This article is ostensibly about biology but it's really about pedagogy—how traditional education squeezes out the sense of discovery and turns many subjects into rote memorization exercises.
This reminds me of the pedagogical philosophy of Seymour Papert, who was heavily influenced by the ideas of Jean Piaget. Piaget's "genetic epistemology" argues that knowledge and understanding is created by interacting with environments, which traditional educational approaches fail to provide.
Papert combined Piaget's ideas with the emergence of computing to argue that children should be taught subjects in a hands-on, exploratory way - and not just for teaching computing! The idea is that by programming in simplified languages, children can discover ideas in subjects like mathematics and grammar - deriving them as they try to solve problems instead of having them dictated to them.
Suppose that biology was taught in a game-like environment where students were designing cells or organisms in some way. Maybe the game could be structured so that each organelle could be "discovered" by the student as they designed the cell to survive in some environment. Perhaps that'd make the purpose of each cell component more grounded and memorable.
Papert's book Mindstorms covers all this in detail, and I highly recommend reading it. I feel like it's especially important today given fears of how AI will affect childhood education. At best, I hope that computing can be a boon to education instead of a detriment if it's woven into pedagogy thoughtfully.
Speaking as a guy who made the pivot to research in life sciences (as a "data scientist") from "full stack software engineer", yes the data and mission is very sexy to a nerdy guy like myself, applying deep learning algorithms to spatial or epigenetic sequencing data of cancer cells to figure out the secret markers or mechanism of cancer cell mestasis or human immune response.
The realistic or unromantic view is you are a cog in the life science industrial complex where you are underpaid and under-appreciated; research often takes years and unclear if you are making progress or scamming the taxpayers like a humanities professor in women's studies (yes even STEM sometimes feels like that); and in computing, unlike tech, you are not the center of attention, most wet lab scientists treat you more like a resource, a grad student they need to make their pvalue or figure panel pop nicely versus a "full stack software engineer" - And if you don't like it, hundreds of thousands of post-doc's or grad students are waiting to take your place for their shot - not in pursing their passion but for a visa in America.
The real value I learned from my pivot from pivoting away from tech and pivoting into Biology is ironically how to gamble. I joined a Discord/Slack sub-channel for #options-trading, #sports-betting and #poker during my studies for a Masters in data science with other degenerate students who loved gambling, and how to identify, automate and size +EV plays in gambling or derivatives trading. I make more than 2-3x what I make in W-2 from my capital gains and W2-G than my W-2 for past the 6 years. But that is not put shade on biological sciences and rather giving credit to Biology for teaching me how to analyze data and gamble.
I suspect that the money taxpayers used to spend on humanities professors in women's studies is a pittance compared to the money they're now wasting because grab-em-by-the-***** regime never took one of those classes. Ignoring half of your population comes at the price of social unrest, which it turns out is very expensive.
My original point is to make a point that biology or academia in general is very romantic to outsiders - but it's not a very +EV play unless (1) you are already very independently wealth, or (2) you are really really into the subject and know what you're signing up for (the long odds, hours and politics). 99% of the people will take this as a pessimistic view and stop there but 1% will actually pursue option (2).
RE: your political point, I submit to you many institutions are very left-leaning and "Woke-1" was defeated by its emphasis on shaming tactics and identity politics - which ironically brought upon the identity politics of the right and the current "regimen's" backlash on defunding DEI initiatives, which hurts ironically the sciences most due to its outsized reliance from NIH/NSF/DARPA etc. And I welcome actually "Woke-2.0" where DSA is actually focused on kitchen table issues such as grocery and health insurance cost; and anticipate that our political pendulum will swing to the left at the next cycle.
Yes for me, it's mutually beneficial and gives me a quick way to polarize, filter out people I don't want waste time associating with (and vice versa too - people who are institutionalist, professional managerial class (PMCs); thank you for making my point!)
I did always love biology, not because of my teachers, but because of my own wonder of it ("I sort of get how an engine works, but how do humans work?"). And I became a biologist, and thinking about the things this author describes indeed still blows my mind. I get the high level of a lot of things now, but every time I need to do a deep dive, I feel like "how the hell can this even work". But it works, and it works incredibly well. I still think it's the nicest field to be in (even though I love computers and Linux and FOSS as well).
