Category Archives: Science Communication

Everybody Who Isn’t ”Viewers Like You”

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Last week, I talked about how truthseekers get paid. But truth-tellers and truth-seekers are different things.

Consider educational kids’ shows on public television.

Nobody who works on Sesame Street is out there uncovering new letters and numbers. Bill Nye’s show wasn’t bringing analysis fresh from the lab.

The purpose of these shows is to educate. The purpose of education is to change minds.

So who pays for educational kids’ shows on public television?

If you’re from the US and watched PBS growing up, you remember one answer: “viewers like you!” US public television is supported by donations, ordinary people across the country who want it to keep on educating kids.

But you also might remember the lists of names that came before “viewers like you”. Some of those were things like “the Department of Education” or “a grant from the National Science Foundation”: government programs, in other words. Others were philanthropists and private foundations. Some were tied to companies, like the Intel Foundation, or Juicy Juice.

All of these groups, from government departments to donors, are trying to change kids’ minds. They support specific shows on specific topics, where they want kids to be better-informed. The same groups have the same kind of impact on schools. For example, I remember in elementary school we all learned to play a recorder, because a wealthy donor had given the school recorders out of the idea that music education was especially important.

For a truth-seeker like a journalist, accepting that kind of funding would be a problem. Grants for journalists tend to support things like travel, letting journalists learn more about specific topics, not pre-judging the conclusion. But children’s television is about truth-telling, not truth-seeking, so our standards are different. We trust the people making children’s television to care about whether they’re telling the truth. And because the topics aren’t new, we don’t usually worry about their judgement being biased.

All this is rather obvious. But now, consider science YouTube.

Some science YouTubers seem to have a mission much like children’s television. They’re there to teach, not to make independent judgements. They don’t search for truth on their own. And some of them are funded by educational grants, much like children’s television.

Others are a bit more like journalists, or even activists. People follow them for their opinions, to hear their assessment. They’re trying to be truth-seekers.

On YouTube, it’s not always obvious which is which.

There’s a particular group of philanthropists called Effective Altruists, and many of them are concerned about AI. So in between funding things like anti-malaria bed nets, some of them are giving grants to YouTubers to make educational content about AI-related risks.

Apparently, they reached out to Sabine Hossenfelder, which was a bad idea. Sabine Hossenfelder’s followers aren’t just looking for education on known facts. They’re looking for her judgements, her literal bullshit-rating on ideas. And so while she’s paid by “viewers like you”, she’s not really the type to get paid by that type of grant.

What I want to emphasize, and what looked like it was getting lost in the discussion, was that their pitch would have been totally reasonable for other YouTubers. Educators do occasionally get grants to educate on specific topics. This is in fact a totally normal thing. Some YouTubers are educators first and foremost, they aren’t there as truth-seekers, but truth-tellers, with a real difference in how careful they need to be about bias.

Some YouTubers are different from other YouTubers. News at 11.

Paying the Truthseekers

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Academics and journalists have a lot in common, at least in principle.

Whether you’re a reporter or a professor, your job is to go out into the world and figure out the truth. You’re supposed to be careful, to check and correct for how you might be wrong. And at the end of the day you’re supposed to communicate what you found.

The differences mostly come in how you’re paid.

You could imagine some sort of pure truthseeker, paid purely by how well they tell the truth. People would ask them to find out the truth about something, and pay them for the service. And the truthseekers with the best track record would get the most clients. But neither profession really works like this.

Journalism comes closest. Once upon a time, people bought newspapers in order to be the first to know when something important happened. While there’s still a little bit of that going on (I guess this is what Bloomberg Terminals are for?), it’s a lot less central because of the internet. Now, there are hundreds of ways to find out about things, from a multitude of news sites to social media. More and more, people expect to be able to get information for free.

