Rabkin's Dictum: If you don't understand something, it's because you aren't aware of its context.
Building off of a discussion with Andy Matuschak at Edge Esmeralda about his talk How Might We Learn:
There's an apparent tension between in-context, just-in-time learning, and working one's way through a structured, abstract curriculum.
The product sketches in How Might We Learn bridge this gap by imagining an AI (or more broadly, a ubiquitous computing system) that has access to both the world of a learner's desires & capacities, & the world of the discipline, tradition, industry they're operating in.
So at every moment, following along with a learner, it can find the next right action, the necessary context, the next step in the skill progression, which might be asking a question, pointing to the relevant portion of a text, generating a dynamic representation, providing an interactive exercise, ... so that the learner progresses.
There's also an apparent gap between tacit knowledge--e.g. how does an improvisational dancer know what move to make next?--& legible, transmissible knowledge. Tacit knowledge is called tacit because it's difficult to express.
But we can also imagine our system observing that dancer and finding a next right action to support them not as a learner, but as a teacher. It can use the same capacity to synthesize context to help express & represent tacit knowledge.
it might start with direct data capture:
and continue through interviewing with dynamically generated questions, prompts, provocations:
And all of this can feed a machine learning system that can tease out the hidden patterns and make them legible--in other words, to translate from an unknown language into a known one.
Last year, Robin Sloan asked: "What could I do with a universal function — a tool for turning just about any X into just about any Y with plain language instructions?"
He was asking in the context of software systems across the web -- but now we can ask this question again with X and Y as bodies of knowledge, whether they reside in computers, humans, or anything else.
Related: