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I made a comment a few days ago in the context of increasing complexity of a lot of things in our lives, in which I mentioned > The problem is, continuously ed

I made a comment a few days ago in the context of increasing complexity of a lot of things in our lives, in which I mentioned > The problem is, continuously educating new people to know ever more and to be able to handle more and more sophisticated systems has a continuously increasing cost to society too, since we don't live any longer than before. https://news.ycombinator.com/item?id=35470905#35477122 https://news.ycombinator.com/item?id=35470905#35477122 This is one thing where aging slower could be very important for us. Increasing complexity alone requires more time for developing, planning, handling and maintaining a lot of our devices and infrastructure. Experience gained over long periods is worth much more. It also requires a higher up-front "penalty" in the form of more education before we can even get started with being productive in many interesting and worthwhile projects. For example, compare starting with Linux kernel programming in the 1990s vs. now, or building a house many decades ago vs. now. On the other hand, our capacity to place the anto-aging benefits with the right people are questionable. We can only hope that higher-level processes, not controlled by us, will still lead us to good outcomes overall. Similar with a lot of stuff already going on which we hardly have any direct control over, even in cases where "in theory" (meaning a theory that does things like "if we all just..", disregarding that coordination and information are physical and cost time and energy and a working algorithm) we could. So adding one more thing for the universe to sort out for us may not make much of a difference anyway, and having the moneyed classes go first, probably for a long time because the anti-aging solution probably won't be a simple pill, but a complex ongoing long-term process, might still work out. For humanity as a whole, if not for the (less lucky) individuals. It probably widens the gaps even more, in wealth and in education and in opportunities. Might still be worth a shot.

gcanyon 4y ago
But there are so, so many things abstracted away from our need to understand them. People a 120 years ago had to memorize trig tables. People 60 years ago had to learn how to operate a slide rule and understand how to handle accuracy. People 30 years ago had to learn how to do algebra and calculus. People 10 years ago needed to know how to set up the equations to ask Wolfram Alpha to solve the problem. Today, we're closing in on being able to say, "Draw up plans to build a mixed-use building on this plot with at least 20,000 square feet of retail and 60 residential units." And getting back an answer.
- justinclift 4y ago
  > ... an answer. Heh Heh Heh People -20 years ago need to learn algebra, calculus, slide rules, accuracy, and trig tables as the answers they're getting don't work and they're not sure what to do.
  - gcanyon 4y ago
    I suppose that might be true if something catastrophic happens, but hopefully that's unlikely. We'll see...
- ted_dunning 4y ago
  Your postulates are wrong * Nobody ever had to memorize trig tables (unless you mean the values for 30, 45 and 60 degrees) * Understanding accuracy is not associated with just slide rules. It is ubiquitous whenever you make measurements. Moreso if you calculate with these measured values. * People have been learning algebra and calculus for hundreds of years. They still are doing so. * Symbolic math programs like maxima, maple, wolfram alpha, sage and others only solve some problems, but they have been used for 40 years or more for particular situations. Given this, forgive me if I think your conclusion is flawed. You can ask a LLM model that answer today. And you will get an answer. Understanding what that answer means and how it is a form of hooey still requires domain knowledge. And it will for a very long time.
  - gcanyon 4y ago
    Trig tables: I remember reading that, but I can't find a cite and I'm happy to concede the point here, but having to have a book (you do acknowledge that such tables were a thing?) that you physically look things up in is hardly better. Accuracy: first, I can't believe I cross-wired accuracy and precision. Still, you seem to be responding as if I had gotten it right, so I'll respond in kind: sure, understanding precision is still an important concept, but it was much more so when working with a mechanical device that managed at most 2-4 digits of precision. I'm guessing that with 64-bit values, precision isn't a big topic of conversation outside of NASA. (That's hyperbole) You're saying that algebra and calculus are just as tedious/necessary now as they were 30 years ago? To be clear, I'm sort of fudging -- Mathematica is actually 34 years old. But my point is that tools like it have changed who needs to learn the techniques, and what learning the techniques look like. And of course it's easier to be certain that basically no one today needs to know how to use a slide rule than to say no one needs to be able to solve a quadratic -- the more recent the change, the less absolute it will be. Finally, "a very long time" seems optimistic. As an analogy, there were articles written in 2010 saying that it would be "a very long time" before computers beat anyone reasonably skilled at Go. It was less than ten years later that the very best humans couldn't beat computers. It's impossible to know where fast progress will be made vs. slow. I purposefully chose a hyperbolic example to illustrate the point, and it's entirely possible that architecture won't be a field handled well by AI/ML in ten years. But I think it's certain that over the next several years, multiple fields that humans regard as being as complex and domain-knowledge-dependent as architecture will be automated.