In that environment, the news has to compete not on the facts themselves, but on how it presents them. People pay for news that’s curated well to match their interests, or news that feels more respectable. And more than either of those, they pay for news that’s entertaining. So while truthseeking skills pay, writing skills often end up mattering more. In a sense, it’s why it’s possible for me to do journalism at all. I was trained in the academic truthseeking tradition, not the journalistic one. I got into journalism by impressing editors with my writing, not my ability to suss out the truth.

That academic truthseeking tradition is quite different, in part because the rewards for it are much more indirect. Academics pay comes from two main sources: research grants, and student tuition. Students are mostly there to learn old facts, not new ones, so that source of money supports research only in so far that students believe that a successful researcher with time for research will also be a better teacher.

Research grants, in principle, pay for truthseeking. But they’re typically paid by governments, which often don’t have a clear idea of what they’d like to learn, since the more practical questions are already being researched by private companies. So the decision gets delegated out to other academics, who have a vague shared sense of what’s worth knowing and what’s not. Accuracy should have an impact: that is, it should be easier to get grants if you’re better at finding the truth. But in practice, unless someone does so badly they trigger a scandal, academics don’t usually get things all that wrong. So grants are mostly based on other factors.

Paying someone purely to deliver the truth, not to entertain or match a culture, seems tricky. You could imagine sci-fi scenarios. What if we could track the logic people used to make decisions, and demand payment if those decisions were based on facts we uncovered, like a journalist getting a percentage of every short made in response to bad news they dug up about a company? What if governments paid in proportion to how valuable academic ideas turned out to be, centuries after they were discovered, and modern-day academics sold shares in that future payout to fund themselves? What if prediction markets something something?

For the moment, academics and journalists are both in a weird middle space. They’re truthseekers, still, by culture and inclination and desire. But they’re paid for something else.

Don’t Judge an Explanation by Its Cover

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Dark matter bugs people.

I’ve talked before about why, and why it, and other beyond-the-standard-model proposals like those inspired by MOND, are nonetheless credible with physicists. But beyond the logic in that post, there’s a deeper reason people find dark matter strange. It’s that they don’t know what kind of an explanation dark matter is.

Dark matter sounds very lazy. If you can’t explain the movements of stars based on the matter you can see, then proposing invisible matter sounds like the easy way out. But it’s actually a lot less easy than it sounds, because matter is something quite specific. Matter gravitates and bends light. Matter moves. Matter can be described with a pressure, one like gas and dust and not like other things like light or the Higgs field. If you propose a new type of matter, you have to check and see that all of those consequences hold, with detailed implications for almost every observation every astronomer takes.

For the most part, those consequences have been checked, and they do hold. Sometimes they fail, and it’s those failures, and not the idea that dark matter is “lazy”, that drive dark matter’s critics in the physics profession. Physicists who oppose dark matter have other explanations with their own consequences, for example new types of quantum fields that often get described to the public as “modified gravity”. When they argue against dark matter, they do it by comparing those consequences in detail, working through the implications and seeing which phenomena hold.

Dark matter, as it turns out, is a very constraining explanation, one with strict consequences. There are other corners of physics where the explanations may seem less lazy, but actually have fewer consequences, and thereby less scientific heft.

For example, consider the debate about evidence for dark energy I wrote about last month. A key question there was how to interpret light from supernovae. Some groups argued that supernovae change in brightness with distance, others that they change based on how old their galaxies are. Sabine Hossenfelder glossed the debate by saying it comes down to how you model supernovae. And while that’s true, it can give the wrong impression.

You might think that these people are comparing detailed computer models of supernovae, and making different assumptions when they set their models up. But in reality, it’s much less detailed. The people on both sides of this debate are looking at correlations, trying to draw statistical lines through supernova datasets. The difference between one model and another isn’t a complicated physical setup you can put into a simulation, it’s just which lines on a graph you account for and which you ignore.

Because of that, while these models may sound much more sophisticated than dark matter, they actually have much less scientific weight. The different supernova models don’t have grand, widespread consequences, they’re not mucking with the laws of physics or proposing new classes of object that every astronomer needs to account for. They’re pretty much just proposing tweaks to how to interpret one very specific type of data. That makes their questions much harder to resolve, and their answers much less universally convincing.

