Tag Archives: press

Post on the Weak Gravity Conjecture for FirstPrinciples.org

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I have another piece this week on the FirstPrinciples.org Hub. If you’d like to know who they are, I say a bit about my impressions of them in my post on the last piece I had there. They’re still finding their niche, so there may be shifts in the kind of content they cover over time, but for now they’ve given me an opportunity to cover a few topics that are off the beaten path.

This time, the piece is what we in the journalism biz call an “explainer”. Instead of interviewing people about cutting-edge science, I wrote a piece to explain an older idea. It’s an idea that’s pretty cool, in a way I think a lot of people can actually understand: a black hole puzzle that might explain why gravity is the weakest force. It’s an idea that’s had an enormous influence, both in the string theory world where it originated and on people speculating more broadly about the rules of quantum gravity. If you want to learn more, read the piece!

Since I didn’t interview anyone for this piece, I don’t have the same sort of “bonus content” I sometimes give. Instead of interviewing, I brushed up on the topic, and the best resource I found was this review article written by Dan Harlow, Ben Heidenreich, Matthew Reece, and Tom Rudelius. It gave me a much better idea of the subtleties: how many different ways there are to interpret the original conjecture, and how different attempts to build on it reflect on different facets and highlight different implications. If you are a physicist curious what the whole thing is about, I recommend reading that review: while I try to give a flavor of some of the subtleties, a piece for a broad audience can only do so much.

This Week, at FirstPrinciples.org

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I’ve got a piece out this week in a new venue: FirstPrinciples.org, where I’ve written a profile of a startup called Vaire Computing.

Vaire works on reversible computing, an idea that tries to leverage thermodynamics to make a computer that wastes as little heat as possible. While I learned a lot of fun things that didn’t make it into the piece…I’m not going to tell you them this week! That’s because I’m working on another piece about reversible computing, focused on a different aspect of the field. When that piece is out I’ll have a big “bonus material post” talking about what I learned writing both pieces.

This week, instead, the bonus material is about FirstPrinciples.org itself, where you’ll be seeing me write more often in future. The First Principles Foundation was founded by Ildar Shar, a Canadian tech entrepreneur who thinks that physics is pretty cool. (Good taste that!) His foundation aims to support scientific progress, especially in addressing the big, fundamental questions. They give grants, analyze research trends, build scientific productivity tools…and most relevantly for me, publish science news on their website, in a section called the Hub.

The first time I glanced through the Hub, it was clear that FirstPrinciples and I have a lot in common. Like me, they’re interested both in scientific accomplishments and in the human infrastructure that makes them possible. They’ve interviewed figures in the open access movement, like the creators of arXiv and SciPost. On the science side, they mix coverage of the mainstream and reputable with outsiders challenging the status quo, and hot news topics with explainers of key concepts. They’re still new, and still figuring out what they want to be. But from my glimpse on the way, it looks like they’re going somewhere good.

Science Journalism Tasting Notes

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When you’ve done a lot of science communication you start to see patterns. You notice the choices people make when they write a public talk or a TV script, the different goals and practical constraints that shape a piece. I’ve likened it to watching an old kung fu movie and seeing where the wires are.

I don’t have a lot of experience doing science journalism, I can’t see the wires yet. But I’m starting to notice things, subtle elements like notes at a wine-tasting. Just like science communication by academics, science journalism is shaped by a variety of different goals.

First, there’s the need for news to be “new”. A classic news story is about something that happened recently, or even something that’s happening right now. Historical stories usually only show up as new “revelations”, something the journalist or a researcher recently dug up. This isn’t a strict requirement, and it seems looser in science journalism than in other types of journalism: sometimes you can have a piece on something cool the audience might not know, even if it’s not “new”. But it shapes how things are covered, it means that a piece on something old will often have something tying it back to a recent paper or an ongoing research topic.

Then, a news story should usually also be a “story”. Science communication can sometimes involve a grab-bag of different topics, like a TED talk that shows off a few different examples. Journalistic pieces often try to deliver one core message, with details that don’t fit the narrative needing to wait for another piece where they fit better. You might be tempted to round this off to saying that journalists are better writers than academics, since it’s easier for a reader to absorb one message than many. But I think it also ties to the structure. Journalists do have content with multiple messages, it just usually is not published as one story, but a thematic collection of stories.

