Advait Sarkar

But she's also maintained direct material engagement at strategic points.

She read the relevant portions of the document herself.

She constructed her decisions and her argument herself.

And ultimately, it can be said, she has written this document herself.

Moreover, she worked better because of AI.

AI provocations at every stage of the process kept her metacognitively engaged, always looking for critiques, alternatives, and lateral moves.

We have been studying the effects of tools like this, and the results are promising.

You can demonstrably reintroduce critical thinking into AI-assisted workflows.

You can reverse the loss of creativity and enhance it instead.

You can build powerful tools for memory that enable knowledge workers to read and write at speed with greater intentionality and remember it too.

It turns out, with the right principles of design, you can build tools that are the best of both worlds, applying the awesome speed and flexibility of this technology to protect and enhance human thought.

These are simple, general principles like ensuring that the tool preserves material engagement, offers productive resistance, and scaffolds metacognition.

And while we've been primarily studying professional knowledge workers, we believe that these principles can extend to all aspects of AI use, including when we use it in our daily lives, our hobbies, and even in education.

I repeat, efficiency is not the aim of tools for thought.

Better thinking is.

But sometimes you can't have both.

I used to think there was no such thing as a free lunch in human thinking.

This is so much better than a free lunch.

This is a lunch that pays you to eat it.

I want to close with some thoughts on the values that we have in developing AI software.