Tag Archives: science communication

School Facts and Research Facts

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

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.

Where Are All These Views Coming From?

It’s been a weird year.

It’s been a weird year for many reasons, of course. But it’s been a particularly weird year for this blog.

To start, let me show you a more normal year, 2024:

Aside from a small uptick in January due to a certain unexpected announcement, this was a pretty typical year. I got 70-80 thousand views from 30-40 thousand unique visitors, spread fairly evenly throughout the year.

Now, take a look at 2025:

Something started happening this Fall. I went from getting 6000 views and 3000 visitors in a typical month, to roughly quintupling those numbers.

And for the life of me, I can’t figure out why.

WordPress, the site that hosts this blog, gives me tools to track where my viewers are coming from, and what they’re seeing.

It gives me a list of “referrers”, the other websites where people click on links to mine. Normally, this shows me where people are coming from: if I came up on a popular blog or reddit post, and people are following a link here. This year, though, looks totally normal. No new site is referring these people to me. Either the site they’re coming from is hidden, or they’re typing in my blog’s address by hand.

Looking at countries tells me a bit more. In a typical year, I get a bit under half of my views from the US, and the rest from a smattering of other English-speaking or European countries. This year, here’s what those stats look like:

So that tells me something. The new views appear to be coming from China. And what are these new viewers reading?

This year, my top post is a post from 2021, Reality as an Algebra of Observables. It wasn’t particularly popular when it came out, and while I liked the idea behind it, I don’t think I wrote it all that well. It’s not something that suddenly became relevant to the news, or to pop culture. It just suddenly started getting more and more and more views, this Fall:

In second place, a post about the 2022 Nobel Prize follows the same pattern. The pattern continues for a bit, but eventually the posts views get more uniform. My post France for Non-EU Spouses of EU Citizens, for example, has no weird pattern of increasing views: it’s just popular.

So far, this is weird. It gets weirder.

On a lark, I decided to look at the day-by-day statistics, rather than month-by-month. And before the growth really starts to show, I noticed something very strange.

In August, I had a huge number of views on August 1, a third of the month in one day. I had a new post out that day, but that post isn’t the one that gets the most views. Instead…it’s Reality as an Algebra of Observables.

That huge peak is a bit different from the later growth, though. It only shows in views, not in number of visitors. And it’s from the US, not China.

September, in comparison, looks normal. October looks like August, with a huge peak on October 3. This time, most of the views are still from the US, but a decent number are from China, and the visitors number is also higher.

In November, a few days in to the month, a new pattern kicks in:

Now, visitors and views are almost equal, as if each visitor shows up, looks at precisely one post, and leaves. The views are overwhelmingly from China, with 27 thousand out of 32 thousand views. And the most popular post, more popular even than my conveniently named 4gravitons.com homepage that usually tops the ratings…is Reality as an Algebra of Observables.

I don’t know what’s going on here, and I welcome speculation. Is this some extremely strange bot, accessing one unremarkable post of mine from a huge number of Chinese IP addresses? Or are there actual people reading this post? Was it shared on a Chinese social media app that WordPress can’t track? Maybe it’s part of a course?

For a while, I’d thought that if I somehow managed to get a lot more views, I could consider monetizing in some way, like opening a Patreon. History blogger Brett Deveraux gets around 140 thousand views on his top posts, and makes about three-quarters of his income from Patreon. If I could get a post a tenth as popular as his, maybe I could start making a little money from this blog?

The thing is, I can only do that if I have some idea of who’s viewing the blog, and what they want. And I don’t know why they want Reality as an Algebra of Observables.

Bonus Info For “Cosmic Paradox Reveals the Awful Consequence of an Observer-Free Universe”

I had a piece in Quanta Magazine recently, about a tricky paradox that’s puzzling quantum gravity researchers and some early hints at its resolution.