Combining those two goals, there’s a tendency for news to focus on what happened. “First they had the idea, then there were challenges, then they made their discovery, now they look to the future.” You can’t just do that, though, because of another goal: pedagogy. Your audience doesn’t know everything you know. In order for them to understand what happened, there are often other things they have to understand. In non-science news, this can sometimes be brief, a paragraph that gives the background for people who have been “living under a rock”. In science news, there’s a lot more to explain. You have to teach something, and teaching well can demand a structure very different from the one-step-at a time narrative of what happened. Balancing these two is tricky, and it’s something I’m still learning how to do, as can be attested by the editors who’ve had to rearrange some of my pieces to make the story flow better.

News in general cares about being independent, about journalists who figure out the story and tell the truth regardless of what the people in power are saying. Science news is strange because, if a scientist gets covered at all, it’s almost always positive. Aside from the occasional scandal or replication crisis, science news tends to portray scientific developments as valuable, “good news” rather than “bad news”. If you’re a politician or a company, hearing from a journalist might make you worry. If you say the wrong thing, you might come off badly. If you’re a scientist, your biggest worry is that a journalist might twist your words into a falsehood that makes your work sound too good. On the other hand, a journalist who regularly publishes negative things about scientists would probably have a hard time finding scientists to talk to! There are basic journalistic ethics questions here that one probably learns about at journalism school and we who sneak in with no training have to learn another way.

These are the flavors I’ve tasted so far: novelty and narrative vs. education, positivity vs. accuracy. I’ll doubtless see more over the years, and go from someone who kind of knows what they’re doing to someone who can mentor others. With that in mind, I should get to writing!

Ways Freelance Journalism Is Different From Academic Writing

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A while back, I was surprised when I saw the writer of a well-researched webcomic assume that academics are paid for their articles. I ended up writing a post explaining how academic publishing actually works.

Now that I’m out of academia, I’m noticing some confusion on the other side. I’m doing freelance journalism, and the academics I talk to tend to have some common misunderstandings. So academics, this post is for you: a FAQ of questions I’ve been asked about freelance journalism. Freelance journalism is more varied than academia, and I’ve only been doing it a little while, so all of my answers will be limited to my experience.

Q: What happens first? Do they ask you to write something? Do you write an article and send it to them?

Academics are used to writing an article, then sending it to a journal, which sends it out to reviewers to decide whether to accept it. In freelance journalism in my experience, you almost never write an article before it’s accepted. (I can think of one exception I’ve run into, and that was for an opinion piece.)

Sometimes, an editor reaches out to a freelancer and asks them to take on an assignment to write a particular sort of article. This happens more freelancers that have been working with particular editors for a long time. I’m new to this, so the majority of the time I have to “pitch”. That means I email an editor describing the kind of piece I want to write. I give a short description of the topic and why it’s interesting. If the editor is interested, they’ll ask some follow-up questions, then tell me what they want me to focus on, how long the piece should be, and how much they’ll pay me. (The last two are related, many places pay by the word.) After that, I can write a draft.

Q: Wait, you’re paid by the word? Then why not make your articles super long, like Victor Hugo?

I’m paid per word assigned, not per word in the finished piece. The piece doesn’t have to strictly stick to the word limit, but it should be roughly the right size, and I work with the editor to try to get it there. In practice, places seem to have a few standard size ranges and internal terminology for what they are (“blog”, “essay”, “short news”, “feature”). These aren’t always the same as the categories readers see online. Some places have a web page listing these categories for prospective freelancers, but many don’t, so you have to either infer them from the lengths of articles online or learn them over time from the editors.

Q: Why didn’t you mention this important person or idea?

Because pieces pay more by the word, it’s easier as a freelancer to sell shorter pieces than longer ones. For science news, favoring shorter pieces also makes some pedagogical sense. People usually take away only a few key messages from a piece, if you try to pack in too much you run a serious risk of losing people. After I’ve submitted a draft, I work with the editor to polish it, and usually that means cutting off side-stories and “by-the-ways” to make the key points as vivid as possible.