Agreed, I loved my biology courses and lab work and had always had a similar sense of wonder about it all. It's interesting, I'm not sure that came from any teacher in particular and I bet there are plenty of people who just never feel it no matter how you teach the subject. That said, those are beautiful illustrations referenced in the article and they have a ton of teaching value, and I think a lot of core concepts that went over my head would have been way more accessible using tools like that.
Physics was like that as well, and from my limited experience chemistry too.
The history of physics and the theory of it is great. A Brief History of Time is an awesome read.
Studying physics is not like that. Studying formulas, applying them to situations, and of course very math heavy.
One thing I regret is the experiments as well. In physics and chemistry they were kind of a blur. Just following instructions and sometimes they didn’t work out and no one knew why. I never learned the most important thing: how to design an experiment. Following a long recipe then reading the result is much less useful than observing a thing, forming a testable, falsifiable hypothesis about that thing, and then testing it.
Last thing I’ll say is you probably aren’t going to get the “wonder” of science from a science class. Those classes are there to tell you the answers, but the most interesting part is discovering the answers yourself which is not possible in a one semester survey course.
Most of my courses were very "Point A" to "Point B". You're given a set of formulae, then a problem, then you use some combinations of those formulae to solve the problem. Most labs were the same way: you're given an exact script to follow without any explanation of the experiment design. It felt like both were optimized for easy instruction / grading and not for learning new skills or concepts.
Only two of the courses I took were substantially different. One was an upper division lab that actually was more open-ended, where we were given a goal and some equipment and had to figure out how to use the equipment to meet the goal. Another was a more conceptual course where we explored how to approach broad problems to come up with rough estimates for a wide variety of questions. Both were much more engaging, but I saw many students good at the typical course type struggle with how open ended these courses were.
> One thing I regret is the experiments as well. In physics and chemistry they were kind of a blur.
Well, a lot of places would penalize you if your data is incorrect, so most of the focus ends up on execution rather than the why. If you were angling for a high GPA for whatever reason, you cannot afford to experiment too much during lab work. It's another case entirely of course if you are conducting research.
> the focus ends up on execution rather than the why
Exactly right. School teaches you that the point of running an experiment is to try and get the same result as the teacher, while performing a ritual with steps called "hypothesis" and "method".
I realized after getting a degree in engineering from CMU that I should've loved biology so I went back to school after working as a software engineer for a year and studied neurobiology. And since then, I've suggested that people early in their career should take a break and go back to school and study something totally different.
In Zen and the Art of Motorcycle Maintenance Robert M. Pirsig suggests something very similar. He makes the point that students should go and work a job before picking what to study because they'll see where the value comes from (he of course puts it in much better words)
I've heard this advice a lot with respect to graduate school/PhD work. And indeed, the students that came from industry jobs tended to be much more impressive; some of that was probably from the "real-world" experience, and some probably from a self-selection effect where folks who came in from a presumably well paying job had to have really wanted it and were therefore more motivated.
That might be difficult given the job market now compared to Pirsig's time. Of course you could get menial job but that won't tell you much about the real job you want, just about what work is like in general.
I had a similar experience with nature. My dad was the outdoors type, a conservation officer who loved hunting & fishing; I wanted nothing more than to be inside reading an encyclopedia. I have always liked science, but biology was just one subject among many.
When I became an adult, I gravitated to computers because there is so much to learn about them. My focus has been infrastructure, but I've picked up software development, assembly, kernel hacking, data science, and a dozen other things along the way (mostly at amateur levels, but I'm always happy to learn).
I have have other interests (economics, homebrewing, astronomy, sociology, making music), but in each of those cases I learned what I wanted to after a few years & moved away. When covid hit, I picked up natural history through iNaturalist -- and that has so far been very very different, much more the same kind of endless opportunity for discovery that computers felt like.
There is so much weirdness in biology. Parasitic wasps with genes that came from viruses that suppress caterpillar immune systems, male spiders that have appendages (pedipalps) that look like boxing gloves, the many kinds of bumble bees around me, introduced species, nests, microorganisms -- it's insane. It's higher up the stack than the stuff the author is describing, but no less wonderfully complex and fascinating.
