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The hope is that the facilities, and perhaps more importantly the close interconnections between outstanding scientists in different fields, that it provides, will lead to it being more than the sum of its parts.

Some science directly addresses so-called “big questions”. How did life begin? What is everything made of? How did the universe begin? Often these big questions are posed within a specific theoretical framework; the Higgs boson is an example of how a good theory can condense a set of very big questions - essentially “What is mass?”

big projects are inevitably political to some extent, if only because of the fondness leaders have for making grand (or “grandiose”, as Amos would have it) announcements. Many big projects are international, which can bring in other elements, and requires decision-making frameworks that, while imperfect, do exist even if not all scientists are fully aware of them.

But perhaps the paper by Liao, Sandberg and Roache will turn out to be a prank played on the journal, like the Sokal hoax, named after the physicist whose paper deploying post-modern gobbledegook to show that “quantum gravity is a social and linguistic construct” was published in a cultural studies journal.

It’s easy to imagine academics sitting around swapping the most outrageous solutions to climate change and then daring one another to have them published. I hope this will turn out to be the case. In the meantime I cringe at the thought of what the long-dead giants of Western philosophy would make of their discipline’s response to the climate crisis.

Peterson randomly assigned participants to one of two groups: one whose members read “The Lady With the Dog,” an Anton Chekhov short story centered on marital infidelity, and another whose members read a “nonfictionalized” version of the story, written in the form of a report from a divorce court.

The personality scores of those who read the nonfiction text remained much the same. But the personality scores of those who read the Chekhov story fluctuated. The changes were not large but they were statistically significant, and they were correlated with the intensity of emotions people experienced as they read the story.

Matthew Carland, asked participants to read one of eight short stories or one of eight essays.

Chekhov’s story seemed to get people to start thinking about their personalities — about themselves — in new ways.

We had expected that people who read a piece of fiction would experience the greatest fluctuation in their personality scores, but we didn’t find this. The genre of the text — fiction or nonfiction — didn’t matter much; what mattered was the degree of perceived artistry. Those who read a story or essay that they judged to be artistic changed their personality scores significantly more than did those who judged what they read to be less artistic.

we drew on the studies described above, as well as on research that compared preoccupations of famous fiction writers with those of famous physicists, to outline a psychological conception of artistic literature as being based not on persuasion or instruction (as, for example, the Roman poet Horace theorized in “The Art of Poetry”) but on indirect communication.

the idea of communication that has effects of a nonpersuasive yet transformative kind has rarely been considered in psychology. We hope our studies encourage others to investigate further this important kind of influence.

even genuine scientists are human and as such susceptible to the allure of offering up new paradigms (as the historian of science Thomas Kuhn put it)

paleontologist Stephen Jay Gould insisted that his conception of “punctuated equilibria” (a kind of Marxist biology that blurred the lines between evolution and revolution), which he developed along with fellow paleontologist Niles Eldredge, upended the traditional Darwinian understanding of how natural selection works.

This notion doesn’t constitute a fundamental departure from plain old evolution by natural selection; it simply italicizes that sometimes the process is comparatively rapid, other times slower.

In addition, they have long had a peculiar perspective on evolution, because of the limitations of the fossil record

Darwin was a pioneering geologist as well as the greatest of all biologists, and his insights were backgrounded by the key concept of uniformitarianism, as advocated by Charles Lyell, his friend and mentor

previously regnant paradigm among geologists had been “catastrophism

fossil record was therefore seen as reflecting the creation and extinction of new species by an array of dramatic and “unnatural” dei ex machina.

Of late, however, uniformitarianism has been on a losing streak. Catastrophism is back, with a bang . . . or a flood, or a burst of extraterrestrial radiation, or an onslaught of unpleasant, previously submerged chemicals

This emphasis on catastrophes is the first of a triad of novelties on which “A New History of Life” is based. The second involves an enhanced role for some common but insufficiently appreciated inorganic molecules, notably carbon dioxide, oxygen and hydrogen sulfide.

Life didn’t so much unfold smoothly over hundreds of millions of years as lurch chaotically in response to diverse crises and opportunities: too much oxygen, too little carbon dioxide, too little oxygen, too much carbon dioxide, too hot, too cold

So far, so good, except that in their eagerness to emphasize what is new and different, the authors teeter on the verge of the same trap as Gould: exaggerating the novelty of their own ideas.