Q: Do you do those cool illustrations?

Academia has a big focus on individual merit. The expectation is that when you write something, you do almost all of the work yourself, to the extent that more programming-heavy fields like physics and math do their own typesetting.

Industry, including journalism, is more comfortable delegating. Places will generally have someone on-staff to handle illustrations. I suggest diagrams that could be helpful to the piece and do a sketch of what they could look like, but it’s someone else’s job to turn that into nice readable graphic design.

Q: Why is the title like that? Why doesn’t that sound like you?

Editors in journalistic outlets are much more involved than in academic journals. Editors won’t just suggest edits, they’ll change wording directly and even input full sentences of their own. The title and subtitle of a piece in particular can change a lot (in part because they impact SEO), and in some places these can be changed by the editor quite late in the process. I’ve had a few pieces whose title changed after I’d signed off on them, or even after they first appeared.

Q: Are your pieces peer-reviewed?

The news doesn’t have peer review, no. Some places, like Quanta Magazine, do fact-checking. Quanta pays independent fact-checkers for longer pieces, while for shorter pieces it’s the writer’s job to verify key facts, confirming dates and the accuracy of quotes.

Q: Can you show me the piece before it’s published, so I can check it?

That’s almost never an option. Journalists tend to have strict rules about showing a piece before it’s published, related to more political areas where they want to preserve the ability to surprise wrongdoers and the independence to find their own opinions. Science news seems like it shouldn’t require this kind of thing as much, it’s not like we normally write hit pieces. But we’re not publicists either.

In a few cases, I’ve had people who were worried about something being conveyed incorrectly, or misleadingly. For those, I offer to do more in the fact-checking stage. I can sometimes show you quotes or paraphrase how I’m describing something, to check whether I’m getting something wrong. But under no circumstances can I show you the full text.

Q: What can I do to make it more likely I’ll get quoted?

Pieces are short, and written for a general, if educated, audience. Long quotes are harder to use because they eat into word count, and quotes with technical terms are harder to use because we try to limit the number of terms we ask the reader to remember. Quotes that mention a lot of concepts can be harder to find a place for, too: concepts are introduced gradually over the piece, so a quote that mentions almost everything that comes up will only make sense to the reader at the very end.

In a science news piece, quotes can serve a couple different roles. They can give authority, an expert’s judgement confirming that something is important or real. They can convey excitement, letting the reader see a scientist’s emotions. And sometimes, they can give an explanation. This last only happens when the explanation is very efficient and clear. If the journalist can give a better explanation, they’re likely to use that instead.

So if you want to be quoted, keep that in mind. Try to say things that are short and don’t use a lot of technical jargon or bring in too many concepts at once. Convey judgement, which things are important and why, and convey passion, what drives you and excited you about a topic. I am allowed to edit quotes down, so I can take a piece of a longer quote that’s cleaner or cut a long list of examples from an otherwise compelling statement. I can correct grammar and get rid of filler words and obvious mistakes. But I can’t put words in your mouth, I have to work with what you actually said, and if you don’t say anything I can use then you won’t get quoted.

Freelancing in [Country That Includes Greenland]

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(Why mention Greenland? It’s a movie reference.)

I figured I’d give an update on my personal life.

A year ago, I resigned from my position in France and moved back to Denmark. I had planned to spend a few months as a visiting researcher in my old haunts at the Niels Bohr Institute, courtesy of the spare funding of a generous friend. There turned out to be more funding than expected, and what was planned as just a few months was extended to almost a year.

I spent that year learning something new. It was still an amplitudes project, trying to make particle physics predictions more efficient. But this time I used Python. I looked into reinforcement learning and PyTorch, played with using a locally hosted Large Language Model to generate random code, and ended up getting good results from a classic genetic programming approach. Along the way I set up a SQL database, configured Docker containers, and puzzled out interactions with CUDA. I’ve got a paper in the works, I’ll post about it when it’s out.