If you’re not a scientist, if you read science news, it can be hard to tell the difference. Some ideas in science may sound simple, but have a whole raft of consequences that distinguish them from other ideas. Others may sound sophisticated, but are much more like “fudge factors”, only distinguished by statistical arguments, not by a rich trail of qualitative evidence.

For the most part, as an outsider, you’ll never know which is which. But as always, it’s best to be aware of your limits.

Newsworthiness Guide for Scientists

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I had a recurring “elevator pitch” at Lancefest earlier this summer. After explaining that I’m a science journalist now, I’d end with “so if you run into a story, let me know!”

One person had a question that left me stumped: “What counts as a story?”

For those of us who don’t happen to be Einstein

I didn’t have a good response then. I’ve got a better one now, though I’m afraid it doesn’t fit in an elevator pitch. This is all based on my experience, so take it with a grain of salt. But here are the criteria that seem to matter:

First, a story usually needs a news hook. News is, in particular, supposed to be “new”. That doesn’t mean I can’t write about history, or established science. But editors like those stories a lot better if there is some recent development, within the past year or so, to tie it to. The new development doesn’t have to be all that important, the story can mostly focus on something else. But it needs to be somewhere in there.

Second, news stories are usually qualitative, not quantitative. I need to be able to tell a story about what happened, what actions people took and why they mattered. Quantitative developments usually only make the news if they’re so big that they shade into the qualitative: something doubling unexpectedly, for example.

Third, ideally a science news story is something that is getting the experts excited. Journalists aren’t supposed to judge the scientific merit of ideas on their own, they’re supposed to rely on experts. The most solid stories, the ones that are easiest to pitch, are ones where there’s a community of experts that largely think something is cool. That makes it easier to get good quotes, and easier to justify its relevance. If you accomplished something and you’re having trouble convincing anyone it matters, don’t start with me, start with your colleagues!

Fourth: less importantly, it helps when stories have a human angle. If you can tell a tale about how you came up with an idea, if you came from an unusual background, if something was hotly debated but now is deemed essential: these things sweeten a story, they capture readers’ interest, and editors see their value.

Finally, stories involve something changing. It can be something that just changed now, for a news piece, but it can also be something that changed over time, for a feature in a magazine. The key is change. “Old method still works” is not going to excite people, and it won’t count as news.

After writing all that out, I’m still not sure I answered the original question. But hopefully I’ve at least given some tips that can get you started. If you’re a scientist, and you see something that hits most of the boxes on this list but hasn’t been covered in the news yet, consider reaching out to me. You may have run into a story!

Bonus Info for “Quantum ‘Jamming’ Explores the Truly Fundamental Principles of Nature”

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I had a new piece in Quanta Magazine last week, about a hypothetical trick in theories beyond quantum mechanics called jamming.

Sometimes, I get science news stories from contacts. Sometimes I see an academic post something cool on X or Bluesky. But when the stories aren’t coming easy, I open up arXiv.org, click on “new”, and start browsing. And occasionally, I spot something cool.

That happened with jamming. I saw the concept mentioned in an abstract, the idea that someone could “jam” quantum entanglement from afar, like you would jam a radio signal. I hadn’t heard of it before. I wanted to know more. And after I talked to Quanta’s editors, they wanted to know more too.

Jamming is not possible under the rules of quantum mechanics we know. Instead, it’s something that could be possible in a kind of super-quantum mechanics, a theory even weirder than the famously weird theory we use today. In my piece for Quanta, I talked about where the idea of jamming comes from, and why it’s spurring discussion in recent years. In this post, I wanted to give some “bonus info” that didn’t fit into the piece.

One theme I didn’t have as much space to explore is causality.

