Michael Black Profile picture
Dec 3, 2022 18 tweets 3 min read Read on X
In the LLM-science discussion, I see a common misconception that science is a thing you do and that writing about it is separate and can be automated. I’ve written over 300 scientific papers and can assure you that science writing can’t be separated from science doing. Why? 1/18
Anyone who has taught knows the following is true. You think you understand something until you go to teach it. Explaining something to others reveals gaps in your understanding that you didn’t know you had. Well, writing a scientific paper is a form of teaching. 2/18
Your paper is teaching your reader about your hypothesis, problem, method, the prior work in the field, your results, and what it all means for future work. When you write up your work and find it challenging, this is typically because you don’t yet fully understand it. 3/18
The writing reveals what you don’t know. Years ago, Michal Irani gave me good advice. She said you can write the introduction to your paper long before the science is done and that this helps structure your thinking. 4/18
Of course, you have to rewrite it once you know the outcome of your work but she’s right. You can tell the story before the ending is known. I am constantly training my students how to structure a story because doing so leads to good science. 5/18
What’s the problem in the world? Why isn’t it solved? What's your key insight that lets you solve it when others couldn’t? Why is it novel? What’s your solution? Who’s your audience? What do they care about? What do they know? 6/18
None of these questions are about grammar. None are about English proficiency. They're about “thinking proficiency”. They're about understanding your contribution and why it’s important. They help structure an argument that's logical. 7/18
Use Grammarly, please. It's not cheating unless you’re taking a grammar test. By trying to write your story, you find the holes in your story. If you do this early, you have time to go back and let this drive your science. 8/18
Because people often have trouble getting started writing, I tell them to make a talk instead. The idea of telling a story to a room full of people makes it easier to get the structure right. If you have a really great talk, turning it into a great paper is relatively easy. 9/18
I have my students write a “shitty first draft”. All I care about is structure, logic, and story. We often sketch the figures and plots that we imagine on a whiteboard, take a photo, and put them in the paper. We build the whole structure before the work is done. 10/18
I guarantee that this leads to better science and better papers than rushing to write up something after you finish all the experiments. The early writing process leads to you realizing that you are missing experiments. 11/18
Most students would love for me to write their paper for them. They know I can do it faster. They also know that I’ll rewrite a lot of what they’ve written. So why should they do it? Because, it will help them become good scientists. 12/18
A good scientist has to be a good communicator. We don’t do science as a private activity. Imagine I structured all the papers and wrote them all and the students just coded and ran experiments. Or imagine an LLM did this. 13/18
One of the hardest things I ask them to do is to come up with an “elevator pitch”. This requires distilling something huge and complex into a sentence. To do so, you really have to understand the core of your contribution. 14/18
What about related work? Nobody reads that right? That could be automated, right? I think it's one of the most important parts of a paper for both the author and the field. 15/18
I am often grappling with a sprawling literature and my job is to organize it in some way that provides insight. This may let others see the field in a new light and can lead them to new discoveries. 16/18
I know that I’m fortunate. I’m a native English speaker, raised by literate parents, and the mechanics of writing come naturally. But I don’t care about grammar. I care about ideas, logic, and story. It’s your argument that matters. 17/18
Summary: science thinking, writing, and doing are inseparable. Focus on story. Write early. Write a shitty first draft. And do yourself a favor: write it yourself. I promise that writing about your science will improve your science. 18/18

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More from @Michael_J_Black

Apr 29, 2024
Young scientists regularly ask me for career advice. Academia or industry? Big company or startup? US or Europe?  Good scientists in AI disciplines are fortunate to have many choices. But choosing can be stressful. I always give the same advice. 1/10
There is no globally-optimal life. There is no sequence of choices in life that will produce the "perfect life" or "perfect career". This is hard to accept but, once you accept it, it's very freeing. 2/10
So my advice is to choose the option that is the most fun. Why fun? Shouldn't you maximize future reward? Maximize future options? Maximize impact? Maximize income? 3/10
Read 10 tweets
Apr 22, 2024
Build what you need and use what you build. This is a core philosophy of my research. It shifts the focus away from publishing “papers” to what really matters — impact. This thread unpacks why I think this is a successful approach to science. 1/10 Or see:
perceiving-systems.blog/en/post/build-…
At the start of any research project, I ask my students “Who’s your customer?” By customer, I don’t mean “paying customer”. I mean “who needs what you’re proposing?” Who will use it? Who cares? If you can’t answer this, then the work is likely to be irrelevant. 2/10
A good answer to “who’s your customer?” can be “me”. If you need it, then you need it. And if you need it, there are probably other people out there in the world like you who will need it too. Corollary: if you aren’t going to use it, why do you think others will? 3/10
Read 11 tweets
Jan 11, 2023
These are exciting times. There's a sense that AI will change everything, including how science is done. Implicit in this excitement is the hope that everything will change for the better. Let’s look at that. First, we need to define “better.”
Here, it’s the idea that science serves people to produce new artifacts (drugs, technologies, etc) that improve our lives. Behind this definition is a utilitarian view of science that is not quite correct and doesn't apply to all disciplines but that's a complex story for later.
Instead, I’ll focus on whether the AI utopia in science is likely. The argument goes like this: science is the domain of a few self-selected wizards who keep the rest of the population out through arcane jargon and ancient rituals.
Read 17 tweets
Jan 9, 2023
.@ylecun writes “science must solely evaluate *impact*” and “evaluating work done by humans has ABSOLUTELY NOTHING TO DO with scientific publication.” Original emphasis retained. Let’s unpack the notion of impact and the evaluation of humans in science.
Consider the claim that all that matters in science is impact. This sounds sensible but requires the ability to *measure* impact. In ML today, the turnaround time between innovation and application is short. the “customer base” is huge, and impact may seem easy to evaluate.
But groundbreaking innovation often languishes in the shadows for years or decades before having measurable impact; e.g. research on neural nets before they proved their merit. During this pre-impact stage, the machinery of science is designed to make bets, albeit imperfectly.
Read 13 tweets
Dec 1, 2022
I repeat: Easily produced science text that's wrong does not advance science, improve science productivity, or make science more accessible. I like research on LLMs but the blind belief in their goodness does a disservice to them and science. Here is an example from #ChatGPT 1/5 Image
SMPL is actually short for Skinned Multi-Person Linear model. #SMPL is a popular 3D model of the body that's based on linear blend skinning with pose-corrective blend shapes. It's learned from 3D scans of people, making it accurate and compatible with rendering engines. 2/5 Image
Despite what #ChatGPT thinks, it wasn't developed at Berkeley or the MPI for Informatics. It was developed in the @PerceivingSys department of the @MPI_IS (the Max Planck Institute for Intelligent Systems). Run it again and you'll get different answers every time. 3/5
Read 5 tweets
Nov 22, 2022
With LLMs for science out there (#Galactica) we need new ethics rules for scientific publication. Existing rules regarding plagiarism, fraud, and authorship need to be rethought for LLMs to safeguard public trust in science. Long thread about trust, peer review, & LLMs. (1/23)
I’ll state the obvious because it doesn’t seem to be obvious to everyone. Science depends on public trust. The public funds basic research and leaves scientists alone to decide what to study and how to study it. This is an amazing system that works. (2/23)
But it only works if scientists and the public each uphold their part of the deal. The pressure on scientists today to publish has never been greater. Publication and citation metrics are widely used for evaluation. (3/23)
Read 23 tweets

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