Two Books On Making Decisions Under Uncertainty
This is a repost (with edits) from my old blog. I shall focus all my writing efforts on Medium, as it is just easier that way.
When I graduated from college in 2009, the job market was still shaken by the Lehman Brothers collapse on September 15, 2008. My initial career plans went out of the window, and I was in and out of a couple of jobs within the first five years of graduation. During that period, I envied people who had dream careers (doctor, lawyer, architect) from a young age, and had set career paths to follow. It was only when I landed my data role in a Singapore startup in 2019 that I finally felt my career was going some where. Even so, analytics is an evolving field that has no definite career path. I had to learn to function in a highly uncertain, unstructured and information-starved environment.
Dealing Uncertainty
During this journey, I found two books that complemented my intuitions about decision making under extremely uncertain conditions. The books were The Signal and the Noise by Nate Silver and Thinking In Bets by Annie Duke, and their core message is that in life, we have to make decisions with incomplete information.
The Books
I read Signal a few years after graduation, and I was intrigued by the wide spectrum of topics covered relating to predictions, from economic forecasts, predicting earthquakes to interviewing a professional sports bettor. Signal also briefly covered the intuitions of Bayesian statistics. Bayesian statistics stipulates that we have a set of base probabilities (a priori) on different events unfolding, and when new information come in, we can update our probabilities and relevant actions or predictions accordingly.
Bets, on the other hand, was written by a ex-professional poker player who transferred her poker skills to consult organisations on decision-making under uncertain conditions. Poker is a particularly apt mirror of life, because it has a strong element of uncertainty. The poker players do not know what cards will be dealt until the game ends. Hence, the same strategies in poker can lead to different outcomes, depending on what cards are eventually dealt. Bets also went deeper into the probabilistic thinking strategies she honed as a professional poker player, and how she applies them to situations beyond the poker table. These include stating the odds of how confident you are (I am 80% sure), preparing a pre-committed strategy before executing a plan, and having peers to review your strategies and blindspots.
Learnings
I realise when two vastly different professions were converging onto similar ideas, and I saw how relevant they are to my highly uncertain and unstructured life in the field of analytics.
I learned to frame life situations as hypotheses to test and validate with data. Future actions will then be based the learnings I get from how these hypotheses play out. Some of the questions I have asked myself include: Should I still apply for a PhD? Should I learn to code? If so, what programming language should I learn? Will any company hire a self-taught programmer like me ? After identifying these important hypotheses, I took small actions to gather information and feedback to adjust my expected probabilities of achieving a certain outcome. Being able to correctly assess my probabilities gave me the confidence to know when to double down on my endeavours (learn coding, apply for tech roles) and when to cut my losses (stop my PhD applications). Ultimately, these hypotheses and probability estimates directly influence the many decisions and actions that I took in my life. This was how I took calculated and iterative bets.
Resulting & Self-Care
Bets introduced the idea of resulting in poker, where a player judges the quality of his game decisions based on its outcomes. A poker player needs to appreciate that even if he made all the right moves, he can still lose due to bad luck. He can also win a hand due to pure good luck. Resulting reminds us to focus on the quality of our decisions and not their outcomes.
Because my best efforts can still lead to undesirable outcomes, I learned to not see them as see failures, but more as learning opportunities to update my probability estimates. This mental model helps reduce some anguish of seeing myself as a failure, and allows me focus what I can learn from the outcome to improve the quality of my decision making skills in the long run.
Bonus Content — Type One / Type Two Decisions
Another concept that comfortably compliments this topic of uncertainty is the Type One / Type Two decisions framework that Jeff Bezos and Amazon uses. Generally, we should make as many reversible (Type Two) decisions as possible, because they allow us to quickly learn from them, and we can reverse them if we need to. It is the non-reversible, Type One decisions that we need to be careful, as they may bring irreversible damage if proven bad.
This idea has allowed me to focus more on what I can learn from different uncertain situations, or what uncertainty in my life that I need to resolve before I can make more confident decisions.
Conclusion
I only covered briefly what both books covered. Both books are well-written, informative, and provide really thoughtful ideas on how to structure decision-makings in ones life. If you are a non-fiction book reader, I hope I did a good job sharing why I feel these two books are really worth a read.
Also, if you are a Singapore library fan like me, or just want to support more of such book recommendation writings, consider to use my web app to locate these two books (and other books) in our Singapore libraries! I wrote a free web app that uses the official National Library Board (NLB) APIs to show where your books of interest are at, and I am showing the book availabilities by libraries, which is different from how NLB does it now their website and app.
