💾 Archived View for nox.im › posts › 2022 › 0116 › cognitive-biases captured on 2023-11-04 at 11:20:57. Gemini links have been rewritten to link to archived content

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Cognitive Biases

We're living in a world with too much information for our human brain to process and filter[1]. If we're not careful, we're getting constantly distracted and cannot focus. This makes us susceptible to all sorts of cognitive biases, leading us to draw false conclusions about the world and our surroundings. In order to avoid biases, it is important to become self aware first and subsequently aware of the most common biases. I'll start listing a few in this post and will expand on this.

1: process and filter

Confirmation Bias

A well understood bias is the **confirmation bias**. It affects how we test and evaluate hypotheses. It is the tendency to seek or interpret information in such a way that supports our existing beliefs and expectations. We can confirm any hypothesis with Google (or substitute any privacy respecting search engine), it is just a matter of asking the right question. But it goes even further, as even access to the same set of data allows us to draw very different conclusions depending on our world view.

*To avoid confirmation bias, it is important to seek information that both confirms but also contradicts our presumptions.**

Selection Bias

The selection bias also often leads us to faulty conclusions. It is sometimes called sampling bias and includes subtypes such as survivorship bias and is a result of poor data collection. We cannot easily draw "the seven habits of highly effective people" (don't read it) from those few that were successful and ignore those that failed that may have had the same habits.

*We can avoid selection bias by randomizing data collection.**

Recency Bias

Recency bias is a result of fading memory and makes us favor recent events when evaluating information. This is often a factor when evaluating employee performance but also when thinking about employer compensation.

*Review information chronologically since the last decision to avoid recency bias**.

Anchoring Bias

Dan Ariely looks at length at anchoring biases in his brilliant book 'Predictably Irrational'. It is the idea that we're using pre existing data as a reference point for subsequent decision making. This is used in supermarkets where a very expensive item of the same kind is always present to ensure we perceive the items next to it as a value buy or even "cheap".

It is important to be aware of your bias and acknowledge it. **Delay decisions until you can drop the anchor and its bias or until you get better information.**