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#47 Human-centered Design in Data Science
Hugo speaks with Peter Bull about the importance of human-centered design in data science. Peter is a data scientist for social good and co-founder of Driven Data, a company that brings cutting-edge practices in data science and crowdsourcing to some of the world's biggest social challenges and the organizations taking them on, including machine learning competitions for social good. They’ll speak about the practice of considering how humans interact with data and data products and how important it is to consider them while designing your data projects. They’ll see how human-centered design provides a robust and reproducible framework for involving the end-user all through the data work, illuminated by examples such as DrivenData’s work in financial services and Mobile Money in Tanzania. Along the way, they’ll discuss the role of empathy in data science, the increasingly important conversation around data ethics and much, much more.LINKS FROM THE SHOW
FROM THE INTERVIEW
- Peter on Twitter
- DrivenData
- Deon (Ethics Checklist)
- Cookiecutter Data Science
- If you liked this interview, you might be interested in working with DrivenData! Currently, the team is looking for a software engineer who loves the idea of building Python applications for social impact. Apply Here!
FROM THE SEGMENTS
Probability Distributions and their Stories (with Justin Bois at ~24:00)
- Justin's Website at Caltech
- Probability distributions and their stories (By Justin Bois)
Studies in Interpretability (with Peadar Coyle at ~38:10)
- Interpretable ML Symposium
- How will the GDPR impact machine learning? (By Andrew Burt)
- How to use Bayesian Stats in your daily job (Gates, Perry, Zorn (2002))
- Fairness in Machine Learning (By Moritz Hardt)
Original music and sounds by The Sticks.