Ask Why! Finding motives, causes, and purpose in data science

Some people equate predictive modelling with data science, thinking that mastering various machine learning techniques is the key that unlocks the mysteries of the field. However, there is much more to data science than the What and How of predictive modelling. I recently gave a talk where I argued the importance of asking Why, touching on three different topics: stakeholder motives, cause-and-effect relationships, and finding a sense of purpose. A video of the talk is available below. Unfortunately, the videographer mostly focused on me pacing rather than on the screen, but you can check out the slides here (note that you need to use both the left/right and up/down arrows to see all the slides).

If you’re interested in the topics covered in the talk, here are a few posts you should read.

Stakeholders and their motives

Causality and experimentation

Purpose, ethics, and my personal path

Cover image: Why by Ksayer

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