Things begin to unravel when it comes to the third leg of Messrs. Ward and Kirschvink’s purported paradigmatic novelty: a supposed role for ecosystems—rain forests, deserts, rivers, coral reefs, deep-sea vents—as units of evolutionary change

“While the history of life may be populated by species,” they write, “it has been the evolution of ecosystems that has been the most influential factor in arriving at the modern-day assemblage of life. . . . [W]e know that on occasion in the deep past entirely new ecosystems appear, populated by new kinds of life.” True enough, but it is those “new kinds of life,” not whole ecosystems, upon which natural selection acts.

One of the most common popular misconceptions about evolution is that it proceeds “for the good of the species.”

The problem is that smaller, nimbler units are far more likely to reproduce differentially than are larger, clumsier, more heterogeneous ones. Insofar as ecosystems are consequential for evolution—and doubtless they are—it is because, like occasional catastrophes, they provide the immediate environment within which something not-so-new is acted out.

This is natural selection doing its same-old, same-old thing: acting by a statistically potent process of variation combined with selective retention and differential reproduction, a process that necessarily operates within the particular ecosystem that a given lineage occupies.

ut biological complexity is only part of the challenge in figuring out what kind of theory of the brain we’re seeking.

What we are really looking for is a bridge, some way of connecting two separate scientific languages — those of neuroscience and psychology.

An example is the discovery of DNA, which allowed us to understand how genetic information could be represented and replicated in a physical structure. In one stroke, this bridge transformed biology from a mystery — in which the physical basis of life was almost entirely unknown — into a tractable if challenging set of problems

We know that there must be some lawful relation between assemblies of neurons and the elements of thought, but we are currently at a loss to describe those laws.

So even if inflation itself seems unlikely, multiplying by the infinite number of universes it creates makes it quite plausible that we find ourselves in a post-inflationary situation.

ather than explaining why we live precisely in this kind of universe, eternal inflation admits there are many kinds of local universes, and expresses the hope that ones like ours are more likely than other kinds.

aturalness is a subtle criterion. In the case of inflationary cosmology, the drive to find a natural theory seems to have paid off handsomely, but perhaps other seemingly unnatural features of our world must simply be accepted. Ultimately it’s nature, not us, that decides what’s natural.

A decade ago, he moved from Brandeis to Columbia, which now has one of the biggest groups of theoretical neuroscientists in the world, he says, and which has a new university-wide focus on integrating brain science with other disciplines.

a “pioneer of computational neuroscience.” Mr. Abbott brought the mathematical skills of a physicist to the field, but he is able to plunge right into the difficulties of dealing with actual brain experiments

the goal is to discover the physiological mechanism in the data.

For example, he asks why does one pattern of neurons firing “make you jump off the couch and run out the door and others make you just sit there and do nothing?” It could be, Dr. Abbott says, that simultaneous firing of all the neurons causes you to take action. Or it could be that it is the number of neurons firing that prompts an action.

“We’ve looked at the nervous system from the two ends in,” Dr. Abbott said, meaning sensations that flow into the brain and actions that are initiated there. “Somewhere in the middle is really intelligence, right? That’s where the action is.”

In the brain, somehow, stored memories and desires like hunger or thirst are added to information about the world, and actions are the result. This is the case for all sorts of animals, not just humans. It is thinking, at the most basic level.

The Higgs boson completed the Standard Model, a suite of equations that agrees with all the experiments that have been done on earth. But that model is not the end of physics. It does not explain dark matter or dark energy, the two major constituents of the cosmos, for example, or why the universe is made of matter instead of antimatter.

For decades, theorists have flirted with a concept called supersymmetry that would address some of these issues and produce a bounty of new particles for CERN’s collider.

Einstein noted that the public recognition of his accomplishment had a political slant. “Today I am described in Germany as a ‘German servant,’ and in England as a ‘Swiss Jew,’ ” he said. “Should it ever be my fate to be represented as a bête noire, I should, on the contrary, become a ‘Swiss Jew’ for the Germans and a ‘German servant’ for the English.”

After World World II, a new generation of physicists in the United States began to focus on relativity from their perch within the “military-industrial complex.” Here, political exigencies accelerated a deeper appreciation of Einstein’s theory, in unanticipated ways.

With GPS, the warping of time that Einstein imagined assumed operational significance. (Later, GPS was opened to the commercial market, and now billions of people rely on general relativity to find their place in the world, every single day.)

