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Naval Ravikant on leaning against heuristics and bias

Simple heuristics aren't so simple after all

Hello world!

You might know, I am a big fan of Naval Ravikant. Born in India, he moved to the US with his brother and mother when he was nine.

He went on to become the founder of AngelList, Product Hunt and some other large technology companies.

He invested in Uber, Twitter, Postmates, Notion and 200 other companies.

Last but not least, Naval is the author of the book “The Almanack of Naval Ravikant”. Maybe a loaded title, but it is a strong book.

On my trip to Melbourne this week, I re-read it again, and stumbled over a couple of pages which are perfectly in line with my last research on decision-making and risk-taking, heuristics and biases.

I wanted to share some highlights with you today. Keep it short and spicy!

The following is an excerpt from the book, page 103 - 112:

“The classical virtues are all decision-making heuristics to make one optimize for the long term rather than for the short term. (…)

During decision-making, the brain is a memory prediction machine. A lousy way to do memory prediction is “X happened in the past, therefore X will happen in the future.” It’s too based on specific circumstances. What you want is principles. You want mental models. (…)

I don’t believe I have the ability to say what is going to work. Rather, I try to eliminate what’s not going to work. I think being successful is just about not making mistakes. It’s not about having correct judgment. It’s about avoiding incorrect judgments. (…)

Simple heuristic: If you’re evenly split on a difficult decision, take the path more painful in the short term.

If you have two choices to make, and they’re relatively equal choices, take the path more difficult and more painful in the short term. What’s actually going on is one of these paths requires short-term pain. And the other path leads to pain further out in the future. And what your brain is doing through conflict-avoidance is trying to push off the short-term pain.

By definition, if the two are even and one has short-term pain, that path has long-term gain associated. With the law of compound interest, long-term gain is what you want to go toward. Your brain is overvaluing the side with the short-term happiness and trying to avoid the one with short-term pain.

So you have to cancel the tendency out (it’s a powerful subconscious tendency) by leaning into the pain. As you know, most of the gains in life come from suffering in the short term so you can get paid in the long term.”

While this might sound a bit pompous, it is very close to what I discussed over the past weeks.

Heuristics and biases are shortcuts for faster decision-making.

They are built to reduce risk and increase the likelihood of survival.

The brain is wired to reduce physical or emotional and mental pain. Short-term rewards are preferred.

I might be the only person on earth who gets so stubbornly interested in this. But it really blows my mind to think how many decisions we make each day and year, that are based on biological wirings suited for the environment 10,000 years ago.

To make the best decisions possible in our fast-paced lives, we need to understand and then reverse-engineer decision-making. It does not mean to excel-sheet the life out of every decision. But it means to put away initial tendencies, calm down the “let’s have it easy and simple” brain and be comfortable with some first uncomfortable steps.

When I look back, every “uncomfortable” decision in my life, stepping away from music into IT, from working full-time and doing my BA every single evening and weekend for 4 years, moving to Nairobi and live in Africa, joining a company that nobody knew in 2016 and see it grow to a 5000 people global organization, moving to Australia, all of these were uncomfortable. There was always more work and admin. I could have netflixed each night.

But none of the decisions do I regret.

Hence why I can relate with Naval’s words.

Enjoy your Thursday or have a good night - depending on your time zone!

Alex

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