Perhaps if we allowed kids to move away from that idea of the "big college entrance exam" or similar we could dive into the deeper stuff like...what do YOU want to be when you get older, what problems do YOU want to try to solve and so on. If someone wants to work on video games then start pushing them down that path as soon as possible...get them to learn coding, media design, computer graphics and so on.
There are two ways to sort it out: teach people how to learn first, and teach them how a (small) variety of professions that are in demand work.
Only then, specialization. Current Chinese model is to identify talents early then force specialize and reject people even at advanced stages, leaving them with nothing.
Western model used to be more general even a century back, but is going now more the same way.
People are passed without working knowledge of estimation and arithmetics even, have no idea about basic politics and more.
It is superior in employing talent but leaves many broken people ultimately resulting in social costs.
Short name: rat race.
Old factory model provided identical education, relatively broad, to everyone (zero help if you got stuck) - and provided single vocational education on top. (Including research vocations.)
Yet more ancient one started with a trade education based on propinquity; rather than scouting and filtering.
This is less true in the USA than any other country I know of. The "college entrance exam" is not nearly as decisive or as prepared for as in other countries and most of the curriculum has nothing to do with it.
The SAT & ACT are also mostly limited to the humanities and math (and science for the ACT), with an optional writing section. China requires Math, Chinese, a foreign language, and any three of Physics, Chemistry, Biology, Geography, Politics, and History. With the SAT all those elective subjects are separate exams and most people do not take them.
I want to say there is a misconception about what technology does for education as current MOOCs mainly focuses on distribution, rather than what distribution enables which is to invest in what you distribute. But realistically that is probably more about incentives. They just do the easiest thing and effectively ends up giving everyone "reality tv" rather than "game of thrones".
What this kind of technology in education also enables is distributing the learning path, the planning or even part of the teaching. You can have hundreds of people spending large resources designing the systems and materials since it can be used by a lot of people, and also can be distributed to where it makes the most difference.
Of course it all comes back to the mindset and what reasons you do them for. They whole thing could of course also end up being a mess, or even abusive. But that is the challenge with technology.
That's why you see a race for obscurity -- lots of jargon to describe the complexity of the system.
In reality, good educational software is about good design, good goal alignment, good assessments, good sequencing, good intervention material -- it's all based on classic instructional design, not a superior algorithm. Has the software been set up to support data driven continuous improvement? That is more important than an algorithm.
That I know how it works because I wrote the thing doesn't take away from the miracle that it makes that kind of money for doing complicated but not all that complicated stuff.
When I look at generative adversarial networks and the recent attention-based language models I am similarly amazed at what they can do.
But I am also 100% aware of their limitations and I think the hype that they are near-term AGI technology is the real magical thinking.
My impression of Squirrel AI is really just using more advanced analytics for education, which is good in concept; but really they are selling parents' the fear that "if you don't buy our services, your children WILL be left behind."
You can't just dump content in and hope for the best.
Most research in this area is drawn from the domain of “Intelligent Tutoring Systems,” (ITSs), thoroughly described in Woolf’s book “Building Intelligent Interactive Tutors.” [WOOLFE2009].
I'd say the classic Intelligent Tutor System construction was pioneered by ADVISOR [BWB2000]. It's a two-agent architecture that first trains a student model on real-world data, then uses the student model to train a pedagogical agent using a more resource intensive algorithm. Most modern ITSs make use of Representation Learning (RL) to train the pedagogical agent.
One of the main techniques for structuring the problem domain is Bayesian Knowledge Tracing (BKT) [CA1995], where you model the domain being learned as a Bayesian skills network; i.e. a 4-tuple of probabilities (init, learning, guess, slip), updated in a Bayesian fashion. An excellent survey work in this area is given in [BGTPF2010].
If you're interested in the RL part of the problem, and how it can work with this setup you might want to look into partially observable Markov decision process — POMDPs. Emma Brunskill has done some nice work in this area.
