Artificial intelligence is on the verge of being employed across various sectors like offices, warehouses, call centers, clinics, and classrooms. In light of pushback from those impacted by job displacement, the industry might consider cash transfer solutions, such as universal basic income, as a way to address these issues.
This approach seems to diminish negotiation power at work and creates unintended social and financial dependencies. It doesn’t have to be this way, though. There’s a chance to shift the narrative, create a more equitable space, and ensure that those absorbing the negative impacts of AI also share in its benefits.
What does this look like? An open, competitive market. Modern data rights. Responsible management. Implementing technology that enhances shared benefits. Most crucially, public access to the gains brought about by AI.
The U.S. should establish a professionally managed, firewall-style public wealth fund that invests in a diverse range of stocks throughout the AI sector and distributes annual dividends tied to the gains from AI advancements.
This model prioritizes public dividends over basic income, utilizing competition and regulatory frameworks related to data, labor, and energy to maintain an open playing field. It aims to provide the public with meaningful, lasting stock while ensuring that negative effects are controlled.
A potential collaboration between Nvidia, AMD, and the U.S. government—where they contribute 15% of revenue from certain advanced chip sales—could serve as a foundation for creating this public AI wealth fund.
This fund could be capitalized with stock warrants from companies benefiting from significant subsidies or tax incentives. It would help address excess earnings from remarkable AI margins and charge location-based fees based on subsidized energy or water usage by data centers.
Basic financial rules should guide the fund: preserve the principal while paying out universal dividends from the realized gains. These dividends would start small but grow as the fund develops, keeping in line with public interests and performance without resorting to persistent deficit financing.
The benefits from this fund should complement open markets and personal economic choices.
Congress ought to consider exclusive transactions as potentially anti-competitive once certain market thresholds are met. Scrutiny should be applied to the introduction of new entities in the AI space, particularly evaluating “Model Plus Platform” types for possible vertical constraints. Additionally, interoperability and portability—defined as API usage, export formats, and ease of transition—should be standard, with set timelines and clear exit strategies. These regulations would protect the public from entrenched barriers.
People need straightforward options to opt-out of their personal data being used for training, a right to know if their information is utilized, and remedies for any fraudulent applications. In high-stakes contexts like employment, housing, healthcare, finance, and critical infrastructure, those deploying AI should bear responsibility. They need to show that their use of AI is beneficial and meets these obligations.
The Federal Trade Commission should investigate misleading AI claims, manipulative practices, and data misuse. The Department of Justice and the FTC can also challenge exclusive contracts and deals. Moreover, the Securities and Exchange Commission may require disclosures about both AI strategies and impacts on the workforce stemming from AI changes. Citizenship agencies could implement requirements for transparency, auditability, and rights to appeal in automated decisions. Energy and water regulators should demand detailed reports from large data centers and outline conditions for interconnections.
It’s essential for the executive branch and states to move in concert. States should create their AI wealth funds linked to the national fund while managing independent grant projects that run parallel to national initiatives, ensuring access to shared revenues and equity. A collaborative federal research cloud encompassing universities, national labs, and state innovation hubs would allow academia and students to tap into shared AI resources without dependencies on commercial credits.
Inquire with the systems used by your school, employer, or healthcare provider about how they evaluate their tools, and the processes for challenging decisions made. Public funding tied to AI should guarantee rights to ownership, transparency, and choices to exit.
Engage with elected leaders. Emphasize the necessity of building a public AI wealth fund for our country.