The paradox comes from trying to describe “closed universes”, which are universes where it is impossible to reach the edge, even if you had infinite time to do it. This could be because the universe wraps around like a globe, or because the universe is expanding so fast no traveler could ever reach an edge. Recently, theoretical physicists have been trying to describe these closed universes, and have noticed a weird issue: each such universe appears to have only one possible quantum state. In general, quantum systems have more possible states the more complex they are, so for a whole universe to have only one possible state is a very strange thing, implying a bizarrely simple universe. Most worryingly, our universe may well be closed. Does that mean that secretly, the real world has only one possible state?

There is a possible solution that a few groups are playing around with. The argument that a closed universe has only one state depends on the fact that nothing inside a closed universe can reach the edge. But if nothing can reach the edge, then trying to observe the universe as a whole from outside would tell you nothing of use. Instead, any reasonable measurement would have to come from inside the universe. Such a measurement introduces a new kind of “edge of the universe”, this time not in the far distance, but close by: the edge between an observer and the rest of the world. And when you add that edge to the calculations, the universe stops being closed, and has all the many states it ought to.

This was an unusually tricky story for me to understand. I narrowly avoided several misconceptions, and I’m still not sure I managed to dodge all of them. Likewise, it was unusually tricky for the editors to understand, and I suspect it was especially tricky for Quanta’s social media team to understand.

It was also, quite clearly, tricky for the readers to understand. So I thought I would use this post to clear up a few misconceptions. I’ll say a bit more about what I learned investigating this piece, and try to clarify what the result does and does not mean.

Q: I’m confused about the math terms you’re using. Doesn’t a closed set contain its boundary?

A: Annoyingly, what physicists mean by a closed universe is a bit different from what mathematicians mean by a closed manifold, which is in turn more restrictive than what mathematicians mean by a closed set. One way to think about this that helped me is that in an open set you can take a limit that takes you out of the set, which is like being able to describe a (possibly infinite) path that takes you “out of the universe”. A closed set doesn’t have that, every path, no matter how long, still ends up in the same universe.

Q: So a bunch of string theorists did a calculation and got a result that doesn’t make sense, a one-state universe. What if they’re just wrong?

A: Two things:

First, the people I talked to emphasized that it’s pretty hard to wiggle out of the conclusion. It’s not just a matter of saying you don’t believe in string theory and that’s that. The argument is based in pretty fundamental principles, and it’s not easy to propose a way out that doesn’t mess up something even more important.

That’s not to say it’s impossible. One of the people I interviewed, Henry Maxfield, thinks that some of the recent arguments are misunderstanding how to use one of their core techniques, in a way that accidentally presupposes the one-state universe.

But even he thinks that the bigger point, that closed universes have only one state, is probably true.

And that’s largely due to a second reason: there are older arguments that back the conclusion up.

One of the oldest dates back to John Wheeler, a physicist famous for both deep musings about the nature of space and time and coining evocative terms like “wormhole”. In the 1960’s, Wheeler argued that, in a theory where space and time can be curved, one should think of a system’s state as including every configuration it can evolve into over time, since it can be tricky to specify a moment “right now”. In a closed universe, you could expect a quantum system to explore every possible configuration…meaning that such a universe should be described by only one state.

Later, physicists studying holography ran into a similar conclusion. They kept noticing systems in quantum gravity where you can describe everything that happens inside by what happens on the edges. If there are no edges, that seems to suggest that in some sense there is nothing inside. Apparently, Lenny Susskind had a slide at the end of talks in the 90’s where he kept bringing up this point.

So even if the modern arguments are wrong, and even if string theory is wrong…it still looks like the overall conclusion is right.

Q: If a closed universe has only one state, does that make it deterministic, and thus classical?

A: Oh boy…

So, on the one hand, there is an idea, which I think also goes back to Wheeler, that asks: “if the universe as a whole has a wavefunction, how does it collapse?” One possibility is that the universe has only one state, so that nobody is needed to collapse the wavefunction, it already is in a definite state.

On the other hand, a universe with only one state does not actually look much like a classical universe. Our universe looks classical largely due to a process called decoherence, where small quantum systems interact with big quantum systems with many states, diluting quantum effects until the world looks classical. If there is only one state, there are no big systems to interact with, and the world has large quantum fluctuations that make it look very different from a classical universe.