Quantum mechanics famously seems to do weird things with cause and effect. In a double-slit experiment, photons pass one by one through one of two slits in a wall, headed to a photographic screen. No matter how slowly and carefully you send the photons, their distribution on the other end will show interference between the two possible paths, one through each slit, even though each photon only goes through one. It’s as if before hitting the screen, the photons are simultaneously traveling on every possible path, only to pick one in the moment the photon is detected.

Einstein was bothered by this. He imagined a photographic screen so large it would take light years to cross. How could detecting a photon on one side change the possibility of detecting a photon on the other side? That seemed, to him, to require signals traveling faster than light, which in turn would screw up cause and effect, as any way to send a signal faster than light can also, from another perspective, send a signal back in time.

The answer most physicists accept is that no signal can be sent in this way…at least, in the modern sense. Quantum outcomes are random, so while you could imagine that a measurement in one place changes the outcome in another place, your choice to measure has no effect on that distant outcome. You can’t intentionally send a message faster than light. We call that “no-signaling”, and it prevents the paradoxes of time travel.

Jamming obeys similar rules. A jammer (in the story in my article, a magician named Jim) can modify the entanglement between two distant particles, seemingly faster than light. But he can only do this in a way that involves randomness, so that the probabilities for measurement results for each individual particle stay the same. Instead, he can only modify how measurements between the two particles are related, their correlation. And he can only do this if the two particles can only be compared in a region that he can reach without traveling faster than light.

That’s enough to allow Jim to break the security of many quantum cryptography procedures. He can do this for example by mimicking entanglement: quantum cryptography often uses entanglement to verify that a message hasn’t been tampered with. If you can modify correlations from afar, you can make two particles appear to be entangled when actually they’re related by some other rules, which give you access to the secret that others are trying to hide.

Part of what’s still under discussion, is whether that kind of trick is compatible with causality. This depends a lot on how you think causality is supposed to work, and while the people I talked to are trying to get the story straight, they weren’t in agreement yet. In particular, Vilasini and Colbeck seemed to think that there was an important difference between the way that jamming bends causality and the way that ordinary quantum mechanics does, while Eckstein and Ramanathan weren’t so sure.

More broadly, Vilasini and Colbeck have a broader way of thinking about causality that I only barely touched on. Part of that is ways you can think of one event causing another even if no signal can be sent between them. Part of that is time loops, but of a limited kind: loops that can’t cause paradoxes, because they’re loops of causes, but not intentional signals. Vilasini and Colbeck have argued that jamming, if it existed, could be used to set up these kind of limited time loops, in a piece that was covered by New Scientist. It should be emphasized that these are really very limited time loops, for more reasons than one. They’re also limited to being in only one spatial dimension: that is, everyone in the loop has to be lined up in exactly a straight line. And I got the impression they also require everyone to activate their measurement or jamming devices instantly: with any small delay, the loop breaks.

I said even less about Mirjam Weilenmann’s critique, because there were bigger aspects that the researchers still disagreed on when I spoke with them. Weilenmann’s argument looks at what happens when there are multiple jammers, jamming different pairs of entangled particles. I got the impression from her that she felt she had found a contradiction in these examples, where jamming could only work if it broke its essential no-signaling rules. But Eckstein and Ramanathan seemed to think she was describing a scenario where one jammer could cause noise that would disrupt another jammer, “jamming the jammers” in a sense that didn’t cause any fundamental problems, just introduced jammer vs. jammer combat to make the story more interesting. I opted to not say much about this, since it was clear that things weren’t resolved yet. The researchers are still talking, and I look forward to hearing what they conclude when they reach agreement.

I also didn’t say much about tests in the real world. But that is something Eckstein and collaborators are actively exploring. They’re investigating experiments that could show deviations from quantum mechanics in a variety of contexts, from tabletops in university labs to particle colliders. The hope is that some of these strange ideas could actually be tested.

In general, the impression I got was that despite the seeds of this topic being laid thirty years ago, and reintroduced to the field ten years ago…the topic is heating up right now, in a way it hadn’t before. I’m expecting more jamming papers. If they’re cool enough, I may even cover some of them.