[WOOLF2009]: Woolf, Beverly Park. 2009. Building Intelligent Interactive Tutors: Student-Centered Strategies for Revolutionizing e-Learning. Amsterdam ; Boston: Morgan Kaufmann Publishers/Elsevier.
[BWB2000]: Beck, Joseph, Beverly Park Woolf, and Carole R. Beal. "ADVISOR: A machine learning architecture for intelligent tutor construction." AAAI/IAAI 2000 (2000): 552-557.
[CA1995]: Corbett, Albert T., and John R. Anderson. "Knowledge tracing: Modeling the acquisition of procedural knowledge." User modeling and user-adapted interaction 4, no. 4 (1994): 253-278.
[BGTPF2010]: Brunskill, Emma, Sunil Garg, Clint Tseng, Joyojeet Pal, and Leah Findlater. "Evaluating an adaptive multi-user educational tool for low-resource environments." In Proceedings of the IEEE/ACM International Conference on Information and Communication Technologies and Development, pp. 13-16. 2010.
ISD is a cousin to the SDLC method of developing software. They both involve gap analysis and the construction of a solution.
My experience has been, that of the few first-tier astronomy graduate students that aren't mistaken about the color of the Sun, as many learned it in seminar coverage of common misconceptions in astronomy education, as learned it in their own atypically extensive and successful astronomy education. Current content is really, really bad. A "Primer" will require much better.
AI doesn't help much if your large textbook publisher's science education content is written by inexpensive liberal arts majors with no science background, consulting with "scientists". If one instead uses science graduate students, double majoring in education, with misconception lists in hand, you might get that Sun color right. Maybe. And interviewing researchers about their own research areas is even better. But...
Say you're writing a children's picture book about atoms. What magnitude of domain expertise support do you need? How about a small room full of MIT physics professors? Is that enough?
Can you see a bare atomic nucleus with your naked eye? Why not? Did you just now say too small, rather than beyond-violet "color"? That much is easy. But what if you wish to discover that a couple of atypical atomic nuclei can be seen with your room-lit naked eye, can be made to brightly fluoresce visibly (a multi-step spin-isomer decay, with one step visible)? So you can include a photo, of a glowing green dot in a vacuum vessel, in your picture book, to reinforce that nuclei are real physical objects. My experience has been that a room of MIT professors, most with some nuclear physics background, is likely an insufficient gathering of expertise. Unless it's a lunch for a visiting professor, whose focus is nucleus simulation, who self-describes their focus as a (with emphasis) "small" subfield, and who perhaps thinks all this obvious. Reflect on that: A room full of MIT physics professors is insufficient domain expertise to write an excellent children's picture book about atoms. How might we then go about writing a Primer, if it takes such an awesome gathering of expertise?
Before Primers can be airdropped, they need to be written. And I suggest we're not yet even at the point of recognizing and acknowledging the primary challenge there, let alone scoping, funding, and addressing it. It's not pedagogy and ed tech that's blocking the road to a Primer. It's the sciences. And their incentives and funding.
It's something I'd love to be working on, but finding people to work with has been a challenge.
Once we have these open source books then it becomes significantly easier to build additional tools on top of that source material - exams, practice questions, lecture videos, study notes etc.
Most of the ed tech players I see are simply developing tools that are trying to fit into a broken system. Simply put - the current system needs to be scrapped and replaced with something better, built with the internet in mind and built to be a major disruptor of GLOBAL education.
I am currently working on a side project trying to bring it to MVP stage. This is the idea I have in mind: Let's build a new platform that rebuilds education for the 21st century - start with writing open source textbooks. At the beginning, they don't need to be perfect, they can be revised as the platform grows. Then build a bunch of innovative self-study type tools using the latest in technology to make learning efficient, easy and fun. In terms of monetization - simple advertising and premium services (tutoring, live streamed classes with teachers etc.) and of course a simple credentialing system with the possibly to have proctored exams to add validity. Long-term vision would be this: a type 1 civilization university - all major subjects would have a course with a free textbook and an amazing set of tools to self-study it (or affordable options to get tutoring/view live streamed lectures with real teachers). Add in localization tools to translate all of these courses into the top 20+ languages. Each course would have a rigorousness protected exam for students to get a employment worthy credential. Eliminate all admission requirements and allow everyone to attend for free.
