What Does It Mean to Learn?

The real shame is that academic fashion jerked violently in the direction of Derrida and company in the mid-to-late-60s before anyone had time to really dwell with and appreciate the power of Gadamer’s philosophical hermeneutics. His masterpiece was only published in 1960, when he himself was 60! It’s a mature and deep reflection on themes he had been studying for 40 years. Ricoeur grasped its power, of course, but the whole Habermasian-Derridan-Foucauldian critical project flavored Ricoeur’s approach. Richard Rorty gestured in similar directions, with less depth (and certainly far less phenomenological power).

But invest the time to read Gadamer. It’s worth it.

But the argument that we should not learn while young because "It's not useful to us then" is a ridiculous premise to argue with. Perhaps I misunderstand it. Then saying that things benefit us far down the road, long after the original moment of learning...

I don't understand this line of thinking at all. Linking this to "educability" as a sort of hidden superpower makes me say "oh, really now?".

Like most scientists, he has to focus his ideas on a track with research directions which expand outwards, excite, and provide new directions and conversationality. He may not be aware of doing this.

Rare is the day when we see a psychologist studying things like how applying a new learning technique to class A effects all the other classes the student takes.

Rare is it we study flow state and motivation of the long term and find meaningful ways at a cohort intra-country level to increase happiness at school or final grades across the board, rather than just one course which the researchers focus on. And when that has been done in Scandinavia, who lead in PISA and happiness as adults and teens, scientists in the US ignore the research by and large. It's sad.

This is what I don't like about education research and theories. They can be worthwhile research directions, but diminished to theorizing, rather than application.

We do know modelling learning will involve fitting a multidimensional curve among a set of data points. There are multitudes of ways to do curve fitting. Our biggest issue, however, is to imitate the way the human brain does it. For this we still don't know how to do learn like a human. But we do know in it's most basic form that learning can be simply fitting a 2 dimensional straight line among a set of two dimensional data points.

Anyone who has used StackOverflow (or ChatGPT) to solve a programming problem knows this is completely false. Has the author never heard of “learn by doing”?

Personally, I think there's a set of outcomes here. To acquire knowledge usefully demands both retention and some ability to apply abstraction/synthesis to the knowledge acquired. Simply being a repositary of knowledge is not in itself usually useful, unless you want to win a competition for the most digits of pi, or ability to recite the Koran from memory, but latent within that ability are other skills which we often decry as "not intelligent" or "simply parroting facts" -the amount of facts you can recall aren't useful in the same way that synthesis over those facts is.

Isn't' this IQ? "Educable” seems like the latest iteration of 'multiple intelligences' or the 'street smarts' vs. 'book smarts' distinction.

Sidenote: it doesn't seem to me that the writer understands AI, its moving frontier, and its likely near-term abilities.

Law students write papers, ER students to CPR on dummies, and when I learn any new concept, framework or language, I build something with it. Don't toy and learning projects count?

> The "Empty Cup" or "The Empty Vessel" parable: 'A cup that is already full, whether with knowledge, opinions, or experiences, cannot be filled again. It is only the empty cup that can truly learn and absorb new information.'

He makes various arguments in the book that I disagree with, two of which I've put below. On the whole I think it is directionally correct though, and worth reading.

The first quibble I have is about humanity's most characteristic trait. In the book, he writes: "The mark of humanity is that a single individual can acquire the knowledge created by so many other individuals. It is this ability to absorb theories at scale, rather than the ability to contribute to their creation, that I identify as humanity's most characteristic trait".

I don't think that ability to acquire knowledge from other people is our most most characteristic trait. Creativity is. Learning is a form of knowledge-creation, and it is a creative process. We don't passively "absorb" theories when we learn from someone else. Instead, we actively look for and attempt to resolve problems between our existing ideas and the new ideas to create something new.

Another thing I disagree with is when he touches on AGI. He makes the argument that "we should not be fearful of a technological singularity that would make us powerless against AI systems". This is because it will "asymptote, at least qualitatively, to the human capability of educability and no more".

This is reminiscent of David Deutsch's argument that people are universal explainers, and AGI will also be a universal explainer; there is nothing beyond such universality, so they will not fundamentally be different from us (at least, there is nothing that they could do that we couldn't in principle understand ourselves).

I think this is true, but it misses something. It doesn't address the point that there is a meaningful difference between a person thinking at 1x speed (biological human speed) and a person thinking at e.g. 100000x speed (AGI running on fast hardware). You can be outsmarted by something that wants to outsmart you, even if you both possess fully universal educability/creativity, if it can generate orders of magnitude more ideas than you can per unit time. Whether we should be fearful or not about this is unclear, but I do think it is an important consideration.

His overall message though, is good and worth pondering: "Educability implies that humans, whatever our genetic differences at birth, have a unique capability to transcend these differences through the knowledge, skills, and culture we acquire after birth. We are born equal because any differences we have are subject to enormous subsequent changes through individual life experience, education, and effort. This capacity for change, growth, and improvement is the great equalizer. It is possible for billions of people to continuously diverge in skills, beliefs, and knowledge, all becoming self-evidently different from each other. This characteristic of our humanity, which accounts for our civilization, also makes us equal."

Leslie Valiant, an eminent computer scientist who teaches at Harvard, sees this as a strength. He calls our ability to learn over the long term “educability,” and in his new book, “The Importance of Being Educable,” he argues that it’s key to our success.

https://x.com/edulix/status/1827493741441249588