Predistribution AI Lab

For too long, our economy has short-changed the workers, communities, and other stakeholders that are critical to the value creation process. But the advent of AI is an inflection point. Neither capitalism nor democracy can function with vast imbalances in wealth and power.

The Predistribution AI Lab is facilitating peer-learning and co-creative opportunities for companies, investors, their stakeholders, and other specialists to gather and refine solutions. The Lab will be guided by  the following principles:

Ownership

Compensate workers in companies and communities in infrastructure and natural resource projects for the risks that they take and the value that they create in the production process with equity-linked compensation.

Why Broaden Ownership

Broadening equity ownership of companies supports broad-based prosperity and aligns the incentives of companies and their stakeholders. This contributes to stronger corporate performance, even as the number of owners increases. This expansion also restores trust in institutions.

What This Might Look Like in Practice

  • Workers receive equity-linked compensation in addition to a living wage, proportional to their salaries and modeled after executive compensation.
  • Companies map other core stakeholders who take risk and create value, such as communities hosting data centers, power plants, and natural resource projects, and compensate them with equity, thereby aligning incentives and contributing to broad-based prosperity.
  • AI companies offer equity-linked compensation to content creators and other professionals whose knowledge is being used to train technology.
  • Diversified investment accounts complement the above to avoid risks of equity exposure to just one company.

Governance

Center the valuable perspectives of corporate stakeholders, including workers, communities, and consumers, through corporate governance reforms.

Why Broaden Corporate Governance Participation

Workers, communities, and consumers have a strong sense of what is happening “on the ground” with companies. They have valuable insights that can help companies stay ahead of the curve on emerging opportunities and risks.

When it comes to training AI and AI safety, incorporating a variety of perspectives will ensure this incredible technology works broadly for humanity. Breaking through the glass ceiling to offer opportunities for stakeholders to participate in corporate governance, including in the boardroom , can also help restore trust in institutions.

What This Might Look Like in Practice

Workers, community members, and consumers can participate in corporate governance training and be considered for roles in companies that enhance corporate governance, such as works councils, advisory councils, or board directorships.

Balance Versus Concentration

Maintain a decentralized approach to ensure that workers and communities do not become dependent on meager benefits from universal basic income or distributions from sovereign wealth funds alone.

Why Take a Decentralized Approach

If society relies on universal basic income or a sovereign wealth fund alone, workers and community members who take risks and create value will not be rewarded directly and commensurately for their contributions to the production process.

Productivity and societal decision-making, therefore, will remain concentrated in the hands of the relatively few owners who control the bulk of productive assets. Such concentration threatens the dynamism of markets and the health of functioning democracies.

What This Might Look Like in Practice

Companies reform their contracts with stakeholders to include them in ownership and governance, thereby fostering agency, dignity, and respect rather than leaving most of the society dependent.

Holistic and Co-Creative Approach

Support adjacent, necessary solutions and iterate proposals with others.

Why Take a Holistic and Co-Creative Approach

The economy is a complex system. There is no “silver bullet” solution.

Different stakeholders, companies, investors, and geographies will have different needs and priorities. A mosaic of ideas can help identify blind spots and avoid unintended negative consequences.

What This Could Look Like in Practice

Integrate governance and ownership solutions with other approaches, such as training and reskilling programs that advance opportunities for workers and small businesses through economic transitions.

Bring together companies, investors, their stakeholders, and specialists in collaborative design workshops.

The Predistribution AI Lab is launching with three foundational discussion papers, which include macro-financial stress tests demonstrating the incentive for change. The papers elaborate on the above proposed solutions, to be refined and workshopped further. We hope you will join us in the co-creation process!

The first paper in PDI’s Predistribution AI Lab series models how declining returns to labor and rising unemployment could ripple through consumption, tax revenue, mortgage and corporate debt, equities, pensions, and insurance assets - and ultimately diversified investment portfolios. Across four scenarios (three drawn from Dario Amodei’s unemployment projections, one from historical labor trends), it frames AI as an inflection point that could either deepen these risks or spur a redesign of economic structures to avoid them.
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The second paper in PDI’s Predistribution AI Lab series proposes practical responses to the risks raised in Part I - chiefly broadening equity-linked compensation and corporate governance to include the workers, communities, and content creators (“human” and “social capital”) who create value alongside executives and investors. Against a backdrop of declining returns to labor and shareholder-first governance, it argues that broadening ownership can realign stakeholder incentives, bring wider perspectives to safe AI development, and sustain the aggregate demand the economy and investment portfolios depend on.
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The third paper in PDI’s Predistribution AI Lab series prototypes a three-pillar intervention for rideshare drivers displaced by autonomous vehicles: ongoing cash income, equity in AV platforms, and diversified investment accounts. It weighs the model against alternatives like UBI, sovereign wealth funds, and purpose trusts, and notes it can adapt to other groups - from communities hosting infrastructure to content creators whose work trains AI.
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