, charcoal will burn, zinc will heat up, and so on. Now I will bring into contact three objects at a time, for example, sugar, zinc and flame; charcoal, sugar and flame; sulfuric acid, zinc and water; etc., and again I shall experience phenomena. Finally I bring into contact four objects at a time, for example, sugar, zinc, charcoal, and sulfuric acid. Ostensibly this is a very simple method, because in this fashion I could make not merely one but a dozen inventions. But will such an effort not exceed my capability? It certainly will. A hundred objects, combined in twos, threes and fours, will make over 4 million combinations; so if I made 100 combinations a day, it would take me over 110 years to exhaust them all![82]
But if by myself I am not up to the task, a sizable group of people will be. If 1,000 of us came together to produce the combinations that I have described, then any one person would only have to carry out slightly more than 4,000 combinations. If each of us performed just 10 combinations a day, together we would finish them all in less than a year and a half: 1,000 people would make an invention which a single man would have to spend more than 110 years to make…[83][k]
The conclusion is quite clear: a society that wants to win renown with its discoveries and inventions has to have a great many persons working in every branch of knowledge. One or a few men of learning and genius mean nothing today, or nearly nothing, because everything is now done by large numbers. I would like to offer the following simile: Inventions and discoveries are like a lottery; not every player wins, but from among the many players a few must win. The point is not that John or Paul, because they want to make an invention and because they work for it, shall make an invention; but where thousands want an invention and work for it, the invention must appear, as surely as an unsupported rock must fall to the ground.[83][l]
But, asks Prus, "What force drives [the] toilsome, often frustrated efforts [of the investigators]? What thread will clew these people through hitherto unexplored fields of study?"[84][m]
[T]he answer is very simple: man is driven to efforts, including those of making discoveries and inventions, by needs; and the thread that guides him is observation: observation of the works of nature and of man.[84]
I have said that the mainspring of all discoveries and inventions is needs. In fact, is there any work of man that does not satisfy some need? We build railroads because we need rapid transportation; we build clocks because we need to measure time; we build sewing machines because the speed of [unaided] human hands is insufficient. We abandon home and family and depart for distant lands because we are drawn by curiosity to see what lies elsewhere. We forsake the society of people and we spend long hours in exhausting contemplation because we are driven by a hunger for knowledge, by a desire to solve the challenges that are constantly thrown up by the world and by life![84]
Needs never cease; on the contrary, they are always growing. While the pauper thinks about a piece of bread for lunch, the rich man thinks about wine after lunch. The foot traveler dreams of a rudimentary wagon; the railroad passenger demands a heater. The infant is cramped in its cradle; the mature man is cramped in the world. In short, everyone has his needs, and everyone desires to satisfy them, and that desire is an inexhaustible source of new discoveries, new inventions, in short, of all progress.[85]
But needs are general, such as the needs for food, sleep and clothing; and special, such as needs for a new steam engine, a new telescope, a new hammer, a new wrench. To understand the former needs, it suffices to be a human being; to understand the latter needs, one must be a specialist—an expert worker. Who knows better than a tailor what it is that tailors need, and who better than a tailor knows how to find the right way to satisfy the need?[86]
Now consider how observation can lead man to new ideas; and to that end, as an example, let us imagine how, more or less, clay products came to be invented.[86]
Suppose that somewhere there lived on clayey soil a primitive people who already knew fire. When rain fell on the ground, the clay turned doughy; and if, shortly after the rain, a fire was set on top of the clay, the clay under the fire became fired and hardened. If such an event occurred several times, the people might observe and thereafter remember that fired clay becomes hard like stone and does not soften in water. One of the primitives might also, when walking on wet clay, have impressed deep tracks into it; after the sun had dried the ground and rain had fallen again, the primitives might have observed that water remains in those hollows longer than on the surface. Inspecting the wet clay, the people might have observed that this material can be easily kneaded in one's fingers and accepts various forms.[87]
Some ingenious persons might have started shaping clay into various animal forms [...] etc., including something shaped like a tortoise shell, which was in use at the time. Others, remembering that clay hardens in fire, might have fired the hollowed-out mass, thereby creating the first [clay] bowl.[88]
After that, it was a relatively easy matter to perfect the new invention; someone else could discover clay more suitable for such manufactures; someone else could invent a glaze, and so on, with nature and observation at every step pointing out to man the way to invention. [...][88]
[This example] illustrates how people arrive at various ideas: by closely observing all things and wondering about all things.[88]
Take another example. [S]ometimes, in a pane of glass, we find disks and bubbles, looking through which we see objects more distinctly than with the naked eye. Suppose that an alert person, spotting such a bubble in a pane, took out a piece of glass and showed it to others as a toy. Possibly among them there was a man with weak vision who found that, through the bubble in the pane, he saw better than with the naked eye. Closer investigation showed that bilaterally convex glass strengthens weak vision, and in this way eyeglasses were invented. People may first have cut glass for eyeglasses from glass panes, but in time others began grinding smooth pieces of glass into convex lenses and producing proper eyeglasses.[89]
The art of grinding eyeglasses was known almost 600 years ago. A couple of hundred years later, the children of a certain eyeglass grinder, while playing with lenses, placed one in front of another and found that they could see better through two lenses than through one. They informed their father about this curious occurrence, and he began producing tubes with two magnifying lenses and selling them as a toy. Galileo, the great Italian scientist, on learning of this toy, used it for a different purpose and built the first telescope.[90]
This example, too, shows us that observation leads man by the hand to inventions. This example again demonstrates the truth of gradualness in the development of inventions, but above all also the fact that education amplifies man's inventiveness. A simple lens-grinder formed two magnifying glasses into a toy—while Galileo, one of the most learned men of his time, made a telescope. As Galileo's mind was superior to the craftsman's mind, so the invention of the telescope was superior to the invention of a toy.[90] [...]
The three laws [that have been discussed here] are immensely important and do not apply only to discoveries and inventions, but they pervade all of nature. An oak does not immediately become an oak but begins as an acorn, then becomes a seedling, later a little tree, and finally a mighty oak: we see here the law of gradualness. A seed that has been sown will not germinate until it finds sufficient heat, water, soil and air: here we see the law of dependence. Finally, no animal or plant, or even stone, is something homogeneous and simple but is composed of various organs: here we see the law of combination.[91]
Prus holds that, over time, the multiplication of discoveries and inventions has improved the quality of people's lives and has expanded their knowledge. "This gradual advance of civilized societies, this constant growth in knowledge of the objects that exist in nature, this constant increase in the number of tools and useful materials, is termed progress, or the growth of civilization."[92] Conversely, Prus warns, "societies and people that do not make inventions or know how to use them, lead miserable lives and ultimately perish."[93][n]
Reproducibility
A fundamental feature of the scientific enterprise is
With a view to improving reproducibility of scientific results, it has been suggested that research-funding agencies finance only projects that include a plan for making their work transparent. In 2016 the U.S. National Institutes of Health introduced new application instructions and review questions to encourage scientists to improve reproducibility. The NIH requests more information on how the study builds on previous work, and a list of variables that could affect the study, such as the sex of animal subjects—a previously overlooked factor that led many studies to describe phenomena found in male animals as universal.[95]
Likewise, the questions that a funder can ask in advance could be asked by journals and reviewers. One solution is "registered reports", a preregistration of studies whereby a scientist submits, for publication, research analysis and design plans before actually doing the study. Peer reviewers then evaluate the methodology, and the journal promises to print the results, no matter what they are. In order to prevent over-reliance on preregistered studies—which could encourage safer, less venturesome research, thus over-correcting the problem—the preregistered-studies model could be operated in tandem with the traditional results-focused model, which may sometimes be more friendly to serendipitous discoveries.[95]