The quote from Lewis Thomas really hit home for me: "People ought to be walking around all day, all through their waking hours calling to each other in endless wonderment, talking of nothing except that" [cell|insect|weird relationship|phenology|behaviour]. Kudos to the author for putting this all into words so well, and for adding a dozen books to my must-read list.
As an ex-microbiologist, the thing I can't stand is how smelly life is. Be in the same room as gangrenous flesh and your intestinal fortitude will be severely tested.
Other than that, I don't mind it, but I still prefer silicon.
>How come we memorized chemical formulas but didn’t talk about that [exciting stuff about developmental biology]
You can argue that about any subject. People want to take physics and learn stuff about black holes but instead the intro courses are about balls rolling down inclined planes and other such "boring" things. But you have to know the basics before you can understand the "cool" stuff!
Yes, you should have. While I can understand that not all high school biology teachers will drag you by the nose and make you see the wonder of biology, and textbooks are often awful, I’m confused why this means the author couldn’t go read on their own (as they eventually did).
I could write a similar screed, as a biologist, that I should have loved computer science, but find it a zoo of names that somehow manage to make even less sense than biology.
Yet natural curiousity kept me interested enough in comouters, and the day to day need to interact with them meant I had to have some understanding of these systems.
What is sad is, as a society, we don’t think of biology as being similarly useful in our daily interactions with the environment and other people.
But I urge anyone who’s annoyed by the biology text book and the list of names: please put in effort to look below. Neither biology nor the brain is a complete black box, and what we have learned over the past few decades is thick with beautiful structure and organization.
But also accept that biology is different. You can’t compact all of it to a few equations because unlike physics and basic elemental chemistry, biochemistry is still finding new rules and new efficiencies.
The rules of biology will never neatly compact to the point where individual molecules and cells and their identities are meaningless. That is the price of complexity that is under constant evolutionary pressure.
But we don’t need to remember every name, thankfully. At some point, you learn to classify by composition and function sufficiently that a wholly new protein just slots in, updates your mental model, and you move on better informed.
This resonated strongly. I hated biology as a kid but have been blown away at the wonder of it all as I've started to study it as an adult. I wish more of the magnificence and wonder of it all was conveyed vs the rote memorization that is so commonly taught.
>It was only in college, when I read Douglas Hofstadter’s Gödel, Escher, Bach
I see this book referenced all the time (HN, tech CEOs, misc. articles, etc), especially from folks who got into AI early. Is it really that amazing? Or is this some kind of signaling folks like to do to prove their smarts? Or both?
The author prefers people read his newer book I am a strange loop since it more directly represents his views. He’s apparently frustrated that nobody gets the point of GEB (which is to discuss consciousness).
If you like the mathematical aspects of computer science and computability theory, cranking out proofs using lambda calculus and Turing machines fascinates you, and you think Lisp is an elegant language, you may like it. For the average developer, it's unlikely to be interesting.
I read it shortly after it came out when I was in high school and it was sort of a mind blow - perhaps just because in the early 80s we didn't really get exposed to so many interesting ideas.
I wasn't a huge fan, to be honest. some good ideas, but overall the book felt self-indulgent. "metamagical themas" is a far better book if you want to read one thing by hofstadter, and "le ton beau de marot" if you want a deep dive into something.
It is unique; you've certainly never read anything else quite like it. Hofstadter is a deep and careful thinker who loves language and wordplay. He writes in order to communicate something he has spent a long time thinking about, not merely for the sake of cranking out a book. I've read a number of his other books, and some of his ways of thinking have stuck with me for years and shaped the way I see the world.
It's definitely signaling for the majority of people still talking about it today. Though, that's not saying much that you didn't already know about the groups you mentioned.
Being that it's more of a Gen Xer pop-sci book, it's not to "prove smarts", but to share a vibe. It belongs on someone's shelf next to their copies of The Naked Lunch and Aja. Maybe even a signed copy of A New Kind of Science?
I'm not trying to be dismissive. It's just true. Nobody is even ashamed of it, nor should be. It's an interesting and still relevant perspective, but because there's no resolution to this line of thinking, many find it underwhelming. There's no "aha" moment to be found in any of this. Just lots of introspection.
You gotta take the good with the bad though. The tall grass is an easy place to hide.
