01:16:33
PAIR Symposium 2020: Seattle session (full event)
01:35:02
PAIR Symposium 2020: London session (full event)
01:29:34
PAIR Symposium 2020: Boston session (full event)
10:44
PAIR Symposium 2020 (Seattle): Mindy DelliCarpini: Simulating Intelligence: Prototyping for ML
10:23
PAIR Symposium 2020 (Seattle): Donald Martin: Causal maps for AI development "territories"
08:55
PAIR Symposium 2020 (Boston): Margaret Mitchell: Intentional ignorance is a value-laden choice
10:02
PAIR Symposium 2020 (Boston): Ed Chi: A twist on loss functions as boundary objects
09:56
PAIR Symposium 2020 (Boston): Sendhil Mullainathan: Algorithms and Interpretations: Two Stories
10:40
PAIR Symposium 2020 (London): Nithya Sambasivan: Human Data Interaction in AI
10:09
PAIR Symposium 2020 (London): Annelien Bredenoord: Ethics Parallel Research
11:58
PAIR Symposium 2020 (London): Catherine D'Ignazio: "Boundary Object: Counterdata Sets"
13:00
PAIR Symposium 2020 (London): Charlotte Lee: Boundary Objects for Creativity & Innovation
02:12
Highlights from PAIR Symposium 2019
33:01
Tic-Tac-Toe the Hard Way - Ep 9: Lessons learned
24:27
Tic-Tac-Toe the Hard Way - Ep 8: Head to Head: The Even Bigger ML Smackdown!
02:10
Introducing Tic-Tac-Toe the Hard Way
21:21
Tic-Tac-Toe the Hard Way - Ep 7: Enter tic-tac-two
25:20
Tic-Tac-Toe the Hard Way - Ep 6: Head to Head: the Big ML Smackdown!
26:05
Tic-Tac-Toe the Hard Way - Ep 5: Give that model a treat!: Reinforcement learning explained
17:15
Tic-Tac-Toe the Hard Way - Ep 4: Beating random: What it means to have trained a model
21:38
Tic-Tac-Toe the Hard Way - Ep 3: From tic-tac-toe moves to ML model
23:27
Tic-Tac-Toe the Hard Way - Ep 2: What does a tic-tac-toe board look like to machine learning?
22:02
Tic-Tac-Toe the Hard Way - Ep 1: Howdy, and the myth of “pouring in data”
26:21
PAIR Symposium - Making Music with Magenta - Douglas Eck, Signe Norly and Claire Kayacik
19:57
PAIR Symposium - Q&A: Investing in the UX of AI - Jess Holbrook and Matt Webb
26:37
PAIR Symposium - Interview + Q&A - Fernanda Viegas and Nigel Shadbolt
23:32
PAIR Symposium - Using PAIR Tools - What if and Tensorflow.js - Mahima Pushkarna and Yannick Assogba
22:31
PAIR Symposium - Designing for Participatory ML + Q&A - Chris Noessel
16:08
PAIR Symposium - Rethink Policy with AI - Cosmina Dorobantu
25:30
PAIR Symposium - Panel: Transparency in AI
28:35
PAIR Symposium - The Metaphysics of ML - David Weinberger
22:11
PAIR Symposium - AI for Social Good + Q&A - Wadhwani AI - Raghu Dharmaraju
19:35
PAIR Symposium - Q&A: AI Explainability - Martin Wattenberg and Simone Stumpf
22:10
PAIR Symposium - Societal and Regulatory Challenges of Encrypted Data Analysis - Michael Veale
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About
The People + AI Research (PAIR) initiative at Google advances the research and design of people-centric AI systems. We’re interested in the full spectrum of human interaction with AI, from supporting the engineers and teams building AI to understanding people’s everyday experiences with AI.
Learn more at pair.withgoogle.com
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