Databites 100 Series: Machine Learning: What’s Fair and How Do We Decide?

Data & Society

Suchana Seth speaks about different definitions of fairness in the context of machine learning. Suchana Seth is a physicist-turned-data scientist from India. She has built scalable data science solutions for startups and industry research labs, and holds patents in text mining and natural language processing. Suchana believes in the power of data to drive positive change, volunteers with DataKind, mentors data-for-good projects, and advises research on IoT ethics. She is also passionate about closing the gender gap in data science, and leads data science workshops with organizations like Women Who Code.

Chapters

1. What is the machine learning research community doing to combat instances of algorithmic bias? (00:00:00)

2. We have many different possible definitions of fairness to use, how do we choose the right one? (00:05:07)