Data Science and Machine Translation w/ John DeNero

We've been told time and time again that we need to understand data in context: it's an ethical imperative. Not every language gets an LLM; not every population fully understands a technology that's deployed in their community with or without everyone's consent; and certainly we're told that we will make better, safer conclusions with our data if we understand the context. John DeNero looks at things differently: instead of an ethical imperative for understanding data in context, John talks about a structural one. For example, accurately translating language necessitates understanding the context. It's almost as if he read a bunch of French critical theory, thought about deconstruction, and realized that a structural imperative has an ethical valence as well—and vice versa. It's not a paradox, it's deconstruction.

This interview covers John's work as a professor of data science and computer science, his experience as a senior research scientist at Google Translate, thoughts on AI and language, and keeping up with the slang of today's youth.

John DeNero is the Faculty Director of Data Science Undergraduate Studies (DSUS) and Associate Teaching Professor in the UC Berkeley EECS department. He is the co-founder and Chief Scientist at lilt.

John's website

Google Scholar

A Class-Based Agreement Model for Generating Accurately Inflected Translations

This episode is dedicated to MukhammadAziz Umurzokov and Ella Cook, the two Brown University students who passed away on December 13th, 2025.