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Machine learning and artificial intelligence are dramatically changing the way businesses operate and people live. The TWIML AI Podcast brings the top minds and ideas from the world of ML and AI to a broad and influential community of ML/AI researchers, data scientists, engineers and tech-savvy business and IT leaders.

Hosted by Sam Charrington, a sought after industry analyst, speaker, commentator and thought leader.

Apr 23, 2020

Today we’re joined by Ben Green, PhD Candidate at Harvard, Affiliate at the Berkman Klein Center for Internet & Society at Harvard, Research Fellow at the AI Now Institute at NYU. 

Ben’s research is focused on social and policy impacts of data science, with a focus on algorithmic fairness, municipal governments, and the criminal justice system. In our conversation, we discuss his paper ‘Good' Isn't Good Enough,’ which explores the 2 things he feels are missing from data science and machine learning projects, papers and research; A grounded definition of what “good” actually means, and the absence of a “theory of change.” We also talk through how he thinks about the unintended consequence associated with the application of technology to social good, and his theory for the relationship between technology and social impact. 

The complete show notes for this episode can be found at