Watch: Human roles & AI
Talks retain evidence and review limitations
Critical synopses on human judgement, delegation and responsibility around AI.
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Human–AI interaction
Expectations, feedback and judgement when people use AI systems.
11 connections
These are editorial connections by subject, not claims of collaboration, endorsement or equal evidence quality. This first topic collection covers the new AI, robotics, security, interface design and preparation resources; it is not a complete index of the reading room.
Video collection
Research paper
RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control
Open publication · abstract-only review; full PDF could not be retrieved for this review
The abstract describes training vision-language models with robot trajectories and web-derived vision-language tasks, representing robot actions as tokens. This connects language-based instructions with physical robot control.
Person
Fei-Fei Li
Researcher · United States
Follow her publications to connect perception, simulation and robot learning. This is a research profile, not a claim that she practises as a UX designer.
Research centre or group
Stanford Institute for Human-Centered AI (HAI)
Interdisciplinary institute · United States
Useful for human-centred framing, research reports and public discussions. Assess the methods of each publication separately; institutional standing is not an evidence label.
Carnegie Mellon Robotics Institute: Human–Robot Interaction
Research area within an institute · United States
Particularly relevant to readable behaviour, assistance and collaboration. Follow individual studies rather than treating a laboratory demonstration as evidence of general readiness.
Research & guidance
Guidelines for Human-AI Interaction
Peer-reviewed conference paper · background · Open author manuscript · full text reviewed
A set of 18 guidelines, refined through several evaluation stages, including 49 design practitioners assessing 20 AI-infused products. Useful for examining expectations, correction and user control across an interaction.
Principles of Mixed-Initiative User Interfaces
Peer-reviewed conference paper · background · Open author manuscript · full text reviewed
Examines how automated assistance and direct user control can work together, illustrated by the LookOut scheduling prototype. It connects intervention timing and uncertainty about a user’s intentions to the costs of acting.
Design foundations for agents
Practitioner guidance · not an empirical study · Public page text reviewed · some linked material may require sign-in
A starting point for agent design covering responsible AI, accessibility and interaction foundations. Use it to locate implementation guidance and identify questions for your own evaluation.
Learning pathway
Will my existing skills lose value?
Editorial activity · beginner and experienced routes
Strengthen judgement alongside production skills.
How much technical knowledge do I need?
Editorial activity · beginner and experienced routes
Learn enough to question capabilities, limitations and dependencies.
How do I design for agents that take action?
Editorial activity · beginner and experienced routes
Make delegation, intervention and recovery explicit.