All the while, on the side, I’ve been seeking out stories. I’ve not just been a writer, but a journalist, tracking down leads and interviewing experts. I had three pieces in Quanta Magazine and one in Ars Technica.

Based on that, I know I can make money doing science journalism. What I don’t know yet is whether I can make a living doing it. This year, I’ll figure that out. With the project at the Niels Bohr Institute over, I’ll have more time to seek out leads and pitch to more outlets. I’ll see whether I can turn a skill into a career.

So if you’re a scientist with a story to tell, if you’ve discovered something or accomplished something or just know something that the public doesn’t, and that you want to share: do reach out. There’s a lot that can be of interest, passion that can be shared.

At the same time, I don’t know yet whether I can make a living as a freelancer. Many people try and don’t succeed. So I’m keeping my CV polished and my eyes open. I have more experience now with Data Science tools, and I’ve got a few side projects cooking that should give me a bit more. I have a few directions in mind, but ultimately, I’m flexible. I like being part of a team, and with enthusiastic and competent colleagues I can get excited about pretty much anything. So if you’re hiring in Copenhagen, if you’re open to someone with ten years of STEM experience who’s just starting to see what industry has to offer, then let’s chat. Even if we’re not a good fit, I bet you’ve got a good story to tell.

At Ars Technica Last Week, With a Piece on How Wacky Ideas Become Big Experiments

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I had a piece last week at Ars Technica about the path ideas in physics take to become full-fledged experiments.

My original idea for the story was a light-hearted short news piece. A physicist at the University of Kansas, Steven Prohira, had just posted a proposal for wiring up a forest to detect high-energy neutrinos, using the trees like giant antennas.

Chatting to experts, what at first seemed silly started feeling like a hook for something more. Prohira has a strong track record, and the experts I talked to took his idea seriously. They had significant doubts, but I was struck by how answerable those doubts were, how rather than dismissing the whole enterprise they had in mind a list of questions one could actually test. I wrote a blog post laying out that impression here.

The editor at Ars was interested, so I dug deeper. Prohira’s story became a window on a wider-ranging question: how do experiments happen? How does a scientist convince the community to work on a project, and the government to fund it? How do ideas get tested before these giant experiments get built?

I tracked down researchers from existing experiments and got their stories. They told me how detecting particles from space takes ingenuity, with wacky ideas involving the natural world being surprisingly common. They walked me through tales of prototypes and jury-rigging and feasibility studies and approval processes.

The highlights of those tales ended up in the piece, but there was a lot I couldn’t include. In particular, I had a long chat with Sunil Gupta about the twists and turns taken by the GRAPES experiment in India. Luckily for you, some of the most interesting stories have already been covered, for example their measurement of the voltage of a thunderstorm or repurposing used building materials to keep costs down. I haven’t yet found his story about stirring wavelength-shifting chemicals all night using a propeller mounted on a power drill, but I suspect it’s out there somewhere. If not, maybe it can be the start of a new piece!

Replacing Space-Time With the Space in Your Eyes

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Nima Arkani-Hamed thinks space-time is doomed.

That doesn’t mean he thinks it’s about to be destroyed by a supervillain. Rather, Nima, like many physicists, thinks that space and time are just approximations to a deeper reality. In order to make sense of gravity in a quantum world, seemingly fundamental ideas, like that particles move through particular places at particular times, will probably need to become more flexible.

But while most people who think space-time is doomed research quantum gravity, Nima’s path is different. Nima has been studying scattering amplitudes, formulas used by particle physicists to predict how likely particles are to collide in particular ways. He has been trying to find ways to calculate these scattering amplitudes without referring directly to particles traveling through space and time. In the long run, the hope is that knowing how to do these calculations will help suggest new theories beyond particle physics, theories that can’t be described with space and time at all.

Ten years ago, Nima figured out how to do this in a particular theory, one that doesn’t describe the real world. For that theory he was able to find a new picture of how to calculate scattering amplitudes based on a combinatorical, geometric space with no reference to particles traveling through space-time. He gave this space the catchy name “the amplituhedron“. In the years since, he found a few other “hedra” describing different theories.