Q: How, exactly, are you defining “observer”?

A: A few commenters helpfully chimed in to talk about how physics models observers as “witness” systems, objects that preserve some record of what happens to them. A simple example is a ball sitting next to a bowl: if you find the ball in the bowl later, it means something moved it. This process, preserving what happens and making it more obvious, is in essence how physicists think about observers.

However, this isn’t the whole story in this case. Here, different research groups introducing observers are doing it in different ways. That’s, in part, why none of them are confident they have the right answer.

One of the approaches describes an observer in terms of its path through space and time, its worldline. Instead of a detailed witness system with specific properties, all they do is pick out a line and say “the observer is there”. Identifying that line, and declaring it different from its surroundings, seems to be enough to recover the complexity the universe ought to have.

The other approach treats the witness system in a bit more detail. We usually treat an observer in quantum mechanics as infinitely large compared to the quantum systems they measure. This approach instead gives the observer a finite size, and uses that to estimate how far their experience will be from classical physics.

Crucially, both approaches aren’t a matter of defining a physical object, and looking for it in the theory. Given a collection of atoms, neither team can tell you what is an observer, and what isn’t. Instead, in each approach, the observer is arbitrary: a choice, made by us when we use quantum mechanics, of what to count as an observer and what to count as the rest of the world. That choice can be made in many different ways, and each approach tries to describe what happens when you change that choice.

This is part of what makes this approach uncomfortable to some more philosophically-minded physicists: it treats observers not as a predictable part of the physical world, but as a mathematical description used to make statements about the world.

Q: If these ideas come from AdS/CFT, which is an open universe, how do you use them to describe a closed universe?

A: While more examples emerged later, initially theorists were thinking about two types of closed universes:

First, think about a black hole. You may have heard that when you fall into a black hole, you watch the whole universe age away before your eyes, due to the dramatic differences in the passage of time caused by the extreme gravity. Once you’ve seen the outside universe fade away, you are essentially in a closed universe of your own. The outside world will never affect you again, and you are isolated, with no path to the outside. These black hole interiors are one of the examples theorists looked at.

The other example are so-called “baby universes”. When physicists use quantum mechanics to calculate the chance of something happening, they have to add up every possible series of events that could have happened in between. For quantum gravity, this includes every possible arrangement of space and time. This includes arrangements with different shapes, including ones with tiny extra “baby universes” which branch off from the main universe and return. Universes with these “baby universes” are another example that theorists considered to understand closed universes.

Q: So wait, are you actually saying the universe needs to be observed to exist? That’s ridiculous, didn’t the universe exist long before humans existed to observe it? Is this some sort of Copenhagen Interpretation thing, or that thing called QBism?

You’re starting to ask philosophical questions, and here’s the thing:

There are physicists who spend their time thinking about how to interpret quantum mechanics. They talk to philosophers, and try to figure out how to answer these kinds of questions in a consistent and systematic way, keeping track of all the potential pitfalls and implications. They’re part of a subfield called “quantum foundations”.

The physicists whose work I was talking about in that piece are not those people.

Of the people I interviewed, one of them, Rob Myers, probably has lunch with quantum foundations researchers on occasion. The others, based at places like MIT and the IAS, probably don’t even do that.

Instead, these are people trying to solve a technical problem, people whose first inclination is to put philosophy to the side, and “shut up and calculate”. These people did a calculation that ought to have worked, checking how many quantum states they could find in a closed universe, and found a weird and annoying answer: just one. Trying to solve the problem, they’ve done technical calculation work, introducing a path through the universe, or a boundary around an observer, and seeing what happens. While some of them may have their own philosophical leanings, they’re not writing works of philosophy. Their papers don’t talk through the philosophical implications of their ideas in all that much detail, and they may well have different thoughts as to what those implications are.

So while I suspect I know the answers they would give to some of these questions, I’m not sure.

Instead, how about I tell you what I think?

I’m not a philosopher, I can’t promise my views will be consistent, that they won’t suffer from some pitfall. But unlike other people’s views, I can tell you what my own views are.