Trust Is a Tree

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Scientists trust what they think they can verify.

In principle, you can work your way through the proof of every mathematical theorem. With enough money and time, you could replicate every experiment. For every expert opinion, you could dig through the literature and find how it was justified.

And while a scientist can’t actually do that for every field, they might be able to for the ones they care about most. In your specialty, you probably can check the logic behind every claim. And you know that enough people try, that you can trust your colleagues’ work.

As a science journalist, most of the time, you can’t do those checks. You don’t even pretend you can. Instead, you build trust, like a tree.

You start with a grounding. A former scientist might trust their former colleagues, people they trusted, as a scientist, to do (and know) good work. A non-scientist has to start somewhere else. They might use prestige, looking up those tenured folks at Harvard or Princeton or Stanford. They might look to who other journalists trusted, scientists who’ve already been in the news. They might track journals or roles, assuming that a publication in Nature, or a position on a national grant committee, has a special meaning.

And if things stopped there, it would be a pretty elitist system. It still can be, and often is. But there is another step, which softens it.

The trust builds.

When I want to know if a paper in an unfamiliar field makes sense, if it’s worth covering, I try to ask someone I trust. Sometimes, they don’t know, and shrug. Other, more useful, times, they don’t know, but they have a suggestion: someone they trust, who can give me the answer.

And so I ask the new person, and now I trust someone more.

And suppose the new person says the new paper is good, and worth covering, good science and all that jazz.

Well, now I can trust its authors too, right?

So when the next paper comes, I now don’t just have that first someone. I have the person they recommended, and the authors of the previous paper.

The trust builds out, and up, like branches on a tree.

Practice, Don’t Memorize, Understand Justifications, Not Stories

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Teaching is one of those things that’s always controversial.

There seems to be a constant tug of war between two approaches. In one, thought of as old-fashioned and practical, students are expected to work hard, study to memorize facts and formulas, and end up with an impressive ability to reproduce the knowledge of the past. In the other, presented as more modern or more permissive, students aren’t supposed to memorize, but to understand, to get intuition for how things work, and are expected to end up more creative and analytical, able to come up with new ideas and understand things in ways their predecessors could not. This whole thing then gets muddled further with discussions of which skills actually matter in the modern day, with the technology of the hour standing in. If adults can use calculators, why should students be able to do arithmetic? If adults can use AI, why should students be able to draw, or write, or reason?

I’ve taught a little in my day, though likely less than I should. More frequently, I’ve learned. And, with apologies to the teachers and education experts who read this blog, I’ve got my own opinion.

I don’t think anyone in the old-fashioned/new-fashioned tug of war is thinking about education right.

People talk about memorization, when they should be talking about practice.

We want kids to be able to multiply and divide numbers. That’s not because they won’t have calculators. It’s because we want to teach them things that build on top of multiplying and dividing numbers. We want some of them to learn how to multiply and divide polynomials, and if you don’t know how to multiply and divide numbers, then learning to multiply and divide polynomials is almost impossible. We want some of them to learn abstract generalizations, groups and rings and fields, and if you’re not comfortable with the basics, then learning these is almost impossible. And for everyone, we want them to get used to making a logical argument why something is true, in a context where we can easily judge whether the argument works.

This doesn’t mean that we need students to memorize their times tables, though. It helps, sure. But we don’t actually care whether students can recite 5 times 7 equals 35, that’s not our end goal. Instead, we want to make sure that students can do these operations, and that they find them easy to do. And ultimately, that doesn’t come from memorization, but from practice. It comes from using the ideas, again and again, until it’s obvious how to step ahead to the results. You can’t replicate that with pure understanding, like some more modern approaches try to. You need the “muscle memory”, and that takes real practice. But you also can’t get there by memorizing isolated facts for an exam. You need to use them.