Now, he’s got a new approach. The new approach doesn’t have the same kind of catchy name: people sometimes call it surfaceology, or curve integral formalism. Like the amplituhedron, it involves concepts from combinatorics and geometry. It isn’t quite as “pure” as the amplituhedron: it uses a bit more from ordinary particle physics, and while it avoids specific paths in space-time it does care about the shape of those paths. Still, it has one big advantage: unlike the amplituhedron, Nima’s new approach looks like it can work for at least a few of the theories that actually describe the real world.

The amplituhedron was mysterious. Instead of space and time, it described the world in terms of a geometric space whose meaning was unclear. Nima’s new approach also describes the world in terms of a geometric space, but this space’s meaning is a lot more clear.

The space is called “kinematic space”. That probably still sounds mysterious. “Kinematic” in physics refers to motion. In the beginning of a physics class when you study velocity and acceleration before you’ve introduced a single force, you’re studying kinematics. In particle physics, kinematic refers to the motion of the particles you detect. If you see an electron going up and to the right at a tenth the speed of light, those are its kinematics.

Kinematic space, then, is the space of observations. By saying that his approach is based on ideas in kinematic space, what Nima is saying is that it describes colliding particles not based on what they might be doing before they’re detected, but on mathematics that asks questions only about facts about the particles that can be observed.

(For the experts: this isn’t quite true, because he still needs a concept of loop momenta. He’s getting the actual integrands from his approach, rather than the dual definition he got from the amplituhedron. But he does still have to integrate one way or another.)

Quantum mechanics famously has many interpretations. In my experience, Nima’s favorite interpretation is the one known as “shut up and calculate”. Instead of arguing about the nature of an indeterminately philosophical “real world”, Nima thinks quantum physics is a tool to calculate things people can observe in experiments, and that’s the part we should care about.

From a practical perspective, I agree with him. And I think if you have this perspective, then ultimately, kinematic space is where your theories have to live. Kinematic space is nothing more or less than the space of observations, the space defined by where things land in your detectors, or if you’re a human and not a collider, in your eyes. If you want to strip away all the speculation about the nature of reality, this is all that is left over. Any theory, of any reality, will have to be described in this way. So if you think reality might need a totally new weird theory, it makes sense to approach things like Nima does, and start with the one thing that will always remain: observations.

At Quanta This Week, With a Piece on Multiple Imputation

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I’ve got another piece in Quanta Magazine this week.

While my past articles in Quanta have been about physics, this time I’m stretching my science journalism muscles in a new direction. I was chatting with a friend who works for a pharmaceutical company, and he told me about a statistical technique that sounded ridiculous. Luckily, he’s a patient person, and after annoying him and a statistician family member for a while I understood that the technique actually made sense. Since I love sharing counterintuitive facts, I thought this would be a great story to share with Quanta’s readers. I then tracked down more statisticians, and annoyed them in a more professional way, finally resulting in the Quanta piece.

The technique is called multiple imputation, and is a way to deal with missing data. By filling in (“imputing”) missing information with good enough guesses, you can treat a dataset with missing data as if it was complete. If you do this imputation multiple times with the help of a source of randomness, you can also model how uncertain those guesses are, so your final statistical estimates are as uncertain as they ought to be. That, in a nutshell, is multiple imputation.

In the piece, I try to cover the key points: how the technique came to be, how it spread, and why people use it. To complement that, in this post I wanted to get a little bit closer to the technical details, and say a bit about why some of the workarounds a naive physicist would come up with don’t actually work.

If you’re anything like me, multiple imputation sounds like a very weird way to deal with missing data. In order to fill in missing data, you have to use statistical techniques to find good guesses. Why can’t you just use the same techniques to analyze the data in the first place? And why do you have to use a random number generator to model your uncertainty, instead of just doing propagation of errors?

It turns out, you can sort of do both of these things. Full Information Maximum Likelihood is a method where you use all the data you have, and only the data you have, without imputing anything or throwing anything out. The catch is that you need a model, one with parameters you can try to find the most likely values for. Physicists usually do have a model like this (for example, the Standard Model), so I assumed everyone would. But for many things you want to measure in social science and medicine, you don’t have any such model, so multiple imputation ends up being more versatile in practice.