Writing a bad article is easy. And pervasive in science education.
I'm suggesting there's a level of excellence, at which even a small fragment of an article, for any audience, takes a surprisingly large gathering of expertise. So large as to be implausible with current social/technical/incentive infrastructure. And I'm speculating that it's an interesting level of excellence, with benefits that might justify the investment. Or at least the discussion of the possibility.
> write the high-level draft and then allowing a community of people to edit and revise it
I'm unsure how to describe why I don't buy this.
Imagine a draft newspaper article, which says "Foos do qux". The fact-checker objects, "But some foos don't do qux". The reporter "fixes" the draft with "Most foos do qux". The newspaper fact-checker says "yes, that's great", and it goes to press. Then someone who actually understands foos, points out to a colleague, that the entire focus on qux was misguided, confusing, and engenders misconceptions, and that indeed, the very concepts of foo and qux are badly flawed. "It's news media - what do you expect?" the colleague responds.
So there's a concept that you can wordsmith you way out of getting something badly wrong. You've likely seen some process where two parties have profoundly different concepts, but instead of discussing concepts, are engaged in text tweaking.
But what if, in excellent content, even high-level organization is sensitive to expertise-intensive details?
"Ok, for the foundational concept, we have proposals for atoms, a different definition of atoms, molecules with atoms as a degenerate case, atoms in molecules, nuclei, electron energy, electron clouds, configuration spaces, trajectory spaces, ... . Let's explore the correctness, accessibility and fruitfulness of each foundation." What if you can't even write a draft title, let alone structure a presentation, until after a massive collaborative process among educators, research scientists, and creative catalysts?
> the incentive problem...to encourage people to contribute
An MIT project to create cell-biology VR content approached the need for expertise by pulling in researchers for interviews about their areas. But there was a reoccurring difficulty... getting the researchers to leave. Such was their enthusiasm.
So I offer the hopeful possibility, that a project with just-the-right sweet-spot shape, might accomplish things that seem impossibly difficult, when seen less clearly.
> open source books
I'm sympathetic to OER. But in the context of transformative improvement...
Chemistry education research describes chemistry education content using adjectives like "incoherent", and as leaving both teachers and students steeped in misconceptions. It's not clear to me that a reasonably scaled OER effort can move that needle.
Years ago, NSF almost decided to create a national science education wiki, analogous in scale to wikipedia. That might have had critical mass for transformative change. But they didn't.
If you make having a high percentage at a standardised tests the point of education and use software to make you drive those numbers up, negative externalities are going to come back to you in a few decades in crazy ways... And the article does note this: "Earlier this month, the government also unveiled a set of guidelines to focus more on physical, moral, and artistic education". How much that's going to be gamed as well is going to be interesting I guess.
Now this same exchange could have happened between any two students with the basic alignments of "objective science" versus "natural sciences", but it did seem telling of a certain pure-science tilt on the part of the student from China. To push that further, one could say that the "objective science" angle lacked a certain "intellectual humility" in the inquiry, with an emphasis on the correctness of the machine results, and an assumption that better math will produce "winning" output. No real evidence, but that was an impression at that moment.
During agrarian times, it was back-breaking work. During the industrial revolution, it was in sweat shops. Once office became computerised, it became office drudge work. Industrial revolution came with promises of leisure, but they did not materialise (see "In Praise of Idleness" by Bertrand Russell. )
Incomes of the majority, and the debt due to consumerist needs of the majority are kept in balance so that no one has leisure time to fulfil their true human potential, and you need to work 3 decades to subsist.
I somehow tend to think that the coming A. I. revolution, if it does come at all, will leave things as they are in a new form - the more things change, the more they remain the same.
