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We’ve covered science for 100 years. here’s how it has — and hasn’t — changed.

There’s more detail and sophistication, but some of the questions remain the same

By Tom Siegfried

Contributing Correspondent

April 2, 2021 at 6:00 am

A century ago, articles in the precursor to Science News frequently focused on astronomy and space, exploring such issues as whether other planets existed beyond Neptune.

SCIEPRO/Science Photo Library/Getty Images

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A century ago, people needed help to understand science. Much as they do today.

Then as now, it wasn’t always easy to sort the accurate from the erroneous. Mainstream media, then as now, regarded science as secondary to other aspects of their mission. And when science made the news, it was often (then as now) garbled, naïve or dangerously misleading.

E.W. Scripps, a prominent newspaper publisher, and William Emerson Ritter, a biologist, perceived a need. They envisioned a service that would provide reliable news about science to the world, dedicated to truth and clarity. For Scripps and Ritter, science journalism had a noble purpose: “To discover the truth about all sorts of things of human concern, and to report it truthfully and in language comprehensible to those whose welfare is involved.”

And so Science Service was born, 100 years ago — soon to give birth to the magazine now known as Science News .

In its first year of existence, Science Service delivered its weekly dispatches to newspapers in the form of mimeographed packets. By 1922 those packets became available to the public by subscription, giving birth to Science News-Letter , the progenitor of Science News . Then as now, the magazine’s readers feasted on a smorgasbord of delicious tidbits from a menu encompassing all flavors of science — from the atom to outer space, from agriculture to oceanography, from transportation to, of course, food and nutrition.

In those early days, much of the new enterprise’s coverage focused on space, such as the possibility of planets beyond Neptune. Experts shared their views on whether spiral-shaped clouds in deep space were far-off entire galaxies of stars , like the Milky Way, or embryonic solar systems just now forming within the Milky Way. Articles explored the latest speculation about life on Venus ( here and here ) or on Mars .

Regular coverage was also devoted to new technologies — particularly radio. One Science Service dispatch informed readers on how to make their own home radio set — for $6 . And in 1922 Science News-Letter reported on an astounding radio breakthrough: a set that could operate without a battery . You could just plug it in to an electrical outlet.

To celebrate our upcoming 100th anniversary, we’ve launched a series that highlights some of the biggest advances in science over the last century. Visit our Century of Science site to see the series as it unfolds.

Much of the century’s scientific future was presaged in those early reports. In May 1921, an article on recent subatomic experiments noted the “dream of scientist and novelist alike that man would one day learn how … to utilize the vast stores of energy inside of atoms .” In 1922 Science Service editor Edwin Slosson speculated that the “smallest unit of positive electricity” (the proton) might “be a complex of many positive and negative particles ,” a dim but prescient preview of the existence of quarks.

True, some prognostications did not age so well. A 1921 prediction that the United States would be forced to adopt the metric system for commercial transactions is still awaiting fulfillment. A simple, common, international auxiliary language — “confidently predicted” in 1921 to become “a part of every educated person’s equipment” — remains unestablished today. And despite serious considerations of calendar reform by astronomers and church dignitaries reported in May 1922, well over 1,000 of the same old months have since passed without the slightest alteration.

On the other hand, “the favorite fruit of Americans of the generations to follow us will be the avocado,” as predicted in 1921, is possibly arguable, though there was no mention of toast — just the suggestion that “a few crackers and an avocado sprinkled with a little salt make a hearty and well-balanced lunch.”

One happily false prognostication was the repeated forecast of the rise of eugenics as a “scientific” endeavor.

“The organization of an artificial selection is only a question of time. It will be possible to renew as a whole, in a few centuries, all humanity, and to replace the mass by another much superior mass,” a “distinguished authority on anthropo-sociology” declared in a Science Service news item from 1921 . Another eugenicist proclaimed that “Eugenic Science” should be applied to “shed the light of reason on the primeval instinct of reproduction,” so that “disgenic marriages” would be banned just as bigamy and incest are.

In the century since, thanks to saner and more sophisticated knowledge of genetics (and more social enlightenment in general), eugenics has been disavowed by science and is now revived in spirit only by the ignorant or malevolent. And during that time, real science has progressed to an elevated degree of sophistication in many other ways, to an extent almost unimaginable to the scientists and journalists of the 1920s.

It turns out that the past century’s groundbreaking experimental discoveries, revolutionary theoretical revelations and prescient speculations have not eliminated science’s familiarity with false starts, unfortunate missteps and shortsighted prejudices.

When Science Service (now Society for Science) launched its mission, astronomers were unaware of the extent of the universe. No biologist knew what DNA did, or how brain chemistry regulated behavior. Geologists saw that Earth’s continents looked like separated puzzle pieces, but declared that to be a coincidence.

Modern scientists know better. Scientists now understand a lot more about the details of the atom’s interior, the molecules of life, the intricacies of the brain , the innards of the Earth and the expanse of the cosmos .

Yet somehow scientists still pursue the same questions, if now on higher levels of theoretical abstraction rooted in deeper layers of empirical evidence. We know how the molecules of life work, but not always how they react to novel diseases. We know how the brain works, except for those afflicted by dementia or depression (or when consciousness is part of the question). We know a lot about how the Earth works, but not enough to always foresee how it will respond to what humans are doing to it. We think we know a lot about the universe, but we’re not sure if ours is the only one, and we can’t explain how gravity, the dominant force across the cosmos, can coexist with the forces governing atoms.

It turns out that the past century’s groundbreaking experimental discoveries, revolutionary theoretical revelations and prescient speculations have not eliminated science’s familiarity with false starts, unfortunate missteps and shortsighted prejudices. Researchers today have expanded the scope of the reality they can explore, yet still stumble through the remaining uncharted jungles of nature’s facts and laws, seeking further clues to how the world works.

To paraphrase an old philosophy joke, science is more like it is today than it ever has been. In other words, science remains as challenging as ever to human inquiry. And the need to communicate its progress, perceived by Scripps and Ritter a century ago, remains as essential now as then.

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October 1, 1994

17 min read

The Evolution of the Universe

Some 15 billion years ago the universe emerged from a hot, dense sea of matter and energy. As the cosmos expanded and cooled, it spawned galaxies, stars, planets and life

By P. James E. Peebles , David N. Schramm , Edwin L. Turner & Richard G. Kron

GALAXY CLUSTER is representative of what the universe looked like when it was 60 percent of its present age. The Hubble Space Telescope captured the image by focusing on the cluster as it completed 10 orbits. This image is one of the longest and clearest exposures ever produced. Several pairs of galaxies appear to be caught in one another’s gravitational field. Such interactions are rarely found in nearby clusters and are evidence that the universe is evolving.

Editor’s Note (10/8/19): Cosmologist James Peebles won a 2019 Nobel Prize in Physics for his contributions to theories of how our universe began and evolved. He describes these ideas in this article, which he co-wrote for  Scientific American  in 1994.

At a particular instant roughly 15 billion years ago, all the matter and energy we can observe, concentrated in a region smaller than a dime, began to expand and cool at an incredibly rapid rate. By the time the temperature had dropped to 100 million times that of the sun’s core, the forces of nature assumed their present properties, and the elementary particles known as quarks roamed freely in a sea of energy. When the universe had expanded an additional 1,000 times, all the matter we can measure filled a region the size of the solar system.

At that time, the free quarks became confined in neutrons and protons. After the universe had grown by another factor of 1,000, protons and neutrons combined to form atomic nuclei, including most of the helium and deuterium present today. All of this occurred within the first minute of the expansion. Conditions were still too hot, however, for atomic nuclei to capture electrons. Neutral atoms appeared in abundance only after the expansion had continued for 300,000 years and the universe was 1,000 times smaller than it is now. The neutral atoms then began to coalesce into gas clouds, which later evolved into stars. By the time the universe had expanded to one fifth its present size, the stars had formed groups recognizable as young galaxies.

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When the universe was half its present size, nuclear reactions in stars had produced most of the heavy elements from which terrestrial planets were made. Our solar system is relatively young: it formed five billion years ago, when the universe was two thirds its present size. Over time the formation of stars has consumed the supply of gas in galaxies, and hence the population of stars is waning. Fifteen billion years from now stars like our sun will be relatively rare, making the universe a far less hospitable place for observers like us.

Our understanding of the genesis and evolution of the universe is one of the great achievements of 20th-century science. This knowledge comes from decades of innovative experiments and theories. Modern telescopes on the ground and in space detect the light from galaxies billions of light-years away, showing us what the universe looked like when it was young. Particle accelerators probe the basic physics of the high-energy environment of the early universe. Satellites detect the cosmic background radiation left over from the early stages of expansion, providing an image of the universe on the largest scales we can observe.

Our best efforts to explain this wealth of data are embodied in a theory known as the standard cosmological model or the big bang cosmology. The major claim of the theory is that in the largescale average the universe is expanding in a nearly homogeneous way from a dense early state. At present, there are no fundamental challenges to the big bang theory, although there are certainly unresolved issues within the theory itself. Astronomers are not sure, for example, how the galaxies were formed, but there is no reason to think the process did not occur within the framework of the big bang. Indeed, the predictions of the theory have survived all tests to date.

Yet the big bang model goes only so far, and many fundamental mysteries remain. What was the universe like before it was expanding? (No observation we have made allows us to look back beyond the moment at which the expansion began.) What will happen in the distant future, when the last of the stars exhaust the supply of nuclear fuel? No one knows the answers yet.

Our universe may be viewed in many lights—by mystics, theologians, philosophers or scientists. In science we adopt the plodding route: we accept only what is tested by experiment or observation. Albert Einstein gave us the now well-tested and accepted Theory of General Relativity, which establishes the relations between mass, energy, space and time. Einstein showed that a homogeneous distribution of matter in space fits nicely with his theory. He assumed without discussion that the universe is static, unchanging in the large-scale average [see “How Cosmology Became a Science,” by Stephen G. Brush; SCIENTIFIC AMERICAN, August 1992].

In 1922 the Russian theorist Alexander A. Friedmann realized that Einstein’s universe is unstable; the slightest perturbation would cause it to expand or contract. At that time, Vesto M. Slipher of Lowell Observatory was collecting the first evidence that galaxies are actually moving apart. Then, in 1929, the eminent astronomer Edwin P. Hubble showed that the rate a galaxy is moving away from us is roughly proportional to its distance from us.

MULTIPLE IMAGES of a distant quasar ( left ) are the result of an effect known as gravitational lensing. The effect occurs when light from a distant object is bent by the gravitational field of an intervening galaxy. In this case, the galaxy, which is visible in the center, produces four images of the quasar. The photograph was produced using the Hubble telescope.

The existence of an expanding universe implies that the cosmos has evolved from a dense concentration of matter into the present broadly spread distribution of galaxies. Fred Hoyle, an English cosmologist, was the first to call this process the big bang. Hoyle intended to disparage the theory, but the name was so catchy it gained popularity. It is somewhat misleading, however, to describe the expansion as some type of explosion of matter away from some particular point in space.

That is not the picture at all: in Einstein’s universe the concept of space and the distribution of matter are intimately linked; the observed expansion of the system of galaxies reveals the unfolding of space itself. An essential feature of the theory is that the average density in space declines as the universe expands; the distribution of matter forms no observable edge. In an explosion the fastest particles move out into empty space, but in the big bang cosmology, particles uniformly fill all space. The expansion of the universe has had little influence on the size of galaxies or even clusters of galaxies that are bound by gravity; space is simply opening up between them. In this sense, the expansion is similar to a rising loaf of raisin bread. The dough is analogous to space, and the raisins, to clusters of galaxies. As the dough expands, the raisins move apart. Moreover, the speed with which any two raisins move apart is directly and positively related to the amount of dough separating them.

The evidence for the expansion of the universe has been accumulating for some 60 years. The first important clue is the redshift. A galaxy emits or absorbs some wavelengths of light more strongly than others. If the galaxy is moving away from us, these emission and absorption features are shifted to longer wavelengths—that is, they become redder as the recession velocity increases. This phenomenon is known as the redshift.

