Supply-Side vs Demand-Side AI Regulation
Supply-side regulation addresses genuine risks — the potential for AI systems to perpetuate bias, produce harmful outputs, compromise privacy, concentrate market power — and its development is both necessary and inevitable. But it is also the form of regulation most susceptible to capture, because it directly affects the competitive dynamics of the AI industry. The parties with the largest financial stakes in the outcome of supply-side regulation are also the parties with the greatest resources to invest in shaping the regulatory outcome. Demand-side regulation — investment in citizen capability, educational reform, transition support, information infrastructure — does not directly affect the competitive dynamics of the AI industry, which means it attracts less lobbying and is less susceptible to capture. But it directly affects the capacity of the broader society to benefit from the deployment phase.
In the AI Story
The distinction maps onto the installation-deployment distinction. Supply-side regulation operates primarily at the installation-phase level — constraining the technology's installation. Demand-side regulation operates at the deployment-phase level — building the institutional infrastructure that enables broad benefit. Both are necessary, but their political dynamics and susceptibility to capture differ substantially.
Edo Segal's advocacy in The Orange Pill for demand-side regulation aligns with Perez's framework in a structural way: the most durable deployment-phase institutions are the ones that expand the capability of citizens rather than constrain the technology companies. Universal education did not constrain the factory system's operation; it produced a population that could participate in the industrial economy. The G.I. Bill did not constrain employers; it produced an educated workforce. The analogous AI-age demand-side infrastructure would not constrain AI companies but would produce a citizenry capable of navigating the AI-augmented economy.
The European Union's AI Act is primarily supply-side regulation; the American approach through executive orders and agency guidance is also primarily supply-side. Demand-side regulation — investment in citizen capability, educational transformation, transition support — remains underdeveloped in both jurisdictions, for structural reasons: demand-side regulation requires sustained public investment without immediate visible returns, which is politically more difficult than the supply-side regulation that can be enacted as a response to specific visible harms.
The principle that the most effective deployment-phase institutions have historically been the ones that expanded capability rather than constrained it is one of the framework's most practically useful prescriptions. Universal education empowered workers. Social insurance empowered workers to take risks. Demand-side AI regulation should follow this pattern: expanding the capacity of citizens, workers, and communities to participate in the AI-augmented economy, rather than merely constraining the companies that build the tools.
Origin
The supply-demand distinction in AI regulation was articulated by Segal in The Orange Pill and is developed within the Perez framework in the Carlota Perez book.
Key Ideas
Supply-side. Regulates what companies may build.
Demand-side. Empowers citizens to navigate the technology.
Capture asymmetry. Supply-side regulation is more susceptible to capture than demand-side.
Historical precedent. Successful deployment-phase institutions have expanded capability rather than constrained technology.
Underdeveloped. Demand-side regulation remains neglected in current regulatory frameworks.
Appears in the Orange Pill Cycle
Further reading
- Edo Segal, The Orange Pill (2026)
- Carlota Perez, "What Is AI's Place in History?" (2024)
- Archon Fung, Empowered Participatory Governance (2003)