Developing transformative AI (TAI) presents one of the most significant opportunities and challenges for society. Yet, there is no widely accepted roadmap for what a successful transition to TAI should look like. Discussions often focus on risks, such as misalignment or misuse, rather than defining a realistic, optimistic outcome. Without a shared vision, efforts to guide AI development may lack coordination, leading to missed opportunities or unintended consequences.

Creating a Roadmap for Beneficial AI

One way to address this gap could be developing a detailed yet practical vision for how humanity could transition safely and successfully to a world with TAI. This vision might cover:

• Technical alignment: How to ensure TAI behaves as intended without catastrophic failures.
• Governance models: How policymakers, researchers, and corporations could collaborate to regulate and guide AI development.
• Societal integration: How TAI could solve pressing global challenges while minimizing economic and social disruptions.
• Cultural preservation: How human values and autonomy can be maintained in an AI-driven future.

This could take the form of a whitepaper, informed by experts in AI safety, economics, ethics, and policy, ensuring a balanced and well-researched perspective.

Aligning Stakeholder Incentives

For such a vision to gain traction, key players would need compelling reasons to adopt it. For example:

• AI labs might benefit from a clearer ethical and strategic framework that reduces uncertainty and backlash.
• Governments could use the vision to shape policies that foster innovation while protecting public interests.
• Civil society could advocate for equitable AI benefits based on a well-defined set of principles.

An initial step could involve creating a draft discussion paper to test interest and refine the vision through feedback from thought leaders before full-scale development.

Execution and Evolution

Starting small with an MVP—such as a summary proposal—could help assess feasibility and gather early support. If successful, the project could expand into a more detailed report, refined through stakeholder workshops and expert reviews. To stay relevant, the document could be designed for periodic updates, ensuring it adapts to new advancements in AI and governance.

By providing a concrete yet adaptable framework, this effort could help align global AI development toward a future that maximizes benefits while minimizing risks.