#017 | Decision Quality vs Luck

Weekly newsletter on Natural Language Processing (#NLP365), Entrepreneurship, and Life Design content!

Hey friends,

This week, I have slowly shifted from reading to making level 4 notes on the books I have read. Over the weeks, I will share some of my notes and thoughts here and include at least one action point from the book 📚. This week, I made notes on Thinking in Bets: Making Smarter Decisions When You.

The Relationship between Decisions and Outcomes isn’t perfectly correlated.

People often think that good outcomes comes from good decisions and bad outcomes comes from bad decisions but in reality, there are many other factors that’s beyond your control that influence the final outcome .

When you make a decision about the future, you are making a bet that certain outcome will happen. It can be a good bet (a good decision) but that doesn’t mean the desired outcome will happen.

In the book, it uses poker as an example. When you bet on a good hand, you tend to have an asymmetric percentage of winning (80% win / 20% lose) but that doesn’t mean you are going to win. If you lose on a good hand, does that mean you have made a bad decision? No, it’s just bad luck! Similarly, if you win on a bad hand, that doesn’t mean you have made a good decision, it might mean that you got lucky.

Therefore, being able to differentiate between decision quality and luck is essential in your life journey

So what makes a good decision?

A good decision is when you have a good process that accurately represents your knowledge in the area of the decision. A good process should factor in some variation of uncertainty and figuring out how unsure you are. You need to make your best guess knowing that different outcomes could happen.

To factor in uncertainty in your thinking, you need to think probabilistically and avoid the trap of black-and-white thinking.

To make better decision, we need to explore alternative outcomes that’s in between the extremes level of right and wrong. By exploring alternative outcomes, we are recognising that just because something went wrong does’t mean that we have made a bad decision. It' simply means that one outcome out of a set of possible outcomes have occurred (despite low probability from our decision making process). And this also applies to when you experience good outcomes.

Therefore, making better decisions is about calibrating among all the shades of grey (all possible outcomes to the best of your ability).

Action Takeaway

Think probabilistically and avoid the trap of black-and-white thinking!

This week I finished reading:

  1. The Laws of Human Nature (26th Apr - In Progress)

Total: 35 / 26 books | 3 / 26 level 4 notes | 2 / 12 actions

❓Question of the Week

Does your best decision always lead to a good outcome? Does your worst decision always lead to a bad outcome? Have you experience anything different, where good decisions lead to a bad outcome?

Share your thoughts by replying to this email. I would love to hear from you! 👻 👻 👻

🐦 Tweet of the Week

💡 Quote of the Week

I tell teams that the most important benefit is just that you decided to focus your product work on a single target market at a time — Inspired

🔥 Recommendation(s) of the Week

April 2021’s Habit of the Month has just concluded! We wanted to encourage people to read consistently and as a group, we have read a total of 11370 MINUTES, covering over 50+ books! We are very excited and happy with the results!

We have received feedbacks for our first Habit of the Month challenge and have made some adjustment for May 2021.

For May 2021, we are introducing new habits that surrounds the theme of wellness and health. This involves forming at least one of the three daily habits:

  1. Read for at least 2 minutes

  2. Exercise for at least 2 minutes

  3. Sleep for at least 7 hours

If you are interested in joining May’s Habit of the Month challenge, please join Zeroton’s Slack Channel here.

🔦 AI Research - CS224W: Machine Learning with Graphs

I was recommended this Stanford’s CS224W module, covering machine learning with graphs, for those who wants to get into graph neural networks. I will be going over this module over the next few weeks so will share some of my thoughts :)

🎥 This Week on YouTube

That’s it for this week! I hope you find something useful from this newsletter. More to come next Sunday! Have a good week ahead! 🎮

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