I absolutely experienced this in college. I signed up as a computer science student, as one does. I took all of the freshmen classes across broad topics, and the first biology class was basically just like the article describes. Words and memorization and microbiology and boring stuff. Who cares, let's get back to the dorm room to play CounterStrike on the school LAN.
But then I took the second required biology course. And rather than be about memorizing the krebs cycle, it was macrobiology. Ecology, evolution, and everything I hadn't realized I wanted to learn about the world around me. I instantly fell in love and 99'd the class. I changed my major to Biology, went pretty heavy into biology and chemistry, and didn't take more than a few Java classes in Comp Sci. I graduated with a B.S. in Biology.
I'm still a software developer, mind you, but I wouldn't trade the Biology degree for anything. Learning statistics, experimental design and experimentation, and just having the opportunity to deep dive into the physical world from the biggest to the smallest details, it was life-changing.
I still ended up learning data models, algorithms, and probably would be a better engineer if I had dug in deep on comp sci, but I like to think the biology degree helped me be a better developer for different reasons.
This article is ostensibly about biology but it's really about pedagogy—how traditional education squeezes out the sense of discovery and turns many subjects into rote memorization exercises.
This reminds me of the pedagogical philosophy of Seymour Papert, who was heavily influenced by the ideas of Jean Piaget. Piaget's "genetic epistemology" argues that knowledge and understanding is created by interacting with environments, which traditional educational approaches fail to provide.
Papert combined Piaget's ideas with the emergence of computing to argue that children should be taught subjects in a hands-on, exploratory way - and not just for teaching computing! The idea is that by programming in simplified languages, children can discover ideas in subjects like mathematics and grammar - deriving them as they try to solve problems instead of having them dictated to them.
Suppose that biology was taught in a game-like environment where students were designing cells or organisms in some way. Maybe the game could be structured so that each organelle could be "discovered" by the student as they designed the cell to survive in some environment. Perhaps that'd make the purpose of each cell component more grounded and memorable.
Papert's book Mindstorms covers all this in detail, and I highly recommend reading it. I feel like it's especially important today given fears of how AI will affect childhood education. At best, I hope that computing can be a boon to education instead of a detriment if it's woven into pedagogy thoughtfully.
This is a very romantic view of life sciences.
Speaking as a guy who made the pivot to research in life sciences (as a "data scientist") from "full stack software engineer", yes the data and mission is very sexy to a nerdy guy like myself, applying deep learning algorithms to spatial or epigenetic sequencing data of cancer cells to figure out the secret markers or mechanism of cancer cell mestasis or human immune response.
The realistic or unromantic view is you are a cog in the life science industrial complex where you are underpaid and under-appreciated; research often takes years and unclear if you are making progress or scamming the taxpayers like a humanities professor in women's studies (yes even STEM sometimes feels like that); and in computing, unlike tech, you are not the center of attention, most wet lab scientists treat you more like a resource, a grad student they need to make their pvalue or figure panel pop nicely versus a "full stack software engineer" - And if you don't like it, hundreds of thousands of post-doc's or grad students are waiting to take your place for their shot - not in pursing their passion but for a visa in America.
The real value I learned from my pivot from pivoting away from tech and pivoting into Biology is ironically how to gamble. I joined a Discord/Slack sub-channel for #options-trading, #sports-betting and #poker during my studies for a Masters in data science with other degenerate students who loved gambling, and how to identify, automate and size +EV plays in gambling or derivatives trading. I make more than 2-3x what I make in W-2 from my capital gains and W2-G than my W-2 for past the 6 years. But that is not put shade on biological sciences and rather giving credit to Biology for teaching me how to analyze data and gamble.
> The real value I learned from my pivot from pivoting away from tech and pivoting into Biology is ironically how to gamble
Lol that took a turn, I was expecting a link to a how to course at the end; or some nfl week one picks!
Where can I learn what you learn to make +EV plays? I did some poker back in the day, it was fun :)
One of my favorite books was The Mathematics of Poker
You should buy my ebook on how to get rich quick by selling ebooks, it has excellent EV and guarantees returns that beats the market.
