Adaptive Capacity

A coordinated international tax regime that raises effective corporate tax rates on the largest, most profitable multinational enterprises.

A net wealth tax targeting the accumulated value of assets (minus liabilities) rather than income flows.

Taxes on AI companies paid via newly-issued equity stakes rather than cash, giving the public both dividend income and a governance voice in AI firms.

Compensating individuals and creators for the use of their personal data and intellectual property in training AI models, treating data contributions as a form of labor or capital.

Temporary income supplements to displaced workers who accept reemployment at lower pay, bridging the gap between their old and new wages.

Government funding that partially or fully covers wages for displaced or at-risk workers, incentivizing employers to maintain employment during periods of AI-driven disruption.

Fiscal incentives to employers who invest in worker retraining, hire displaced workers, or adopt labor-augmenting rather than labor-replacing AI technologies.

Government funding for compute clusters and data centers, and clean energy, to prevent monopolistic control of AI capabilities and democratize access for researchers and startups.

Guaranteed free or heavily subsidized access to essential services, from healthcare and education to housing and digital connectivity, decoupled from employment status.

Government employment of last resort, directing willing workers toward projects with collective societal benefits in areas like infrastructure, caregiving, and environmental restoration.

Scaling-up tax credit programs to reach a broader set of displaced and low-wage workers through the existing tax code.

Pre-legislated fiscal rules that activate automatically when economic indicators cross defined thresholds, providing countercyclical support without requiring new legislation.

Adaptations to central bank frameworks, such as interest rate policy, targeted lending facilities, or digital currencies, to manage disruptions to inflation and financial stability.

Legal frameworks that assign financial responsibility for AI-caused harms to developers and deployers, balancing innovation incentives with victim compensation.

Modernized competition enforcement to prevent dominant firms from leveraging control over essential AI infrastructure to stifle competition and capture outsized economic value.

Reserved board seats at AI companies for workers and public interest representatives, giving those affected by corporate decisions a formal governance voice.

Government acquisition of non-controlling equity stakes in AI companies and critical technology firms, securing public influence and wealth capture without full nationalization.

New or reformed international bodies for AI governance, capable of setting standards, monitoring compliance, coordinating research, and ensuring that AI development serves global rather than narrowly national or corporate interests.

Multilateral development bank financing for AI infrastructure in ways that embed benefit-sharing requirements, labor transition support, and accountability frameworks into loan terms.

AI literacy embedded across all education levels, covering how AI systems work and their societal implications, along with the critical thinking skills needed to navigate an AI-permeated world.

Professional development programs that train teachers to integrate AI tools into instruction and model responsible use for students.