Hubble’s measurements indicated that the redshift of a distant galaxy is greater than that of one closer to the earth. This relation, now known as Hubble’s law, is just what one would expect in a uniformly expanding universe. Hubble’s law says the recession velocity of a galaxy is equal to its distance multiplied by a quantity called Hubble’s constant. The redshift effect in nearby galaxies is relatively subtle, requiring good instrumentation to detect it. In contrast, the redshift of very distant objects—radio galaxies and quasars—is an awesome phenomenon; some appear to be moving away at greater than 90 percent of the speed of light.

Hubble contributed to another crucial part of the picture. He counted the number of visible galaxies in different directions in the sky and found that they appear to be rather uniformly distributed. The value of Hubble’s constant seemed to be the same in all directions, a necessary consequence of uniform expansion. Modern surveys confirm the fundamental tenet that the universe is homogeneous on large scales. Although maps of the distribution of the nearby galaxies display clumpiness, deeper surveys reveal considerable uniformity.

The Milky Way, for instance, resides in a knot of two dozen galaxies; these in turn are part of a complex of galaxies that protrudes from the so-called local supercluster. The hierarchy of clustering has been traced up to dimensions of about 500 million light-years. The fluctuations in the average density of matter diminish as the scale of the structure being investigated increases. In maps that cover distances that reach close to the observable limit, the average density of matter changes by less than a tenth of a percent.

To test Hubble’s law, astronomers need to measure distances to galaxies. One method for gauging distance is to observe the apparent brightness of a galaxy. If one galaxy is four times fainter in the night sky than an otherwise comparable galaxy, then it can be estimated to be twice as far away. This expectation has now been tested over the whole of the visible range of distances.

HOMOGENEOUS DISTRIBUTION of galaxies is apparent in a map that includes objects from 300 to 1,000 million light-years away. The only inhomogeneity, a gap near the center line, occurs because part of the sky is obscured by the Milky Way. Michael Strauss of the Institute for Advanced Study in Princeton, N.J., created the map using data from NASA’s Infrared Astronomical Satellite .

Some critics of the theory have pointed out that a galaxy that appears to be smaller and fainter might not actually be more distant. Fortunately, there is a direct indication that objects whose redshifts are larger really are more distant. The evidence comes from observations of an effect known as gravitational lensing. An object as massive and compact as a galaxy can act as a crude lens, producing a distorted, magnified image (or even many images) of any background radiation source that lies behind it. Such an object does so by bending the paths of light rays and other electromagnetic radiation. So if a galaxy sits in the line of sight between the earth and some distant object, it will bend the light rays from the object so that they are observable [see “Gravitational Lenses,” by Edwin L. Turner; SCIENTIFIC AMERICAN, July 1988]. During the past decade, astronomers have discovered more than a dozen gravitational lenses. The object behind the lens is always found to have a higher redshift than the lens itself, confirming the qualitative prediction of Hubble’s law.

Hubble’s law has great significance not only because it describes the expansion of the universe but also because it can be used to calculate the age of the cosmos. To be precise, the time elapsed since the big bang is a function of the present value of Hubble’s constant and its rate of change. Astronomers have determined the approximate rate of the expansion, but no one has yet been able to measure the second value precisely.

Still, one can estimate this quantity from knowledge of the universe’s average density. One expects that because gravity exerts a force that opposes expansion, galaxies would tend to move apart more slowly now than they did in the past. The rate of change in expansion is therefore related to the gravitational pull of the universe set by its average density. If the density is that of just the visible material in and around galaxies, the age of the universe probably lies between 12 and 20 billion years. (The range allows for the uncertainty in the rate of expansion.)

Yet many researchers believe the density is greater than this minimum value. So-called dark matter would make up the difference. A strongly defended argument holds that the universe is just dense enough that in the remote future the expansion will slow almost to zero. Under this assumption, the age of the universe decreases to the range of seven to 13 billion years.

DENSITY of neutrons and protons in the universe determined the abundances of certain elements. For a higher density universe, the computed helium abundance is little different, and the computed abundance of deuterium is considerably lower. The shaded region is consistent with the observations, ranging from an abundance of 24 percent for helium to one part in 1010 for the lithium isotope. This quantitative agreement is a prime success of the big bang cosmology.

To improve these estimates, many astronomers are involved in intensive research to measure both the distances to galaxies and the density of the universe. Estimates of the expansion time provide an important test for the big bang model of the universe. If the theory is correct, everything in the visible universe should be younger than the expansion time computed from Hubble’s law.

These two timescales do appear to be in at least rough concordance. For example, the oldest stars in the disk of the Milky Way galaxy are about nine billion years old—an estimate derived from the rate of cooling of white dwarf stars. The stars in the halo of the Milky Way are somewhat older, about 15 billion years—a value derived from the rate of nuclear fuel consumption in the cores of these stars. The ages of the oldest known chemical elements are also approximately 15 billion years—a number that comes from radioactive dating techniques. Workers in laboratories have derived these age estimates from atomic and nuclear physics. It is noteworthy that their results agree, at least approximately, with the age that astronomers have derived by measuring cosmic expansion.

Another theory, the steady state theory, also succeeds in accounting for the expansion and homogeneity of the universe. In 1946 three physicists in England—Hoyle, Hermann Bondi and Thomas Gold—proposed such a cosmology. In their theory the universe is forever expanding, and matter is created spontaneously to fill the voids. As this material accumulates, they suggested, it forms new stars to replace the old. This steady state hypothesis predicts that ensembles of galaxies close to us should look statistically the same as those far away. The big bang cosmology makes a different prediction: if galaxies were all formed long ago, distant galaxies should look younger than those nearby because light from them requires a longer time to reach us. Such galaxies should contain more shortlived stars and more gas out of which future generations of stars will form.

The test is simple conceptually, but it took decades for astronomers to develop detectors sensitive enough to study distant galaxies in detail. When astronomers examine nearby galaxies that are powerful emitters of radio wavelengths, they see, at optical wavelengths, relatively round systems of stars. Distant radio galaxies, on the other hand, appear to have elongated and sometimes irregular structures. Moreover, in most distant radio galaxies, unlike the ones nearby, the distribution of light tends to be aligned with the pattern of the radio emission.

Likewise, when astronomers study the population of massive, dense clusters of galaxies, they find differences between those that are close and those far away. Distant clusters contain bluish galaxies that show evidence of ongoing star formation. Similar clusters that are nearby contain reddish galaxies in which active star formation ceased long ago. Observations made with the Hubble Space Telescope confirm that at least some of the enhanced star formation in these younger clusters may be the result of collisions between their member galaxies, a process that is much rarer in the present epoch.

DISTANT GALAXIES differ greatly from those nearby—an observation that shows that galaxies evolved from earlier, more irregular forms. Among galaxies that are bright at both optical ( blue ) and radio ( red ) wavelengths, the nearby galaxies tend to have smooth elliptical shapes at optical wavelengths and very elongated radio images. As redshift, and therefore distance, increases, galaxies have more irregular elongated forms that appear aligned at optical and radio wavelengths. The galaxy at the far right is seen as it was at 10 percent of the present age of the universe. The images were assembled by Pat McCarthy of the Carnegie Institute.

So if galaxies are all moving away from one another and are evolving from earlier forms, it seems logical that they were once crowded together in some dense sea of matter and energy. Indeed, in 1927, before much was known about distant galaxies, a Belgian cosmologist and priest, Georges Lemaître, proposed that the expansion of the universe might be traced to an exceedingly dense state he called the primeval “super-atom.” It might even be possible, he thought, to detect remnant radiation from the primeval atom. But what would this radiation signature look like?

When the universe was very young and hot, radiation could not travel very far without being absorbed and emitted by some particle. This continuous exchange of energy maintained a state of thermal equilibrium; any particular region was unlikely to be much hotter or cooler than the average. When matter and energy settle to such a state, the result is a so-called thermal spectrum, where the intensity of radiation at each wavelength is a definite function of the temperature. Hence, radiation originating in the hot big bang is recognizable by its spectrum.

In fact, this thermal cosmic background radiation has been detected. While working on the development of radar in the 1940s, Robert H. Dicke, then at the Massachusetts Institute of Technology, invented the microwave radiometer—a device capable of detecting low levels of radiation. In the 1960s Bell Laboratories used a radiometer in a telescope that would track the early communications satellites Echo-1 and Telstar. The engineer who built this instrument found that it was detecting unexpected radiation. Arno A. Penzias and Robert W. Wilson identified the signal as the cosmic background radiation. It is interesting that Penzias and Wilson were led to this idea by the news that Dicke had suggested that one ought to use a radiometer to search for the cosmic background.

Astronomers have studied this radiation in great detail using the Cosmic Background Explorer (COBE) satellite and a number of rocket-launched, balloon-borne and ground-based experiments. The cosmic background radiation has two distinctive properties. First, it is nearly the same in all directions. (As George F. Smoot of Lawrence Berkeley Laboratory and his team discovered in 1992, the variation is just one part per 100,000.) The interpretation is that the radiation uniformly fills space, as predicted in the big bang cosmology. Second, the spectrum is very close to that of an object in thermal equilibrium at 2.726 kelvins above absolute zero. To be sure, the cosmic background radiation was produced when the universe was far hotter than 2.726 degrees, yet researchers anticipated correctly that the apparent temperature of the radiation would be low. In the 1930s Richard C. Tolman of the California Institute of Technology showed that the temperature of the cosmic background would diminish because of the universe’s expansion.

The cosmic background radiation provides direct evidence that the universe did expand from a dense, hot state, for this is the condition needed to produce the radiation. In the dense, hot early universe thermonuclear reactions produced elements heavier than hydrogen, including deuterium, helium and lithium. It is striking that the computed mix of the light elements agrees with the observed abundances. That is, all evidence indicates that the light elements were produced in the hot, young universe, whereas the heavier elements appeared later, as products of the thermonuclear reactions that power stars.

The theory for the origin of the light elements emerged from the burst of research that followed the end of World War II. George Gamow and graduate student Ralph A. Alpher of George Washington University and Robert Herman of the Johns Hopkins University Applied Physics Laboratory and others used nuclear physics data from the war e›ort to predict what kind of nuclear processes might have occurred in the early universe and what elements might have been produced. Alpher and Herman also realized that a remnant of the original expansion would still be detectable in the existing universe.

Despite the fact that significant details of this pioneering work were in error, it forged a link between nuclear physics and cosmology. The workers demonstrated that the early universe could be viewed as a type of thermonuclear reactor. As a result, physicists have now precisely calculated the abundances of light elements produced in the big bang and how those quantities have changed because of subsequent events in the interstellar medium and nuclear processes in stars.

Our grasp of the conditions that prevailed in the early universe does not translate into a full understanding of how galaxies formed. Nevertheless, we do have quite a few pieces of the puzzle. Gravity causes the growth of density fluctuations in the distribution of matter, because it more strongly slows the expansion of denser regions, making them grow still denser. This process is observed in the growth of nearby clusters of galaxies, and the galaxies themselves were probably assembled by the same process on a smaller scale.

The growth of structure in the early universe was prevented by radiation pressure, but that changed when the universe had expanded to about 0.1 percent of its present size. At that point, the temperature was about 3,000 kelvins, cool enough to allow the ions and electrons to combine to form neutral hydrogen and helium. The neutral matter was able to slip through the radiation and to form gas clouds that could collapse to star clusters. Observations show that by the time the universe was one fifth its present size, matter had gathered into gas clouds large enough to be called young galaxies.

A pressing challenge now is to reconcile the apparent uniformity of the early universe with the lumpy distribution of galaxies in the present universe. Astronomers know that the density of the early universe did not vary by much, because they observe only slight irregularities in the cosmic background radiation. So far it has been easy to develop theories that are consistent with the available measurements, but more critical tests are in progress. In particular, different theories for galaxy formation predict quite different fluctuations in the cosmic background radiation on angular scales less than about one degree. Measurements of such tiny fluctuations have not yet been done, but they might be accomplished in the generation of experiments now under way. It will be exciting to learn whether any of the theories of galaxy formation now under consideration survive these tests.

