216: Robot and Human Collaboration with Julie Shah
January 6th, 2021 · 1 hr 4 mins
About this Episode
02:21 - Julie’s Superpower: Working Really Hard and Maintaining Focused Attention on Things for a Long Period of Time
04:25 - Robotics and Working in Artificial Intelligence (AI)
- What To Expect When You're Expecting Robots: The Future of Human-Robot Collaboration (Julie and Laura Major’s book)
11:10 - Structuring and Optimizing the World for Machines, AI, and Robots
- The Turing Test
- Labeled Data
- Teslas vs Airplanes
- Mode Confusion
- Ten challenges for making automation a "team player" in joint human-agent activity
26:10 - Understanding Output and Building Calibrated Trust
- Mental Models
33:39 - Robots and Humans in Public Spaces
- Predictability
- Directability
- Standardization
- Infrastructure
- Safety Imperatives
- Future of Work Implications
- Joint Activity
51:41 - What To Expect When You're Expecting Robots: The Future of Human-Robot Collaboration (Book Discussion)
54:40 - More on Human/Machine Collaboration:
- Girl Decoded: A Scientist's Quest to Reclaim Our Humanity by Bringing Emotional Intelligence to Technology
- Reinforcement learning with human teachers: Evidence of feedback and guidance with implications for learning performance
- Evaluating fluency in human–robot collaboration
Reflections:
Rein: There may be a sense in which AI or ML systems are categorically different from the sorts of systems we’ve tried to control in the past because you can’t characterize the variety of the system anymore just by observing its inputs and outputs.
Damien: Artificial intelligence is not human intelligence, nor should it be. The goals are making systems and human lives better; not making the computer better.
Julie: Aim for mediocrity!
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