IMHO the article is about "data" as in "personal information", but let's indulge in your generalization.
In logic, you have definitions that are extensional (list of objects of the defined type) or intensional (conditions on the object of the type). Perhaps you can think of first representation as data, and the other representation as model or program.
But it's not trivial to convert between the two representations. From extensional to intensional is machine learning, and the other way you face a constraint satisfaction problem.
If we could somehow do both efficiently enough, then perhaps we could represent everything intensionally, as generative programs, and get rid of "data". But we don't know how to do this or whether it is possible.
> IMHO the article is about "data" as in "personal information", but let's indulge in your generalization.
That is weird on its own, because I don't see how Kay's quote could be in any way about it. I appreciate the article on its own, but in context of the quote and discussion it's taken from, it feels like it's only related because it uses the word "data".
In logic, you have definitions that are extensional (list of objects of the defined type) or intensional (conditions on the object of the type). Perhaps you can think of first representation as data, and the other representation as model or program.
But it's not trivial to convert between the two representations. From extensional to intensional is machine learning, and the other way you face a constraint satisfaction problem.
If we could somehow do both efficiently enough, then perhaps we could represent everything intensionally, as generative programs, and get rid of "data". But we don't know how to do this or whether it is possible.