The "replication crisis" is compounded by a finding, published in a study summarized in 2021 by historian of science Naomi Oreskes, that nonreplicable studies are cited oftener than replicable ones: in other words, that bad science seems to get more attention than good science. If a substantial proportion of science is unreplicable, it will not provide a valid basis for decision-making and may delay the use of science for developing new medicines and technologies. It may also undermine the public's trust, making it harder to get people vaccinated or act against climate change.[96]
The study tracked papers – in psychology journals, economics journals, and in Science and Nature – with documented failures of replication. The unreplicable papers were cited more than average, even after news of their unreplicability had been published.[96]
"These results," writes Oreskes, "parallel those of a 2018 study. An analysis of 126,000 rumor cascades on Twitter showed that false news spread faster and reached more people than verified true claims. [I]t was people, not [ro]bots, who were responsible for the disproportionate spread of falsehoods online."[96]
Rediscovery
A 2016 Scientific American report highlights the role of rediscovery in science. Indiana University Bloomington researchers combed through 22 million scientific papers published over the previous century and found dozens of "Sleeping Beauties"—studies that lay dormant for years before getting noticed.[97] The top finds, which languished longest and later received the most intense attention from scientists, came from the fields of chemistry, physics, and statistics. The dormant findings were wakened by scientists from other disciplines, such as medicine, in search of fresh insights, and by the ability to test once-theoretical postulations.[97] Sleeping Beauties will likely become even more common in the future because of increasing accessibility of scientific literature.[97] The Scientific American report lists the top 15 Sleeping Beauties: 7 in chemistry, 5 in physics, 2 in statistics, and 1 in metallurgy.[97] Examples include:
Herbert Freundlich's "Concerning Adsorption in Solutions" (1906), the first mathematical model of adsorption, when atoms or molecules adhere to a surface. Today both environmental remediation and decontamination in industrial settings rely heavily on adsorption.[97]
J[ohn] Turkevich, P. C. Stevenson, J. Hillier, "A Study of the Nucleation and Growth Processes in the Synthesis of Colloidal Gold", Discuss. Faraday. Soc., 1951, 11, pp. 55–75, explains how to suspend
William S. Hummers and Richard E Offeman, "Preparation of Graphitic Oxide",
Multiple discovery
Historians and sociologists have remarked the occurrence, in
Merton contrasted a "multiple" with a "singleton" — a discovery that has been made uniquely by a single scientist or group of scientists working together.[103] He believed that it is multiple discoveries, rather than unique ones, that represent the common pattern in science.[104]
Multiple discoveries in the history of science provide evidence for
The phenomenon of multiple independent discoveries and inventions can be viewed as a consequence of
Technology
Psychology of science
Habitus
Yale University physicist-astronomer Priyamvada Natarajan, writing of the virtually-simultaneous 1846 discovery of the planet Neptune by Urbain Le Verrier and John Couch Adams (after other astronomers, as early as Galileo Galilei in 1612, had unwittingly observed the planet), comments:
The episode is but one of many that proves science is not a dispassionate, neutral, and objective endeavor but rather one in which the violent clash of ideas and personal ambitions often combines with serendipity to propel new discoveries.[108]
Nonconformance
A practical question concerns the traits that enable some individuals to achieve extraordinary results in their fields of work—and how such
Schilling chose innovators in natural science and technology rather than in other fields because she found much more consensus about important contributions to natural science and technology than, for example, to art or music.[110] She further limited the set to individuals associated with multiple innovations. "When an individual is associated with only a single major invention, it is much harder to know whether the invention was caused by the inventor's personal characteristics or by simply being at the right place at the right time."[111]
The eight individuals were all extremely intelligent, but "that is not enough to make someone a serial breakthrough innovator."[109] Nearly all these innovators showed very high levels of social detachment, or separateness (a notable exception being Benjamin Franklin).[112] "Their isolation meant that they were less exposed to dominant ideas and norms, and their sense of not belonging meant that even when exposed to dominant ideas and norms, they were often less inclined to adopt them."[113] From an early age, they had all shown extreme faith in their ability to overcome obstacles—what psychology calls "self-efficacy".[113]
"Most [of them, writes Schilling] were driven by
Most of the innovators also worked hard and tirelessly because they found work extremely rewarding. Some had an extremely high need for achievement. Many also appeared to find work
"Almost all breakthrough innovation," writes Schilling, "starts with an unusual idea or with beliefs that break with conventional wisdom.... However, creative ideas alone are almost never enough. Many people have creative ideas, even brilliant ones. But usually we lack the time, knowledge, money, or motivation to act on those ideas." It is generally hard to get others' help in implementing original ideas because the ideas are often initially hard for others to understand and value. Thus each of Schilling's breakthrough innovators showed extraordinary effort and persistence.[117] Even so, writes Schilling, "being at the right place at the right time still matter[ed]."[118]
Lichenology
When Swiss botanist
A self-taught naturalist, Trevor Goward, has helped create a paradigm shift in the study of lichens and perhaps of all life-forms by doing something that people did in pre-scientific times: going out into nature and closely observing. His essays about lichens were largely ignored by most researchers because Goward has no scientific degrees and because some of his radical ideas are not supported by rigorous data.[120]
When Goward told Toby Spribille, who at the time lacked a high-school education, about some of his lichenological ideas, Goward recalls, "He said I was delusional." Ultimately Spribille passed a high-school equivalency examination, obtained a Ph.D. in lichenology at the University of Graz in Austria, and became an assistant professor of the ecology and evolution of symbiosis at the University of Alberta. In July 2016 Spribille and his co-authors published a ground-breaking paper in Science revealing that many lichens contain a second fungus.
Spribille credits Goward with having "a huge influence on my thinking. [His essays] gave me license to think about lichens in [an unorthodox way] and freed me to see the patterns I worked out in Bryoria with my co-authors." Even so, "one of the most difficult things was allowing myself to have an open mind to the idea that 150 years of literature may have entirely missed the theoretical possibility that there would be more than one fungal partner in the lichen symbiosis." Spribille says that academia's emphasis on the canon of what others have established as important is inherently limiting.[121]
Leadership
Contrary to previous studies indicating that higher
Studied were 379 men and women business leaders in 30 countries, including the fields of banking, retail, and technology. The managers took IQ tests—an imperfect but robust predictor of performance in many areas—and each was rated on leadership style and effectiveness by an average of 8 co-workers. IQ correlated positively with ratings of leadership effectiveness, strategy formation, vision, and several other characteristics—up to a point. The ratings peaked at an IQ of about 120, which is higher than some 80% of office workers. Beyond that, the ratings declined. The researchers suggested that the ideal IQ could be higher or lower in various fields, depending on whether technical or social skills are more valued in a given work culture.[122]
Psychologist Paul Sackett, not involved in the research, comments: "To me, the right interpretation of the work would be that it highlights a need to understand what high-IQ leaders do that leads to lower perceptions by followers. The wrong interpretation would be,'Don't hire high-IQ leaders.'"
Sociology of science
Specialization
Academic specialization produces great benefits for science and technology by focusing effort on discrete disciplines. But excessively narrow specialization can act as a roadblock to productive collaboration between traditional disciplines.
In 2017, in
The latter, fourth Flatiron Institute division was inspired by a 2017 presentation to the institute's leadership by
Mentoring
Sociologist
Social viscosity ensures that not every qualified novice scientist attains access to the most productive centers of scientific thought. Nevertheless, writes Zuckerman, "To some extent, students of promise can choose masters with whom to work and masters can choose among the cohorts of students who present themselves for study. This process of bilateral assortative selection is conspicuously at work among the ultra-elite of science. Actual and prospective members of that elite select their scientist parents and therewith their scientist ancestors just as later they select their scientist progeny and therewith their scientist descendants."[129]
Zuckerman writes: "[T]he lines of elite apprentices to elite masters who had themselves been elite apprentices, and so on indefinitely, often reach far back into the
Collaboration
Sociologist Michael P. Farrell has studied close creative groups and writes: "Most of the fragile insights that laid the foundation of a new vision emerged not when the whole group was together, and not when members worked alone, but when they collaborated and repsonded to one another in pairs."
Twosome collaborations have also been prominent in creative endeavors outside the
The same point was made by
Politics
Big Science
What has been dubbed "
Earlier successful Big Science projects had habituated politicians, mass media, and the public to view Big Science programs with sometimes uncritical favor.[137]
The U.S.'s BRAIN Initiative was inspired by concern about the spread and cost of
In the European Union, the
As of 2019, the European Union's Human Brain Project had not lived up to its extravagant promise.[140]
Funding
Government funding
Myhrvold writes that such arguments are dangerously wrong: without government support, most basic scientific research will never happen. "This is most clearly true for the kind of pure research that has delivered... great intellectual benefits but no profits, such as the work that brought us the Higgs boson, or the understanding that a supermassive black hole sits at the center of the Milky Way, or the discovery of methane seas on the surface of Saturn's moon Titan. Company research laboratories used to do this kind of work: experimental evidence for the Big Bang was discovered at AT&T's Bell Labs, resulting in a Nobel Prize. Now those days are gone."[141]
Even in applied fields such as
Company researchers now have to focus narrowly on innovations that can quickly bring revenue; otherwise the research budget could not be justified to the company's investors. "Those who believe profit-driven companies will altruistically pay for basic science that has wide-ranging benefits—but mostly to others and not for a generation—are naive.... If government were to leave it to the private sector to pay for basic research, most science would come to a screeching halt. What research survived would be done largely in secret, for fear of handing the next big thing to a rival."[141]
Governmental investment is equally vital in the field of biological research. According to William A. Haseltine, a former Harvard Medical School professor and founder of that university's cancer and HIV / AIDS research departments, early efforts to control the COVID-19 pandemic were hampered by governments and industry everywhere having "pulled the plug on coronavirus research funding in 2006 after the first SARS [...] pandemic faded away and again in the years immediately following the MERS [outbreak, also caused by a coronavirus] when it seemed to be controllable.[142] [...] The development of promising anti-SARS and MERS drugs, which might have been active against SARS–CoV-2 [in the Covid-19 pandemic] as well, was left unfinished for lack of money."[143] Haseltine continues:
We learned from the
National Cancer Act in 1971. This [had] built the science we needed to identify and understand HIV in the 1980s, although of course no one knew that payoff was coming.[143]In the 1980s the
Reagan administration did not want to talk about AIDS or commit much funding to HIV research. [But o]nce the news broke that actor Rock Hudson was seriously ill with AIDS, [...] $320 million [were added to] the fiscal 1986 budget for AIDS research. [...] I helped [...] design this first congressionally funded AIDS research program with Anthony Fauci, the doctor now leading [the U.S.] fight against COVID-19.[143][...][The] tool set for virus and pharmaceutical research has improved enormously in the past 36 years since HIV was discovered. What used to take five or 10 years in the 1980s and 1990s in many cases now can be done in five or 10 months. We can rapidly identify and synthesize chemicals to predict which drugs will be effective. We can do
cryoelectron microscopy to probe virus structures and simulate molecule-by-molecule interactions in a matter of weeks – something that used to take years. The lesson is to never let down our guard when it comes to funding antiviral research. We would have no hope of beating COVID-19 if it were not for the molecular biology gains we made during earlier virus battles. What we learn this time around will help us [...] during the next pandemic, but we must keep the money coming.[143]
Private funding
A complementary perspective on the funding of scientific research is given by D.T. Max, writing about the
The Flatiron Institute is part of a trend in the sciences toward privately funded research. In the United States,
These institutes have done much good, partly by providing alternatives to more rigid systems. But private foundations also have liabilities. Wealthy benefactors tend to direct their funding toward their personal enthusiasms. And foundations are not taxed; much of the money that supports them would otherwise have gone to the government.[144]
Funding biases
Funding too few scientists: "[M]ajor success [in scientific research] is largely the result of luck, as well as hard work. The investigators currently enjoying huge funding are not necessarily genuine superstars; they may simply be the best connected." Solutions: "Use a
No reward for transparency: "Many scientific protocols, analysis methods, computational processes and data are opaque. [M]any top findings cannot be reproduced. That is the case for two out of three top psychology papers, one out of three top papers in experimental economics and more than 75 percent of top papers identifying new cancer drug targets. [S]cientists are not rewarded for sharing their techniques." Solutions: "Create better infrastructure for enabling transparency, openness and sharing. Make transparency a prerequisite for funding. [P]referentially hire, promote or tenure... champions of transparency."[145]
No encouragement for replication: Replication is indispensable to the scientific method. Yet, under pressure to produce new discoveries, researchers tend to have little incentive, and much counterincentive, to try replicating results of previous studies. Solutions: "Funding agencies must pay for replication studies. Scientists' advancement should be based not only on their discoveries but also on their replication track record."[145]
No funding for young scientists: "Werner Heisenberg, Albert Einstein, Paul Dirac and Wolfgang Pauli made their top contributions in their mid-20s." But the average age of biomedical scientists receiving their first substantial grant is 46. The average age for a full professor in the U.S. is 55. Solutions: "A larger proportion of funding should be earmarked for young investigators. Universities should try to shift the aging distribution of their faculty by hiring more young investigators."[145]
Biased funding sources: "Most funding for
Funding the wrong fields: "Well-funded fields attract more scientists to work for them, which increases their lobbying reach, fueling a vicious circle. Some entrenched fields absorb enormous funding even though they have clearly demonstrated limited yield or uncorrectable flaws." Solutions: "Independent, impartial assessment of output is necessary for lavishly funded fields. More funds should be earmarked for new fields and fields that are high risk. Researchers should be encouraged to switch fields, whereas currently they are incentivized to focus in one area."[146]
Not spending enough: The U.S. military budget ($886 billion) is 24 times the budget of the National Institutes of Health ($37 billion). "Investment in science benefits society at large, yet attempts to convince the public often make matters worse when otherwise well-intentioned science leaders promise the impossible, such as promptly eliminating all cancer or Alzheimer's disease." Solutions: "We need to communicate how science funding is used by making the process of science clearer, including the number of scientists it takes to make major accomplishments.... We would also make a more convincing case for science if we could show that we do work hard on improving how we run it."[146]
Rewarding big spenders: "Hiring, promotion and
No funding for high-risk ideas: "The pressure that taxpayer money be 'well spent' leads government funders to back projects most likely to pay off with a positive result, even if riskier projects might lead to more important, but less assured, advances. Industry also avoids investing in high-risk projects... Innovation is extremely difficult, if not impossible, to predict..." Solutions: "Fund excellent scientists rather than projects and give them freedom to pursue research avenues as they see fit. Some institutions such as Howard Hughes Medical Institute already use this model with success." It must be communicated to the public and to policy-makers that science is a cumulative investment, that no one can know in advance which projects will succeed, and that success must be judged on the total agenda, not on a single experiment or result.[146]
Lack of good data: "There is relatively limited evidence about which scientific practices work best. We need more research on research ('
Diversity
Naomi Oreskes, professor of the history of science at Harvard University, writes about the desirability of diversity in the backgrounds of scientists.
The history of science is rife with [...] cases of
gender bias; it was scientists, after all, who codified the concept of race as a biological category that was not simply descriptive but also hierarchical.[148][...]
