courses ·

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.

Certificate requires 3+ karma · you have 0

1. 01

   Start here: what this course is about

   Welcome to Scaling Human-Centered AI

   Read first. ~4 minutes.

2. 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.

3. 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.

4. 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.

5. 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.

6. 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.

7. 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.

8. 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.

9. 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. 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. 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. 12

    Closing: what to take with you

    Closing: Scale Without Losing the Human

    Wrap-up. ~3 minutes.

Log in to track your progress.