The authors claim that philosophy abandoned its relationship to other disciplines by creating its own purified domain, accessible only to credentialed professionals. It is true that from roughly 1930 to 1950, some philosophers — logical empiricists, in particular — did speak of philosophy having its own exclusive subject matter. But since that subject matter was logical analysis aimed at unifying all of science, interdisciplinarity was front and center.

Philosophy also played a role in 20th-century physics, influencing the great physicists Albert Einstein, Niels Bohr and Werner Heisenberg. The philosophers Moritz Schlick and Hans Reichenbach reciprocated that interest by assimilating the new physics into their philosophies.

developed ideas relating logic to linguistic meaning that provided a framework for studying meaning in all human languages. Others, including Paul Grice and J.L. Austin, explained how linguistic meaning mixes with contextual information to enrich communicative contents and how certain linguistic performances change social facts. Today a new philosophical conception of the relationship between meaning and cognition adds a further dimension to linguistic science.

Decision theory — the science of rational norms governing action, belief and decision under uncertainty — was developed by the 20th-century philosophers Frank Ramsey, Rudolph Carnap, Richard Jeffrey and others. It plays a foundational role in political science and economics by telling us what rationality requires, given our evidence, priorities and the strength of our beliefs. Today, no area of philosophy is more successful in attracting top young minds.

Philosophy also assisted psychology in its long march away from narrow behaviorism and speculative Freudianism. The mid-20th-century functionalist perspective pioneered by Hilary Putnam was particularly important. According to it, pain, pleasure and belief are neither behavioral dispositions nor bare neurological states. They are interacting internal causes, capable of very different physical realizations, that serve the goals of individuals in specific ways. This view is now embedded in cognitive psychology and neuroscience.

philosopher-mathematicians Gottlob Frege, Bertrand Russell, Kurt Gödel, Alonzo Church and Alan Turing invented symbolic logic, helped establish the set-theoretic foundations of mathematics, and gave us the formal theory of computation that ushered in the digital age

Philosophy of biology is following a similar path. Today’s philosophy of science is less accessible than Aristotle’s natural philosophy chiefly because it systematizes a larger, more technically sophisticated body of knowledge.

Philosophy’s interaction with mathematics, linguistics, economics, political science, psychology and physics requires specialization. Far from fostering isolation, this specialization makes communication and cooperation among disciplines possible. This has always been so.

Nor did scientific progress rob philosophy of its former scientific subject matter, leaving it to concentrate on the broadly moral. In fact, philosophy thrives when enough is known to make progress conceivable, but it remains unachieved because of methodological confusion. Philosophy helps break the impasse by articulating new questions, posing possible solutions and forging new conceptual tools.

Our knowledge of the universe and ourselves expands like a ripple surrounding a pebble dropped in a pool. As we move away from the center of the spreading circle, its area, representing our secure knowledge, grows. But so does its circumference, representing the border where knowledge blurs into uncertainty and speculation, and methodological confusion returns. Philosophy patrols the border, trying to understand how we got there and to conceptualize our next move.  Its job is unending.

Although progress in ethics, political philosophy and the illumination of life’s meaning has been less impressive than advances in some other areas, it is accelerating.

the advances in our understanding because of careful formulation and critical evaluation of theories of goodness, rightness, justice and human flourishing by philosophers since 1970 compare well to the advances made by philosophers from Aristotle to 1970

The knowledge required to maintain philosophy’s continuing task, including its vital connection to other disciplines, is too vast to be held in one mind. Despite the often-repeated idea that philosophy’s true calling can only be fulfilled in the public square, philosophers actually function best in universities, where they acquire and share knowledge with their colleagues in other disciplines. It is also vital for philosophers to engage students — both those who major in the subject, and those who do not. Although philosophy has never had a mass audience, it remains remarkably accessible to the average student; unlike the natural sciences, its frontiers can be reached in a few undergraduate courses.

David Marr, a neuroscientist colleague of Chomsky's at MIT, defined a general framework for studying complex biological systems (like the brain) in his influential book Vision,

a complex biological system can be understood at three distinct levels. The first level ("computational level") describes the input and output to the system, which define the task the system is performing. In the case of the visual system, the input might be the image projected on our retina and the output might our brain's identification of the objects present in the image we had observed. The second level ("algorithmic level") describes the procedure by which an input is converted to an output, i.e. how the image on our retina can be processed to achieve the task described by the computational level. Finally, the third level ("implementation level") describes how our own biological hardware of cells implements the procedure described by the algorithmic level.

