https://praxis.fortelabs.co/progressive-summarization-ii-examples-and-metaphors-5f9b8b7108df/

Let’s look at how a single source can proceed through the layers of progressive summarization.

These are Layer 1 notes I took on an article on postrationalism, a topic I’m interested in. This is 373 words, which would take about 2 minutes to read at an average reading speed. 2 minutes doesn’t seem like much, but when you consider that these notes could have no relevance to the task at hand, it’s a lot of attention to pay for nothing. Especially considering this is dense, challenging material.

For Layer 2, I bolded what I thought were the key points:

We’re down to 181 words now, about half as long. But it’s the best half, which means a lot of value has been added. It will only take me a minute to get the gist of this note now, and spacing out the bold passages also makes reading faster.

For Layer 3, I highlighted the best of the best parts:

Now we’re down to just 60 words in 3 sections, which I can scan in 10–20 seconds. This is 6–12 times faster than the full, Layer 1 notes (not to mention the full original article). Imagine what you could accomplish consuming sources 6–12 times faster, OR consuming 6–12 times as many sources in the same amount of time. While at the same time, repackaging those insights in a form that Future You can easily find and use.

Let’s do an experiment: in about 20 seconds, scan just those 3 highlighted passages. Are they enough to give you the gist of this article? I’ll wait…

The answer is, probably not! They are enough for me only because of my personal context, prior reading, and experience summarizing this note. This is why this summarization process has to be done manually and individually. There are some layers and some sources where external tools can help, but until we develop not only artificial intelligence, but extended artificial cognition, summarization won’t be something we can fully outsource.

By the way, this example illustrates why tags will never be adequate for long-term, open-ended research. The following are words and terms found somewhere in this text. Can you imagine how complex your tagging system would have to be to cover even part of this list?

The text itself is its own best tagging system. I think we should focus on surfacing the key terms already found there, instead of dreaming up tags. Because here’s the catch: even if you used tags to find this note, you would still have to evaluate it quickly for relevance.

Here’s another example of Layer 3 notes, from the book The Future of Work by Jacob Morgan, which you can view in their entirety here:

I didn’t find the book particularly insightful. It was mostly a listing of major trends I already knew about. But it does contain lots of good research findings, which I can use for my own purposes, including in some cases to make opposing arguments. This is why usefulness is such a, well, useful thing to look for: it’s like walking through a junkyard for pieces of junk cars you can rip out and repurpose. You aren’t limited to the perspective or knowledge of the author. You start your own thinking at the level of the best thinking out there, instead of at ground level.

With these most useful parts highlighted, Future Me’s attention is brought directly to them. He will be able to quickly scan the highlighted parts, and load up those juicy tidbits without having to re-read the whole book, which would be a waste of time.