> or scamming the taxpayers like a humanities professor in women's studies (yes even STEM sometimes feels like that);
one thing's for sure, there are certain spaces for people who lack people skills, and that seems to be associated with "STEM" skills
I suspect that the money taxpayers used to spend on humanities professors in women's studies is a pittance compared to the money they're now wasting because grab-em-by-the-***** regime never took one of those classes. Ignoring half of your population comes at the price of social unrest, which it turns out is very expensive.
This applies just as well to biology.
My original point is to make a point that biology or academia in general is very romantic to outsiders - but it's not a very +EV play unless (1) you are already very independently wealth, or (2) you are really really into the subject and know what you're signing up for (the long odds, hours and politics). 99% of the people will take this as a pessimistic view and stop there but 1% will actually pursue option (2).
RE: your political point, I submit to you many institutions are very left-leaning and "Woke-1" was defeated by its emphasis on shaming tactics and identity politics - which ironically brought upon the identity politics of the right and the current "regimen's" backlash on defunding DEI initiatives, which hurts ironically the sciences most due to its outsized reliance from NIH/NSF/DARPA etc. And I welcome actually "Woke-2.0" where DSA is actually focused on kitchen table issues such as grocery and health insurance cost; and anticipate that our political pendulum will swing to the left at the next cycle.
Yes for me, it's mutually beneficial and gives me a quick way to polarize, filter out people I don't want waste time associating with (and vice versa too - people who are institutionalist, professional managerial class (PMCs); thank you for making my point!)
I did always love biology, not because of my teachers, but because of my own wonder of it ("I sort of get how an engine works, but how do humans work?"). And I became a biologist, and thinking about the things this author describes indeed still blows my mind. I get the high level of a lot of things now, but every time I need to do a deep dive, I feel like "how the hell can this even work". But it works, and it works incredibly well. I still think it's the nicest field to be in (even though I love computers and Linux and FOSS as well).
Agreed, I loved my biology courses and lab work and had always had a similar sense of wonder about it all. It's interesting, I'm not sure that came from any teacher in particular and I bet there are plenty of people who just never feel it no matter how you teach the subject. That said, those are beautiful illustrations referenced in the article and they have a ton of teaching value, and I think a lot of core concepts that went over my head would have been way more accessible using tools like that.
This is why I loved biology; I must have had better high school teachers than the OP, because basically all of what he writes was conveyed.
This is one of those perennial HN favorites
https://hn.algolia.com/?query=I%20should%20have%20loved%20bi...
yes! I first found it on HN. The other front page piece on Thickness reminded me of it.
Always happy to pass along a good article to the next generation of Posters
Yep, and given that the original author posted it in 2020, should probably be marked (2020).
Physics was like that as well, and from my limited experience chemistry too.
The history of physics and the theory of it is great. A Brief History of Time is an awesome read.
Studying physics is not like that. Studying formulas, applying them to situations, and of course very math heavy.
One thing I regret is the experiments as well. In physics and chemistry they were kind of a blur. Just following instructions and sometimes they didn’t work out and no one knew why. I never learned the most important thing: how to design an experiment. Following a long recipe then reading the result is much less useful than observing a thing, forming a testable, falsifiable hypothesis about that thing, and then testing it.
Last thing I’ll say is you probably aren’t going to get the “wonder” of science from a science class. Those classes are there to tell you the answers, but the most interesting part is discovering the answers yourself which is not possible in a one semester survey course.
As a physics major I agree a lot with this.
Most of my courses were very "Point A" to "Point B". You're given a set of formulae, then a problem, then you use some combinations of those formulae to solve the problem. Most labs were the same way: you're given an exact script to follow without any explanation of the experiment design. It felt like both were optimized for easy instruction / grading and not for learning new skills or concepts.
Only two of the courses I took were substantially different. One was an upper division lab that actually was more open-ended, where we were given a goal and some equipment and had to figure out how to use the equipment to meet the goal. Another was a more conceptual course where we explored how to approach broad problems to come up with rough estimates for a wide variety of questions. Both were much more engaging, but I saw many students good at the typical course type struggle with how open ended these courses were.
> One thing I regret is the experiments as well. In physics and chemistry they were kind of a blur.