heuristics – intellectual shortcuts that often work but sometimes fail spectacularly. (Believing that men are, in general, better than women in math is one tiring example.) [...][148][...] Science is a collective effort, and it works best when scientific communities are diverse. [H]eterogeneous communities are more likely than homogeneous ones to be able to identify blind spots and correct them. Science does not correct itself; scientists correct one another through critical interrogation. And that means being willing to interrogate not just claims about the external world but claims about [scientists'] own practices and processes as well.[148]
Sexual bias
Claire Pomeroy, president of the
Though the percentage of doctorates awarded to women in
The problem is a culture of unconscious bias that leaves many women feeling demoralized and marginalized. In one study, science faculty were given identical résumés in which the names and genders of two applicants were interchanged; both male and female faculty judged the male applicant to be more competent and offered him a higher salary.[149]
Unconscious bias also appears as "microassaults" against
"When I speak to groups of women scientists," writes Pomeroy, "I often ask them if they have ever been in a meeting where they made a recommendation, had it ignored, and then heard a man receive praise and support for making the same point a few minutes later. Each time the majority of women in the audience raise their hands. Microassaults are especially damaging when they come from a
Sexual harassment
A novel approach to the reporting of sexual harassment, dubbed Callisto, that has been adopted by some institutions of higher education, lets aggrieved persons record experiences of sexual harassment, date-stamped, without actually formally reporting them. This program lets people see if others have recorded experiences of harassment from the same individual, and share information anonymously.[150]
Deterrent stereotypes
An early insight into these disparities was provided to Cimpian and Leslie by the work of psychologist Carol Dweck. She and her colleagues had shown that a person's beliefs about ability matter a great deal for that person's ultimate success. A person who sees talent as a stable trait is motivated to "show off this aptitude" and to avoid making mistakes. By contrast, a person who adopts a "growth mindset" sees his or her current capacity as a work in progress: for such a person, mistakes are not an indictment but a valuable signal highlighting which of their skills are in need of work.[154] Cimpian and Leslie and their collaborators tested the hypothesis that attitudes, about "genius" and about the unacceptability of making mistakes, within various academic fields may account for the relative attractiveness of those fields for American women and African-Americans. They did so by contacting academic professionals from a wide range of disciplines and asking them whether they thought that some form of exceptional intellectual talent was required for success in their field. The answers received from almost 2,000 academics in 30 fields matched the distribution of Ph.D.s in the way that Cimpian and Leslie had expected: fields that placed more value on brilliance also conferred fewer Ph.D.s on women and African-Americans. The proportion of women and African-American Ph.D.s in psychology, for example, was higher than the parallel proportions for philosophy, mathematics, or physics.[155]
Further investigation showed that non-academics share similar ideas of which fields require brilliance. Exposure to these ideas at home or school could discourage young members of stereotyped groups from pursuing certain careers, such as those in the natural sciences or engineering. To explore this, Cimpian and Leslie asked hundreds of five-, six-, and seven-year-old boys and girls questions that measured whether they associated being "really, really smart" (i.e., "brilliant") with their sex. The results, published in January 2017 in Science, were consistent with scientific literature on the early acquisition of sex stereotypes. Five-year-old boys and girls showed no difference in their self-assessment; but by age six, girls were less likely to think that girls are "really, really smart." The authors next introduced another group of five-, six-, and seven-year-olds to unfamiliar gamelike activities that the authors described as being "for children who are really, really smart." Comparison of boys' and girls' interest in these activities at each age showed no sex difference at age five but significantly greater interest from boys at ages six and seven—exactly the ages when stereotypes emerge.[156]
Cimpian and Leslie conclude that, "Given current societal stereotypes, messages that portray [genius or brilliance] as singularly necessary [for academic success] may needlessly discourage talented members of stereotyped groups."[156]
Academic snobbery
Largely as a result of his growing popularity, astronomer and science popularizer Carl Sagan, creator of the 1980 PBS TV Cosmos series, came to be ridiculed by scientist peers and failed to receive tenure at Harvard University in the 1960s and membership in the National Academy of Sciences in the 1990s. The eponymous "Sagan effect" persists: as a group, scientists still discourage individual investigators from engaging with the public unless they are already well-established senior researchers.[157][158]
The operation of the Sagan effect deprives society of the full range of expertise needed to make informed decisions about complex questions, including
A number of factors contribute to the Sagan effect's durability. At the height of the Scientific Revolution in the 17th century, many researchers emulated the example of Isaac Newton, who dedicated himself to physics and mathematics and never married. These scientists were viewed as pure seekers of truth who were not distracted by more mundane concerns. Similarly, today anything that takes scientists away from their research, such as having a hobby or taking part in public debates, can undermine their credibility as researchers.[159]
Another, more prosaic factor in the Sagan effect's persistence may be professional jealousy.[159]
However, there appear to be some signs that engaging with the rest of society is becoming less hazardous to a career in science. So many people have social-media accounts now that becoming a public figure is not as unusual for scientists as previously. Moreover, as traditional funding sources stagnate, going public sometimes leads to new, unconventional funding streams. A few institutions such as Emory University and the Massachusetts Institute of Technology may have begun to appreciate outreach as an area of academic activity, in addition to the traditional roles of research, teaching, and administration. Exceptional among federal funding agencies, the National Science Foundation now officially favors popularization.[160][158]
Institutional snobbery
Like
Public relations
Resistance, among some of the public, to accepting vaccination and the reality of climate change may be traceable partly to several decades of partisan attacks on government, leading to distrust of government science and then of science generally.[163]
Many scientists themselves have been loth to involve themselves in public policy debates for fear of losing credibility: they worry that if they participate in public debate on a contested question, they will be viewed as biased and discounted as partisan. However, studies show that most people want to hear from scientists on matters within their areas of expertise. Research also suggests that scientists can feel comfortable offering policy advice within their fields. "The ozone story", writes Naomi Oreskes, "is a case in point: no one knew better than ozone scientists about the cause of the dangerous hole and therefore what needed to be done to fix it."[164]
Oreskes, however, identifies a factor that does "turn off" the public: scientists' frequent use of jargon – of expressions that tend to be misinterpreted by, or incomprehensible to, laypersons.[163]
In
When astronomers say "
communication accommodation," which means speaking so that the listener can understand.[163]
Publish or perish
"[R]esearchers," writes
When – for a number of possible reasons – publication in legitimate
One reason why some scientists publish in predatory journals is that prestigious scientific journals may charge scientists thousands of dollars for publishing, whereas a predatory journal typically charges less than $200. (Hence authors of papers in the predatory journals are disproportionately located in less wealthy countries and institutions.)[167]
Publishing in predatory journals can be life-threatening when physicians and patients accept spurious claims about medical treatments; and invalid studies can wrongly influence public policy. More such predatory journals are appearing every year. In 2008 Jeffrey Beall, a University of Colorado librarian, developed a list of predatory journals which he updated for several years.[168]
Naomi Oreskes argues that, "[t]o put an end to predatory practices, universities and other research institutions need to find ways to correct the incentives that lead scholars to prioritize publication quantity... Setting a maximum limit on the number of articles that hiring or funding committees can consider might help... as could placing less importance on the number of citations an author gets. After all, the purpose of science is not merely to produce papers. It is to produce papers that tell us something truthful and meaningful about the world."[169]
Data fabrication
The perverse incentive to "publish or perish" is often facilitated by the fabrication of data. A classic example is the identical-twin-studies results of Cyril Burt, which – soon after Burt's death – were found to have been based on fabricated data.
Writes Gideon Lewish-Kraus:
"One of the confounding things about the
Joe Simmons, a
"[A] field cannot reward truth if it does not or cannot decipher it, so it rewards other things instead. Interestingness. Novelty. Speed. Impact. Fantasy. And it effectively punishes the opposite. Intuitive Findings. Incremental Progress. Care. Curiosity. Reality."[171]
Accelerating science
"[R]ecent years", however, writes Oreskes, "[have] seen important papers, written by prominent scientists and published in prestigious journals,
Academics at leading universities in the United States and Europe are subject to
"Good science [and scholarship take] time", writes Oreskes. "More than 50 years elapsed between the 1543 publication of
See also
- Agnotology
- AI effect
- AI winter
- Artificial general intelligence
- Artificial intelligence
- Brevity law (also called Zipf's law of abbreviation)
- Cancel culture
- Chinese room
- Cyril Burt
- Data fabrication
- Demarcation problem
- Denialism
- Economics of science
- Economics of scientific knowledge
- Hard and soft science
- Historic recurrence
- Historiography of science
- History of military technology
- History of science
- History of science policy
- History of technology
- Impact factor
- Informetrics
- Interdisciplinarity
- Invalid science
- Junk science
- List of examples of Stigler's law
- List of misnamed theorems
- List of multiple discoveries
- List of scientific misconduct incidents
- Little Science, Big Science
- Matilda effect
- Matthew effect
- Mertonian norms
- Metascience
- Military funding of science
- Multiple discovery
- Philosophy of science
- Politicization of science
- Principle of least effort
- Pseudoscience
- Publication bias
- Publish or perish
- Replicability
- Replication crisis
- Reproducibility Project
- Retraction in academic publishing
- Role of chance in scientific discoveries
- Science and technology studies
- Science Citation Index Expanded
- Science of science policy
- Science studies
- Science, technology and society
- Scientific misconduct
- Scientometrics
- Serendipity
- Social physics (aka sociophysics)
- Sociology of knowledge
- Sociology of science
- Sociology of scientific ignorance
- Sociology of scientific knowledge
- Stigler's law of eponymy
- Technological singularity
- Women in computing
- Women in science
- Women in STEM fields
- Woozle effect
- Workplace bullying in academia
- Zipf's law
Notes
- ^ This meaning of "logology" is distinct from "the study of words", as the term was introduced by Kenneth Burke in The Rhetoric of Religion: Studies in Logology (1961), which sought to find a universal theory and methodology of language.[3] In introducing the book, Burke wrote: "If we defined 'theology' as 'words about God', then by 'logology' we should mean 'words about words'". Burke's "logology", in this theological sense, has been cited as a useful tool of sociology.[4]
- ^ Maria Ossowska and Stanisław Ossowski concluded that, while the singling out of a certain group of questions into a separate, "autonomous" discipline might be insignificant from a theoretical standpoint, it is not so from a practical one: "A new grouping of [questions] lends additional importance to the original [questions] and gives rise to new ones and [to] new ideas. The new grouping marks out the direction of new investigations; moreover, it may exercise an influence on university studies [and on] the found[ing] of chairs, periodicals and societies."[7]
- ^ Other thinkers associated with the Polish school of logology who "have [also] gained international recognition" include Kazimierz Twardowski, Tadeusz Kotarbiński, Kazimierz Ajdukiewicz, Ludwik Fleck, and Stefan Amsterdamski.[17]
- ^ Historian of science Steven Shapin, in discussing the broad range of scientific interests of the German physiologist and physicist Hermann von Helmholtz (1821–94), observes that "In nineteenth-century Germany, both philology and chemistry, for example, counted as Wissenschaften – that is, as rational, rigorous, and systematic forms of inquiry...in English, "science" came to stand largely for systematic studies of nature; chemistry counts as a science, philology does not."[20]
- imposter syndrome.... Truth can be elusive even in the best-established theories. Quantum mechanics is as well tested a theory as can be, yet its interpretation remains inscrutable. [p. 30.] The deeper physicists dive into reality, the more reality seems to evaporate." [p. 34.][23]
- on 24 October 2018 what questions he would like to see answered, listed the same three questions, in the same order, that Gleiser describes as unknowable.
