Through our lives we build mental models of the world that we apply in all our interactions and decisions.
There are three major problems with this:
- No mental models are right, some are just more useful than others. This means that however good our mental models are, they can be improved.
- Having highly developed mental models that we have refined through our life makes us more prone to bias. We tend to look for confirming evidence and discard contradictory information.
- The world is constantly changing. Our mental models that served us well yesterday may not work as well tomorrow.
From convictions to probabilistic thinking
One of the most valuable shifts we can take in our thinking is to shift from convictions to probabilistic thinking.
Instead of deciding whether something is correct or incorrect, we should always attribute a probability to it. That might be close to zero or 100%, but it should never be either.
In Chapter 4 of Thriving on Overload on The Power of Filtering I introduce Bayes Theorem and how it can be applied to improve our thinking.
Bayes Theorem
Bayes Theorem is a fundamental concept in statistics that provides a way to calculate the probability of an event. It works by starting with an initial probability, called the prior probability, and then updating this probability as new information becomes available.
The theorem is applied in a range of fields such as finance and healthcare, as well as in machine learning, for example to continually improve the accuracy of image recognition systems or natural language processing.
Advantages of shifting to Bayesian thinking
Applying these principles, we can by default assess any situation in terms of probabilities.
- Once we mentally attribute a probability to an event, this sensitizes us to information that will adjust that probability.
- It reduces or even eliminates our biases, making us open to evidence that shifts our assessments, rather than perceiving information differently depending on whether it confirms or contradicts our views.
- Bayesian thinking is also extremely valuable in helping group decision-making. If you get members of a board or executive team to attribute probabilities to potential outcomes you immediately get past arguing what you believe to assessing whether new data adjusts your opinion.
Bayes Theorem is a simple mathematical formula, but the underlying concept is one we can readily apply to our thinking processes.
In the book Superforecasting, which studies the small minority who excel at forecasting complex events, the authors note that “what matters far more to the super-forecasters than Bayes’ theorem is Bayes’ core insight of gradually getting closer to the truth by constantly updating in proportion to the weight of the evidence.”
This one simple shift in your thinking processes can be invaluable in helping you thrive in a world of overload.
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