To start off: yes, the universe existed before humans. No, there is nothing special about our minds, we don’t have psychic powers to create the universe with our thoughts or anything dumb like that.

What I think is that, if we want to describe the world, we ought to take lessons from science.

Science works. It works for many reasons, but two important ones stand out.

Science works because it leads to technology, and it leads to technology because it guides actions. It lets us ask, if I do this, what will happen? What will I experience?

And science works because it lets people reach agreement. It lets people reach agreement because it lets us ask, if I observe this, what do I expect you to observe? And if we agree, we can agree on the science.

Ultimately, if we want to describe the world with the virtues of science, our descriptions need to obey this rule: they need to let us ask “what if?” questions about observations.

That means that science cannot avoid an observer. It can often hide the observer, place them far away and give them an infinite mind to behold what they see, so that one observer is essentially the same as another. But we shouldn’t expect to always be able to do this. Sometimes, we can’t avoid saying something about the observer: about where they are, or how big they are, for example.

These observers, though, don’t have to actually exist. We should be able to ask “what if” questions about others, and that means we should be able to dream up fictional observers, and ask, if they existed, what would they see? We can imagine observers swimming in the quark-gluon plasma after the Big Bang, or sitting inside a black hole’s event horizon, or outside our visible universe. The existence of the observer isn’t a physical requirement, but a methodological one: a restriction on how we can make useful, scientific statements about the world. Our theory doesn’t have to explain where observers “come from”, and can’t and shouldn’t do that. The observers aren’t part of the physical world being described, they’re a precondition for us to describe that world.

Is this the Copenhagen Interpretation? I’m not a historian, but I don’t think so. The impression I get is that there was no real Copenhagen Interpretation, that Bohr and Heisenberg, while more deeply interested in philosophy than many physicists today, didn’t actually think things through in enough depth to have a perspective you can name and argue with.

Is this QBism? I don’t think so. It aligns with some things QBists say, but they say a lot of silly things as well. It’s probably some kind of instrumentalism, for what that’s worth.

Is it logical positivism? I’ve been told logical positivists would argue that the world outside the visible universe does not exist. If that’s true, I’m not a logical positivist.

Is it pragmatism? Maybe? What I’ve seen of pragmatism definitely appeals to me, but I’ve seen my share of negative characterizations as well.

In the end, it’s an idea about what’s useful and what’s not, about what moves science forward and what doesn’t. It tries to avoid being preoccupied with unanswerable questions, and as much as possible to cash things out in testable statements. If I do this, what happens? What if I did that instead?

The results I covered for Quanta, to me, show that the observer matters on a deep level. That isn’t a physical statement, it isn’t a mystical statement. It’s a methodological statement: if we want to be scientists, we can’t give up on the observer.

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

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.

Explain/Teach/Advocate

Scientists have different goals when they communicate, leading to different styles, or registers, of communication. If you don’t notice what register a scientist is using, you might think they’re saying something they’re not. And if you notice someone using the wrong register for a situation, they may not actually be a scientist.

Sometimes, a scientist is trying to explain an idea to the general public. The point of these explanations is to give you appreciation and intuition for the science, not to understand it in detail. This register makes heavy use of metaphors, and sometimes also slogans. It should almost never be taken literally, and a contradiction between two different scientist explanations usually just means they are using incompatible metaphors for the same concept. Sometimes, scientists who do this a lot will comment on other metaphors you might have heard, referencing other slogans to help explain what those explanations miss. They do this knowing that they do, in the end, agree on the actual science: they’re just trying to give you another metaphor, with a deeper intuition for a neglected part of the story.

Other times, scientists are trying to teach a student to be able to do something. Teaching can use metaphors or slogans as introductions, but quickly moves past them, because it wants to show the students something they can use: an equation, a diagram, a classification. If a scientist shows you any of these equations/diagrams/classifications without explaining what they mean, then you’re not the student they had in mind: they had designed their lesson for someone who already knew those things. Teaching may convey the kinds of appreciation and intuition that explanations for the general public do, but that goal gets much less emphasis. The main goal is for students with the appropriate background to learn to do something new.