The emphasis here is on the internal structure of the system that enables it to perform a task, rather than on external association between past behavior of the system and the environment. The goal is to dig into the "black box" that drives the system and describe its inner workings, much like how a computer scientist would explain how a cleverly designed piece of software works and how it can be executed on a desktop computer.

As written today, the history of cognitive science is a story of the unequivocal triumph of an essentially Chomskyian approach over Skinner's behaviorist paradigm -- an achievement commonly referred to as the "cognitive revolution,"

While this may be a relatively accurate depiction in cognitive science and psychology, behaviorist thinking is far from dead in related disciplines. Behaviorist experimental paradigms and associationist explanations for animal behavior are used routinely by neuroscientists

Chomsky critiqued the field of AI for adopting an approach reminiscent of behaviorism, except in more modern, computationally sophisticated form. Chomsky argued that the field's heavy use of statistical techniques to pick regularities in masses of data is unlikely to yield the explanatory insight that science ought to offer. For Chomsky, the "new AI" -- focused on using statistical learning techniques to better mine and predict data -- is unlikely to yield general principles about the nature of intelligent beings or about cognition.

Behaviorist principles of associations could not explain the richness of linguistic knowledge, our endlessly creative use of it, or how quickly children acquire it with only minimal and imperfect exposure to language presented by their environment.

it has been argued in my view rather plausibly, though neuroscientists don't like it -- that neuroscience for the last couple hundred years has been on the wrong track.

Implicit in this endeavor is the assumption that with enough sophisticated statistical tools and a large enough collection of data, signals of interest can be weeded it out from the noise in large and poorly understood biological systems.

Brenner, a contemporary of Chomsky who also participated in the same symposium on AI, was equally skeptical about new systems approaches to understanding the brain. When describing an up-and-coming systems approach to mapping brain circuits called Connectomics, which seeks to map the wiring of all neurons in the brain (i.e. diagramming which nerve cells are connected to others), Brenner called it a "form of insanity."

These debates raise an old and general question in the philosophy of science: What makes a satisfying scientific theory or explanation, and how ought success be defined for science?

Ever since Isaiah Berlin's famous essay, it has become a favorite pastime of academics to place various thinkers and scientists on the "Hedgehog-Fox" continuum: the Hedgehog, a meticulous and specialized worker, driven by incremental progress in a clearly defined field versus the Fox, a flashier, ideas-driven thinker who jumps from question to question, ignoring field boundaries and applying his or her skills where they seem applicable.

Chomsky's work has had tremendous influence on a variety of fields outside his own, including computer science and philosophy, and he has not shied away from discussing and critiquing the influence of these ideas, making him a particularly interesting person to interview.

If you take a look at the progress of science, the sciences are kind of a continuum, but they're broken up into fields. The greatest progress is in the sciences that study the simplest systems. So take, say physics -- greatest progress there. But one of the reasons is that the physicists have an advantage that no other branch of sciences has. If something gets too complicated, they hand it to someone else.

If a molecule is too big, you give it to the chemists. The chemists, for them, if the molecule is too big or the system gets too big, you give it to the biologists. And if it gets too big for them, they give it to the psychologists, and finally it ends up in the hands of the literary critic, and so on.

An unlikely pair, systems biology and artificial intelligence both face the same fundamental task of reverse-engineering a highly complex system whose inner workings are largely a mystery

neuroscience developed kind of enthralled to associationism and related views of the way humans and animals work. And as a result they've been looking for things that have the properties of associationist psychology.

a bunch of particles can share these states at the same time, effectively becoming instances of the same particle. And so: entanglement.

possible to strip away all of this indeterminateness

wave functions are very fragile, subject to a “collapse” in which all of those possibilities become just a single particle at a single point at a single time.

physicists have observed a very peculiar behavior of electrons in supercooled baths of helium. When an electron enters the bath, it acts to

two probabilities can be isolated from each other, cordoned off like quantum crime scenes

it’s possible to take a wave function and isolate it into different parts. So, if our electron has some probability of being in position (x1,y1,z1) and another probability of being in position (x2,y2,z2), those two probabilities can be isolated from each other, cordoned off like quantum crime scenes

using tiny bubbles of helium as physical “traps.

trapping the chance of finding the electron, not pieces of the electron

when a macroscopic human attempts to measure a quantum mechanical system: The wave drops away and all that’s left is a boring, well-defined thing.

repel the surrounding helium atoms, forming its own little bubble or cavity in the process.