The present-day universe has provided ample opportunity for the development of life as we know it—there are some 100 billion billion stars similar to the sun in the part of the universe we can observe. The big bang cosmology implies, however, that life is possible only for a bounded span of time: the universe was too hot in the distant past, and it has limited resources for the future. Most galaxies are still producing new stars, but many others have already exhausted their supply of gas. Thirty billion years from now, galaxies will be much darker and filled with dead or dying stars, so there will be far fewer planets capable of supporting life as it now exists.

The universe may expand forever, in which case all the galaxies and stars will eventually grow dark and cold. The alternative to this big chill is a big crunch. If the mass of the universe is large enough, gravity will eventually reverse the expansion, and all matter and energy will be reunited. During the next decade, as researchers improve techniques for measuring the mass of the universe, we may learn whether the present expansion is headed toward a big chill or a big crunch.

In the near future, we expect new experiments to provide a better understanding of the big bang. As we improve measurements of the expansion rate and the ages of stars, we may be able to confirm that the stars are indeed younger than the expanding universe. The larger telescopes recently completed or under construction may allow us to see how the mass of the universe affects the curvature of spacetime, which in turn influences our observations of distant galaxies.

We will also continue to study issues that the big bang cosmology does not address. We do not know why there was a big bang or what may have existed before. We do not know whether our universe has siblings—other expanding regions well removed from what we can observe. We do not understand why the fundamental constants of nature have the values they do. Advances in particle physics suggest some interesting ways these questions might be answered; the challenge is to find experimental tests of the ideas.

In following the debate on such matters of cosmology, one should bear in mind that all physical theories are approximations of reality that can fail if pushed too far. Physical science advances by incorporating earlier theories that are experimentally supported into larger, more encompassing frameworks. The big bang theory is supported by a wealth of evidence: it explains the cosmic background radiation, the abundances of light elements and the Hubble expansion. Thus, any new cosmology surely will include the big bang picture. Whatever developments the coming decades may bring, cosmology has moved from a branch of philosophy to a physical science where hypotheses meet the test of observation and experiment.

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Regions & Countries

Key findings about americans’ confidence in science and their views on scientists’ role in society.

Science issues – whether connected with climate, childhood vaccines or new techniques in biotechnology – are part of the fabric of civic life, raising a range of social, ethical and policy issues for the citizenry. As members of the scientific community gather at the annual meeting of the American Association for the Advancement of Science (AAAS) this week, here is a roundup of key takeaways from our studies of U.S. public opinion about science issues and their effect on society. If you’re on Twitter, follow @pewscience for more science findings.

The data for this post was drawn from multiple different surveys. The most recent was a survey of 3,627 U.S. adults conducted Oct. 1 to Oct. 13, 2019. This post also draws on data from surveys conducted in January 2019, December 2018, April-May 2018 and March 2016. All surveys were conducted using the American Trends Panel (ATP), an online survey panel that is recruited through national, random sampling of residential addresses. This way nearly all U.S. adults have a chance of being selected. The survey is weighted to be representative of the U.S. adult population by gender, race, ethnicity, education and other categories. Read more about the ATP’s methodology .

Following are the questions and responses for surveys used in this post, as well as each survey’s methodology:

• October 2019 survey: Questions | Methodology
• January 2019 survey: Questions | Methodology
• December 2018 survey: Questions | Methodology
• April-May 2018 survey: Questions | Methodology
• March 2016 survey: Questions | Methodology

1 Some public divides over science issues are aligned with partisanship, while many others are not. Science issues can be a key battleground for facts and information in society. Climate science has been part of an ongoing discourse around scientific evidence, how to attribute average temperature increases in the Earth’s climate system, and the kinds of policy actions needed. While public divides over climate and energy issues are often aligned with political party affiliation, public attitudes on other science-related issues are not.

For example, there are differences in public beliefs around the risks and benefits of childhood vaccines. Such differences arise amid civic debates about the spread of false information about vaccines. While such beliefs have important implications for public health, they are not particularly political in nature.

In fact, Republicans and independents who lean to the GOP are just as likely as Democrats and independents who lean to the Democratic Party to say that, overall, the benefits of the measles, mumps and rubella vaccine outweigh the risks (89% and 88% respectively).

2 Americans have differing views about some emerging scientific and technological developments. Scientific and technological developments are a key source of innovation and, therefore, change in society. Pew Research Center studies have explored public reactions to emergent developments from genetic engineering techniques, automation and more. One field at the forefront of public reaction is the use of gene editing of babies or genetic engineering of animals. Americans have mixed views over whether the use of gene editing to reduce a baby’s risk of serious disease that could occur over their lifetime is appropriate (60%) or is taking medical technology too far (38%), according to a 2018 survey . Similarly, about six-in-ten Americans (57%) said that genetic engineering of animals to grow organs or tissues for humans needing a transplant would be appropriate, while four-in-ten (41%) said it would be taking technology too far.

When we asked Americans about a future where a brain chip implant would give otherwise healthy individuals much improved cognitive abilities, a 69% majority said they were very or somewhat worried about the possibility. By contrast, about half as many (34%) were enthusiastic. Further, as people think about the effects of automation technologies in the workplace, more say automation has brought more harm than help to American workers.

One theme running through our findings on emerging science and technology is that public hesitancy often is tied to concern about the loss of human control, especially if such developments would be at odds with personal, religious and ethical values. In looking across seven developments related to automation and the potential use of biomedical interventions to “enhance” human abilities, Center studies found that proposals that would increase peoples’ control over these technologies were met with greater acceptance.

3 Most in the U.S. see net benefits from science for society, and they expect more ahead. About three-quarters of Americans (73%) say science has, on balance, had a mostly positive effect on society. And 82% expect future scientific developments to yield benefits for society in years to come.

The overall portrait is one of strong public support for the benefits of science to society, though the degree to which Americans embrace this idea differs sizably by race and ethnicity as well as by levels of science knowledge.

Such findings are in line with those of the General Social Survey on the effects of scientific research. In 2018, about three-quarters of Americans (74%) said the benefits of scientific research outweigh any harmful results. Support for scientific research by this measure has been roughly stable since the 1980s.

4 The share of Americans with confidence in scientists to act in the public interest has increased since 2016. Public confidence in scientists to act in the public interest tilts positive and has increased over the past few years. As of 2019, 35% of Americans report a great deal of confidence in scientists to act in the public interest, up from 21% in 2016.

About half of the public (51%) reports a “fair amount” of confidence in scientists, and just 13% have not too much or no confidence in this group to act in the public interest.

Public trust in scientists by this measure stands in contrast to that for other groups and institutions. One of the hallmarks of the current times has been low trust in government and other institutions. One-in-ten or fewer say they have a great deal of confidence in elected officials (4%) or the news media (9%) to act in the public interest.

5 Americans differ over the role and value of scientific experts in policy matters. While confidence in scientists overall tilts positive, people’s perspectives about the role and value of scientific experts on policy issues tends to vary. Six-in-ten U.S. adults believe that scientists should take an active role in policy debates about scientific issues, while about four-in-ten (39%) say, instead, that scientists should focus on establishing sound scientific facts and stay out of such debates.

Democrats are more inclined than Republicans to think scientists should have an active role in science policy matters. Indeed, most Democrats and Democratic-leaning independents (73%) hold this position, compared with 43% of Republicans and GOP leaners.

More than four-in-ten U.S. adults (45%) say that scientific experts usually make better policy decisions than other people, while a similar share (48%) says such decisions are neither better nor worse than other people’s and 7% say scientific experts’ decisions are usually worse than other people’s.

Here, too, Democrats tend to hold scientific experts in higher esteem than do Republicans: 54% of Democrats say scientists’ policy decisions are usually better than those of other people, while two-thirds of Republicans (66%) say that scientists’ decisions are either no different from or worse than other people’s.

6 Factual knowledge alone does not explain public confidence in the scientific method to produce sound conclusions. Overall, a 63% majority of Americans say the scientific method generally produces sound conclusions, while 35% think it can be used to produce “any result a researcher wants.” People’s level of knowledge can influence beliefs about these matters, but it does so through the lens of partisanship, a tendency known as motivated reasoning.

Beliefs about this matter illustrate that science knowledge levels sometimes correlate with public attitudes. But partisanship has a stronger role.

Democrats are more likely to express confidence in the scientific method to produce accurate conclusions than do Republicans, on average. Most Democrats with high levels of science knowledge (86%, based on an 11-item index of factual knowledge questions) say the scientific method generally produces accurate conclusions. By comparison, 52% of Democrats with low science knowledge say this. But science knowledge has little bearing on Republicans’ beliefs about the scientific method.

7 Trust in practitioners like medical doctors and dietitians is stronger than that for researchers in these fields, but skepticism about scientific integrity is widespread. Scientists work in a wide array of fields and specialties. A 2019 Pew Research Center survey found public trust in medical doctors and dietitians to be higher than that for researchers working in these areas. For example, 48% of U.S. adults say that medical doctors give fair and accurate information all or most of the time. By comparison, 32% of U.S. adults say the same about medical research scientists. And six-in-ten Americans say dietitians care about their patients’ best interests all or most of the time, while about half as many (29%) say this about nutrition research scientists with the same frequency.

One factor in public trust of scientists is familiarity with their work. For example, people who were more familiar with what medical science researchers do were more trusting of these researchers to express care or concern for the public interest, to do their job with competence and to provide fair and accurate information. Familiarity with the work of scientists was related to trust for all six specialties we studied.

But when it comes to questions of scientists’ transparency and accountability, most Americans are skeptical. About two-in-ten or fewer U.S. adults say that scientists are transparent about potential conflicts of interest with industry groups all or most of the time. Similar shares (roughly between one-in-ten and two-in-ten) say that scientists admit their mistakes and take responsibility for them all or most of the time.

This data shows clearly that when it comes to questions of transparency and accountability, most in the general public are attuned to the potential for self-serving interests to skew science findings and recommendations. These findings echo calls for increased transparency and accountability across many sectors and industries today.

8 What boosts public trust in scientific research findings? Most say it’s making data openly available. A 57% majority of Americans say they trust scientific research findings more when the data is openly available to the public. And about half of the U.S. public (52%) say they are more likely to trust research that has been independently reviewed.

The question of who funds the research is also consequential for how people think about scientific research. A 58% majority say they have lower trust when research is funded by an industry group. By comparison, about half of Americans (48%) say government funding for research has no particular effect on how much they trust the findings; 28% say this decreases their trust and 23% say it increases their trust.

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• Published: 29 July 2021

The evolution of our understanding of human development over the last 10 years

• Ali H. Brivanlou   ORCID: orcid.org/0000-0002-1761-280X 1 &
• Norbert Gleicher   ORCID: orcid.org/0000-0002-0202-4167 2 , 3 , 4  

Nature Communications volume  12 , Article number:  4615 ( 2021 ) Cite this article

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• Developmental biology
• Embryogenesis

As it fulfills an irresistible need to understand our own origins, research on human development occupies a unique niche in scientific and medical research. In this Comment, we explore the progress in our understanding of human development over the past 10 years. The focus is on basic research, clinical applications, and ethical considerations.

What basic research has taught us about human development

Over the last decade, progress in understanding our own development was mostly driven by the emergence and combination of remarkable new technologies. New molecular biology tools such as single-cell RNA-sequencing (sc-RNA-seq) unveiled the earliest genetic signature of the three cell lineages of the human blastocyst and allowed for the discovery of human-specific signatures 1 , 2 , 3 . CRISPR/Cas9 genome editing has offered further access to in vitro functional studies in human blastocysts 4 . However, as we discuss below, an ethical line was crossed when a group claimed that genetically modified human embryos had been transferred, leading to births 5 when neither public opinion nor a consensus within the scientific community had been reached regarding whether crossing the germline in in vitro fertilization (IVF) was safe and ethically acceptable.