Understanding is important too, though. We need students to know the limits of their knowledge, not just what they’ve been taught but why it’s true. It’s the only way to get adults who can generalize, who can accept that maybe there is a type of math with numbers that square to zero without dismissing it as a plot to corrupt the youth. It’s the only way to get students who can go to the next level, and the next, and then generate new knowledge on their own.

But that understanding often gets left by the wayside, when teachers forget what it’s for. If you try to teach the Pythagorean theorem by showing a few examples, or tell students stories where different types of energy are different “stuff”, you’re trying to convey an intuitive understanding, but not the useful kind. What you’re trying to give the students is stories about how things work. But the kind of understanding we need students to have isn’t of stories. It’s of justifications, and arguments. Students should understand why what they are taught is true, and understanding why doesn’t mean having a feeling in their hearts about it: it means they can convince a skeptic.

It’s easier, for a world full of overworked teachers from a variety of backgrounds, to teach the simpler versions of these. It’s easy for a traditionalist teacher to drill their students on memorization, and test them on memorization. It’s easier for a sympathetic teacher to tell students stories, based on stories the teacher thinks they understand.

But if you want the traditionalist approach to work, you have to actually do things, to practice using ideas rather than merely know them, to have that experience down as reflexively as those times tables. And if you want the modern approach to work, you have to actually understand why what you’re teaching is true, the way you would convince a skeptic that it is true, and then convey those justifications to the students.

And if you, instead, are a student:

Don’t worry about memorizing facts, you’ll drill too hard and stress yourself out. Don’t worry about finding a comfortable story, because no story is true. Use the ideas you’re learning. Use them to convince yourself, and to convince others. Use them again and again, until you reach for them as easily as breathing. When you can use what you’re learning, and know why it holds, then you’re ready to move forward.

School Facts and Research Facts

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As you grow up, teachers try to teach you how the world works. This is more difficult than it sounds, because teaching you something is a much harder goal than just telling you something. A teacher wants you to remember what you’re told. They want you to act on it, and to generalize it. And they want you to do this not just for today’s material, but to set a foundation for next year, and the next. They’re setting you up for progress through a whole school system, with its own expectations.

Because of that, not everything a teacher tells you is, itself, a fact about the world. Some things you hear from teachers are liked the scaffolds on a building. They’re facts that only make sense in the context of school, support that lets you build to a point where you can learn other facts, and throw away the school facts that got you there.

Not every student uses all of that scaffolding, though. The scaffold has to be complete enough that some students can use it to go on, getting degrees in science or mathematics, and eventually becoming researchers where they use facts more deeply linked to the real world. But most students don’t become researchers. So the scaffold sits there, unused. And many people, as their lives move on, mistake the scaffold for the real world.

Here’s an example. How do you calculate something like this?

3+4\div (3-1)\times 5

From school, you might remember order of operations, or PEMDAS. First parentheses, then exponents, multiplication, division, addition, and finally subtraction. If you ran into that calculation in school, you could easily work it out.

But out of school, in the real world? Trick question, you never calculate something like that to begin with.

When I wrote this post, I had to look up how to write \div and \times. In the research world, people are far more likely to run into calculations like this:

3+5\frac{4}{3-1}

Here, it’s easier to keep track of what order you need to do things. In other situations, you might be writing a computer program (or an Excel spreadsheet formula, which is also a computer program). Then you follow that programming language’s rules for order of operations, which may or may not match PEMDAS.

PEMDAS was taught to you in school for good reason. It got you used to following rules to understand notation, and gave you tools the teachers needed to teach you other things. But it isn’t a fact about the universe. It’s a fact about school.

Once you start looking around for these “school facts”, they show up everywhere.

Are there really “three states of matter”, solid, liquid, and gas? Or four, if you add plasma? Well, sort of. There are real scientific definitions for solids, liquids, gases, and plasmas, and they play a real role in how people model big groups of atoms, “matter” in a quite specific sense. But they can’t be used to describe literally everything. If you start asking what state of matter light or spacetime is, you’ve substituted a simplification that was useful for school (“everything is one of three states of matter”) for the actual facts in the real world.