That an electron (or other particle) can be in many places at the same time is strange enough, but the notion that those possibilities can be captured and shuttled away adds a whole new twist.

wave function isn’t a physical thing. It’s mathematics that describe a phenomenon.

The electron, upon measurement, will be in precisely one bubble.

“No one is sure what actually constitutes a measurement,”

Is consciousness required? We don’t really know.”

Around 100 years ago, quantum mechanics was a purely theoretical topic, only developed to understand certain properties of atoms

But today, quantum mechanics is the basis of our use of all semiconductors in computers and mobile phones

Despite these direct and indirect benefits, most theoretical physicists have a very different motive for their work. They simply want to improve humanity’s understanding of the universe. While this might not immediately impact everyone’s lives, I believe it is just as important a reason for pursuing fundamental research

It somehow seems that every new level of understanding we achieve comes in tandem with new, more fundamental questions. It is never enough to know what we now know. We always want to continue looking behind newly arising curtains. In that respect, I consider fundamental physics a basic part of human culture.

Many biological ideas proposed during the past 150 years stood in stark conflict with what everybody assumed to be true. The acceptance of these ideas required an ideological revolution. And no biologist has been responsible for more—and for more drastic—modifications of the average person’s worldview than Charles Darwin

. Evolutionary biology, in contrast with physics and chemistry, is a historical science—the evolutionist attempts to explain events and processes that have already taken place. Laws and experiments are inappropriate techniques for the explication of such events and processes. Instead one constructs a historical narrative, consisting of a tentative reconstruction of the particular scenario that led to the events one is trying to explain.

The discovery of natural selection, by Darwin and Alfred Russel Wallace, must itself be counted as an extraordinary philosophical advance

The concept of natural selection had remarkable power for explaining directional and adaptive changes. Its nature is simplicity itself. It is not a force like the forces described in the laws of physics; its mechanism is simply the elimination of inferior individuals

A diverse population is a necessity for the proper working of natural selection

Because of the importance of variation, natural selection should be considered a two-step process: the production of abundant variation is followed by the elimination of inferior individuals

By adopting natural selection, Darwin settled the several-thousandyear- old argument among philosophers over chance or necessity. Change on the earth is the result of both, the first step being dominated by randomness, the second by necessity

Another aspect of the new philosophy of biology concerns the role of laws. Laws give way to concepts in Darwinism. In the physical sciences, as a rule, theories are based on laws; for example, the laws of motion led to the theory of gravitation. In evolutionary biology, however, theories are largely based on concepts such as competition, female choice, selection, succession and dominance. These biological concepts, and the theories based on them, cannot be reduced to the laws and theories of the physical sciences

Despite the initial resistance by physicists and philosophers, the role of contingency and chance in natural processes is now almost universally acknowledged. Many biologists and philosophers deny the existence of universal laws in biology and suggest that all regularities be stated in probabilistic terms, as nearly all so-called biological laws have exceptions. Philosopher of science Karl Popper’s famous test of falsification therefore cannot be applied in these cases.

To borrow Darwin’s phrase, there is grandeur in this view of life. New modes of thinking have been, and are being, evolved. Almost every component in modern man’s belief system is somehow affected by Darwinian principles

Tyson praises science as an “exercise in finding what is true” that’s based on peer-reviewed experimentation backed by other experiments and counter-experiments that gives birth to an “emergent truth.” He points out that science is “not something to toy with.” “You can’t say, ‘I chose not to believe in E=mc2,’” he says, referring to physicist Albert Einstein’s corroborated theory of special relativity. “You don’t have that option. It is true, whether or not you believe in it.”

Tyson warns that every minute someone is in denial of a scientific truth delays the “political solution that should have been established years ago.”  “Recognize what science is, and allow to be what it can and should be: In the service of civilization,” he says. “It’s in our hands.”

