Scaling Human-Centered AI

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Most AI systems scale by removing humans from the loop. This course teaches the opposite: how to build AI systems that keep humans meaningful as the system grows. Augmentation patterns, distributed decision-making, and the economic logic of human-AI collaboration at scale.

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01
Start here: what this course is about
Welcome to Scaling Human-Centered AI
Read first. ~4 minutes.
02
Start here: what is human-centered AI?
Stanford HAI: Human-Centered Artificial Intelligence↗
Stanford HAI's definition: AI guided by human impact, inspired by human intelligence, designed to augment not replace.
03
Design principles for human-centered AI
How Do We Design and Develop Human-Centered AI?↗
Concrete design principles from Stanford. AI that communicates, collaborates and augments people effectively.
04
The math of human-AI collaboration
Roles of Artificial Intelligence in Collaboration with Humans↗
Management Science research: when AI automates, when it augments, when humans work alone. Optimal task allocation.
05
How augmentation works in real workplaces
Understanding Human-AI Augmentation in the Workplace↗
Systematic academic review of human-AI augmentation patterns in production environments.
06
How AI is reshaping team dynamics
Stanford HAI Launches AI and Organizations Lab↗
New Stanford lab studying AI's effect on workplace coordination, jobs, and team structures.
07
Designing org structures for human-AI work
Augmentation, Not Automation: Designing Workplaces Where Humans Thrive↗
Start with augmentation. Automate stable steps over time. Keep humans on judgment-heavy work.
08
The economics of partial automation
Economics of Human and AI Collaboration: When is Partial Automation More Attractive than Full Automation?↗
Why hybrid systems often beat fully automated ones, even when AI could technically do the task alone.
09
When HITL hits the wall
Human-in-the-loop has hit the wall. It's time for AI to oversee AI↗
Critical view: HITL was built for discrete decisions. It breaks at billion-user scale. What comes next.
10
Scaling responsibly: a framework
Responsible AI Implementation: A Human-centered Framework for Accelerating the Innovation Process↗
End-to-end framework for scaling AI products while keeping humans meaningful and in control. Academic source.
11
State of the art: the agentic organization (McKinsey)
The Agentic Organization: The Next Paradigm for the AI Era - McKinsey↗
McKinsey on redesigning the enterprise around an agentic organization where humans and AI agents create value together.
12
Closing: what to take with you
Closing: Scale Without Losing the Human
Wrap-up. ~3 minutes.