The field of AI alignment faces a significant challenge in developing strategic clarity about how to navigate the development of transformative artificial intelligence (TAI). Currently, there is a lack of comprehensive examples demonstrating what constitutes high-quality strategic work that provides actionable insights into long-term technological trajectories and their societal implications. Without such examples, it becomes difficult for researchers and policymakers to identify which types of analysis will be most valuable for shaping safe development pathways for advanced AI systems.

Cataloging and Analyzing Strategic Work

One way to address this gap could be to systematically catalog and analyze historical examples of strategic work that provided crucial insights about transformative technologies, such as nuclear weapons, or about TAI itself. This analysis could identify patterns in what made these insights valuable, how they were generated, and how they influenced decision-making. The output could serve as both a reference for current AI alignment researchers and a template for producing new strategic insights. Potential beneficiaries of this work might include:

• AI alignment researchers seeking models for impactful work
• Policy analysts working on AI governance frameworks
• Technology forecasters improving prediction methodologies

Execution and Validation

An initial phase could involve compiling a list of candidate examples through literature reviews and expert interviews, followed by developing an evaluation framework to assess their strategic value. A subsequent analysis phase might conduct in-depth case studies of the most valuable examples to identify common patterns in methodology, communication, and impact. To validate the approach, key assumptions would need testing, such as whether historical patterns from other technologies are applicable to AI alignment and whether insights can be operationalized into practical guidelines.

Differentiating from Existing Work

While projects like Nick Bostrom's "Superintelligence" or Toby Ord's "The Precipice" offer philosophical analyses of AI risks, this approach would focus more empirically on specific cases of strategic work and their mechanics. Similarly, while organizations like CSET have explored historical analogies for AI, this project could go deeper into analyzing what made certain insights particularly valuable, with an emphasis on research methodology rather than just policy implications.

By providing a systematic framework grounded in concrete historical examples, this approach could help researchers and policymakers better understand what constitutes high-quality strategic analysis in the AI domain, while acknowledging where analogies to past technologies may break down.