Finally, sometimes scientists are trying to advocate for a scientific point. In this register, and only in this register, are they trying to convince people who don’t already trust them. This kind of communication can include metaphors and slogans as decoration, but the bulk will be filled with details, and those details should constitute evidence: they should be a structured argument, one that lays out, scientifically, why others should come to the same conclusion.

A piece that tries to address multiple audiences can move between registers in a clean way. But if the register jumps back and forth, or if the wrong register is being used for a task, that usually means trouble. That trouble can be simple boredom, like a scientist’s typical conference talk that can’t decide whether it just wants other scientists to appreciate the work, whether it wants to teach them enough to actually use it, or whether it needs to convince any skeptics. It can also be more sinister: a lot of crackpots write pieces that are ostensibly aimed at convincing other scientists, but are almost entirely metaphors and slogans, pieces good at tugging on the general public’s intuition without actually giving scientists anything meaningful to engage with.

If you’re writing, or speaking, know what register you need to use to do what you’re trying to do! And if you run into a piece that doesn’t make sense, consider that it might be in a different register than you thought.

Newsworthiness Bias

I had a chat about journalism recently, and I had a realization about just how weird science journalism, in particular, is.

Journalists aren’t supposed to be cheerleaders. Journalism and PR have very different goals (which is why I keep those sides of my work separate). A journalist is supposed to be uncompromising, to write the truth even if it paints the source in a bad light.

Norms are built around this. Serious journalistic outlets usually don’t let sources see pieces before they’re published. The source doesn’t have the final say in how they’re portrayed: the journalist reserves the right to surprise them if justified. Investigative journalists can be superstars, digging up damning secrets about the powerful.

When a journalist starts a project, the piece might turn out positive, or negative. A politician might be the best path forward, or a disingenuous grifter. A business might be a great investment opportunity, or a total scam. A popular piece of art might be a triumph, or a disappointment.

And a scientific result?

It might be a fraud, of course. Scientific fraud does exist, and is a real problem. But it’s not common, really. Pick a random scientific paper, filter by papers you might consider reporting on in the first place, and you’re very unlikely to find a fraudulent result. Science journalists occasionally report on spectacularly audacious scientific frauds, or frauds in papers that have already made the headlines. But you don’t expect fraud in the average paper you cover.

It might be scientifically misguided: flawed statistics, a gap in a proof, a misuse of concepts. Journalists aren’t usually equipped to ferret out these issues, though. Instead, this is handled in principle by peer review, and in practice by the scientific community outside of the peer review process.

Instead, for a scientific result, the most common negative judgement isn’t that it’s a lie, or a mistake. It’s that it’s boring.

And certainly, a good science journalist can judge a paper as boring. But there is a key difference between doing that, and judging a politician as crooked or a popular work of art as mediocre. You can write an article about the lying candidate for governor, or the letdown Tarantino movie. But if a scientific result is boring, and nobody else has covered it…then it isn’t newsworthy.

In science, people don’t usually publish their failures, their negative results, their ho-hum obvious conclusions. That fills the literature with only the successes, a phenomenon called publication bias. It also means, though, that scientists try to make their results sound more successful, more important and interesting, than they actually are. Some of the folks fighting the replication crisis have coined a term for this: they call it importance hacking.

The same incentives apply to journalists, especially freelancers. Starting out, it was far from clear that I could make enough to live on. I felt like I had to make every lead count, to find a newsworthy angle on every story idea I could find, because who knew when I would find another one? Over time, I learned to balance that pull better. Now that I’m making most of my income from consulting instead, the pressure has eased almost entirely: there are things I’m tempted to importance-hack for the sake of friends, but nothing that I need to importance-hack to stay in the black.

Doing journalism on the side may be good for me personally at the moment, but it’s not really a model. Much like we need career scientists, even if their work is sometimes boring, we need career journalists, even if they’re sometimes pressured to overhype.

So if we don’t want to incentivize science journalists to be science cheerleaders, what can we do instead?

