“Applied science” by Ben Krasnow. A YouTube channel about building physics-intensive projects in a home laboratory. Big ones are things like an electron microscope or a mass spectrometer, but the ones I find fascinating are smaller things like an electroluminescent display or a novel dye. He demonstrates the whole process of scientific experiment— finding and understanding references, setting up a process for trying stuff, failing repeatedly, learning from mistakes, noticing oddities… He doesn’t just show you the final polished procedure— “here’s how to make an X”. He shows you the whole journey— “Here’s how I discovered how to make X”.
You seem very concerned that people in the videos should have legible symbols of success. I don’t think that much affects how useful the videos are, but just in case I’m wrong, I looked on LinkedIn, where I found this self-assesment:
<begin copied text>
I specialize in the design and construction of electromechanical prototypes. My core skillset includes electronic circuit design, PCB layout, mechanical design, machining, and sensor/actuator selection. This allows me to implement and test ideas for rapid evaluation or iteration. Much of the work that I did for my research devices business included a fast timeline, going from customer sketch to final product in less than a month. These products were used to collect data for peer-reviewed scientific papers, and I enjoyed working closely with the end user to solve their data collection challenges. I did similar work at Valve to quickly implement and test internal prototypes.
I’m gonna quote from this article about why you’d prefer to learn tacit knowledge from “believable people” i.e. those who have 1) a record of at least 3 different successes and 2) have great explanations of their approach when probed.
Believability works for two reasons: a common-sense one, and a more interesting, less obvious one.
The common-sense reasoning is pretty obvious: when you want advice for practical skills, you should talk to people who have those skills. For instance, if you want advice on swimming, you don’t go to someone who has never swum before, you go to an accomplished swimmer instead. For some reason we seem to forget this when we talk about more abstract skills like marketing or investing or business.
The two requirements for believability makes more sense when seen in this light: many domains in life are more probabilistic than swimming, so you’ll want at least three successes to rule out luck. You’ll also want people to have ‘great explanations’ when you probe them because otherwise they won’t be of much help to you.
The more interesting, less obvious reason that believability works is because reality has a surprising amount of detail. I’m quoting from a famous article by John Salvatier, which you should read in its entirety. Salvatier opens with a story about building stairs, and then writes:
It’s tempting to think ‘So what?’ and dismiss these details as incidental or specific to stair carpentry. And they are specific to stair carpentry; that’s what makes them details. But the existence of a surprising number of meaningful details is not specific to stairs. Surprising detail is a near universal property of getting up close and personal with reality.
You can see this everywhere if you look. For example, you’ve probably had the experience of doing something for the first time, maybe growing vegetables or using a Haskell package for the first time, and being frustrated by how many annoying snags there were. Then you got more practice and then you told yourself ‘man, it was so simple all along, I don’t know why I had so much trouble’. We run into a fundamental property of the universe and mistake it for a personal failing.
If you’re a programmer, you might think that the fiddliness of programming is a special feature of programming, but really it’s that everything is fiddly, but you only notice the fiddliness when you’re new, and in programming you do new things more often.
You might think the fiddly detailiness of things is limited to human centric domains, and that physics itself is simple and elegant. That’s true in some sense – the physical laws themselves tend to be quite simple – but the manifestation of those laws is often complex and counterintuitive.
The point that Salvatier makes is that everything is more complex and fiddly than you think. At the end of the piece, Salvatier argues that if you’re not aware of this fact, it’s likely you’ll miss out on some obvious cue in the environment that will then cause you — and other novices — to get stuck.
Why does this matter? Well, it matters once you consider the fact that practical advice has to account for all of this fiddliness — but in a roundabout way: good practical advice nearly never provides an exhaustive description of all the fiddliness you will experience. It can’t: it would make the advice too long-winded. Instead, good practical advice will tend to focus on the salient features of the skill or the domain, but in a way that will make the fiddliness of reality tractable.
In practice, how this often feels like is something like “Ahh, I didn’t get why the advice was phrased that way, but I see now. Ok.”
Think about what this means, though. It means that you cannot tell the difference between advice from a believable person and advice from a non-believable person from examination of the advice alone. To a novice, advice from a non-believable person will seem just as logical and as reasonable as advice from a more believable person, except for the fact that it will not work. And the reason it will not work (or that it will work less well) is that advice from less believable individuals will either focus on the wrong set of fiddly details, or fail to account for some of the fiddliness of reality.
To put this another way, when you hear the words “I don’t see why X can’t work …” from a person who isn’t yet believable in that domain, alarm bells should go off in your head. This person has not tested their ideas against reality, and — worse — they are not likely to know which set of fiddly details are important to account for.
Background: From his LinkedIn: “I specialize in the design and construction of electromechanical prototypes. My core skillset includes electronic circuit design, PCB layout, mechanical design, machining, and sensor/actuator selection. This allows me to implement and test ideas for rapid evaluation or iteration. Much of the work that I did for my research devices business included a fast timeline, going from customer sketch to final product in less than a month. These products were used to collect data for peer-reviewed scientific papers, and I enjoyed working closely with the end user to solve their data collection challenges. I did similar work at Valve to quickly implement and test internal prototypes.”