- ^ Herbert Spencer argued that the ultimate "reality existing behind all appearances is, and must ever be, unknown."[25]
- Einstein could have simplified matters considerably by coining a word such as mattergy, matter and energymerely being different forms of mattergy, mattergy I and mattergy II.” The matter and energy comprising the universe are interconvertible in obedience to Einstein's equation. They are also interdependent: the production of energy requires the use of material things, such as fossil fuels, dams, solar panels, or wind turbines; and the production of material things universally requires the application of energy. The Latin-Greek hybrid word "mattergy" denotes the underlying unity of matter and energy. The word "mattergy" in turn gives rise to the adjective "matergetic" and the noun "matergetics," which latter could serve as a synonym for "physics." Since, however, such a synonym is superfluous, "matergetics" is available as a term for theholistic study of the use of natural and human-made resources, and of the downstream effects of their use (or, in some cases, of failure to use them). One such effect, currently of critical importance, is thenuclear wastes. An example of failure to use a resource may be the nonuse of ainfectious disease. Perhaps it might be useful if there were established an online, freely accessible information source on Matergetics -- on the use of, misuse of, or failure to use resources... resources of materials, energy, and societal organization that currently exist or in future may come into being.
- ^ In October 2018 and March 2019, an AI system flew two Boeing 737 Max 8 planes, with their passengers and crews, into the ground.[55]
- ^ Albert Einstein writes: "[C]ombinatory play seems to be the essential feature in productive thought — before there is any connection with logical construction in words or other kinds of signs which can be communicated to others."[76]
- ^ Ludicrous as this metaphor for the process of invention may sound, it brings to mind some experiments that would soon be done by Prus' contemporary, the inventor Thomas Edison—nowhere more so than in his exhaustive search for a practicable light-bulb filament. (Edison's work with electric light bulbs also illustrates Prus' law of gradualness: many earlier inventors had previously devised incandescent lamps; Edison's was merely the first commercially practical incandescent light.)
- ^ In a similar vein, dual Nobel-laureate chemist and peace activist Linus Pauling – when asked, after a circa 1961 public lecture at Monterey Peninsula College, how he came up with ideas – replied that, in order to come up with a good idea, a person must think up many ideas and discard the ones that don't work.
- .
- interbellum Polish School of Mathematics; within three generations, methods of solving World War II-era German Enigma ciphers– methods that contributed substantially to Allied victory in the war.
- marine scientists of the first class who work in fields statutorily excluded from consideration for Nobel prizes."[128]
- eugenicist whose interests were tied to a delusional notion of seeding the human race with his own DNA. Given this stance, it is particularly disturbing that he focused his largesse on research on the genetic basis of human behavior. [...] [T]he interests of funders often influence the work done. [...] [W]hen Epstein got into trouble, several faculty members defended him and even visited him in jail. When [his] lawyer, Harvard professor Alan Dershowitz, needed help to argue (on semantic grounds) that Epstein was not guilty as charged, he reached out to Harvard psychologist and linguist Steven Pinker. Pinker (who never took funds from Epstein) says he did not know to what use his advice was being put and aided Dershowitz only 'as a favor to a friend and colleague.' [...] Epstein had purchased friends in high places, and those friends had friends who helped him, even if inadvertently."[147]A classic example of the workings of social viscosity.
References
- ISBN 978-83-86062-09-6, English-language summary: pp. 741–43
- JSTOR 25778765. note 3
- ISBN 9780520016101.
- S2CID 145745575.
- ISBN 83-01-03607-9, p. XI.
- ^ Klemens Szaniawski, "Preface", Polish Contributions to the Science of Science, p. VIII.
- ^ Maria Ossowska and Stanisław Ossowski, "The Science of Science", reprinted in Bohdan Walentynowicz, ed., Polish Contributions to the Science of Science, pp. 88–91.
- ^ Bohdan Walentynowicz, ed., Polish Contributions to the Science of Science, passim.
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- ^ Bohdan Walentynowicz, Editor's Note, in Bohdan Walentynowicz, ed., Polish Contributions to the Science of Science, p. XI.
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- ^ a b Marcelo Gleiser, "How Much Can We Know? The reach of the scientific method is constrained by the limitations of our tools and the intrinsic impenetrability of some of nature's deepest questions", Scientific American, vol. 318, no. 6 (June 2018), p. 73.
- ^ George Musser, "Virtual Reality: How Close Can Physics Bring Us to a Truly Fundamental Understanding of the World?", Scientific American, vol. 321, no. 3 (September 2019), pp. 30–35.
- ^ a b c d e f Marcelo Gleiser, "How Much Can We Know?, Scientific American, vol. 318, no. 6 (June 2018), p. 73.
- ^ Herbert Spencer, First Principles (1862), part I: "The Unknowable", chapter IV: "The Relativity of All Knowledge".
- ^ Freeman Dyson, "The Case for Blunders" (review of Mario Livio, Brilliant Blunders: From Darwin to Einstein—Colossal Mistakes by Great Scientists that Changed Our Understanding of Life and the Universe, Simon and Schuster), The New York Review of Books, vol. LXI, no. 4 (March 6, 2014), p. 4.
- ^ a b c d e f g Freeman Dyson, "The Case for Blunders", The New York Review of Books, vol. LXI, no. 4 (March 6, 2014), p. 4.
- ^ Freeman Dyson, "The Case for Blunders", The New York Review of Books, vol. LXI, no. 4 (March 6, 2014), pp. 6, 8.
- ^ Freeman Dyson, "The Case for Blunders", The New York Review of Books, vol. LXI, no. 4 (March 6, 2014), p. 8.
- ^ a b c d e f g Naomi Oreskes, "Is Science Actually 'Right'?: It doesn't deliver absolute truth, but it contains useful elements of truth", Scientific American, vol. 325, no. 1 (July 2021), p. 78.
- , vol. LXII, no. 14 (September 24, 2015), p. 53.
- ^ a b c Jim Holt, "At the Core of Science" (a review of Steven Weinberg, To Explain the World: The Discovery of Modern Science, Harper, 2015), The New York Review of Books, vol. LXII, no. 14 (September 24, 2015), p. 53.
- ^ Jim Holt, "At the Core of Science" (a review of Steven Weinberg, To Explain the World: The Discovery of Modern Science, Harper, 2015), The New York Review of Books, vol. LXII, no. 14 (September 24, 2015), pp. 53–54.
- ^ a b c d e f g h i Jim Holt, "At the Core of Science" (a review of Steven Weinberg, To Explain the World: The Discovery of Modern Science, Harper, 2015), The New York Review of Books, vol. LXII, no. 14 (September 24, 2015), p. 54.
- ^ Joshua Rothman, "The Rules of the Game: How does science really work?" (review of Michael Strevens, The Knowledge Machine: How Irrationality Created Modern Science, Liveright), The New Yorker, 5 October 2020, pp. 67–71. (p. 70.)
- ^ Naomi Oreskes, "Masked Confusion: A trusted source of health information misleads the public by prioritizing rigor over reality", Scientific American, vol. 329, no. 4 (November 2023), pp. 90–91.
- ^ Naomi Oreskes, "Masked Confusion: A trusted source of health information misleads the public by prioritizing rigor over reality", Scientific American, vol. 329, no. 4 (November 2023), p. 90.
- ^ Naomi Oreskes, "Masked Confusion: A trusted source of health information misleads the public by prioritizing rigor over reality", Scientific American, vol. 329, no. 4 (November 2023), pp. 90–91.
- ^ Naomi Oreskes, "Masked Confusion: A trusted source of health information misleads the public by prioritizing rigor over reality", Scientific American, vol. 329, no. 4 (November 2023), p. 90.
- ^ Naomi Oreskes, "Masked Confusion: A trusted source of health information misleads the public by prioritizing rigor over reality", Scientific American, vol. 329, no. 4 (November 2023), pp. 90–91.