In science, one way to address publication bias is with pre-registered studies. A scientist sets out what they plan to test, and a journal agrees to publish the result, no matter what it is. You could imagine something like this for science journalism. I once proposed a recurring column where every month I would cover a random paper from arXiv.org, explaining what it meant to accomplish. I get why the idea was turned down, but I still think about it.

In journalism, the arts offer the closest parallel with a different approach. There are many negative reviews of books, movies, and music, and most of them merely accuse the art of being boring, not evil. These exist because they focus on popular works that people pay attention to anyway, so that any negative coverage has someone to convince. You could imagine applying this model to science, though it could be a bit silly. I’m envisioning a journalist who writes an article every time Witten publishes, rating some papers impressive and others disappointing, the same way a music journalist might cover every Taylor Swift album.

Neither of these models are really satisfactory. You could imagine an even more adversarial model, where journalists run around accusing random scientists of wasting the government’s money, but that seems dramatically worse.

So I’m not sure. Science is weird, and hard to accurately value: if we knew how much something mattered already, it would be engineering, not science. Journalism is weird: it’s public-facing research, where the public facing is the whole point. Their combination? Even weirder.

Hype, Incentives, and Culture

To be clear, hype isn’t just lying.

We have a word for when someone lies to convince someone else to pay them, and that word is fraud. Most of what we call hype doesn’t reach that bar.

Instead, hype lives in a gray zone of affect and metaphor.

Some hype is pure affect. It’s about the subjective details, it’s about mood. “This is amazing” isn’t a lie, or at least, isn’t a lie you can check. They might really be amazed!

Some hype relies on metaphor. A metaphor can’t really be a lie, because a metaphor is always incomplete. But a metaphor can certainly be misleading. It can associate something minor with something important, or add emotional valence that isn’t really warranted.

Hype lies in a gray zone…and precisely because it lives in a gray zone, not everything that looks like hype is intended to be type.

We think of hype as a consequence of incentives. Scientists hype their work to grant committees to get grants, and hype it more to the public for prestige. Companies hype their products to sell them, and their business plans to draw in investors.

But what looks like hype can also be language, and culture.

To many people in the rest of the world, the way Americans talk about almost everything is hype. Everything is bigger and nicer and cooler. This isn’t because Americans are under some sort of weird extra career incentives, though. It’s just how they expect to talk, how they learned to talk, how everyone around them normally talks.

Similarly, people in different industries are used to talking differently. Depending on what work you do, you interpret different metaphors in different ways. What might seem like an enthusiastic endorsement in one industry might be dismissive in another.

In the end, it takes two to communicate: a speaker, and an audience. Speakers want to get their audience excited, and hopefully, if they don’t want to hype, to understand something of the truth. That means understanding how the audience communicates enthusiasm, and how it differs from the speaker. It means understanding language, and culture.

Bonus Info on the LHC and Beyond

Three of my science journalism pieces went up last week!

(This is a total coincidence. One piece was a general explainer “held in reserve” for a nice slot in the schedule, one was a piece I drafted in February, while the third I worked on in May. In journalism, things take as long as they take.)

The shortest piece, at Quanta Magazine, was an explainer about the two types of particles in physics: bosons, and fermions.

I don’t have a ton of bonus info here, because of how tidy the topic is, so just two quick observations.

First, I have the vague impression that Bose, bosons’ namesake, is “claimed” by both modern-day Bangladesh and India. I had friends in grad school who were proud of their fellow physicist from Bangladesh, but while he did his most famous work in Dhaka, he was born and died in Calcutta. Since both were under British India for most of his life, these things likely get complicated.

Second, at the end of the piece I mention a “world on a wire” where fermions and bosons are the same. One example of such a “wire” is a string, like in string theory. One thing all young string theorists learn is “bosonization”: the idea that, in a 1+1-dimensional world like a string, you can re-write any theory with fermions as a theory with bosons, as well as vice versa. This has important implications for how string theory is set up.

Next, in Ars Technica, I had a piece about how LHC physicists are using machine learning to untangle the implications of quantum interference.

