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AI for Social Good: Why "Good" isn't Enough with Ben Green - #368

AI for Social Good: Why "Good" isn't Enough with Ben Green - #368

FromThe TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)


AI for Social Good: Why "Good" isn't Enough with Ben Green - #368

FromThe TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

ratings:
Length:
42 minutes
Released:
Apr 23, 2020
Format:
Podcast episode

Description

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 twimlai.com/talk/368.
Released:
Apr 23, 2020
Format:
Podcast episode

Titles in the series (100)

This Week in Machine Learning & AI is the most popular podcast of its kind. TWiML & AI caters to a highly-targeted audience of machine learning & AI enthusiasts. They are data scientists, developers, founders, CTOs, engineers, architects, IT & product leaders, as well as tech-savvy business leaders. These creators, builders, makers and influencers value TWiML as an authentic, trusted and insightful guide to all that’s interesting and important in the world of machine learning and AI. Technologies covered include: machine learning, artificial intelligence, deep learning, natural language processing, neural networks, analytics, deep learning and more.