Basic income in the age of artificial intelligence cannot wait. Automation could eliminate between 400 and 800 million jobs by 2030, directly affecting workers, public treasuries, and risk managers. Universal Basic Income (UBI) is gaining both practical and moral support as a way to stabilize incomes and demand.
Reasons and Supporting Evidence
The debate over UBI arises from job losses due to the adoption of artificial intelligence and the concentration of wealth in technological capital. Individuals such as Andrew Yang and organizations like the Gerald Huff Fund have warned about this risk. Pilot projects and charitable organizations, including GiveDirectly, have demonstrated positive effects on well-being and entrepreneurship following direct cash transfers.
An analysis argues that UBI allows people to pursue creative and socially valuable work. Cornelia Walther noted that “UBI is not just good social policy—it could be a key economic infrastructure for artificial intelligence.” This perspective highlights the role of UBI as a demand-side instrument: by guaranteeing a minimum income, consumption rises and deflationary pressures driven by automation are reduced.
Criticisms, Funding, and Market Implications
Critics focus on the fiscal cost, the potential disincentive to work, and inflation. However, funding mechanisms have also been proposed, including taxes on automation driven by AI, land value taxes, or environmental levies. Many pilot programs show that the impact on labor participation has been minimal and sometimes positive, helping people access better jobs or encouraging entrepreneurship.
For traders, treasuries, and institutional managers, adopting UBI entails a reconfiguration of demand and macroeconomic risk. Its effects include:
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Maintaining consumption in sectors with high AI adoption.
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Changing fiscal allocations, with new tax bases and potential recurring obligations for governments.
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Impacting the value of assets tied to general consumption and social stability, which is important for liquidity and allocation decisions.
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Driving social innovation and entrepreneurship, according to pilot program evidence.
The urgency of the debate is reinforced by projections of 400 to 800 million jobs that could disappear by 2030. If considered feasible, implementation and funding of UBI move from theory to practice, requiring immediate design and pilot testing.
UBI emerges as a stabilizer of income and demand in the face of automation. Rolling it out through pilot programs and concrete funding models would allow policymakers to assess impacts and prepare for labor and macroeconomic changes brought by artificial intelligence.