If you remember a bit further, maybe you remember there are two types of things, matter and energy? You might have even heard that matter and antimatter annihilate into energy. These are also just school facts, though. “Energy” isn’t something things are made of, it’s a property things have. Instead, your teachers were building scaffolding for understanding the difference between massive and massless particles, or between dark matter and dark energy. Each of those uses different concepts of matter and energy, and each in turn is different than the concept of matter in its states of solid, liquid, and gas. But in school, you need a consistent scaffold to learn, not a mess of different definitions for different applications. So unless you keep going past school, you don’t learn that.

Physics in school likes to work with forces, and forces do sometimes make an appearance in the real world, for example for engineers. But if you’re asking a question about fundamental physics, like “is gravity really a force?”, then you’re treating a school fact as if it was a research fact. Fundamental physics doesn’t care about forces in the same way. It uses different mathematical tools, like Lagrangians and Hamiltonians, to calculate the motion of objects in systems, and uses “force” in a pop science way to describe fundamental interactions.

If you get good enough at this, you can spot which things you learned in school were likely just scaffolding “school facts”, and which are firm enough that they may hold further. Any simple division of the world into categories is likely a school fact, one that let you do exercises on your homework but gets much more complicated when the real world gets involved. Contradictory or messy concepts are usually another sign, showing something fuzzy used to get students comfortable rather than something precise enough for professionals to use. Keep an eye out, and even if you don’t yet know the real facts, you’ll know enough to know what you’re missing.

On Theories of Everything and Cures for Cancer

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Some people are disappointed in physics. Shocking, I know!

Those people, when careful enough, clarify that they’re disappointed in fundamental physics: not the physics of materials or lasers or chemicals or earthquakes, or even the physics of planets and stars, but the physics that asks big fundamental questions, about the underlying laws of the universe and where they come from.

Some of these people are physicists themselves, or were once upon a time. These often have in mind other directions physicists should have gone. They think that, with attention and funding, their own ideas would have gotten us closer to our goals than the ideas that, in practice, got the attention and the funding.

Most of these people, though, aren’t physicists. They’re members of the general public.

It’s disappointment from the general public, I think, that feels the most unfair to physicists. The general public reads history books, and hears about a series of revolutions: Newton and Maxwell, relativity and quantum mechanics, and finally the Standard Model. They read science fiction books, and see physicists finding “theories of everything”, and making teleporters and antigravity engines. And they wonder what made the revolutions stop, and postponed the science fiction future.

Physicists point out, rightly, that this is an oversimplified picture of how the world works. Something happens between those revolutions, the kind of progress not simple enough to summarize for history class. People tinker away at puzzles, and make progress. And they’re still doing that, even for the big fundamental questions. Physicists know more about even faraway flashy topics like quantum gravity than they did ten years ago. And while physicists and ex-physicists can argue about whether that work is on the right path, it’s certainly farther along its own path than it was. We know things we didn’t know before, progress continues to be made. We aren’t at the “revolution” stage yet, or even all that close. But most progress isn’t revolutionary, and no-one can predict how often revolutions should take place. A revolution is never “due”, and thus can never be “overdue”.

Physicists, in turn, often don’t notice how normal this kind of reaction from the public is. They think people are being stirred up by grifters, or negatively polarized by excess hype, that fundamental physics is facing an unfair reaction only shared by political hot-button topics. But while there are grifters, and people turned off by the hype…this is also just how the public thinks about science.

Have you ever heard the phrase “a cure for cancer”?

Fiction is full of scientists working on a cure for cancer, or who discovered a cure for cancer, or were prevented from finding a cure for cancer. It’s practically a trope. It’s literally a trope.

It’s also a real thing people work on, in a sense. Many scientists work on better treatments for a variety of different cancers. They’re making real progress, even dramatic progress. As many whose loved ones have cancer know, it’s much more likely for someone with cancer to survive than it was, say, twenty years ago.