- ^ Naomi Oreskes, "Masked Confusion: A trusted source of health information misleads the public by prioritizing rigor over reality", Scientific American, vol. 329, no. 4 (November 2023), p. 91.
- ^ Kenneth Cukier, "Ready for Robots? How to Think about the Future of AI", Foreign Affairs, vol. 98, no. 4 (July/August 2019), p. 192.
- ^ Naomi Oreskes, "Scientists: Please Speak Plainly", Scientific American, vol. 325, no. 4 (October 2021), p. 88.
- ^ Maloof, Mark. "Artificial Intelligence: An Introduction", Washington, D.C., Georgetown University Department of Computer Science, 30 August 2017, p. 37" (PDF). georgetown.edu. Archived from the original (PDF) on 25 August 2018. Retrieved 29 June 2019.
- ^ John R. Searle, "What Your Computer Can't Know", The New York Review of Books, 9 October 2014, p. 52.
- John R. Searle, "What Your Computer Can't Know", The New York Review of Books, 9 October 2014, p. 53.
- John R. Searle, "What Your Computer Can't Know", The New York Review of Books, 9 October 2014, p. 54.
- ^ Christof Koch, "Proust among the Machines", Scientific American, vol. 321, no. 6 (December 2019), pp. 46–49. (Texts quoted from pp. 48 and 49.)
- ^ Gary Marcus, "Am I Human?: Researchers need new ways to distinguish artificial intelligence from the natural kind", Scientific American, vol. 316, no. 3 (March 2017), p. 63.
- ^ Gary Marcus, "Am I Human?: Researchers need new ways to distinguish artificial intelligence from the natural kind", Scientific American, vol. 316, no. 3 (March 2017), p. 61.
- ^ Pedro Domingos, "Our Digital Doubles: AI will serve our species, not control it", Scientific American, vol. 319, no. 3 (September 2018), p. 93.
- OCLC 1035622189.
- ^ Amanpour, 28 September 2018.
- ^ Paul Scharre, "Killer Apps: The Real Dangers of an AI Arms Race", Foreign Affairs, vol. 98, no. 3 (May/June 2019), pp. 135–44. "Today's AI technologies are powerful but unreliable. Rules-based systems cannot deal with circumstances their programmers did not anticipate. Learning systems are limited by the data on which they were trained. AI failures have already led to tragedy. Advanced autopilot features in cars, although they perform well in some circumstances, have driven cars without warning into trucks, concrete barriers, and parked cars. In the wrong situation, AI systems go from supersmart to superdumb in an instant. When an enemy is trying to manipulate and hack an AI system, the risks are even greater." (p. 140.)
- ^ Schemm, Paul. "'Black box' data show 'clear similarities' between Boeing jet crashes, official says". Los Angeles Times. Retrieved March 22, 2019.
- ^ Kenneth Cukier, "Ready for Robots? How to Think about the Future of AI", Foreign Affairs, vol. 98, no. 4 (July/August 2019), p. 197.
- ^ Kenneth Cukier, "Ready for Robots? How to Think about the Future of AI", Foreign Affairs, vol. 98, no. 4 (July/August 2019), p. 198.
- ISBN 978-0374257835, quoted in The New Yorker, 4 November 2019, "Briefly Noted" section, p. 73.
- ISBN 978 0 14 198241 0, 418 pp.), London Review of Books, vol. 43, no. 2 (21 January 2021), pp. 37–39. Paul Taylor quotation: p. 39.
- ^ Gary Marcus, "Artificial Confidence: Even the newest, buzziest systems of artificial general intelligence are stymied by the same old problems", Scientific American, vol. 327, no. 4 (October 2022), pp. 42–45.
- ^ Gary Marcus, "Artificial Confidence: Even the newest, buzziest systems of artificial general intelligence are stymied by the same old problems", Scientific American, vol. 327, no. 4 (October 2022), p. 45.
- ^ a b Lydia Denworth, "A Significant Problem: Standard scientific methods are under fire. Will anything change?", Scientific American, vol. 321, no. 4 (October 2019), pp. 62–67. (p. 66.)
- ^ Lydia Denworth, "A Significant Problem: Standard scientific methods are under fire. Will anything change?", Scientific American, vol. 321, no. 4 (October 2019), pp. 62–67. (pp. 63-64.)
- ^ Lydia Denworth, "A Significant Problem: Standard scientific methods are under fire. Will anything change?", Scientific American, vol. 321, no. 4 (October 2019), pp. 62–67. (p. 63.)
- ^ Lydia Denworth, "A Significant Problem: Standard scientific methods are under fire. Will anything change?", Scientific American, vol. 321, no. 4 (October 2019), pp. 62–67. (p. 64.)
- ^ a b c d Lydia Denworth, "A Significant Problem: Standard scientific methods are under fire. Will anything change?", Scientific American, vol. 321, no. 4 (October 2019), pp. 62–67. (p. 67.)
- ^ Bolesław Prus, On Discoveries and Inventions: A Public Lecture Delivered on 23 March 1873 by Aleksander Głowacki [Bolesław Prus], Passed by the [Russian] Censor (Warsaw, 21 April 1873), Warsaw, Printed by F. Krokoszyńska, 1873. [1]
- ^ Bolesław Prus, On Discoveries and Inventions: A Public Lecture Delivered on 23 March 1873 by Aleksander Głowacki [Bolesław Prus], Passed by the [Russian] Censor (Warsaw, 21 April 1873), Warsaw, Printed by F. Krokoszyńska, 1873, p. 12.
- ^ Bolesław Prus, On Discoveries and Inventions, p. 3.
- ^ a b Bolesław Prus, On Discoveries and Inventions, p. 4.
- ^ Bolesław Prus, On Discoveries and Inventions, pp. 3–4.
- ^ Bolesław Prus, On Discoveries and Inventions, p. 12.
- ^ Bolesław Prus, On Discoveries and Inventions, pp. 12–13.
- ^ Bolesław Prus, On Discoveries and Inventions, p. 13.
- ^ Bolesław Prus, On Discoveries and Inventions, pp. 13–14.
- ISBN 978-0-517-00393-0, pp. 25–26.
- ^ a b c d Bolesław Prus, On Discoveries and Inventions, p. 14.
- ^ Bolesław Prus, On Discoveries and Inventions, pp. 14–15.
- ^ a b c Bolesław Prus, On Discoveries and Inventions, p. 15.
- ^ Bolesław Prus, On Discoveries and Inventions, pp. 15–16.
- ^ a b Bolesław Prus, On Discoveries and Inventions, p. 16.
- ^ Bolesław Prus, On Discoveries and Inventions, pp. 16–17.
- ^ a b Bolesław Prus, On Discoveries and Inventions, p. 17.
- ^ a b c Bolesław Prus, On Discoveries and Inventions, p. 18.
- ^ Bolesław Prus, On Discoveries and Inventions, pp. 18–19.
- ^ a b Bolesław Prus, On Discoveries and Inventions, p. 19.
- ^ Bolesław Prus, On Discoveries and Inventions, pp. 19–20.
- ^ a b c Bolesław Prus, On Discoveries and Inventions, p. 20.
- ^ Bolesław Prus, On Discoveries and Inventions, pp. 20–21.
- ^ a b Bolesław Prus, On Discoveries and Inventions, p. 21.
- ^ Bolesław Prus, On Discoveries and Inventions, p. 22.
- ^ Bolesław Prus, On Discoveries and Inventions, p. 5.
- ^ Bolesław Prus, On Discoveries and Inventions, p. 24.
- ^ Shannon Palus, "Make Research Reproducible: Better incentives could reduce the alarming number of studies that turn out to be wrong when repeated" (State of the World's Science, 2018), Scientific American, vol. 319, no. 4 (October 2018), p. 58.
- ^ a b Shannon Palus, "Make Research Reproducible", Scientific American, vol. 319, no. 4 (October 2018), p. 59.
- ^ a b c Naomi Oreskes, "The Appeal of Bad Science: Nonreplicable studies are cited strangely often", Scientific American, vol. 325, no. 2 (August 2021), p. 82.
- ^ a b c d e f g h Amber Williams, "Sleeping Beauties of Science: Some of the best research can slumber for years", Scientific American, vol. 314, no. 1 (January 2016), p. 80.
- S2CID 145650007. Reprinted in Robert K. Merton, The Sociology of Science: Theoretical and Empirical Investigations, Chicago, University of Chicago Press,1973, pp. 371–82. [2]
- ISBN 978-0-226-52091-9.
