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Five Cognitive Biases In Data Science (And how to avoid them)
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Five Cognitive Biases In Data Science (And how to avoid them)

Rahul Agarwal's avatar
Rahul Agarwal
May 25, 2020
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MLWhiz | AI Unwrapped
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Five Cognitive Biases In Data Science (And how to avoid them)
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Five Cognitive Biases In Data Science (And how to avoid them)

Recently, I was reading Rolf Dobell’s The Art of Thinking Clearly, which made me think about cognitive biases in a way I never had before. I realized how deeply seated some cognitive biases are. In fact, we often don’t even consciously realize when our thinking is being affected by one. For data scientists, these biases can really change the way we work with data and make our day-to-day decisions, and generally not for the better.

Data science is, despite the seeming objectivity of all the facts we work with, surprisingly subjective in its processes.

As data scientists, our job is to make sense of the facts. In carrying out this analysis, we have to make subjective decisions though. So even though we work with hard facts and data, there’s a strong interpretive component to data science.

As a result, we data scientists need to be extremely careful, because all humans are very much susceptible to cognitive biases. We’re no exception. In fact, I have seen many instances where data scientist…

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