On the embryology side, the development of an in vitro attachment platform for human blastocysts offered a first glance into post-implantation events up to 12 days 1 , 3 , 5 , 6 . This paved the way for several important discoveries, including the observation that the human embryo can self-organize to generate embryonic and extraembryonic germ layers, yolk sac, and amniotic cavities in the absence of maternal influences 5 , 6 ; and the presence of a transient embryonic tissue of trophectodermal lineage, adjacent to the yolk sac, therefore named, yolk-sac trophectoderm ( ysTE ) 5 . The presence of these seemingly human-specific populations was independently confirmed by sc-RNA-seq 1 .

The marriage of stem cell biology with bioengineering gave birth to the field of synthetic embryology 7 , 8 , 9 , 10 , 11 , 12 , 13 . This technology uses human embryonic stem cells (hESCs) cultured on geometrically confined micropatterned substrates to generate 2D in vitro models of human conceptuses, such as models of the gastrula ( gastruloids ) 7 , 8 , 9 , 10 , 11 , 12 , 13 , or parts of the embryo, such as cerebroids and neuruloids 14 . Thousands of nearly identical self-organizing human embryonic structures allow for standardization and reproducibility, which cannot be achieved in standard organoid structures 15 . Cells within these structures can be tracked and quantified in real time with sub-cellular resolution, using sophisticated quantification code, including artificial intelligence 14 .

Human gastruloids induce formation of the primitive streak and have enabled the deciphering of the molecular network underlying gastrulation—the most crucial moment of our lives 7 , 8 , 9 , 10 , 11 , 12 , 13 . 3D models of human epiblasts can spontaneously break axial symmetry, thus providing an assay for the elucidation of molecular events underlying the emergence of antero–posterior polarity 11 , 16 . A highly homogenous population of self-organizing 3D models of amniotic ectoderm-like cells can be obtained by combining microfluidic and microculture approaches 17 .

Finally, the development of interspecies chimeras provided the most stringent in vivo validation of human embryo models 9 , 10 , 18 . Unimaginable in human models, inter-species chimeras have become the next best choice to test whether hESC behavior in self-organizing gastruloids , as observed on microchips, would also occur in an embryonic environment 10 , 18 , 19 . Human/bird chimeras generated from transplanting human gastruloids into early chick embryos in ovo unexpectedly proved more efficient than previous methods 9 , 19 . They allowed for the observation of an entire self-organizing embryonic axis in bird eggs 9 . As birds are closer to dinosaurs than to humans, this high rate of success with these chimeras further suggested that these early patterning events must be highly conserved.

Translational clinical applications that arose from basic research

The past 10 years bore witness to significant clinical progress in reproductive medicine, often translated from basic research. Successful human uterus transplantation and the subsequent birth of healthy offspring was, for example, only achieved after years of meticulous laboratory work in animals 10 . Significant improvements in cryopreservation technology for human eggs and ovarian tissue were also preceded by research in model systems 10 , 20 . Practical clinical applications have been developed for women in need of cancer treatment that are toxic to ovaries. In these cases, oocytes and/or ovarian tissue can be cryopreserved for later use in fertility treatments once the patient is cured of her cancer 21 . This ever-evolving technology has already proven to result in live births, and has also become an integral part of routine infertility treatments with IVF, giving rise to the brand-new concept of fertility extension through egg-freezing.

Diagnostic technologies to assess retrieved eggs and preimplantation-stage embryos in the IVF process have been disappointing. For example, tracking extended embryo culture to blastocyst-stage with time-lapse imaging failed to improve embryo selection 22 . That chromosomal-abnormal embryos increase with maternal (but not paternal) age has been interpreted to mean that chromosomal abnormalities were a principal cause for lower implantation chances and higher miscarriage risks among older women. This assumption led to the rapidly growing utilization of chromosomal testing of human embryos prior to embryo transfer in a procedure recently renamed preimplantation genetic testing for aneuploidy (PGT-A) 23 . The hypothesis behind PGT-A is to exclude chromosomal-abnormal embryos from the transfer, thereby improving implantation potentials of remaining euploid embryos.

Here too, clinical evidence was unable to confirm the hypothesis 24 . Moreover, basic research demonstrated a self-correction mechanism in mouse 25 and human embryos 26 , 27 , 28 , 29 that arose during embryogenesis that was cell lineage-specific to the embryonic cell lineage. In contrast, PGT-A biopsies are obtained from the extraembryonic-derived trophectoderm, rendering any diagnostic procedure at the blastocyst stage ineffective. In addition, mathematical modeling demonstrated that results from a single trophectoderm biopsy could not be extrapolated to the whole embryo 30 . Transfer of PGT-A “chromosomal-abnormal diagnosed embryos” has resulted in the births of over 400 chromosomal-normal offspring 20 , 21 .

In recent years, increasing attention has also been given to the quickly evolving understanding of how interdependent lifestyle and human fertility are 31 , 32 , 33 , including the influence of diet on the microbiome, as in many other areas of medicine.

The ethical significance of understanding human development

Whether in clinical medicine or in the research laboratory, human embryology has remained an ethical minefield, strongly influenced by socio-political and religious considerations. At the core of the controversy resides the special moral value of the human embryo, a subject that has come to the forefront again with the ascent of human embryonic stem cell research 34 . There is, however, little consensus as to how to answer a previously raised question: “ what is an embryo ?” 35 . The term pre-embryo, first introduced in 1986, was defined as the interval up to the appearance of the primitive streak, which marks biological individuation at ~14 days post-fertilization. This definition designated the period beyond 14 days as the time when a pre-embryo attains special moral status 36 , 37 . Paradoxically, the term pre-embryo has been replaced by the indiscriminate use of the term embryo, whether at preimplantation cleavage or blastocyst-stages or post-implantation before day 14. It was suggested that the distinction was important for ethical, moral, and biological relevance. The principal reason is simple: Until a pre-embryo becomes an embryo, there is no way of knowing whether implantation has taken place, whether a pregnancy is developing, whether there is a single pregnancy or twinning, or whether fertilization ended up in a benign (hydatidiform mole) or even in a malignant tumor (choriocarcinoma) 35 . Assigning advanced moral value to embryos at those early stages is, therefore, difficult to defend.

The past 10 years have witnessed innumerous ethical debates related to this subject, each with its own social, historical, and religious justifications, reflecting cultural diversities in human populations. Most are triggered by scientific breakthroughs. We summarize here the major ethical challenges preoccupying reproductive research and clinical practice.

We have already briefly referred to CRISPR/Cas9 genome editing. While the use of sc-RNA-seq to identify the molecular blueprint of human development has not elicited significant controversy, CRISPR/Cas9 genome editing of human embryos has been a topic of intense discussions and is currently permissible only in vitro 38 . An alleged attempt in China of implanting human genome-edited embryos into the uterus supposedly led to two births (one a twin birth). Though widely discussed in the media, neither attempt was published in the medical literature, and therefore cannot be verified 5 , 38 .

The ethical debates surrounding the 14-day rule, quiescent since the early IVF days, experienced a rebirth that was prompted by in vitro human embryo attachment studies and the emergence of synthetic human embryos. Within this context, we note that self-organizing embryo models are nothing more than cells in culture and are certainly not embryos. Regardless of scientific merits, in the U.S., the National Institutes of Health (NIH) currently prohibits the use of public funds for the study of synthetic embryos “for ethical reasons”. After being under an NIH moratorium for more than a year, research on chimeras is now, however, again permitted, though human/non-human primate chimeras remain prohibited.

These ongoing ethical debates mostly also mirror those surrounding the lack of U.S. federal funding for clinical IVF and related research, as well as hESCs-derived model embryos. In this context, the American Society for Reproductive Medicine (ASRM)’s Ethics in Embryo Research Task Force recently made an important statement: “ Scientific research using human embryos advances human health and provides vital insights into reproduction and disease ” 39 .

Provided certain guidelines and safeguards are followed, research with already existing embryos or embryos specifically produced for research should be ethically acceptable as a means of obtaining new knowledge that may benefit human health. ASRM also pointed out that scientists and society must understand which research questions necessitate the use of human embryos.

It is gratifying to acknowledge the history and vitality of ongoing debates, especially since they increasingly mimic decision-making processes in the medical field. These debates are meant to be based on cost-benefit and/or risk-benefit assessments. These debates will, unquestionably, continue and, indeed, considering that every intervention has consequences, must be decided based on careful considerations, including all relevant stakeholders and all parts of society.

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Acknowledgements

We like to thank Min Yang, Jean Marx Santel, Adam Souza, and Amir Brivanlou, for data gathering and critical reading of the manuscript, and constructive criticism.

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A.H.B. and N.G. are co-founders of OvaNova Inc. A.H.B. is a co-founder of Rumi Scientific Inc.

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Brivanlou, A.H., Gleicher, N. The evolution of our understanding of human development over the last 10 years. Nat Commun 12 , 4615 (2021). https://doi.org/10.1038/s41467-021-24793-3

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SCIENCE & ENGINEERING INDICATORS

Science and technology: public perceptions, awareness, and information sources.

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Public Perceptions of Science and Technology

Public opinion on S&T includes beliefs about the general promise and benefits of scientific research for society. In addition, how people think about S&T is likely influenced by the extent to which U.S. adults are aware of specific topics addressed by scientific research and popular conceptualization of those topics. Examples of specific topics investigated by researchers in recent years that could influence future public opinion include artificial intelligence (AI), robotics, and automation technology; neurotechnology; climate change; and water contamination. Popular beliefs about STEM education in the United States also are relevant to discussion of the future of S&T in this country.

General Perceptions of S&T

Americans’ support for S&T as a general enterprise has been consistently positive for at least four decades. Since the late 1970s, the General Social Survey (GSS)—a nationally representative survey of adults in the United States—has assessed Americans’ perceptions of S&T (Smith et al. 2012–18). From 1979 to 2018, the GSS found a clear majority of American adults agreed that the benefits of scientific research strongly or slightly outweigh the harmful results (see Indicators 2022 report “ Science and Technology: Public Perceptions, Awareness, and Information Sources ”). From 1992 to 2022, the GSS also found that most Americans surveyed believed that there would be more opportunities “for the next generation” because of S&T and that they supported federal funding for basic scientific research, even when they did not expect that research to produce immediate benefits ( Figure PPS-1 ). In 2022, 88% of U.S. adults agreed that scientific research that advances the frontiers of knowledge is necessary and deserves federal government support.

• For grouped bar charts, Tab to the first data element (bar/line data point) which will bring up a pop-up with the data details
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U.S. adults who agree that science makes our way of life change too fast, that science provides more opportunities for the next generation, and that the federal government should fund basic scientific research: Selected years, 1992–2022

This figure displays data for years when the question was proffered. Percentages may not add to 100% because of rounding. See Table SPPS-1 through Table SPPS-3 for standard errors. Responses are to the following: Science makes our way of life change too fast. Because of science and technology, there will be more opportunities for the next generation. Even if it brings no immediate benefits, scientific research that advances the frontiers of knowledge is necessary and should be supported by the federal government. Do you strongly agree, agree, disagree, or strongly disagree? This figure displays the percentage of respondents who "strongly agree" or "agree" with the aforementioned statements.

Data are sourced from multiple surveys that used either identical or similar survey items: National Center for Science and Engineering Statistics, Survey of Public Attitudes Toward and Understanding of Science and Technology (1992–2001); University of Michigan, Survey of Consumer Attitudes and Behavior (2004); NORC at the University of Chicago, General Social Survey (2006–22).

Science and Engineering Indicators

One exception to Americans’ tendency to support S&T has been the perception that science makes life change too fast. In the last decade, Americans have been almost evenly split about the view that science has such a downside ( Figure PPS-1 ). Since 2014, the GSS found that roughly half of respondents agreed or strongly agreed that “science makes our way of life change too fast,” moving up from an average of 41% from 1995 to 2012 to an average of 50% from 2014 to 2022.