- ^ Merton's hypothesis is also discussed extensively in Harriet Zuckerman, Scientific Elite: Nobel Laureates in the United States, Free Press, 1979.
- ISBN 978-0-521-22732-2.
- ^ Tori Reeve, Down House: the Home of Charles Darwin, pp. 40-41.
- ^ Robert K. Merton, On Social Structure and Science, p. 307.
- ^ Robert K. Merton, "Singletons and Multiples in Scientific Discovery: a Chapter in the Sociology of Science," Proceedings of the American Philosophical Society, 105: 470–86, 1961. Reprinted in Robert K. Merton, The Sociology of Science: Theoretical and Empirical Investigations, Chicago, University of Chicago Press, 1973, pp. 343–70.
- Historical Novel," The Polish Review, vol. XXXIX, no. 1 (1994), pp. 45-46.
- ^ Wade Roush, "The Big Slowdown: Major technological shifts are fewer and farther between than they once were", Scientific American, vol. 321, no. 2 (August 2019), p. 24.
- ^ Laura Grego and David Wright, "Broken Shield: Missiles designed to destroy incoming nuclear warheads fail frequently in tests and could increase global risk of mass destruction", Scientific American, vol. 320, no. no. 6 (June 2019), pp. 62–67. (p. 67.)
- Dale P. Cruikshank and William Sheehan, Discovering Pluto: Exploration at the Edge of the Solar System, University of Arizona Press, 475 pp.; Alan Stern and David Grinspoon, Chasing New Horizons: Inside the Epic First Mission to Pluto, Picador, 295 pp.; and Adam Morton, Should We Colonize Other Planets?, Polity, 122 pp.), The New York Review of Books, vol. LXVI, no. 16 (24 October 2019), pp. 39–41. (p. 39.)
- ^ ISBN 9781610397926, p. 13.
- ISBN 9781610397926, p. 11.
- ISBN 9781610397926, p. 12.
- ISBN 9781610397926, p. 35.
- ^ ISBN 9781610397926, p. 14.
- ISBN 9781610397926, p. 15.
- ISBN 9781610397926, p. 16.
- ISBN 9781610397926, p. 17.
- ISBN 9781610397926, pp. 17–18.
- ISBN 9781610397926, p. 18.
- ^ Erica Gies, "The Meaning of Lichen: How a self-taught naturalist unearthed hidden symbioses in the wilds of British Columbia—and helped to overturn 150 years of accepted scientific wisdom", Scientific American, vol. 316, no. 6 (June 2017), p. 56.
- ^ Erica Gies, "The Meaning of Lichen", Scientific American, vol. 316, no. 6 (June 2017), pp. 54–55.
- ^ Erica Gies, "The Meaning of Lichen", Scientific American, vol. 316, no. 6 (June 2017), pp. 57–58.
- ^ a b c d e Matthew Hutson, "Ineffective Geniuses?: People with very high IQs can be perceived as worse leaders", Scientific American, vol. 318, no. 3 (March 2018), p. 20.
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- Jim Simons a Wall Street billionaire. His new research center helps scientists mine data for the common good", The New Yorker, 18 & 25 December 2017, p. 72.
- Jim Simons a Wall Street billionaire. His new research center helps scientists mine data for the common good", The New Yorker, 18 & 25 December 2017, p. 76.
- ^ Jim Simons a Wall Street billionaire. His new research center helps scientists mine data for the common good", The New Yorker, 18 & 25 December 2017, p. 83.
- ^ Harriet Zuckerman, Scientific Elite: Nobel Laureates in the United States, New York, The Free Press, 1977, pp. 99–100.
- ^ Harriet Zuckerman, Scientific Elite: Nobel Laureates in the United States, New York, The Free Press, 1977, p. 42.
- ^ Harriet Zuckerman, Scientific Elite: Nobel Laureates in the United States, New York, The Free Press, 1977, p. 104.
- ^ Harriet Zuckerman, Scientific Elite: Nobel Laureates in the United States, New York, The Free Press, 1977, p. 105.
- ^ Michael P. Farrell, Collaborative Circles: Friendship Dynamics and Creative Work, 2001, quoted in James Somers, "Binary Stars: The friendship that made Google huge", The New York Review of Books, 10 December 2018, p. 30.
- ^ James Somers, "Binary Stars: The friendship that made Google huge", The New York Review of Books, 10 December 2018, p. 31.
- ^ James Somers, "Binary Stars: The friendship that made Google huge", The New York Review of Books, 10 December 2018, pp. 28–35.
- ^ James Somers, "Binary Stars: The friendship that made Google huge", The New York Review of Books, 10 December 2018, pp. 30–31.
- ^ "American Masters: Decoding Watson", PBS American Masters series, season 32, episode 9 (2019), first aired on 2 January 2019. [3]
- Big Science?", Scientific American, vol. 313, no. 4 (October 2015), p. 38.
- ^ a b Stefan Theil, "Trouble in Mind", Scientific American, vol. 313, no. 4 (October 2015), p. 42.
- ^ a b Stefan Theil, "Trouble in Mind", Scientific American, vol. 313, no. 4 (October 2015), p. 39.
- ^ Stefan Theil, "Trouble in Mind", Scientific American, vol. 313, no. 4 (October 2015), pp. 38-39.
- ^ Ed Yong, "The Human Brain Project Hasn't Lived Up to Its Promise: Ten years ago, a neuroscientist said that within a decade he could simulate a human brain. Spoiler: It didn't happen", The Atlantic, 22 July 2019. [4]
- ^ a b c d e f Nathan Myhrvold, "Even Genius Needs a Benefactor: Without government resources, basic science will grind to a halt", Scientific American, vol. 314, no. 2 (February 2016), p. 11.
- ^ William A. Haseltine, "What We Learned from AIDS: Lessons from another pandemic for fighting COVID–19", Scientific American, vol. 323, no. 4 (October 2020), pp. 36–41. (p. 40.)
- ^ a b c d William A. Haseltine, "What We Learned from AIDS: Lessons from another pandemic for fighting COVID–19", Scientific American, vol. 323, no. 4 (October 2020), pp. 36–41. (p. 41.)
- ^ Jim Simons a Wall Street billionaire. His new research center helps scientists mine data for the common good", The New Yorker, 18 & 25 December 2017, p. 75.
- ^ John P.A. Ioannidis, "Rethink Funding: The way we pay for science does not encourage the best results" (State of the World's Science, 2018), Scientific American, vol. 319, no. 4 (October 2018), p. 54.
- ^ John P.A. Ioannidis, "Rethink Funding: The way we pay for science does not encourage the best results" (State of the World's Science, 2018), Scientific American, vol. 319, no. 4 (October 2018), p. 55.
- ^ Naomi Oreskes, "Tainted Money Taints Research: How sex offender Jeffrey Epstein bought influence at Harvard University", Scientific American, vol. 323, no. 3 (September 2020), p. 84.
- ^ a b c Naomi Oreskes, "Sexism and Racism Persist in Science: We kid ourselves if we insist that the system will magically correct itself", Scientific American, vol. 323, no. 4 (October 2020), p. 81.
- ^ a b c d e Claire Pomeroy, "Academia's Gender Problem", Scientific American, vol. 314, no. 1 (January 2016), p. 11.
- ^ a b c Clara Moskowitz, "End Harassment: A leader of a major report on sexual misconduct explains how to make science accessible to everyone" (State of the World's Science, 2018), Scientific American, vol. 319, no. 4 (October 2018), p. 61.
- ^ Andrei Cimpian and Sarah-Jane Leslie, "The Brilliance Trap", Scientific American, vol. 317, no. 3 (September 2017), pp. 60–65.
- ^ Andrei Cimpian and Sarah-Jane Leslie, "The Brilliance Trap", Scientific American, vol. 317, no. 3 (September 2017), pp. 61–62.
- ^ Andrei Cimpian and Sarah-Jane Leslie, "The Brilliance Trap", Scientific American, vol. 317, no. 3 (September 2017), p. 62.
- ^ Andrei Cimpian and Sarah-Jane Leslie, "The Brilliance Trap", Scientific American, vol. 317, no. 3 (September 2017), p. 63.
- ^ Andrei Cimpian and Sarah-Jane Leslie, "The Brilliance Trap", Scientific American, vol. 317, no. 3 (September 2017), pp. 63–64.
- ^ a b Andrei Cimpian and Sarah-Jane Leslie, "The Brilliance Trap", Scientific American, vol. 317, no. 3 (September 2017), p. 65.
