216: Robot and Human Collaboration with Julie Shah

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

The Shannon Model

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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