Americans also have tended to report that they trust science, a stance similar to that of residents of the other countries that spend the most on S&T R&D compared with the rest of the world. According to the Wellcome Global Monitor 2020 survey (Gallup 2021a)—the world’s largest study on how people around the world think and feel about science and major health challenges—a majority of Americans surveyed (88%) reported that they trust science “some” or “a lot” ( Figure PPS-2 ). This widespread prevalence of trust was largely consistent with the views of citizens in other countries that, like the United States, have invested substantially in R&D. Overall, 94% of adults in the top 15 countries included in the Wellcome Global Monitor with the largest gross domestic expenditures on R&D as a percentage of 2019 gross domestic product (GDP) reported trusting science “some” or “a lot” ( Figure PPS-2 ). Indicators 2022 report “ Research and Development: U.S. Trends and International Comparisons ”). Iceland was ranked in the top 16 but was not included in the 2020 Wellcome Global Monitor survey, so results presented include 15 of the top 16 countries with the largest gross domestic expenditures on R&D as a percentage of GDP in 2019." data-bs-content="Results include countries with the top 16 gross domestic expenditures on R&D as a percentage of GDP in 2019 (see Indicators 2022 report “ Research and Development: U.S. Trends and International Comparisons ”). Iceland was ranked in the top 16 but was not included in the 2020 Wellcome Global Monitor survey, so results presented include 15 of the top 16 countries with the largest gross domestic expenditures on R&D as a percentage of GDP in 2019." data-endnote-uuid="b7f2d7ed-a854-42bf-bc2f-897eab41a3d7">​ Results include countries with the top 16 gross domestic expenditures on R&D as a percentage of GDP in 2019 (see Indicators 2022 report “ Research and Development: U.S. Trends and International Comparisons ”). Iceland was ranked in the top 16 but was not included in the 2020 Wellcome Global Monitor survey, so results presented include 15 of the top 16 countries with the largest gross domestic expenditures on R&D as a percentage of GDP in 2019.

Trust in science, by country: 2020

Percentages may not add to 100% because of rounding. See Table SPPS-4 for standard errors. Countries are those with top 16 gross domestic expenditures on R&D as a percentage of gross domestic product in 2019, listed in order from highest to lowest (see Indicators 2022 report "Research and Development: U.S. Trends and International Comparisons"). Gallup adjusted each individual country total for nonresponse and population size. The average percentage shown in the figure is the mean across individual country percentages reported by Gallup. In 2019, Iceland was ranked in the top 16 but was not included in the Wellcome Global Monitor 2020 survey; therefore, only 15 of the top 16 countries are shown. Responses are to the following: In general, would you say that you trust science a lot, some, not much, or not at all?

Gallup. 2021. Wellcome Global Monitor 2020.

Despite Americans’ general endorsement of science and the stability of their general perceptions of science over time, there are some notable differences in confidence in S&T between some groups. One source of those variations is the extent to which people understand how scientists conduct research and use the logic of science to generate evidence. This issue will be explored later in this report; see section Public Familiarity with Science and Technology Research Processes .

Perceptions of Scientists

Since the 1980s, Americans’ confidence in scientists has been high relative to their confidence in other professionals (Krause et al. 2019). From 1985 to 2022, most Americans were confident that scientists act in the best interests of society ( Figure PPS-3 ; Table PPS-1 ; also see Indicators 2022 report “ Science and Technology: Public Perceptions, Awareness, and Information Sources ”: Figure PPS-4 ). Over that period, for example, several surveys, including the GSS, asked respondents the extent to which they agreed that scientists are dedicated people who work for the good of humanity, help to solve challenging problems, and work to make life better for the average person. A consistently high percentage of Americans agreed with those statements in every GSS during that period, although there has been some fluctuation. For example, the percentage of Americans who believe scientists work to make life better for the average person ranged from 80% in 1985 to 89% in 2018. The tendency of Americans to express confidence in scientists and scientific institutions is notable, given that some recent headlines have implied a decline in Americans’ levels of trust or even implied widespread mistrust—without accompanying evidence—in scientists (Fearnow 2021; Piccone 2020).

Confidence in scientists to act in the best interests of the public, by survey date: 2016–22

See Table SPPS-6 for standard errors. Responses are to the following: How much confidence, if any, do you have in [scientists ] to act in the best interests of the public?

Pew Research Center, American Trends Panel Wave 17 (2016), conducted 10 May–6 June 2016; American Trends Panel Wave 31 (2018), conducted 29 January–13 February 2018; American Trends Panel Wave 40 (2018), conducted 27 November–10 December 2018; American Trends Panel Wave 42 (2019), conducted 7–21 January 2019; American Trends Panel Wave 66 (2020), conducted 20–26 April 2020; American Trends Panel Wave 79 (2020), conducted 18–29 November 2020; American Trends Panel Wave 100 (2021), conducted 30 November–12 December 2021; and American Trends Panel Wave 114 (2022), conducted 13–18 September 2022.

Confidence in scientists to act in the best interests of the public, by demographic characteristics: 2022

a Income tiers are based on 2021 family incomes that have been adjusted for household size and cost of living in respondents' geographic region. Middle income includes respondents whose family incomes are between two-thirds of and double the median-adjusted family income among the panel of respondents. For a three-person household, upper income is approximately $131,500 and above, middle income is from $43,800 to $131,500, and lower income is less than $43,800.

Percentages may not add to 100% because the nonresponse category for level of confidence is not shown. See Table SPPS-7 for standard errors. Responses are to the following: How much confidence, if any, do you have in [scientists] to act in the best interests of the public?

Pew Research Center, American Trends Panel Wave 114 (2022), conducted 13–28 September 2022.

Recent historical events such as the COVID-19 pandemic have not dramatically dampened the general tendency of Americans to trust scientists. The onset of the COVID-19 pandemic did not immediately coincide with a decline in U.S. adults’ confidence in either scientists in general or medical scientists in April and May 2020 (Funk, Kennedy, and Johnson 2020). The broader empirical picture of Americans’ confidence in scientists in general since 2016 includes a continuous pattern of high confidence levels, with the majority of U.S. adults expressing confidence in scientists at multiple points, as well as a brief uptick in 2019 and 2020 and a regression to 2016 confidence levels by late 2021 ( Figure PPS-3 ). https://www.pewresearch.org/our-methods/u-s-surveys/the-american-trends-panel/ ." data-bs-content="The Pew Research Center provided restricted-use data from September 2022 for this analysis that are presented here and in other sections of this report with the center’s permission. The Pew Research Center’s ATP is a nationally representative survey panel composed of more than 10,000 randomly selected adults in the United States. For more information about the ATP, see https://www.pewresearch.org/our-methods/u-s-surveys/the-american-trends-panel/ ." data-endnote-uuid="233d9b27-bf5b-4a86-b63c-956194cba7bf">​ The Pew Research Center provided restricted-use data from September 2022 for this analysis that are presented here and in other sections of this report with the center’s permission. The Pew Research Center’s ATP is a nationally representative survey panel composed of more than 10,000 randomly selected adults in the United States. For more information about the ATP, see https://www.pewresearch.org/our-methods/u-s-surveys/the-american-trends-panel/ . As recently as September 2022, a clear majority of U.S. adults expressed at least a fair amount of confidence in scientists to act in the best interests of the public ( Figure PPS-3 ), as has been the case for decades. The percentage of U.S. adults expressing a great deal of confidence in scientists in general rose to 39% in April 2020 and remained at 39% in November 2020 before declining to 28% by September 2022.

Data collected for the 2021 3M State of Science Index survey highlight the tendency of U.S. adults to believe their appreciation for science increased following the 2020 onset of the COVID-19 pandemic (3M 2020). A majority of Americans (59%) reported growing more appreciative of science in light of the COVID-19 pandemic according to data collected from September through December 2021 ( Figure PPS-4 ). Such appreciation likely reflected at least in part the public salience of scientific research during the first year of the pandemic.

Impact of the coronavirus or COVID-19 pandemic on U.S. adults' opinion of science: 2021

See Table SPPS-5 for standard errors. Responses are to the following: How has the coronavirus/COVID-19 pandemic impacted your opinion of science? A total of 2,523 adults responded to this question.

3M. 2022. 2022 State of Science Index, conducted 27 September–17 December 2021.

Although confidence in scientists has remained high at a population level for decades, Americans are not uniform in their expressed confidence. According to September 2022 data from the Pew Research Center’s American Trends Panel (ATP), confidence in scientists in general differed by education and income ( Table PPS-1 ). For example, 42% of U.S. adults with a postgraduate degree expressed a great deal of confidence in scientists, whereas 21% of U.S. adults with a high school diploma or less did. Income also predicted confidence in scientists to act in the best interests of society: 37% of U.S. adults in the highest of three family income tiers in the survey expressed a great deal of confidence, whereas 25% of U.S. adults in the lowest family income tier expressed that same level of confidence. What accounts for the differences in confidence in scientists between adults with different education and income levels is an important empirical question. Factors such as race, ethnicity, and sex do not appear to account entirely for the confidence differences between socioeconomic groups, because the 2022 ATP data demonstrate no differences in confidence in scientists as a function of respondent race based on measured categories and because any observed differences reflecting respondent sex and ethnicity were smaller than 10 percentage points ( Table PPS-1 ). Later, this report assesses one factor that predicts confidence—namely, the extent to which people understand how scientific inquiry ideally occurs. (See section Public Familiarity with Science and Technology Research Processes .)

Perceptions of Engineers and Engineering

Social science researchers have limited evidence as to whether Americans draw distinction between scientists and engineers. Some experimental evidence comparing survey respondents’ answers with questions about scientists and engineers suggests that Americans tend not to differentiate between scientists and engineers in terms of their value to society, including 2012 GSS data (see Indicators 2020 report “ Science and Technology: Public Attitudes, Knowledge, and Interest ”). According to a 2013 Pew Research Center study, U.S. adults respect the work of engineers in a similar manner as they respect the work of medical doctors and scientists. The majority of U.S. adults in that study reported holding medical doctors, scientists, and engineers in roughly equal regard (Pew Research Center 2013). (Whether U.S. adults draw distinctions within topical domains, such as distinguishing between medical practitioners who see patients and medical researchers, is unclear.) Among American adults, 63% believed engineers contribute a lot to societal well-being, 65% believed scientists contribute a lot to societal well-being, and 66% believed medical doctors do so. Those positive perceptions of engineering generally align with earlier survey research commissioned for the National Academy of Engineering (NAE 2008).

Perceptions of Specific S&T Topics

Although Americans have tended to broadly support S&T, they sometimes express concerns about specific topics that arise with the publication of new research and the introduction of new technologies. As described in this section, recent peer-reviewed literature highlights evidence on public perceptions of research on a variety of topics, including conceptualizations of AI, robotics, and automation technology; neurotechnology; perceptions of climate change and climate change research; perceptions of water contamination; and beliefs about STEM education. Past public perception research has involved a range of topics about which popular conceptualization has changed over time, such as biotechnology (Bauer 2005). This report includes example topics that have been prominent recently in public discussions and for which available data may be relevant to evaluating Americans’ trust in scientific institutions, understanding of scientific processes, or exposure to scientific activities.

Artificial Intelligence, Robotics, and Automation Technology

Public understanding of what constitutes AI and how to evaluate such technology has evolved. Even prior to recent news coverage of technologies such as content generation applications, AI became a relatively prominent topic in public discussions about science in recent decades compared with previous discourse. Fast and Horvitz (2017) studied 30 years of New York Times references to AI—between 1986 and 2016—and found that mentions of AI, including references both to optimism and concerns about ethics and loss of control, began increasing in 2009. The emergence of new AI developments since 2022 (e.g., refinement of large language model applications) has inspired new survey research (Vogels 2023), although the pace of prominent news coverage has yet to be matched by extensive social science survey research specifically focused on AI technology released since 2022. At the same time, a body of existing survey evidence suggests uncertainty and variation among Americans in their perceptions of AI, robotics, and automation technology, which helps to forecast U.S. adults’ perceptions in the near future.