Well, a lot of places would penalize you if your data is incorrect, so most of the focus ends up on execution rather than the why. If you were angling for a high GPA for whatever reason, you cannot afford to experiment too much during lab work. It's another case entirely of course if you are conducting research.
Really a shame because understanding why your results were incorrect is much more important than stumbling on the right answer by accident.
> the focus ends up on execution rather than the why
Exactly right. School teaches you that the point of running an experiment is to try and get the same result as the teacher, while performing a ritual with steps called "hypothesis" and "method".
I realized after getting a degree in engineering from CMU that I should've loved biology so I went back to school after working as a software engineer for a year and studied neurobiology. And since then, I've suggested that people early in their career should take a break and go back to school and study something totally different.
In Zen and the Art of Motorcycle Maintenance Robert M. Pirsig suggests something very similar. He makes the point that students should go and work a job before picking what to study because they'll see where the value comes from (he of course puts it in much better words)
I've heard this advice a lot with respect to graduate school/PhD work. And indeed, the students that came from industry jobs tended to be much more impressive; some of that was probably from the "real-world" experience, and some probably from a self-selection effect where folks who came in from a presumably well paying job had to have really wanted it and were therefore more motivated.
That might be difficult given the job market now compared to Pirsig's time. Of course you could get menial job but that won't tell you much about the real job you want, just about what work is like in general.
With what money?
I went back to graduate school - where you get paid to be a student
I had a similar experience with nature. My dad was the outdoors type, a conservation officer who loved hunting & fishing; I wanted nothing more than to be inside reading an encyclopedia. I have always liked science, but biology was just one subject among many.
When I became an adult, I gravitated to computers because there is so much to learn about them. My focus has been infrastructure, but I've picked up software development, assembly, kernel hacking, data science, and a dozen other things along the way (mostly at amateur levels, but I'm always happy to learn).
I have have other interests (economics, homebrewing, astronomy, sociology, making music), but in each of those cases I learned what I wanted to after a few years & moved away. When covid hit, I picked up natural history through iNaturalist -- and that has so far been very very different, much more the same kind of endless opportunity for discovery that computers felt like.
There is so much weirdness in biology. Parasitic wasps with genes that came from viruses that suppress caterpillar immune systems, male spiders that have appendages (pedipalps) that look like boxing gloves, the many kinds of bumble bees around me, introduced species, nests, microorganisms -- it's insane. It's higher up the stack than the stuff the author is describing, but no less wonderfully complex and fascinating.
The quote from Lewis Thomas really hit home for me: "People ought to be walking around all day, all through their waking hours calling to each other in endless wonderment, talking of nothing except that" [cell|insect|weird relationship|phenology|behaviour]. Kudos to the author for putting this all into words so well, and for adding a dozen books to my must-read list.
As an ex-microbiologist, the thing I can't stand is how smelly life is. Be in the same room as gangrenous flesh and your intestinal fortitude will be severely tested.
Other than that, I don't mind it, but I still prefer silicon.
>How come we memorized chemical formulas but didn’t talk about that [exciting stuff about developmental biology]
You can argue that about any subject. People want to take physics and learn stuff about black holes but instead the intro courses are about balls rolling down inclined planes and other such "boring" things. But you have to know the basics before you can understand the "cool" stuff!
Yes, you should have. While I can understand that not all high school biology teachers will drag you by the nose and make you see the wonder of biology, and textbooks are often awful, I’m confused why this means the author couldn’t go read on their own (as they eventually did).
I could write a similar screed, as a biologist, that I should have loved computer science, but find it a zoo of names that somehow manage to make even less sense than biology.
Yet natural curiousity kept me interested enough in comouters, and the day to day need to interact with them meant I had to have some understanding of these systems.
What is sad is, as a society, we don’t think of biology as being similarly useful in our daily interactions with the environment and other people.
But I urge anyone who’s annoyed by the biology text book and the list of names: please put in effort to look below. Neither biology nor the brain is a complete black box, and what we have learned over the past few decades is thick with beautiful structure and organization.
But also accept that biology is different. You can’t compact all of it to a few equations because unlike physics and basic elemental chemistry, biochemistry is still finding new rules and new efficiencies.
The rules of biology will never neatly compact to the point where individual molecules and cells and their identities are meaningless. That is the price of complexity that is under constant evolutionary pressure.