(I’ve since changed the formatting standards for this post; I hope you don’t mind me reposting your information to make it more legible for new readers.)
Perfect—thanks for the links! Will add this and the other submission to the post when I get the chance.
You seem very concerned that people in the videos should have legible symbols of success. I don’t think that much affects how useful the videos are, but just in case I’m wrong [...]
The main driving motivation for this was seeing that The Best Textbooks on Every Subject received traction due to a similar mechanism. Another reason was wanting the tacit knowledge in the videos to be knowledge that’s appealing to learn.
I don’t want the mechanism to stop the post from receiving submissions though; this resource-submission genre seems like the kind that benefits from network effects. If anyone has any thoughts as to whether the mechanism is useful or counterproductive, I would be curious to hear.
That was 13 years ago across an ocean of accelerating cultural change, institutional trust, and people maturing. I’m sure you can still find plenty of people who would use mechanisms like that, but I’m pretty sure it’s going to be one of the less important considerations now.
and while I’m here, i also curate something like this. ben krasnow is only the best entry point into a wider world. This list was my best attempt recently, it was particularly aimed at getting programmers into physical engineering topics, trying to removing learned helplessness around it and making the topic feel like something it’s possible to engage with. https://gist.github.com/taygetea/1fcc9817618b1008a812e6f2c58ca987
“Applied science” by Ben Krasnow. A YouTube channel about building physics-intensive projects in a home laboratory. Big ones are things like an electron microscope or a mass spectrometer, but the ones I find fascinating are smaller things like an electroluminescent display or a novel dye. He demonstrates the whole process of scientific experiment— finding and understanding references, setting up a process for trying stuff, failing repeatedly, learning from mistakes, noticing oddities… He doesn’t just show you the final polished procedure— “here’s how to make an X”. He shows you the whole journey— “Here’s how I discovered how to make X”.
You seem very concerned that people in the videos should have legible symbols of success. I don’t think that much affects how useful the videos are, but just in case I’m wrong, I looked on LinkedIn, where I found this self-assesment:
<begin copied text>
I specialize in the design and construction of electromechanical prototypes. My core skillset includes electronic circuit design, PCB layout, mechanical design, machining, and sensor/actuator selection. This allows me to implement and test ideas for rapid evaluation or iteration. Much of the work that I did for my research devices business included a fast timeline, going from customer sketch to final product in less than a month. These products were used to collect data for peer-reviewed scientific papers, and I enjoyed working closely with the end user to solve their data collection challenges. I did similar work at Valve to quickly implement and test internal prototypes.
Check out my youtube channel to see a sample of my personal projects:
http://www.youtube.com/user/bkraz333
<end copied text>
I’m gonna quote from this article about why you’d prefer to learn tacit knowledge from “believable people” i.e. those who have 1) a record of at least 3 different successes and 2) have great explanations of their approach when probed.
Domain: Physics
Link: “Applied Science”
Person: Ben Krasnow
Background: From his LinkedIn: “I specialize in the design and construction of electromechanical prototypes. My core skillset includes electronic circuit design, PCB layout, mechanical design, machining, and sensor/actuator selection. This allows me to implement and test ideas for rapid evaluation or iteration. Much of the work that I did for my research devices business included a fast timeline, going from customer sketch to final product in less than a month. These products were used to collect data for peer-reviewed scientific papers, and I enjoyed working closely with the end user to solve their data collection challenges. I did similar work at Valve to quickly implement and test internal prototypes.”
(I’ve since changed the formatting standards for this post; I hope you don’t mind me reposting your information to make it more legible for new readers.)
Perfect—thanks for the links! Will add this and the other submission to the post when I get the chance.
The main driving motivation for this was seeing that The Best Textbooks on Every Subject received traction due to a similar mechanism. Another reason was wanting the tacit knowledge in the videos to be knowledge that’s appealing to learn.
I don’t want the mechanism to stop the post from receiving submissions though; this resource-submission genre seems like the kind that benefits from network effects. If anyone has any thoughts as to whether the mechanism is useful or counterproductive, I would be curious to hear.
That was 13 years ago across an ocean of accelerating cultural change, institutional trust, and people maturing. I’m sure you can still find plenty of people who would use mechanisms like that, but I’m pretty sure it’s going to be one of the less important considerations now.
and while I’m here, i also curate something like this. ben krasnow is only the best entry point into a wider world. This list was my best attempt recently, it was particularly aimed at getting programmers into physical engineering topics, trying to removing learned helplessness around it and making the topic feel like something it’s possible to engage with. https://gist.github.com/taygetea/1fcc9817618b1008a812e6f2c58ca987
Thanks sharing sharing this! I’ve added one and intend to add more of them when I have more time.