Data from 3M’s 2020 State of Science Index survey suggested some uncertainty among Americans over the definition of AI. https://www.3m.com/3M/en_US/3m-forward-us/2020-summary/ ." data-bs-content="3M shared data for this analysis that are presented here and used with 3M’s permission. The 3M State of Science Index survey is an independent, nationally representative research study commissioned by 3M to track global attitudes toward science. It has been conducted annually since 2018; due to the coronavirus pandemic, however, two waves of data were released in 2020 after an additional survey was fielded during summer 2020. The 2020 Pre-Pandemic Survey was conducted in 14 countries, while the 2020 Pandemic Pulse Survey was conducted in 11 countries; the United States was included in both surveys. For more information about the survey methodology, see https://www.3m.com/3M/en_US/3m-forward-us/2020-summary/ ." data-endnote-uuid="6a8c3b48-ef16-4246-92db-cb62e95a6470">​ 3M shared data for this analysis that are presented here and used with 3M’s permission. The 3M State of Science Index survey is an independent, nationally representative research study commissioned by 3M to track global attitudes toward science. It has been conducted annually since 2018; due to the coronavirus pandemic, however, two waves of data were released in 2020 after an additional survey was fielded during summer 2020. The 2020 Pre-Pandemic Survey was conducted in 14 countries, while the 2020 Pandemic Pulse Survey was conducted in 11 countries; the United States was included in both surveys. For more information about the survey methodology, see https://www.3m.com/3M/en_US/3m-forward-us/2020-summary/ . When Americans were asked how much they know about AI in 2020, 22% reported knowing “nothing” about AI, 17% reported that they know “a lot,” and 62% reported knowing “some” (3M 2020). Americans also recently have varied in their familiarity with different applications of AI. In December 2022, the Pew Research Center asked U.S. respondents about the extent to which they have heard or read about tasks that AI technologies could perform, including prediction of extreme weather events, skin cancer detection, and writing news stories. According to results, 46% of U.S. adults had encountered information about AI being used to aid weather prediction, 22% were aware of information about the use of AI for skin cancer detection, and 33% had heard or read information about AI being employed to write news articles (Funk, Tyson, and Kennedy 2023).

Public understanding of AI, robotics, and automation technology also may change in coming years if patterns of public perceptions predict future tendencies. Evidence suggests, for example, that popular conceptions of automation technology and robotics change as more people have opportunities for direct experience with various automated applications. Tenhundfeld and colleagues (2019, 2020) found that participants’ willingness to rely on an automatic parking feature in an electric car varied as a function of how much experience they had with the technology. Over time, as they gained more experience with the feature, participants’ tendency to allow automation to control the car increased (measured as the lack of behavioral intervention to stop the automated system from operating) (Tenhundfeld et al. 2020).

In a different example, Sanders and colleagues (2017, 2019) investigated human perceptions of robots in terms of perceived trust and willingness to allow a robot to perform various tasks. One of these studies (Sanders et al. 2017) found that prior interaction with robots was positively associated with trust in them. Another study (Sanders et al. 2019) found that participants were more likely to choose a robot for a task that was relatively dangerous and was likely to result in death. Respondents were also more likely to choose humans to do mundane warehouse tasks, noting job and income considerations for human workers and the implications of robots replacing human workers.

In recent years, news outlets have highlighted AI technologies capable of generating content such as news stories and visual images in response to text prompts; for example, Knight (2022) reported on the topic. As noted earlier, the Pew Research Center surveyed Americans in 2022 regarding perceptions of those and other AI technologies. Results revealed a diverse range of perspectives regarding the perceived importance of various AI developments (Funk, Tyson, and Kennedy 2023). Among those who had encountered information about AI to write news articles, 16% viewed such technology as a major advance. Among those who had heard or read about AI to predict extreme weather, 50% saw such technology as a major advance. The perceived importance of AI technology developments may change over time as Americans become more familiar with various AI technologies. At the same time, the 2022 Pew Research Center data also are consistent with the hypothesis that Americans’ judgments about the importance and risks of technologies reflect perceptions of the implications of specific technologies for personal safety and well-being.

Popular imagination regarding AI beyond automated mechanical tasks and robotics is potentially fertile ground for future investigation; currently, however, much about human perceptions of AI remains undocumented. In March 2023, for example, the Pew Research Center surveyed U.S. adults about their awareness and use of ChatGPT, an open-access AI tool that relies on the use of a large language model to respond to user questions and requests for content. Among U.S. adults, 58% reported to have heard at least a little about the technology, but only 14% had used it to learn something new—and, among those who reported having used it, 66% reported it was only somewhat useful, not too useful, or not at all useful (Vogels 2023). That sense of utility may change as users spend more time with the technology or if more users try the technology.

Earlier survey research also has shown some ambivalence in public opinion about AI R&D. Analysis by Zhang and Dafoe (2019) of a public opinion poll of 2,000 adults (ages 18 and older) found that a substantial number (nearly half) of Americans support further development of AI, defined in the survey as “computer systems that perform tasks or make decisions that usually require human intelligence” (Zhang and Dafoe 2019:5). This study is consistent with results from a Pew Research Center report (Johnson and Tyson 2020) in which roughly half of U.S. respondents said that the development of AI “has mostly been a good thing for society.” A related review of public opinion surveys between 2010 and 2022 suggested that U.S. adults tend to anticipate AI will facilitate future advances in medicine (Beets et al. 2023).

Existing evidence also suggests widespread ambivalence and lack of awareness of specific details regarding AI applications. More than a third of participants in the Zhang and Dafoe (2019) analysis, for example, neither supported nor opposed AI development (28%) or were unsure about what they thought of AI development (10%). What support for AI research existed among participants also appears to be conditional. The vast majority (82%) of those surveyed by Zhang and Dafoe believed robots or AI should be carefully managed. A review of over a decade of public opinion data on the use of AI in health care settings also suggested approximately half of U.S. adults are not aware of specific instances in which AI is applied in health care (Beets et al. 2023); in the 2020 Science Media and the Public study conducted by YouGov, for example, 48% of U.S. adults had little or no awareness of the use of AI to improve disease diagnosis efficiency. Taken together, current public perception research on AI suggests that many Americans lack awareness about AI or feel uncertain about it, yet they feel some conditional optimism about it as well. The vast majority of U.S. adults appear to have some concern about future technology management.

Neurotechnology

Neurotechnology refers to manufactured devices that can monitor human brain processes and provide feedback to people based on that monitoring. As Farahany (2023) has noted, consumer neurotechnology devices now include a wide range of tools that connect human brains to computers as well as algorithms that make it possible for computers to analyze and respond to data resulting from brain monitoring. Neurotechnological devices have been developed to treat conditions such as chronic pain, epilepsy, Parkinson’s disease, and depression as well as to assist individuals with disabilities (Sattler and Pietralla 2022). For example, brain-computer interfaces show promise in helping to rehabilitate patients with severe motor impairments, paralysis, and disabilities using wearable or implanted electrodes that harness brain activity to control external devices like wheelchairs and body prostheses (Chaudhary, Birbaumer, and Ramos-Murguialday 2016). Neurotechnology applications to generate feedback from consumers and enable consumer input and control of various interfaces also now exist (Farahany 2023). Neurotechnology development has attracted industry investment and has posed ethical challenges related to identity, privacy protection, data tracking, and rights to cognitive liberty and mental privacy (Farahany 2023; MacDuffie, Ransom, and Klein 2022).

Empirical evidence regarding public perceptions of neurotechnology is limited. Extant data also reflect changes over time in the physical nature of neurotechnology devices; this is important to note, given that developers appear likely to continue changing and improving such devices in coming years. In 2016, the Pew Research Center surveyed U.S. adults regarding biomedical technologies to enhance human abilities and found that 69% of adults reported they would be “very” or “somewhat” worried about brain chips. Moreover, 66% of adults said they would not want enhancements of their brains (Pew Research Center 2016). Similarly, the Pew Research Center reported in 2022 on another study of U.S. adults in which 78% of adults would not want a computer chip implanted in their brain for enhanced cognitive function and improved processing of information if it were available to them (Rainie et al. 2022). Table PPS-2 describes conditions in which respondents reported they would be comfortable with an implanted device. The majority (77%) of U.S. adults reported that they favored the proposed use of computer chip implants in the brain to allow increased movement for people who are paralyzed, for example, whereas a lower percentage (25%) favored the use of implanted chips to make it possible for thoughts in the brain to search content on the Internet without typing. Evidence specifically regarding implanted devices may not necessarily generalize to technologies that are not as physically invasive as implanted devices, however; Sattler and Pietralla (2022) surveyed German adults, for example, and found respondents tended to prefer noninvasive technologies over relatively invasive technologies.

Responses to proposed uses of computer chip implants in the brain: 2021

Percentages may not add to 100%. See  Table SPPS-8  for standard errors. Responses are to the following: Computer chip implants in the brain could be used for a number of purposes. Would you favor or oppose the use of computer chips implants in the brain for each of the following purposes?

Pew Research Center, American Trends Panel Wave 99 (2021), conducted 1–7 November 2021.

At least some evidence also suggests that public acceptance of neurotechnology devices may be conditional on the perceived context and the purposes of use. In two waves of surveys in 2018 and 2019, MacDuffie, Ransom, and Klein (2022) asked a sample of U.S. general public respondents ( n = 1,088) and a sample of industry representatives ( n = 66) about perceptions of “neural devices” that read information from the brain or spinal cord. Most general public respondents (82%) agreed that the topic of user data privacy was important to them, yet only 47% of general public respondents agreed that they were confident neural devices will be designed with privacy in mind. (Among the small sample of industry representatives surveyed, 64% agreed that they were confident devices will be designed with privacy in mind.) In Germany, Sattler and Pietralla (2022) found that moral acceptability and willingness of devices depended on the perceived purposes of those devices. For example, respondents preferred the use of devices for treatment of medical conditions rather than individual human enhancement. Moreover, respondents were not uniform in their acceptance of neurotechnology devices; in the Sattler and Pietralla (2022) study, factors such as perceived stress, religiosity, and gender identity predicted potential user openness to such devices.

In the United States, public opinion research on the frontiers of noninvasive neurotechnology has been limited to date, with available survey data focused on perceptions of either specific technologies such as implanted chips or perceptions of general categories such as neural devices. Some evidence suggests widespread concern among American adults when asked about the use of neurotechnology, but it is currently unclear how well they understand the specific capabilities and planned future uses of such devices. The recent pace of neurotechnology development in various industries and the likely future iteration of device formats and purposes suggest a need for additional public opinion research to address whether such technology changes could be useful.

Climate Change

The percentage of Americans who have expressed concern about the rise in the Earth’s average temperature over time has increased in recent decades (see Indicators 2020 report “ Science and Technology: Public Attitudes, Knowledge, and Interest ”). U.S. adults’ beliefs about climate change S&T include both relatively broad support for including climate scientists in government policy deliberation as well as a common perception that climate scientists do not yet extensively understand climate change mitigation. An April 2021 Pew Research Center survey found that 54% of Americans agree that climate scientists should play a larger role in climate policy debates, although a smaller percentage (18%) agreed that climate scientists currently understand “very well” the best ways to mitigate climate change (Funk 2021). The belief that climate scientists do not extensively understand climate change mitigation possibilities, however, has not dampened support for mitigation strategy research, as illustrated by Pew Research Center data collected in May and June 2023. According to data from the 2023 survey, 67% of U.S. adults believe the United States should prioritize efforts to develop renewable energy sources, such as wind and solar, instead of expanding oil, coal, and natural gas production (Tyson, Funk, and Kennedy 2023). U.S. adults generally acknowledge the relevance of climate science research to societal decision-making even as more remains to be learned about climate change mitigation, and they express support for relevant renewable energy S&T development.

Recent research also offers insight on factors that can shape and influence perceptions of climate change concepts. The vocabulary that researchers use to describe concepts and the use (or absence) of specific examples may affect public understanding of climate change terminology. In a study of understanding of terms from the United Nations’ Intergovernmental Panel on Climate Change reports, for example, respondents expressed difficulty in understanding phrases such as carbon neutral (which refers to processes that result in no net addition of carbon dioxide to the atmosphere) or unprecedented transition —which, in turn, complicated their interpretation of report content (Bruine de Bruin et al. 2021). In addition, exposure to news stories can directly affect public opinion about climate change, both in terms of increasing the perceived general importance of the topic as well as issue-framing effects (Newman, Nisbet, and Nisbet 2018). News references to the credibility of science and scientific institutions can indirectly affect beliefs about the credibility of climate change research (Hmielowski et al. 2014).

