In their terms, manipulating your environment to figure something out is an "epistemic action" – like when you reshuffle your scrabble tiles to make it easier to come up with new possible words.

So what might be going on here?
The authors say that using your external environment to solve a problem is a before-unmeasured element of intelligence.

But, back to what they actually wanted to show.
In psychology the Raven Advanced Progressive Matrices test is used to measure fluid intelligence.
They came up with two versions: a static version, where you solve the matrix just by looking at it, and a click + drag version.

Feel free to laugh at this next sentence in the same highlight – the paper is from 2019...

"Existing artificial intelligence programs never proceed by printing out intermediate results to repeatedly reinspect them."

YES THEY DO, IN 2025!
They are called...REASONING MODELS!

The reason we do this, they say, is that this unburdens our working memory, which in turns allows us to make more complex inferences – we have more "room to think" in our head, if you will.

How do they arrive at that conclusion?
Given that Andy Clark is a co-author, it's no surprise that they start with the observations that humans make use of their environment to think better all the time:

Conclusion up front: their contention is that it matters an awful lot how and that we use tools to augment our intellect

Currently trying to figure out how this maps to/will map to AI and knowledge work

Learned a new term today ( @orpheas.bsky.social posted this on the bird site)
Very useful term: reachback

It's over ten years ago that I saw Fernand Cormon's "Caïn" at the Museé d'Orsay in Paris.

It's huge - 7m x 3.8m. And standing before it you're overwhelmed by the desolation and hopelessness of the picture.

That feeling...that's what we need to fight against.

To get this magic multi-level linking, you need to set up "semantic field functions" and select "Part of":

>Serves Goal is "Part of" goal, which has a field >Area which is "Part of" area

Now the crazy neat thing about Tana is that you can link supertags multiple levels deep:

area > goal > project > task

And on each area, I can show all the projects belonging to any goal that belongs to the area, for example:

Every goal you create in Tanarian Brain is linked to an area – and any area can have many goals, of course.

Goals get a status: current, accomplished, dropped, or failed.

And they get a dashboard for all projects working towards that goal.

One huge part of Tanarian Brain (my Second Brain template for Tana) is a super powerful implementation of Tiago's PARA framework.

The area supertag comes with three things:

1: A status (is the area active or archived)
A list of
2: the goals for the area
3: the projects for it

Areas and Goals in Tana

Let me show you how easy (yet powerful) it is to implement areas and connect them to goals in Tana. If you're looking to implement Tiago Forte's PARA in Tana, this thread is for you:

Can we speed up transhumanism so I can type with two hands and have a third to pet my dog?
Merlin wants to know!