A paradigm dictates:

what is observed and measured

the questions we ask about those observations

how the questions are formulated

how the results are interpreted

how research is carried out

what equipment is appropriate

In fact, Kuhn strongly suggested that research in a deeply entrenched paradigm invariably ends up reinforcing that paradigm, since anything that contradicts it is ignored or else pressed through the preset methods until it conforms to already established dogma

The body of pre-existing evidence in a field conditions and shapes the collection and interpretation of all subsequent evidence. The certainty that the current paradigm is reality itself is precisely what makes it so difficult to accept alternatives.

It is very common for scientists to discard certain models or pick up emerging theories. But once in a while, enough anomalies accumulate within a field that the entire paradigm itself is required to change to accommodate them.

Many physicists in the 19th century were convinced that the Newtonian paradigm that had reigned for 200 years was the pinnacle of discovery and that scientific progress was more or less a question of refinement. When Einstein published his theories on General Relativity, it was not just another idea that could fit comfortably into the existing paradigm. Instead, Newtonian Physics itself was relegated to being a special subclass of the greater paradigm ushered in by General Relativity. Newton’s three laws are still faithfully taught in schools, however we now operate within a paradigm that puts those laws into a much broader context

The concept of paradigm is closely related to the Platonic and Aristotelian views of knowledge. Aristotle believed that knowledge could only be based upon what is already known, the basis of the scientific method. Plato believed that knowledge should be judged by what something could become, the end result, or final purpose. Plato's philosophy is more like the intuitive leaps that cause scientific revolution; Aristotle's the patient gathering of data.

Talk of paradigms and paradigm shifts has since become commonplace — not only in science, but also in business, social movements and beyond.

He suggested that scientific revolutions are not a matter of incremental advance; they involve "paradigm shifts."

Kuhn posited two kinds of scientific change: incremental developments in the course of what he called "normal science," and scientific revolutions that punctuate these more stable periods.

But what, exactly, is a paradigm shift? Or, for that matter, a paradigm?

Accordingly, a paradigm shift is defined as "an important change that happens when the usual way of thinking about or doing something is replaced by a new and different way."

It turns out this question is hard to answer — not because paradigm has an especially technical or obscure definition, but because it has many. In a paper published in 1970, Margaret Masterson presented a careful reading of Kuhn's 1962 book. She identified 21 distinct senses in which Kuhn used the term paradigm.

First, a paradigm could refer to a special kind of achievement

"Achievements that share these two characteristics I shall henceforth refer to as 'paradigms.' "

But in other parts of the text, paradigms cover more ground. Paradigms can offer general epistemological viewpoints, like the "philosophical paradigm initiated by Descartes," or define a broad sweep of reality, as when "Paradigms determine large areas of experience at the same time."

In the end, Masterson distills Kuhn's 21 senses of paradigm into a more respectable three, and she identifies what she sees as both novel and important aspects of Kuhn's "paradigm view" of science. But for our purposes, Masterson's analysis sheds light on two questions that turn out to be related: what Kuhn meant by paradigm in the first place, and how a single word managed to assume such a broad and expansive set of meanings after being unleashed by Kuhn's book.

“There isn’t one method of ‘doing science.’”

In fact, he notes, there are many paths to finding out the answer to something. Which route a researcher chooses may depend on the field of science being studied. It might also depend on whether experimentation is possible, affordable — even ethical.

In the future, she says, students and teachers will be encouraged to think not about the scientific method, but instead about “practices of science” — or the many ways in which scientists look for answers.

But that one-size-fits-all approach doesn’t reflect how scientists in different fields actually “do” science,

In contrast, geologists, scientists who study the history of Earth as recorded in rocks, won’t necessarily do experiments

For example, experimental physicists are scientists who study how particles such as electrons, ions and protons behave. These scientists might perform controlled experiments, starting with clearly defined initial conditions. Then they will change one variable, or factor, at a time.

Geologists are still collecting evidence, “but it’s a different kind of evidence.”

A hypothesis is a testable idea or explanation for something. Starting with a hypothesis is a good way to do science, she acknowledges, “but it’s not the only way.”

“Often, we just start by saying, ‘I wonder’“ Singer says. “Maybe it gives rise to a hypothesis.” Other times, she says, you may need to first gather some data and look to see if a pattern emerges.

Mistakes and unexpected results can be blessings in disguise.

An experiment that doesn’t give the results that a scientist expected does not necessarily mean a researcher did something wrong. In fact, mistakes often point to unexpected results — and sometimes more important data — than the findings that scientists initially anticipated.