Personal experience also may affect interpretation of climate change messages. The extent to which a person has thought about climate change previously also appears to limit possibilities for media content to affect beliefs about climate change (Wonneberger, Meijers, and Schuck 2020). Local weather experiences and natural disasters appear to shape individuals’ beliefs regarding whether climate change is occurring (Sloggy et al. 2021) as well as risk perceptions of climate change and preferences for government climate policy (Kim, Seo, and Sinclair 2021). Research indicates that perceptions of climate change and climate change research are functions of both existing beliefs and patterns in the information environment—suggesting the potential for change but also relative stability if consistent news coverage and online information about climate change slowly accumulate over time.

Water Contamination

Water is vital for human life (Jéquier and Constant 2010), and contaminant-free drinking water is important for human health. Although water quality in the United States generally has improved according to conventional metrics in recent decades, research has documented important threats to human health related to water contamination. Specifically, substances such as lead (GAO 2020) and human-made chemicals such as per- and polyfluoroalkyl substances (PFAS) (GAO 2021)—sometimes found in public drinking water systems, private wells, and various consumer products—can threaten water quality, as can harmful bacteria. News coverage in the past decade has spotlighted the discovery of toxins in drinking water in communities such as Flint, Michigan, and Jackson, Mississippi (Breslow 2022). Despite national news coverage and scientific inquiry regarding the prevalence and effects of contamination, available peer-reviewed literature lacks robust empirical evidence of the extent of public understanding of water contamination research, although recent research suggests the potential value of water research education for encouraging public cooperation with testing efforts (Gibson et al. 2022).

Water safety and quality have been topics featured in public discourse in the United States in recent years. Evidence suggests that water safety and quality topics have increased in prominence on social media platforms. For example, social media posts mentioning PFAS-related content increased on two platforms, Reddit and Twitter (known as X subsequent to this study), by more than sixfold (by 670%) from 2017 to 2019 (Tian et al. 2022), a pattern that study authors attribute in part to news coverage about PFAS exposure in the United States. Survey evidence also suggests that a substantial minority of Americans have harbored concerns about drinking water safety since at least 2018. A 2018 survey of more than 4,000 U.S. adults found that 15% did not believe their home tap water was safe to drink (Park et al. 2023).

Americans’ perceptions of home tap water safety vary by socioeconomic factors. In the Park et al. (2023) study, those with relatively less than a high school diploma were more likely to report concern about home tap water safety compared with those with a college degree, and people living in a household with $35,000 or less in annual income were more likely to report home tap water safety concerns than those with $100,000 or more in annual income. Among those with less than a high school diploma, 21% did not believe their home tap water was safe to drink.

May 2022 ATP data from the Pew Research Center underscore important differences between socioeconomic groups in the perceived quality of local community water ( Figure PPS-5 ). Among Americans with a high school diploma or less, 19% viewed the safety of drinking water as “a big problem” in their local community; among college graduates, however, 12% of adults saw drinking water safety as “a big problem.” Similarly, among those in the lowest income tier of respondents (less than $43,800 annual household income), 25% saw drinking water quality as a big problem, while among those in the highest income bracket (with incomes above $131,500 annually), 8% viewed drinking water as a big problem in their local community. Such perception differences coincide with research on variation between neighborhoods in demonstrable exposure to some types of contaminants such as lead (Xue et al. 2022).

Opinions on safety of drinking water, by demographic characteristics: 2022

Percentages may not add to 100% because the nonresponse category for level of confidence is not shown. See Table SPPS-9 for standard errors. Income tiers are based on 2021 family incomes that have been adjusted for household size and cost of living in respondents' geographic region. Middle income includes respondents whose family incomes are between two-thirds of and double the median-adjusted family income among the panel of respondents. For a three-person household, upper income is approximately $131,500 and above, middle income is from $43,800 to $131,500, and lower income is less than $43,800. Responses are to the following: How much of a problem, if at all, do you think [safety of drinking water] is in your local community?

Pew Research Center, American Trends Panel Wave 108 (2022), conducted 2–8 May 2022.

Aside from evidence of general concerns about water quality, however, the extent to which American adults understand water contamination processes, water quality research, and potential remedies is not yet clear in available peer-reviewed literature. Some evidence suggests that educational information about certain aspects of water quality testing and research can motivate relevant water testing behavior. Experimental evidence from a study with North Carolina residents, for example, demonstrated that residents with a private well who were offered a free well test, along with information as to why such testing is important (e.g., because using one’s senses such as vision or taste alone can be insufficient to detect water problems), tended to opt for testing more than their counterparts (Gibson et al. 2022). Those offered a free test and information were more likely to opt for well testing than those in a control group, those who were offered a free well test without explanatory information, and those who were offered explanatory information without a free well test. Such responses to information about water quality testing may reflect the importance of addressing existing gaps in residents’ mental models of how water researchers conduct their work and what data water testing can produce (Gibson et al. 2022). Future research could investigate whether Americans understand that water safety research comprises different attributes of water quality: those that are apparent to human sensory perception and those that are invisible or not detectable by typical human senses alone.

STEM Education

Public perception of STEM education in K–12 U.S. public schools comprises a mix of fond recollection of science classes; concern about present investment in K–12 schools; and widespread judgment that the STEM education offered to elementary, middle, and high school students in the United States is worse than that offered in at least some other countries. A Pew Research Center survey (Funk and Parker 2018) found that 75% of U.S. adult respondents reported that they liked science courses during their time as K–12 students; 58% of adults reported liking their K–12 mathematics courses. When asked to choose whether they liked those courses because of the subject matter itself or because of the way the subject matter was taught, 68% of those who liked their science courses said the subject matter was the main reason they enjoyed those classes. Despite Americans’ fondness for their own STEM experiences, only 31% of U.S. respondents in October 2019 considered K–12 STEM education in the United States to be at least above average when compared with what is available in other nations ( Figure PPS-6 ). Regarding undergraduate and graduate STEM education in the United States, about half of respondents (52%) thought STEM education in U.S. colleges and universities is above average or the best in the world compared with what is available in other countries. Future inquiry could explore the basis for such perceptions.

Perceptions of U.S. STEM education compared with other nations at K–12 and university levels: 2019

STEM = science, technology, engineering, and mathematics.

Percentages may not add to 100% because the nonresponse category is not shown. See Table SPPS-10 for standard errors. Responses are to the following: I'd like you to compare the United States to other nations in a few different ways. Do you think the U.S. is the best in the world, above average, average or below average? Its science, technology, engineering and math education in grades K to 12. Its science, technology, engineering and math education in colleges and universities.

Pew Research Center, International Science Survey (2019–20), conducted in the United States 1–28 October 2019.

Perceptions of STEM education quality among Americans appear to reflect concerns about resource availability more than reasons such as dismissive cultural beliefs. The 2022 3M State of Science Index survey asked U.S. respondents what barriers were most important in “standing in the way of students accessing a strong STEM education,” and the most common responses were a lack of STEM classes in school, the inability of students to pay for STEM education, and a lack of STEM teachers ( Figure PPS-7 ). Although most Americans see value in STEM education, they typically do not see elementary, middle, and high school STEM education as the best in the world, and they are most likely to cite resource constraints as major barriers to access. Other Science and Engineering Indicators reports focus on institutional measures of STEM education quality in the United States (see Indicators 2024 reports “ Elementary and Secondary STEM Education ” and “ Higher Education in Science and Engineering ”).

U.S. adults' belief on top three barriers to students accessing strong STEM education in the United States: 2021

See Table SPPS-11 for standard errors. Responses are to the following: What do you believe are the top barriers, if any, standing in the way of students currently accessing a strong STEM education within your country? Select top three.

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Understanding Science

How science REALLY works...

• Understanding Science 101
• Misconceptions
• Accepted theories may be modified or overturned as new evidence and perspective emerges.
• Scientists are likely to accept a new or modified theory if it explains everything the old theory did and more.
• The process of theory change may take time and involve controversy, but eventually the scientific explanation that is more accurate will be accepted.

Misconception:  Scientific ideas are absolute and unchanging.

Misconception:  Because scientific ideas are tentative and subject to change, they can’t be trusted.

Correction:  Accepted scientific ideas are well-supported and reliable, but could be revised if warranted by the evidence.  Read more about it.

Even theories change

Accepted theories are the best explanations available so far for how the world works. They have been thoroughly tested , are supported by multiple lines of evidence , and have proved useful in generating explanations and opening up new areas for research. However, science is always a work in progress, and even theories change. How? We’ll look at some over-arching theories in physics as examples:

• Classical mechanics In the 1600s, building on the ideas of others, Isaac Newton constructed a theory (sometimes called classical mechanics or Newtonian mechanics) that, with a simple set of mathematical equations, could explain the movement of objects both in space and on Earth. This single explanation helped us understand both how a thrown baseball travels and how the planets orbit the sun. The theory was powerful, useful, and has proven itself time and time again in studies. Yet it wasn’t perfect…
• Special relativity Classical mechanics was one-upped by Albert Einstein’s theory of special relativity. In contrast to the assumptions of classical mechanics, special relativity postulated that as one’s frame of reference (i.e., where you are and how you are moving) changes, so too do measurements of space and time. So, for example, a person speeding away from Earth in a spacecraft will perceive the distance of the spacecraft’s travel and the elapsed time of the trip to be different than would a person sitting at Cape Canaveral. Special relativity was preferred because it explained more phenomena: it accounted for what was known about the movement of large objects (from baseballs to planets) and helped explain new observations relating to electricity and magnetism.
• General relativity Even special relativity was superseded by another theory. General relativity helped explain everything that special relativity did, as well as our observations of gravitational forces.
• Our next theory… General relativity has been enormously successful and has generated unique expectations that were later borne out in observations, but it too seems up for a change. For example, general relativity doesn’t mesh with what we know about the interactions between extremely tiny particles (which the theory of quantum mechanics addresses). Will physicists develop a new theory that simultaneously helps us understand the interactions between the very large and the very small? Time will tell, but they are certainly working on it!

All the theories described above worked — that is, they generated accurate expectations, were supported by evidence , opened up new avenues of research, and offered satisfying explanations. Classical mechanics, by the way, is still what engineers use to design airplanes and bridges, since it is so accurate in explaining how large (i.e., macroscopic) and slow (i.e., substantially slower than light) objects interact. Nevertheless, the theories described above did change. How? A well-supported theory may be accepted by scientists, even if the theory has some problems. In fact, few theories fit our observations of the world perfectly. There is usually some anomalous observation that doesn’t seem to fit with our current understanding. Scientists assume that by working to understand such anomalies, they’ll either disentangle them to see how they fit with the current theory or they’ll make progress towards a new theory. And eventually that does happen: a new or modified theory is proposed that explains everything that the old theory explained plus other observations that didn’t quite fit with the old theory. When that new or modified theory is proposed to the scientific community, scientists come to understand the new theory, see why it is a superior explanation to the old theory, and eventually, accept the new theory – though this process can take many years.

SCIENTIFIC CONTROVERSY: TRUE OR FALSE?

Here, we’ve discussed true scientific controversy — a debate within the scientific community over which scientific idea is more accurate and should be used as the basis of future research. True scientific controversy involves competing scientific ideas that are evaluated according to the standards of science — i.e., fitting the evidence, generating accurate expectations, offering satisfying explanations, inspiring research, etc. However, occasionally, special interest groups try to misrepresent a non-scientific idea, which meets none of these standards, as inspiring scientific controversy. To learn to identify these false controversies, visit:

• What controversy: Is a controversy misrepresented or blown out of proportion? , one of the tips in our Science Toolkit.
• Science in action

For an example of how evolutionary theory changed to account for a new idea, check out the story of Lynn Margulis,  Cells within cells: An extraordinary claim with extraordinary evidence .

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The scientific method and climate change: How scientists know

By Holly Shaftel, NASA's Jet Propulsion Laboratory

The scientific method is the gold standard for exploring our natural world. You might have learned about it in grade school, but here’s a quick reminder: It’s the process that scientists use to understand everything from animal behavior to the forces that shape our planet—including climate change.

“The way science works is that I go out and study something, and maybe I collect data or write equations, or I run a big computer program,” said Josh Willis, principal investigator of NASA’s Oceans Melting Greenland (OMG) mission and oceanographer at NASA’s Jet Propulsion Laboratory. “And I use it to learn something about how the world works.”

Using the scientific method, scientists have shown that humans are extremely likely the dominant cause of today’s climate change. The story goes back to the late 1800s, but in 1958, for example, Charles Keeling of the Mauna Loa Observatory in Waimea, Hawaii, started taking meticulous measurements of carbon dioxide (CO 2 ) in the atmosphere, showing the first significant evidence of rapidly rising CO 2 levels and producing the Keeling Curve climate scientists know today.

“The way science works is that I go out and study something, and maybe I collect data or write equations, or I run a big computer program, and I use it to learn something about how the world works.”- Josh Willis, NASA oceanographer and Oceans Melting Greenland principal investigator

Since then, thousands of peer-reviewed scientific papers have come to the same conclusion about climate change, telling us that human activities emit greenhouse gases into the atmosphere, raising Earth’s average temperature and bringing a range of consequences to our ecosystems.

“The weight of all of this information taken together points to the single consistent fact that humans and our activity are warming the planet,” Willis said.

The scientific method’s steps

The exact steps of the scientific method can vary by discipline, but since we have only one Earth (and no “test” Earth), climate scientists follow a few general guidelines to better understand carbon dioxide levels, sea level rise, global temperature and more.

• Form a hypothesis (a statement that an experiment can test)
• Make observations (conduct experiments and gather data)
• Analyze and interpret the data
• Draw conclusions
• Publish results that can be validated with further experiments (rinse and repeat)

As you can see, the scientific method is iterative (repetitive), meaning that climate scientists are constantly making new discoveries about the world based on the building blocks of scientific knowledge.

“The weight of all of this information taken together points to the single consistent fact that humans and our activity are warming the planet." - Josh Willis, NASA oceanographer and Oceans Melting Greenland principal investigator

The scientific method at work.

How does the scientific method work in the real world of climate science? Let’s take NASA’s Oceans Melting Greenland (OMG) campaign, a multi-year survey of Greenland’s ice melt that’s paving the way for improved sea level rise estimates, as an example.

• Form a hypothesis OMG hypothesizes that the oceans are playing a major role in Greenland ice loss.
• Make observations Over a five-year period, OMG will survey Greenland by air and ship to collect ocean temperature and salinity (saltiness) data and take ice thinning measurements to help climate scientists better understand how the ice and warming ocean interact with each other. OMG will also collect data on the sea floor’s shape and depth, which determines how much warm water can reach any given glacier.
• Analyze and interpret data As the OMG crew and scientists collect data around 27,000 miles (over 43,000 kilometers) of Greenland coastline over that five-year period, each year scientists will analyze the data to see how much the oceans warmed or cooled and how the ice changed in response.
• Draw conclusions In one OMG study , scientists discovered that many Greenland glaciers extend deeper (some around 1,000 feet, or about 300 meters) beneath the ocean’s surface than once thought, making them quite vulnerable to the warming ocean. They also discovered that Greenland’s west coast is generally more vulnerable than its east coast.
• Publish results Scientists like Willis write up the results, send in the paper for peer review (a process in which other experts in the field anonymously critique the submission), and then those peers determine whether the information is correct and valuable enough to be published in an academic journal, such as Nature or Earth and Planetary Science Letters . Then it becomes another contribution to the well-substantiated body of climate change knowledge, which evolves and grows stronger as scientists gather and confirm more evidence. Other scientists can take that information further by conducting their own studies to better understand sea level rise.

All in all, the scientific method is “a way of going from observations to answers,” NASA terrestrial ecosystem scientist Erika Podest, based at JPL, said. It adds clarity to our way of thinking and shows that scientific knowledge is always evolving.

Related Terms

• Climate Change
• Climate Science
• Earth Science

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National Research Council (US) and Institute of Medicine (US) Forum on Adolescence; Kipke MD, editor. Adolescent Development and the Biology of Puberty: Summary of a Workshop on New Research. Washington (DC): National Academies Press (US); 1999.

Adolescent Development and the Biology of Puberty: Summary of a Workshop on New Research.

• Hardcopy Version at National Academies Press

Changes in the Study of Adolescent Development

Over the last two decades, the research base in the field of adolescent development has undergone a growth spurt. Knowledge has expanded significantly. New studies have allowed more complex views of the multiple dimensions of adolescence, fresh insights into the process and timing of puberty, and new perspectives on the behaviors associated with the second decade of life. At the same time, the field's underlying theoretical assumptions have changed and matured.

Researchers of human development have consistently observed that the second decade of life is a time of dramatic change: a period of rapid physical growth, endocrine (hormone) changes, cognitive development and increasing analytic capability; emotional growth, a time of self-exploration and increasing independence, and active participation in a more complex social universe. For much of this century, scientists and scholars studying adolescence tended to assume that the changes associated with adolescence were almost entirely dictated by biological influences. It has been viewed as a time of storm and stress, best contained or passed through as quickly as possible. Adolescence , a 1904 book by G. Stanley Hall, typified this standpoint. It was Hall who popularized the notion that adolescence is inevitably a time of psychological and emotional turmoil (Hall, 1904). Half a century later, psychoanalytic writers including Anna Freud accepted and augmented Hall's emphasis on turmoil (Petersen, 1988). Even today, "raging hormones" continue to be a popular explanation for the lability, aggression, and sexual activity associated with adolescence (Litt, 1995). Intense conflict between adolescents and their parents is often considered an unavoidable consequence of adolescence (Petersen, 1988). However, this assumption is not supported by scientific evidence. The assumption that turmoil and conflict are inevitable consequences of the teenage years may even have prevented some adolescents from receiving the support and services they needed.

Research is now creating a more realistic view of adolescence. Adolescence continues to be seen as a period of time encompassing difficult developmental challenges, but there is wider recognition that biology is only one factor that affects young people's development, adjustment, and behavior. In fact, there is mounting evidence that parents, members of the community, service providers, and social institutions can both promote healthy development among adolescents and intervene effectively when problems arise.

The study of adolescence is now becoming an increasingly sophisticated science. Thanks to powerful new research tools and other scientific and technological advances, today's theories of adolescent development are more likely to be supported by scientific evidence than in the past. Indeed, there has been sufficient research to allow a reassessment of the nature of adolescent development. At the same time, there is greater recognition that neither puberty nor adolescence can be understood without considering the social and cultural contexts in which young people grow and develop, including the familial and societal values, social and economic conditions, and institutions that they experience. This research has contributed the following to our understanding of adolescence:

• The adolescent years need not be troubled years.

There is now greater recognition that young people can move through the adolescent years without experiencing great trauma or getting into serious trouble; most young people do. Although adolescence can certainly be a challenging span of years, individuals negotiate it with varying degrees of difficulty, just as they do other periods of life. Moreover, when problems do arise during adolescence they should not be considered as "normal"—i.e., that the adolescent will grow out of it—nor should they be ignored (Petersen, 1988).

• Only a segment of the adolescent population is at high risk for experiencing serious problems.

Over the past 50 years, studies conducted in North America and Europe have documented that only about a quarter of the adolescent population is at high risk for, or more vulnerable to, a wide range of psychosocial problems (Carnegie Corporation of New York, 1995). These adolescents are not believed to be at increased risk because of biological or hormonal changes associated with puberty, but rather from a complex interaction among biological, environmental, and social factors. Indeed, as discussed by Anne Petersen, there is mounting evidence that most biological changes interact with a wide range of contextual, psychological, social, and environmental factors that affect behavior (Buchanan et al., 1992; Susman, 1997, see also Brooks-Gunn et al., 1994). Researchers are also concluding that behaviors associated with adolescence, including some high risk behaviors, are influenced by the social milieu (Brooks-Gunn and Reiter, 1990). Studies show that, in contrast to children and adults, the most common causes of mortality among adolescents are associated with social, environmental, and behavioral factors rather than genetic, congenital, or biological diseases. Indeed, many of today's adolescents are using alcohol and other drugs, engaging in unprotected sexual intercourse, and are both victims and perpetrators of violence, which puts them at increased risk for a wide range of developmental and health-related problems, including morbidity and mortality. It is important to note that the leading causes of morbidity and mortality among adolescents are entirely preventable. Although relatively small, a significant number of adolescents also experience morbidity and mortality associated with genetic and congenital disorders (such as cystic fibrosis, muscular dystrophy, cerebral palsy), cancer, and infectious diseases that affect their development, behavior, and well-being.

• Adolescent behavior is influenced by complex interactions between the biological and social contexts.

In the past, researchers tended to conduct research designed to examine the impact of hormones on adolescent behavior. While this work continues, there is now an appreciation for the complex reciprocal relationship and interaction between biological and social environments, and the interaction between these environments and adolescent behavior (Graber et al., 1997).

• Current understanding of adolescent development remains limited.

Although the study of adolescence is becoming more sophisticated in nature, researchers also recognize that the current knowledge base on adolescent development and behavior is quite limited. The research conducted to date has predominately been descriptive in nature, relied on cross-sectional data, and been unidimensional in focus. Indeed, few research studies have successfully considered the multiple factors that collectively influence adolescent development. As discussed by Iris Litt, there is now a growing appreciation that new research is needed, including research that employs longitudinal designs; characterizes developmental changes associated with the onset of puberty well before the age of 8; and seeks to characterize growth and development across the life span—i.e., from infancy to adolescence, young adulthood, adulthood, and the senior years. Studying these developmental stages in isolation from one another provides only a partial and incomplete picture.

• Researchers from diverse fields, including the biological, behavioral, and social sciences, have developed new techniques to study adolescent development.

Use of more rigorous research methods has improved the reliability and validity of the measurement techniques used, and consequently the ability to document the multifaceted dimensions of growth and maturation during adolescence. For example, the development of radioimmunoassay methodology in the late 1960s, and the considerable refinement of that process over the decades, have made it possible to study the hormones that control reproductive maturation. The development of neuroimaging technology in the 1970s created exciting new opportunities for studying brain development; these techniques include more sensitive, easy-to-use hormone assay technology and new brain imaging technologies, allowing insight into brain development and function. Moreover, longitudinal studies are increasingly being designed to characterize the interaction among genetic, biological, familial, environmental, social, and behavioral factors (both risk and protective in nature) among children and adolescents. For example, a valuable new source of data that has the potential to significantly advance the knowledge base of physiological and behavioral development among adolescents is the National Longitudinal Study of Adolescent Health (called Add Health). From the collection of longitudinal data, it will be possible to examine how the timing and tempo of puberty influences social and cognitive development among teenagers. This dataset will also permit analyses to examine how family-, school-and individual-level risk and protective factors are associated with adolescent health and morbidity (e.g., emotional health, violence, substance use, sexuality).

• An Increasing Number of Disciplines are Beginning to Conduct Research on Adolescent Development.

Understanding adolescent development requires answers to a number of difficult questions: how do adolescents develop physically, how do their relationships with parents and friends change, how are young people as a group viewed and treated by society, how does adolescence in our society differ from adolescence in other cultures, and how has adolescence and adolescent development changed over the past few decades. A complete understanding of adolescence, and the potential to answer these questions depends on an integrated approach, and involvement of a wide range of disciplines, including but not limited to endocrinology, psychology, sociology, psychiatry, genetics, anthropology, neuroscience, history, and economics. While each discipline offers its own view point regarding adolescence and adolescent development, the field will not be able to successfully answer these questions without integrating the contributions of different disciplines into a coherent and comprehensive viewpoint. Fortunately, studies of puberty are increasingly drawing on and therefore benefiting from the knowledge base of these diverse fields.

• Cite this Page National Research Council (US) and Institute of Medicine (US) Forum on Adolescence; Kipke MD, editor. Adolescent Development and the Biology of Puberty: Summary of a Workshop on New Research. Washington (DC): National Academies Press (US); 1999. Changes in the Study of Adolescent Development.
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