As a journalist, it’s really easy to fall into a trap where you give the main person you interview too much credit: after all, you’re approaching the story from their perspective. I tried to be cautious about this, only to be stymied when literally everyone else I interviewed praised Aishik Ghosh to the skies and credited him with being the core motivating force behind the project. So I shrugged my shoulders and followed suit. My understanding is that he has been appropriately rewarded and will soon be a professor at Georgia Tech.

I didn’t list the inventors of the NSBI method that Ghosh and co. used, but names like Kyle Cranmer and Johann Brehmer tend to get bandied about. It’s a method that was originally explored for a more general goal, trying to characterize what the Standard Model might be missing, while the work I talk about in the piece takes it in a new direction, closer to the typical things the ATLAS collaboration looks for.

I also did not say nearly as much as I was tempted to about how the ATLAS collaboration publishes papers, which was honestly one of the most intriguing parts of the story for me. There is a huge amount of review that goes on inside ATLAS before one of their papers reaches the outside world, way more than there ever is in a journal’s peer review process. This is especially true for “physics papers”, where ATLAS is announcing a new conclusion about the physical world, as ATLAS’s reputation stands on those conclusions being reliable. That means starting with an “internal note” that’s hundreds of pages long (and sometimes over a thousand), an editorial board that manages the editing process, disseminating the paper to the entire collaboration for comment, and getting specific experts and institute groups within the collaboration to read through the paper in detail. The process is a bit less onerous for “technical papers”, which describe a new method, not a new conclusion about the world. Still, it’s cumbersome enough that for those papers, often scientists don’t publish them “within ATLAS” at all, instead releasing them independently. The results I reported on are special because they involved a physics paper and a technical paper, both within the ATLAS collaboration process. Instead of just working with partial or simplified data, they wanted to demonstrate the method on a “full analysis”, with all the computation and human coordination that requires. Normally, ATLAS wouldn’t go through the whole process of publishing a physics paper without basing it on new data, but this was different: the method had the potential to be so powerful that the more precise results would be worth stating as physics results alone.

(Also, for the people in the comments worried about training a model on old data: that’s not what they did. In physics, they don’t try to train a neural network model to predict the results of colliders, such a model wouldn’t tell us anything useful. They run colliders to tell us whether what they see matches the analytic, Standard, model. The neural network is trained to predict not what the experiment will say, but what the Standard Model will say, as we can usually only figure that out through time-consuming simulations. So it’s trained on (new) simulations, not on experimental data.)

Finally, on Friday I had a piece in Physics Today about the European Strategy for Particle Physics (or ESPP), and in particular, plans for the next big collider.

Before I even started working on this piece, I saw a thread by Patrick Koppenburg on some of the 263 documents submitted for the ESPP update. While my piece ended up mostly focused on the big circular collider plan that most of the field is converging on (the future circular collider, or FCC), Koppenburg’s thread was more wide-ranging, meant to illustrate the breadth of ideas under discussion. Some of that discussion is about the LHC’s current plans, like its “high-luminosity” upgrade that will see it gather data at much higher rates up until 2040. Some of it is assessing broader concerns, which it may surprise some of you to learn includes sustainability: yes, there are more or less sustainable ways to build giant colliders.

The most fun part of the discussion, though, concerns all of the other collider proposals.

Some report progress on new technologies. Muon colliders are the most famous of these, but there are other proposals that would specifically help with a linear collider. I never did end up understanding what Cooled Copper Colliders are all about, beyond that they let you get more energy in a smaller machine without super-cooling. If you know about them, chime in in the comments! Meanwhile, plasma wakefield acceleration could accelerate electrons on a wave of plasma. This has the disadvantage that you want to collide electrons and positrons, and if you try to stick a positron in plasma it will happily annihilate with the first electron it meets. So what do you do? You go half-and-half, with the HALHF project: speed up the electron with a plasma wakefield, accelerate the positron normally, and have them meet in the middle.

