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Study Hacks Blog

Do We Need AI to Revolutionize Work?

In recent months, I’ve been doing a fair number of interviews about my new book, Slow Productivity. I’m often asked during these conversations about the potential impact of artificial intelligence on the world of knowledge work.

I don’t talk much about AI in my book, as it focuses more on advice that individuals can put into place right now to escape busyness and find a more sustainable path toward meaningful accomplishment. But it’s a topic I do think a lot about in my role as a computer scientist and digital theorist, as well as in my recent journalism for The New Yorker (see, for example, this and this).

With this in mind, I thought I would share three current thoughts about the intersections of AI and office productivity…

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Beyond Black Box Management

An Exciting Way to Make a Living

Alex Honnold is an adventure climber. He specializes in free solo ascents, which means he climbs tall things with no ropes. If he falls, he dies.

He’s perhaps most famous for being the first person to free solo Yosemite’s 3000-foot El Capitan wall (see above).

Not long ago, at a live event at the USC Performance Science Institute, Honnold described an interesting technique he used to help prepare for his El Capitan ascent:

“For the full month before I soloed El Cap, I erased all social media off of my phone…I [also] stopped responding to email so much that I stopped getting emails…”

Free soloing turns out to be an endeavor that’s as cognitively demanding as it is physically demanding. Honnold’s distraction-free month was about getting his mind into shape for the big climb.

Alex Honnold’s feats are clearly awe inspiring, but I’m mentioning him here for another reason: his cognitive training provides a hint about a major transformation that might soon upend the world of knowledge work.

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Beyond Flow

A Deliberate Day

Earlier this week, after three days of trying, I proved an interesting theorem. I was studying a certain type of scheduling problem in graphs. I was finally able to prove that without lots of knowledge about the graph no algorithm can solve the problem fast.

This morning I set out to extend this result. I wanted to know what happens if you have more knowledge. After about an hour, I had a partial answer: If the graph is small in a certain way there is an algorithm that can solve the problem fast — I know this because I found it.

Unfortunately, for more general structures I couldn’t make the math play nice. I had a hazy intuition, but attempt after attempt to make it concrete failed. I couldn’t hold the pieces straight in my head. (See here for more on the style of problem I’m talking about here.)

After another 3 – 4 hours I had to stop for the day.

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