(If you want more detail on this, you need to read something written by actual statisticians. The aforementioned statistician family member has a website here that compares and contrasts multiple imputation with full information maximum likelihood.)

What about the randomness? It turns out there is yet another technique, called Fractional Imputation. While multiple imputation randomly chooses different values to impute, fractional imputation gives each value a weight based on the chance for it to come up. This gives the same result…if you can compute the weights, and store all the results. The impression I’ve gotten is that people are working on this, but it isn’t very well-developed.

“Just do propagation of errors”, the thing I wanted to suggest as a physicist, is much less of an option. In many of these datasets, you don’t attribute errors to the base data points to begin with. And on the other hand, if you want to be more sophisticated, then something like propagation of errors is too naive. You have a variety of different variables, correlated with each other in different ways, giving a complicated multivariate distribution. Propagation of errors is already pretty fraught when you go beyond linear relationships (something they don’t tend to tell baby physicists), using it for this would be pushing it rather too far.

The thing I next wanted to suggest, “just carry the distribution through the calculation”, turns out to relate to something I’ve called the “one philosophical problem of my sub-field”. In the area of physics I’ve worked in, a key question is what it means to have “done” an integral. Here, one can ask what it means to do a calculation on a distribution. In both cases, the end goal is to get numbers out: physics predictions on the one hand, statistical estimates on the other. You can get those numbers by “just” doing numerics, using randomness and approximations to estimate the number you’re interested in. And in a way, that’s all you can do. Any time you “just do the integral” or “just carry around the distribution”, the thing you get in the end is some function: it could be a well-understood function like a sine or log, or it could be an exotic function someone defined for that purpose. But whatever function you get, you get numbers out of it the same way. A sine or a log, on a computer, is just an approximation scheme, a program that outputs numbers.

(But we do still care about analytic results, we don’t “just” do numerics. That’s because understanding the analytics helps us do numerics better, we can get more precise numbers faster and more stably. If you’re just carrying around some arbitrarily wiggly distribution, it’s not clear you can do that.)

So at this point, I get it. I’m still curious to see how Fractional Imputation develops, and when I do have an actual model I’d lean to wanting to use Full Information Maximum Likelihood instead. (And there are probably some other caveats I may need to learn at some point!) But I’m comfortable with the idea that Multiple Imputation makes sense for the people using it.

Clickbait or Koan

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Last month, I had a post about a type of theory that is, in a certain sense, “immune to gravity”. These theories don’t allow you to build antigravity machines, and they aren’t totally independent of the overall structure of space-time. But they do ignore the core thing most people think of as gravity, the curvature of space that sends planets around the Sun and apples to the ground. And while that trait isn’t something we can use for new technology, it has led to extremely productive conversations between mathematicians and physicists.

After posting, I had some interesting discussions on twitter. A few people felt that I was over-hyping things. Given all the technical caveats, does it really make sense to say that these theories defy gravity? Isn’t a title like “Gravity-Defying Theories” just clickbait?

Obviously, I don’t think so.

There’s a concept in education called inductive teaching. We remember facts better when they come in context, especially the context of us trying to solve a puzzle. If you try to figure something out, and then find an answer, you’re going to remember that answer better than if you were just told the answer from the beginning. There are some similarities here to the concept of a Zen koan: by asking questions like “what is the sound of one hand clapping?” a Zen master is supposed to get you to think about the world in a different way.

When I post with a counterintuitive title, I’m aiming for that kind of effect. I know that you’ll read the title and think “that can’t be right!” Then you’ll read the post, and hear the explanation. That explanation will stick with you better because you asked that question, because “how can that be right?” is the solution to a puzzle that, in that span of words, you cared about.

