| Very good point! To the extent that we can build on abstractions and black boxes we stand on the shoulders of giants. BTW, perhaps s/human intelligence/science & technology. Does this really work about as well (e.g. leaky abstractions but better than nothing) in all disciplines? Learning math is a pretty much a 'climb the ladder' experience. You don't have to literally discover it all for yourself, but you do still have to learn it. I assume e.g. biology is similar; there are absolutely abstractions upon abstractions, but it takes a tremendous amount of work to level up to the point where you are making breakthroughs. Certainly low hanging fruit abounds, but our individual capacity for learning seems fairly limited in the great scale of things, and has not advanced much in the past few centuries. As a species, we either gain an order-of-magnitude increase in our ability to learn/retain knowledge, or the computer does it all for us. Not sure how much I like the potential adverse side-effects of the 2nd case. Evolution of science / technology is typically drawn on an exponential scale and we're staring up the side of a cliff ahead of us. There are a lot of marvels in the world we have built, but most of them to someone with 15 years of training in the relevant field are not black boxes or magic. I just imagine climbing much further up the cliff and you start to get to that point. E.g. I was watching a video of how the Toyota Prius eCVT works last night. I know fuck-all about CVTs, but I have a passing familiarity with planetary gears, and could follow the 15 minute explanation / walkthrough and learned enough to distinguish eCVT from magic. In 100-500 years I would be surprised if the underlying technology of our personal transportation devices would be remotely so 'accessible'. Isn't it only a matter of time before computers are designing and replicating devices that are sufficiently beyond our capability to understand how they even operate? Or synthetic compounds created by computer algorithms that cure disease but we have literally no idea the mechanism of action? Maybe in a very few problem domains today this is already the case. |
Of course there's also the middle ground option, where the clear distinction between human and computer becomes blurred, and eventually meaningless.