But those cures don’t meet the threshold for science fiction, or for the history books. They don’t move us, like the polio vaccine did, from a world where you know many people with a disease to a world where you know none. They don’t let doctors give you a magical pill, like in a story or a game, that instantly cures your cancer.

For the vast majority of medical researchers, that kind of goal isn’t realistic, and isn’t worth thinking about. The few that do pursue it work towards extreme long-term solutions, like periodically replacing everyone’s skin with a cloned copy.

So while you will run into plenty of media descriptions of scientists working on cures for cancer, you won’t see the kind of thing the public expects is an actual “cure for cancer”. And people are genuinely disappointed about this! “Where’s my cure for cancer?” is a complaint on the same level as “where’s my hovercar?” There are people who think that medical science has made no progress in fifty years, because after all those news articles, we still don’t have a cure for cancer.

I appreciate that there are real problems in what messages are being delivered to the public about physics, both from hypesters in the physics mainstream and grifters outside it. But put those problems aside, and a deeper issue remains. People understand the world as best they can, as a story. And the world is complicated and detailed, full of many people making incremental progress on many things. Compared to a story, the truth is always at a disadvantage.

Reminder to Physics Popularizers: “Discover” Is a Technical Term

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When a word has both an everyday meaning and a technical meaning, it can cause no end of confusion.

I’ve written about this before using one of the most common examples, the word “model”, which means something quite different in the phrases “large language model”, “animal model for Alzheimer’s” and “model train”. And I’ve written about running into this kind of confusion at the beginning of my PhD, with the word “effective”.

But there is one example I see crop up again and again, even with otherwise skilled science communicators. It’s the word “discover”.

“Discover”, in physics, has a technical meaning. It’s a first-ever observation of something, with an associated standard of evidence. In this sense, the LHC discovered the Higgs boson in 2012, and LIGO discovered gravitational waves in 2015. And there are discoveries we can anticipate, like the cosmic neutrino background.

But of course, “discover” has a meaning in everyday English, too.

You probably think I’m going to say that “discover”, in everyday English, doesn’t have the same statistical standards it does in physics. That’s true of course, but it’s also pretty obvious, I don’t think it’s confusing anybody.

Rather, there is a much more important difference that physicists often forget: in everyday English, a discovery is a surprise.

“Discover”, a word arguably popularized by Columbus’s discovery of the Americas, is used pretty much exclusively to refer to learning about something you did not know about yet. It can be minor, like discovering a stick of gum you forgot, or dramatic, like discovering you’ve been transformed into a giant insect.

Now, as a scientist, you might say that everything that hasn’t yet been observed is unknown, ready for discovery. We didn’t know that the Higgs boson existed before the LHC, and we don’t know yet that there is a cosmic neutrino background.

But just because we don’t know something in a technical sense, doesn’t mean it’s surprising. And if something isn’t surprising at all, then in everyday, colloquial English, people don’t call it a discovery. You don’t “discover” that the store has milk today, even if they sometimes run out. You don’t “discover” that a movie is fun, if you went because you heard reviews claim it would be, even if the reviews might have been wrong. You don’t “discover” something you already expect.

At best, maybe you could “discover” something controversial. If you expect to find a lost city of gold, and everyone says you’re crazy, then fine, you can discover the lost city of gold. But if everyone agrees that there is probably a lost city of gold there? Then in everyday English, it would be very strange to say that you were the one who discovered it.

With this in mind, the way physicists use the word “discover” can cause a lot of confusion. It can make people think, as with gravitational waves, that a “discovery” is something totally new, that we weren’t pretty confident before LIGO that gravitational waves exist. And it can make people get jaded, and think physicists are overhyping, talking about “discovering” this or that particle physics fact because an experiment once again did exactly what it was expected to.

My recommendation? If you’re writing for the general public, use other words. The LHC “decisively detected” the Higgs boson. We expect to see “direct evidence” of the cosmic neutrino background. “Discover” has baggage, and should be used with care.