Three arguments
I'm prepared to defend.

Extended Essay · IB

The Costs of Unaccountability: Clearview AI, Market Failure, and the Political Economy of Surveillance

Facial-recognition markets can't be fixed by the regulation we have, only by regulation aimed at a different layer. The essay applies three analytic frameworks to make that case, arguing the markets persist as failures through a compounding failure of economics and political accountability: Pigou's negative externality theory (the social costs of wrongful arrests and racial bias are borne by unconsenting third parties invisible to the transaction), Lukes' three-dimensional power model (companies shape not just procurement decisions but the regulatory agenda and public perception of surveillance as inevitable), and Bradford's Brussels Effect (EU standards achieved market exclusion rather than global norm convergence: Clearview routed around enforcement through deliberate jurisdictional exit).

The core claim: the market failure Clearview AI represents persisted not because it was unidentifiable (the EU formally named the same harms the US Congress acknowledged and ignored) but because the state was simultaneously the technology's largest buyer and its only potential regulator, a structural conflict of interest that existing regulatory frameworks were not designed to address.

SSRN Preprint · Abstract 6187979

The Paradox of Control: How US Semiconductor Export Restrictions Are Reshaping China's Technological Sovereignty

Export controls on semiconductors behave like industrial policy for the country being restricted. The "creative insecurity" hypothesis holds that this kind of geopolitical pressure on a country's technology sector functions as de facto industrial policy, forcing domestic innovation rather than merely restricting trade. This preprint tests that claim against China's semiconductor industry: production capacity, trade flows, and innovation metrics through 2033.

Math IA · IB

Logistic Regression Modeling of G20 Trade Retaliation Patterns

Trade retaliation isn't random; the escalation sequence has structure you can model. This is a quantitative investigation into what predicts bilateral trade retaliation between G20 members, using logistic regression on historical tariff escalation sequences. The work provides the methodological counterpart to the qualitative arguments in the EE and preprint, demonstrating range across the quantitative/qualitative divide rather than treating them as separate domains.