But we don’t need to remember every name, thankfully. At some point, you learn to classify by composition and function sufficiently that a wholly new protein just slots in, updates your mental model, and you move on better informed.
[2020]
previous discussions:
- https://news.ycombinator.com/item?id=25136422
- https://news.ycombinator.com/item?id=32035054
- https://news.ycombinator.com/item?id=40103590
This resonated strongly. I hated biology as a kid but have been blown away at the wonder of it all as I've started to study it as an adult. I wish more of the magnificence and wonder of it all was conveyed vs the rote memorization that is so commonly taught.
If i had access to articles/blogs/YT/TT/AI like this, I'd have had become Leornardo Da Vinci.
I used to be inquisitive but coming from a poor neighborhood, I had no access in the olden days.
This type of article should persist.
maybe a stupid question, but, don’t you have access to all those things now? What’s stopping you from becoming Da Vinci now?
OMG! it's true! I have skipped so much!
One of the threads like this one has prompted me to start reading the book Molecular Biology of the Cell several years ago. I need to get back to it.
>It was only in college, when I read Douglas Hofstadter’s Gödel, Escher, Bach
I see this book referenced all the time (HN, tech CEOs, misc. articles, etc), especially from folks who got into AI early. Is it really that amazing? Or is this some kind of signaling folks like to do to prove their smarts? Or both?
The author prefers people read his newer book I am a strange loop since it more directly represents his views. He’s apparently frustrated that nobody gets the point of GEB (which is to discuss consciousness).
If you like the mathematical aspects of computer science and computability theory, cranking out proofs using lambda calculus and Turing machines fascinates you, and you think Lisp is an elegant language, you may like it. For the average developer, it's unlikely to be interesting.
I read it shortly after it came out when I was in high school and it was sort of a mind blow - perhaps just because in the early 80s we didn't really get exposed to so many interesting ideas.
I wasn't a huge fan, to be honest. some good ideas, but overall the book felt self-indulgent. "metamagical themas" is a far better book if you want to read one thing by hofstadter, and "le ton beau de marot" if you want a deep dive into something.
It is unique; you've certainly never read anything else quite like it. Hofstadter is a deep and careful thinker who loves language and wordplay. He writes in order to communicate something he has spent a long time thinking about, not merely for the sake of cranking out a book. I've read a number of his other books, and some of his ways of thinking have stuck with me for years and shaped the way I see the world.
It's definitely signaling for the majority of people still talking about it today. Though, that's not saying much that you didn't already know about the groups you mentioned.
Being that it's more of a Gen Xer pop-sci book, it's not to "prove smarts", but to share a vibe. It belongs on someone's shelf next to their copies of The Naked Lunch and Aja. Maybe even a signed copy of A New Kind of Science?
I'm not trying to be dismissive. It's just true. Nobody is even ashamed of it, nor should be. It's an interesting and still relevant perspective, but because there's no resolution to this line of thinking, many find it underwhelming. There's no "aha" moment to be found in any of this. Just lots of introspection.
You gotta take the good with the bad though. The tall grass is an easy place to hide.
It's a good book, despite its flaws. It offers a lot of deep insights and I think it really inspired a lot of people, myself included.
I absolutely experienced this in college. I signed up as a computer science student, as one does. I took all of the freshmen classes across broad topics, and the first biology class was basically just like the article describes. Words and memorization and microbiology and boring stuff. Who cares, let's get back to the dorm room to play CounterStrike on the school LAN.
But then I took the second required biology course. And rather than be about memorizing the krebs cycle, it was macrobiology. Ecology, evolution, and everything I hadn't realized I wanted to learn about the world around me. I instantly fell in love and 99'd the class. I changed my major to Biology, went pretty heavy into biology and chemistry, and didn't take more than a few Java classes in Comp Sci. I graduated with a B.S. in Biology.
I'm still a software developer, mind you, but I wouldn't trade the Biology degree for anything. Learning statistics, experimental design and experimentation, and just having the opportunity to deep dive into the physical world from the biggest to the smallest details, it was life-changing.
I still ended up learning data models, algorithms, and probably would be a better engineer if I had dug in deep on comp sci, but I like to think the biology degree helped me be a better developer for different reasons.