Teaching AI ethics through case discussions is hard: most students default to one ethical lens without seeing the others, and class time can’t host five voices at once. Inquiring Agents is a classroom debate tool where five philosopher-agents argue an ethics dilemma through Churchman’s Inquiring Systems while students inject their own perspectives between rounds. Built at Gies for use in business ethics courses.
Project Lead: Vishal Sachdev
Each philosopher-agent embodies a distinct epistemological tradition from Churchman’s 1971 framework
Builds arguments from first principles and logical axioms. Seeks universal truths through formal reasoning, demanding internal consistency and logical coherence in all ethical claims.
Grounds analysis in observable evidence and measurable outcomes. Insists on data-driven evaluation, demanding empirical validation for every ethical claim about AI systems.
Applies the categorical imperative and deontological ethics. Tests whether AI policies could be universalized without contradiction, centering human dignity and moral duty.
Seeks synthesis through thesis-antithesis resolution. Identifies contradictions between competing positions and works toward reconciliation that integrates opposing perspectives.
Evaluates consequences and real-world outcomes holistically. Integrates empirical insights with philosophical reflection, prioritizing practical impact on human flourishing.
A three-round Delphi method with real-time streaming and student participation
Bringing philosophical frameworks to life through interactive AI debate
One Cloudflare Worker file serves the entire app—HTML, CSS, JS, and API proxy. Zero dependencies, zero build step, deploys in seconds.
Students don’t just read about ethical frameworks—they watch them clash in real time and inject their own thinking into the debate.
Implements Churchman’s Design of Inquiring Systems (1971) and the Delphi Method. Adapted from Sridhar Nerur’s original CrewAI notebook.