Others are backup plans, or “budget options”, where CERN could get a bit better measurements on some parameters if they can’t stir up the funding to measure the things they really want. They could put electrons and positrons into the LHC tunnel instead of building a new one, for a weaker machine that could still study the Higgs boson to some extent. They could use a similar experiment to produce Z bosons instead, which could serve as a bridge to a different collider project. Or, they could collider the LHC’s proton beam with an electron beam, for an experiment that mixes advantages and disadvantages of some of the other approaches.

While working on the piece, one resource I found invaluable was this colloquium talk by Tristan du Pree, where he goes through the 263 submissions and digs up a lot of interesting numbers and commentary. Read the slides for quotes from the different national inputs and “solo inputs” with comments from particular senior scientists. I used that talk to get a broad impression of what the community was feeling, and it was interesting how well it was reflected in the people I interviewed. The physicist based in Switzerland felt the most urgency for the FCC plan, while the Dutch sources were more cautious, with other Europeans firmly in the middle.

Going over the FCC report itself, one thing I decided to leave out of the discussion was the cost-benefit analysis. There’s the potential for a cute sound-bite there, “see, the collider is net positive!”, but I’m pretty skeptical of the kind of analysis they’re doing there, even if it is standard practice for government projects. Between the biggest benefits listed being industrial benefits to suppliers and early-career researcher training (is a collider unusually good for either of those things, compared to other ways we spend money?) and the fact that about 10% of the benefit is the science itself (where could one possibly get a number like that?), it feels like whatever reasoning is behind this is probably the kind of thing that makes rigor-minded economists wince. I wasn’t able to track down the full calculation though, so I really don’t know, maybe this makes more sense than it looks.

I think a stronger argument than anything along those lines is a much more basic point, about expertise. Right now, we have a community of people trying to do something that is not merely difficult, but fundamental. This isn’t like sending people to space, where many of the engineering concerns will go away when we can send robots instead. This is fundamental engineering progress in how to manipulate the forces of nature (extremely powerful magnets, high voltages) and process huge streams of data. Pushing those technologies to the limit seems like it’s going to be relevant, almost no matter what we end up doing. That’s still not putting the science first and foremost, but it feels a bit closer to an honest appraisal of what good projects like this do for the world.

Branching Out, and Some Ground Rules

In January, my time at the Niels Bohr Institute ended. Instead of supporting myself by doing science, as I’d done the last thirteen or so years, I started making a living by writing, doing science journalism.

That work picked up. My readers here have seen a few of the pieces already, but there are lots more in the pipeline, getting refined by editors or waiting to be published. It’s given me a bit of income, and a lot of visibility.

That visibility, in turn, has given me new options. It turns out that magazines aren’t the only companies interested in science writing, and journalism isn’t the only way to write for a living. Companies that invest in science want a different kind of writing, one that builds their reputation both with the public and with the scientific community. And as I’ve discovered, if you have enough of a track record, some of those companies will reach out to you.

So I’m branching out, from science journalism to science communications consulting, advising companies how to communicate science. I’ve started working with an exciting client, with big plans for the future. If you follow me on LinkedIn, you’ll have seen a bit about who they are and what I’ll be doing for them.

Here on the blog, I’d like to maintain a bit more separation. Blogging is closer to journalism, and in journalism, one ought to be careful about conflicts of interest. The advice I’ve gotten is that it’s good to establish some ground rules, separating my communications work from my journalistic work, since I intend to keep doing both.

So without further ado, my conflict of interest rules:

  • I will not write in a journalistic capacity about my consulting clients, or their direct competitors.
  • I will not write in a journalistic capacity about the technology my clients are investing in, except in extremely general terms. (For example, most businesses right now are investing in AI. I’ll still write about AI in general, but not about any particular AI technologies my clients are pursuing.)
  • I will more generally maintain a distinction between areas I cover journalistically and areas where I consult. Right now, this means I avoid writing in a journalistic capacity about:
    • Health/biomedical topics
    • Neuroscience
    • Advanced sensors for medical applications

I plan to update these rules over time as I get a better feeling for what kinds of conflict of interest risks I face and what my clients are comfortable with. I now have a Page for this linked in the top menu, clients and editors can check there to see my current conflict of interest rules.