- ^ Stephen L. Macknik, "The Plight of the Celebrity Scientist", Scientific American, vol. 315, no. 4 (October 2016), p. 65.
- ^ a b The Editors, "Go Public or Perish: When universities discourage scientists from speaking out, society suffers", Scientific American, vol. 318, no. 2 (February 2018), p. 6.
- ^ Stephen L. Macknik, "The Plight of the Celebrity Scientist", Scientific American, vol. 315, no. 4 (October 2016), p. 66.
- Stephen L. Macknik, "The Plight of the Celebrity Scientist", Scientific American, vol. 315, no. 4 (October 2016), p. 67.
- ^ Viviane Callier, "Idea Epidemic: An infectious disease model shows how science knowledge spreads", Scientific American, vol. 320, no. 2 (February 2019), p. 14.
- ^ Naomi Oreskes, "Restoring the Road to Opportunity: Media attention to Ivy League schools distracts from the much more important – and undersupported – public university system", Scientific American, vol. 329, no. 5 (December 2023), p. 86.
- ^ a b c d Naomi Oreskes, "Scientists: Please Speak Plainly", Scientific American, vol. 325, no. 4 (October 2021), p. 88.
- ^ Naomi Oreskes, "Scientists as Public Advocates: People are eager to hear from experts in specific areas", Scientific American, vol. 327, no. 3 (September 2022), p.78.
- ^ Naomi Oreskes, "Paper Predators: Journals that print shoddy research put people's lives at risk", Scientific American, vol. 326, no. 6 (June 2022), p. 59.
- ^ Naomi Oreskes, "Paper Predators: Journals that print shoddy research put people's lives at risk", Scientific American, vol. 326, no. 6 (June 2022), p. 59.
- ^ Naomi Oreskes, "Paper Predators: Journals that print shoddy research put people's lives at risk", Scientific American, vol. 326, no. 6 (June 2022), p. 59.
- ^ Naomi Oreskes, "Paper Predators: Journals that print shoddy research put people's lives at risk", Scientific American, vol. 326, no. 6 (June 2022), p. 59.
- ^ Naomi Oreskes, "Paper Predators: Journals that print shoddy research put people's lives at risk", Scientific American, vol. 326, no. 6 (June 2022), p. 59.
- ^ Gideon Lewis-Kraus, "Big Little Lies: Dan Ariely and Francesca Gino got famous studying dishonesty. Did they fabricate some of their work?", The New Yorker, 9 October 2023, pp. 40-53. (p. 51.)
- ^ Gideon Lewis-Kraus, "Big Little Lies: Dan Ariely and Francesca Gino got famous studying dishonesty. Did they fabricate some of their work?", The New Yorker, 9 October 2023, pp. 40-53. (p. 53.)
- ^ Naomi Oreskes, "Trouble in the Fast Lane: Scientific research needs to slow down, not speed up", Scientific American, vol. 330, no.4 (April 2024), p. 69.
- ^ Naomi Oreskes, "Trouble in the Fast Lane: Scientific research needs to slow down, not speed up", Scientific American, vol. 330, no.4 (April 2024), p. 69.
- ^ Naomi Oreskes, "Trouble in the Fast Lane: Scientific research needs to slow down, not speed up", Scientific American, vol. 330, no.4 (April 2024), p. 69.
- ^ Naomi Oreskes, "Trouble in the Fast Lane: Scientific research needs to slow down, not speed up", Scientific American, vol. 330, no.4 (April 2024), p. 69.
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Further reading
- academics are pursuing careers rather than truth, and readers are not getting all the information they deserve." (p. 74.) Writes Darnton: "Most scientific research is subsidized by the federal government." Under a 2022 White House directive, "As of December 31, 2025, all agencies... must require immediate open access... The G7 leaders took a similar stand on May 14, 2023, as did the European Councilon May 23. The tide is turning in favor of unrestricted access, but the countervailing forces are so complex that the future remains cloudy." (p. 73.)
- Dominus, Susan, "Sidelined: American women have been advancing science and technology for centuries. But their achievements weren't recognized until a tough-minded scholar, Margaret W. Rossiter, hit the road and rattled the academic world", Smithsonian, vol. 50, no. 6 (October 2019), pp. 42–53, 80.
- Finkbeiner, Ann, "Women Take On the Stars: A new wave of astronomers are leading a revolution in scientific culture", Scientific American, vol. 326, no. 4 (April 2022), pp. 32–39. Women astronomers have been making progress against professional discrimination and sexual harassment toward women.
- Gleick, James, "The Fate of Free Will" (review of Kevin J. Mitchell, Free Agents: How Evolution Gave Us Free Will, Princeton University Press, 2023, 333 pp.), The New York Review of Books, vol. LXXI, no. 1 (18 January 2024), pp. 27–28, 30. "Agency is what distinguishes us from machines. For biological creatures, reason and purpose come from acting in the world and experiencing the consequences. Artificial intelligences – disembodied, strangers to blood, sweat, and tears – have no occasion for that." (p. 30.)
- Gribbin, John, "Alone in the Milky Way: Why we are probably the only intelligent life in the galaxy", Scientific American, vol. 319, no. 3 (September 2018), pp. 94–99. "Is life likely to exist elsewhere in the [Milky Way] galaxy? Almost certainly yes, given the speed with which it appeared on Earth. Is another technological civilization likely to exist today? Almost certainly no, given the chain of circumstances that led to our existence. These considerations suggest that we are unique not just on our planet but in the whole Milky Way. And if our planet is so special, it becomes all the more important to preserve this unique world for ourselves, our descendants and the many creatures that call Earth home." (p. 99.)
- training datafor such a purpose." (p. 82.)
- Immerwahr, Daniel, "Your Lying Eyes: People now use A.I. to generate fake videos indistinguishable from real ones. How much does it matter?", The New Yorker, 20 November 2023, pp. 54–59. "If by 'deepfakes' we mean realistic videos produced using artificial intelligence that actually deceive people, then they barely exist. The fakes aren't deep, and the deeps aren't fake. [...] A.I.-generated videos are not, in general, operating in our media as counterfeited evidence. Their role better resembles that of cartoons, especially smutty ones." (p. 59.)
- Natarajan, Priyamvada, "Calculating Women" (review of Margot Lee Shetterly, Hidden Figures: The American Dream and the Untold Story of the Black Women Mathematicians Who Helped Win the Space Race, William Morrow; Dava Sobel, The Glass Universe: How the Ladies of the Harvard Observatory Took the Measure of the Stars, Viking; and Nathalia Holt, Rise of the Rocket Girls: The Women Who Propelled Us, from Missiles to the Moon to Mars, Little, Brown), The New York Review of Books, vol. LXIV, no. 9 (25 May 2017), pp. 38–39.
- Oreskes, Naomi, "Nobel Oblige: Rosalind Franklin deserved a Nobel Prize for her work on the structure of DNA. Awarding her one posthumously is the honorable – and scientific – thing to do", Scientific American, vol.329, no. 3 (October 2023), pp. 62–63. "It is the essence of science to recognize errors and correct them. It's time for the Nobel Assembly to embody this ideal and do the same." (p. 63.)
- Press, Eyal, "In Front of Their Faces: Does facial-recognition technology lead police to ignore contradictory evidence?", The New Yorker, 20 November 2023, pp. 20–26.
- Scientific Method: An Evolution of Thinking from Darwin to Dewey, Harvard University Press, 372 pp.), The New York Review of Books, vol. LXVII, no. 11 (2 July 2020), pp. 48–50.
- IQ alone", Scientific American, vol. 329, no. 1 (July/August 2023), p. 7. "Despite its high IQ, ChatGPTfails at tasks that require real humanlike reasoning or an understanding of the physical and social world.... ChatGPT seemed unable to reason logically and tried to rely on its vast database of... facts derived from online texts."
- ISBN 978-1-4214-2673-0, 302 pp.), London Review of Books, vol. 41, no. 14 (18 July 2019), pp. 31–33.
- Scientific American Board of Editors, "Science Suffers from Harassment: A leading organization has said that sexual harassment is scientific misconduct. Where are the others?", Scientific American, vol. 318, no. 3 (March 2018), p. 8.
- Watson, James D., The Double Helix: A Personal Account of the Discovery of the Structure of DNA, New York, Atheneum, 1968.
External links
- American Masters: Decoding Watson - PBS documentary about James Watson, co-discoverer of the structure of DNA, including interviews with Watson, his family, and colleagues. 2019-01-02.