Directed Improvisation with AI
Redefining human agency in an AI-mediated world—from producing answers to directing how humans and AI produce them together
About the Course
Directed Improvisation with AI, introduced by Yuen Yuen Ang in 2026 as a PhD seminar, addresses a central challenge posed by generative AI across organizations: What becomes of human agency when AI can generate answers on demand—and what does it then mean to think and learn?
In higher education, this challenge appears as “students cheating with AI,” prompting bans or restrictions that seek to restore individual effort. This course takes a different approach. In a world where AI is ubiquitous, the task is not to eliminate AI, but to redefine human agency—from producing answers to directing how humans and AI produce them together.
Anchored in Ang’s model of Directed Improvisation, the course centers on the meta-skill of direction, treating AI not as a passive tool but as a complex, co-creative system whose outputs depend on how humans guide it. Moving beyond simple commands and prompts, it introduces a method of paradigm-level direction, drawing on Ang’s AIM (Adaptive, Inclusive & Moral Political Economy)—a paradigm grounded in systems thinking, pluralism, and reflexivity—which students explore through a series of hands-on exercises, using bespoke knowledge infrastructure.
More broadly, the course advances a new conception of human agency in an AI-mediated world—metacognition and meta-direction: the ability to probe and shape how thinking itself unfolds.
Directed Improvisation (DI) is a model for enabling collective creativity that combines top-down direction with bottom-up improvisation, in contrast to rigid control or decentralized chaos.
While DI has appeared in other creative domains such as computer programming and the performing arts, Ang is the first to apply it systematically to development and governance in How China Escaped the Poverty Trap (2016), with later extensions to U.S. innovation policy (2023–25).
Since then, scholars and practitioners have applied DI across a range of settings, including transformative governance in Africa, local governance in India, and delegated growth strategies in the UK. In this course, introduced in 2026, Ang further extends DI to human–AI co-creation.
What is Directed Improvisation?
Generative AI is an extraordinarily promising but also disruptive technology: it can produce fast, fluent answers across a range of tasks, seemingly replacing human cognitive effort. In many settings, this has been interpreted as a threat to learning and employment. In higher education, it appears as “students cheating with AI,” prompting policies that ban, restrict, or penalize its use. Similar concerns arise in journalism, consulting, governance, and other domains: if AI can generate outputs on demand, what remains of human judgment and creativity?
This course shifts the terms of the debate. In a world where AI will be ubiquitous, the task is not to eliminate AI, but to redefine human agency—from producing answers to directing how humans and AI produce them together. Rather than treating AI as a passive tool that executes commands, it treats AI as a co-creative system whose outputs depend on how humans guide it.
The meta-skill explored in the course is direction: the ability to shape how problem-solving or creativity unfolds by structuring its conditions, rather than producing answers directly. Contrary to claims that AI will make humans “lazy,” direction is a higher-order form of cognition—akin to directing an improvised play or cultivating an ecosystem—where outcomes can be influenced but not precisely predicted or controlled.
The course connects these practices to broader questions of pedagogy and governance. We explore why and how institutions often respond to AI through control and regulation. By the end of the course, students will have learned a new orientation toward AI: not as a threat to education or a mere tool that completes their assignments, but as a complex system to be directed.
They will gain awareness of a new form of human agency in an AI-mediated world—metacognition and meta-direction: the ability to probe and shape how thinking itself unfolds.
Learning Objectives
The theoretical foundation of the course is Yuen Yuen Ang’s Directed Improvisation (DI): a model for enabling collective creativity that combines top-down direction with bottom-up improvisation, in contrast to rigid control or decentralized chaos. While directed improvisation has appeared in computer programming and the performing arts, Ang applied it to development and governance in How China Escaped the Poverty Trap (2016). Extended to human–AI interaction, DI reframes the researcher as a director and the AI as an improviser.
Building on this foundation, the course introduces a methodological approach to guiding AI through paradigm-level interventions. Central to this task is Ang’s AIM (Adaptive, Inclusive, Moral Political Economy), a system of thought grounded in three redefined assumptions:
Adaptive: systems thinking instead of mechanical thinking
Inclusive: pluralistic solutions instead of a single universal ideal
Moral: awareness of how power shapes ideas instead of feigned neutrality
Through a series of experiments, students explore how AI responds under different assumptions and paradigms, rather than only adjusting prompts and adding context.