Clickbait is bad for two reasons. First, it sucks you in to reading things that aren’t actually interesting. I write my blog posts because I think they’re interesting, so I hope I avoid that. Second, it can spread misunderstandings. I try to be careful about these, and I have some tips how you can be too:

  1. Correct the misunderstanding early. If I’m worried a post might be misunderstood in a clickbaity way, I make sure that every time I post the link I include a sentence discouraging the misunderstanding. For example, for the post on Gravity-Defying Theories, before the link I wrote “No flying cars, but it is technically possible for something to be immune to gravity”. If I’m especially worried, I’ll also make sure that the first paragraph of the piece corrects the misunderstanding as well.
  2. Know your audience. This means both knowing the normal people who read your work, and how far something might go if it catches on. Your typical readers might be savvy enough to skip the misunderstanding, but if they latch on to the naive explanation immediately then the “koan” effect won’t happen. The wider your reach can be, the more careful you need to be about what you say. If you’re a well-regarded science news piece, don’t write a title saying that scientists have built a wormhole.
  3. Have enough of a conclusion to be “worth it”. This is obviously a bit subjective. If your post introduces a mystery and the answer is that you just made some poetic word choice, your audience is going to feel betrayed, like the puzzle they were considering didn’t have a puzzly answer after all. Whatever you’re teaching in your post, it needs to have enough “meat” that solving it feels like a real discovery, like the reader did some real work to solve it.

I don’t think I always live up to these, but I do try. And I think trying is better than the conservative option, of never having catchy titles that make counterintuitive claims. One of the most fun aspects of science is that sometimes a counterintuitive fact is actually true, and that’s an experience I want to share.

Does Science Require Publication?

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Seen on Twitter:

As is traditional, twitter erupted into dumb arguments over this. Some made fun of Yann LeCun for implying that Elon Musk will be forgotten, which despite any other faults of his seems unlikely. Science popularizer Sabine Hossenfelder pointed out that there are two senses of “publish” getting confused here: publish as in “make public” and publish as in “put in a scientific journal”. The latter tends to be necessary for scientists in practice, but is not required in principle. (The way journals work has changed a lot over just the last century!) The former, Sabine argued, is still 100% necessary.

Plenty of people on twitter still disagreed (this always happens). It got me thinking a bit about the role of publication in science.

When we talk about what science requires or doesn’t require, what are we actually talking about?

“Science” is a word, and like any word its meaning is determined by how it is used. Scientists use the word “science” of course, as do schools and governments and journalists. But if we’re getting into arguments about what does or does not count as science, then we’re asking about a philosophical problem, one in which philosophers of science try to understand what counts as science and what doesn’t.

What do philosophers of science want? Many things, but a big one is to explain why science works so well. Over a few centuries, humanity went from understanding the world in terms of familiar materials and living creatures to decomposing them in terms of molecules and atoms and cells and proteins. In doing this, we radically changed what we were capable of, computers out of the reach of blacksmiths and cures for diseases that weren’t even distinguishable. And while other human endeavors have seen some progress over this time (democracy, human rights…), science’s accomplishment demands an explanation.

Part of that explanation, I think, has to include making results public. Alchemists were interested in many of the things later chemists were, and had started to get some valuable insights. But alchemists were fearful of what their knowledge would bring (especially the ones who actually thought they could turn lead into gold). They published almost only in code. As such, the pieces of progress they made didn’t build up, didn’t aggregate, didn’t become overall progress. It was only when a new scientific culture emerged, when natural philosophers and physicists and chemists started writing to each other as clearly as they could, that knowledge began to build on itself.

Some on twitter pointed out the example of the Manhattan project during World War II. A group of scientists got together and made progress on something almost entirely in secret. Does that not count as science?

I’m willing to bite this bullet: I don’t think it does! When the Soviets tried to replicate the bomb, they mostly had to start from scratch, aside from some smuggled atomic secrets. Today, nations trying to build their own bombs know more, but they still must reinvent most of it. We may think this is a good thing, we may not want more countries to make progress in this way. But I don’t think we can deny that it genuinely does slow progress!

At the same time, to contradict myself a bit: I think you can think of science that happens within a particular community. The scientists of the Manhattan project didn’t publish in journals the Soviets could read. But they did write internal reports, they did publish to each other. I don’t think science by its nature has to include the whole of humanity (if it does, then perhaps studying the inside of black holes really is unscientific). You probably can do science sticking to just your own little world. But it will be slower. Better, for progress’s sake, if you can include people from across the world.