If were were to look at the working hours in a few European countries, it becomes clear that the weekly work hours has diminished from 65-70hrs in the 1870s, to 35-40hrs in 2000s . This, coupled with technology solutions that helps decrease household shores, improves healthcare and decreases time to acquire consumer goods (The list goes on), it becomes clear that we live in unprecedented times in terms of leisure.
It is also interesting to see hunter-gatherer societies, which is estimated to have worked from 2.8 to 7.6 hours. Did the increase in leisure time lead to 'true human potential' for these societies? If not, what makes us believe that it will be different today? Is it possible that more leisure time will lead to more boredom, screen swipe, etc?
If we were to assume that  data will continue to move in the same direction, then we are likely to have further gains in 'leisure time' led by a new technological evolution.
 Working Hours in Hunter-Gatherer and Other Premodern Societies - https://ourworldindata.org/working-hours#note-1
I recommend reading "Accelerando" by Charles Stross which is very imaginative if not in-depth enough... Or potentially the "Culture" series. People there don't just laze forever.
Basic income gives you not just money, but time. If you receive basic income, you can work less. If people live in a culture where everyone must remain in full-time employment until age 65+ and the vacation time they are allotted is meagre (e.g. the North American situation), then it is cold comfort if the money they make allows them to buy basics for more cheaply.
Secondly, while the basics of food or clothing have become cheaper in developed countries (though often only if you are comfortable sacrificing some quality of the product), housing prices are soaring. While a basic income, too, would have a problematic interaction with housing prices, housing costs would remain an issue even in the alternative future you posit.
"...while in communist society, where nobody has one exclusive sphere of activity but each can become accomplished in any branch he wishes, society regulates the general production and thus makes it possible for me to do one thing today and another tomorrow, to hunt in the morning, fish in the afternoon, rear cattle in the evening, criticise after dinner, just as I have a mind, without ever becoming hunter, fisherman, herdsman or critic." --Marx, The German Ideology
Just replace 'society' with 'centralized AI'. To keep busy, maybe the reality if you don't need to create real value anymore is that life becomes a half-empty series of paint nights, cooking classes, and other such role-play.
More likely is that life for many people becomes a lot more time spent staring at one’s phone. Even in places where people have a decent amount of leisure time, a lot of those old community events and social clubs are struggling now.
For example, I believe that ballet got started in part so that Louis the XIV could require his aristocrats to observe the proper etiquette that he'd made up, so that he could better control them.
Point being - they had enough food, shelter, and luxuries supplied to them that they didn't need to work.
"If machines produce everything we need, the outcome will depend on how things are distributed. Everyone can enjoy a life of luxurious leisure if the machine-produced wealth is shared, or most people can end up miserably poor if the machine-owners successfully lobby against wealth redistribution. So far, the trend seems to be toward the second option, with technology driving ever-increasing inequality."
Of course everything old is new, so you could read for example Hannah Arendt. Our societies have mostly evolved out of how to distribute profits from automation. The reason automation is now the boogeyman is because we have changed paths by not thinking about that.
Teaching math this way is likely perfectly fine for middle school
As a game developer, I have a lot of exposure to the art-school types, and it's amazing how poor their grasp is of how anything works, other than EDIT: s/humans/human emotions/ and human-centric narrative.
People may be taught physics and biology, but most of the knowledge will wash through them once they finished their exams and got their grade.
The main problem with public schooling is that the system designers (learning-target criteria setters, curriculum designers, textbook publishers, etc.) don’t properly communicate the fact that surveying the field to build a mental map of it, is the goal of primary (and most secondary) education. So you get teachers, parents, and students all worrying about test scores that show that you don’t understand a particular idea, when the curriculum was never designed to communicate particular ideas, but only the structures containing them.
The problem is that even after years of working in the field you will likely be underpaid, and it won't be possible to find jobs in the field without a direct connection. Another problem is that if you want to go for a PhD to learn beyond that you will need to sit though years and years of useless classes that you have essentially already taken, just to check some boxes. I don't think anyone self motivated to learn things will sit though 6 years of useless classes to check some boxes or at the very least it will be terribly depressing wasting so much life.
At least that is my experience. The open materials for CS and AI are great though.