gcanyon 4y ago

But there are so, so many things abstracted away from our need to understand them. People a 120 years ago had to memorize trig tables. People 60 years ago had to learn how to operate a slide rule and understand how to handle accuracy. People 30 years ago had to learn how to do algebra and calculus. People 10 years ago needed to know how to set up the equations to ask Wolfram Alpha to solve the problem. Today, we're closing in on being able to say, "Draw up plans to build a mixed-use building on this plot with at least 20,000 square feet of retail and 60 residential units." And getting back an answer.

justinclift 4y ago
> ... an answer. Heh Heh Heh People -20 years ago need to learn algebra, calculus, slide rules, accuracy, and trig tables as the answers they're getting don't work and they're not sure what to do.
- gcanyon 4y ago
  I suppose that might be true if something catastrophic happens, but hopefully that's unlikely. We'll see...
ted_dunning 4y ago
Your postulates are wrong * Nobody ever had to memorize trig tables (unless you mean the values for 30, 45 and 60 degrees) * Understanding accuracy is not associated with just slide rules. It is ubiquitous whenever you make measurements. Moreso if you calculate with these measured values. * People have been learning algebra and calculus for hundreds of years. They still are doing so. * Symbolic math programs like maxima, maple, wolfram alpha, sage and others only solve some problems, but they have been used for 40 years or more for particular situations. Given this, forgive me if I think your conclusion is flawed. You can ask a LLM model that answer today. And you will get an answer. Understanding what that answer means and how it is a form of hooey still requires domain knowledge. And it will for a very long time.
- gcanyon 4y ago
  Trig tables: I remember reading that, but I can't find a cite and I'm happy to concede the point here, but having to have a book (you do acknowledge that such tables were a thing?) that you physically look things up in is hardly better. Accuracy: first, I can't believe I cross-wired accuracy and precision. Still, you seem to be responding as if I had gotten it right, so I'll respond in kind: sure, understanding precision is still an important concept, but it was much more so when working with a mechanical device that managed at most 2-4 digits of precision. I'm guessing that with 64-bit values, precision isn't a big topic of conversation outside of NASA. (That's hyperbole) You're saying that algebra and calculus are just as tedious/necessary now as they were 30 years ago? To be clear, I'm sort of fudging -- Mathematica is actually 34 years old. But my point is that tools like it have changed who needs to learn the techniques, and what learning the techniques look like. And of course it's easier to be certain that basically no one today needs to know how to use a slide rule than to say no one needs to be able to solve a quadratic -- the more recent the change, the less absolute it will be. Finally, "a very long time" seems optimistic. As an analogy, there were articles written in 2010 saying that it would be "a very long time" before computers beat anyone reasonably skilled at Go. It was less than ten years later that the very best humans couldn't beat computers. It's impossible to know where fast progress will be made vs. slow. I purposefully chose a hyperbolic example to illustrate the point, and it's entirely possible that architecture won't be a field handled well by AI/ML in ten years. But I think it's certain that over the next several years, multiple fields that humans regard as being as complex and domain-knowledge-dependent as architecture will be automated.