How do you get better at something? What makes AI so valuable?
Input => Output => Feedback/Measurement => Alter input
Cue => Craving => Response => Reward
The Feynman Technique is often referred to as the best way to learn.
- Learn with intent to teach it to somebody else.
- Teach it to somebody else.
- Identify gaps in your explanation, review to better understand it.
- Enhance and simplify.
Read more about this technique on Farnam Street
When you teach you get feedback on your articulation.
You’re often not even aware of your own process. To better understand your process and what’s missing, articulate it.
Feedback allows you to find gaps you couldn’t see before. To improve something, create better feedback loops.
Noisy feedback can ruin you. Carefully select the feedback you pay attention and reduce the noise to get more of the signal.
Your own perspective is valuable, but don’t assume you know it all. Adjust so you’re not able to predict success or failure.
Compare to see which works better. Evaluate the overall success of the strategy you’re using. Decide when you should focus on the strategy you’re already using and when you should experiment with other methods.
Make high intensity, rapid feedback situations. It’s hard, it’s uncomfortable, but you’ll get over that initial aversion much faster than if you wait months or years before getting feedback.
Improving is bottlenecked by feedback loops. To improve faster, create faster feedback loops. AI has the fastest feedback loop ever seen. The process and scale from input to alteration is faster than anything humans are remotely capable of.
Moving forward we need to see how we can enhance our own feedback loops. Just because we have machines doesn’t mean we can stop improving what we know.