
Governing Artificial Intelligence in Education argues that the effectiveness of AI governance in education is shaped less by the strength of regulatory design and more by the capacity to implement, operationalize, and sustain policy within real institutional environments. The brief examines how the United States and the European Union approach AI governance through contrasting models—one decentralized and implementation-driven, the other structured and risk-based—and shows how both systems encounter similar limitations when policies are not translated into practice. Drawing on comparative analysis, it highlights how gaps in institutional capacity, data governance, and oversight mechanisms contribute to uneven outcomes, persistent inequities, and limited evidence of impact on learning and decision-making.
This policy brief proposes a shift from principle-based governance toward implementation-focused frameworks that prioritize operational clarity, institutional readiness, and continuous evaluation. It outlines key policy priorities, including strengthening human and technical capacity, embedding accountability into decision-making processes, and establishing mechanisms to assess how AI systems affect educational outcomes over time. Intended for policymakers, education leaders, and institutional stakeholders, the brief positions AI governance not as a purely regulatory challenge but as a systems-level coordination problem, where effective outcomes depend on aligning policy design with the realities of educational practice.

As AI advances, it returns something more valuable than incremental efficiency gains: time. The Gift of Time: AI, Automation, and the Future of Work in a Time-Rich Economy argues that intelligent systems are compressing workflows and reducing routine cognitive and operational burdens at scale—reshaping how work is structured and how value is created. This opinion piece examines the compression of work across sectors, shifts in employment structures, and the implications of an economy in which machines perform an increasing share of necessary tasks.
From an education perspective, it outlines two diverging futures in a time-rich society: one in which reclaimed time supports learning, creativity, and civic engagement, and another in which it is absorbed by attention-maximizing digital systems. The paper contends that leaders across education, policy, and industry must make deliberate choices about how AI-generated time is distributed and used. It proposes that governance frameworks incorporate time-based metrics alongside financial returns, and that closing the reskilling divide is essential to ensuring that the time dividend expands inclusion rather than deepening inequality. By treating time as a first-class economic and ethical variable, the paper positions AI not only as a driver of productivity but as a lever for long-term human flourishing.

Unpacking Perpetual Decentralized Exchanges examines how decentralized finance is reshaping market structures beyond access, focusing on the design of systems that balance openness, efficiency, and risk in the absence of intermediaries. It positions Perp DEXs as a critical evolution, enabling leveraged derivatives trading through non-custodial, on-chain infrastructure, and outlines their core mechanics—including liquidity models, oracle systems, funding mechanisms, liquidation frameworks, order matching, and smart contracts—across leading platforms such as dYdX, GMX, Hyperliquid, and Synthetix.
The analysis identifies structural challenges such as fragmented liquidity, oracle dependency, governance centralization, and user-level risk exposure, while evaluating emerging pathways including cross-chain liquidity aggregation, diversified oracle systems, DAO-based governance, and AI-driven optimization. The report ultimately frames Perp DEXs as a foundational layer of decentralized financial markets, where sustained progress will depend on aligning technical innovation with robust system design, resilient infrastructure, and stable market dynamics.