In a world being rapidly reshaped by automation, the once-radical idea of providing everyone with a cash stipend – a universal basic income (UBI) – is gaining surprising traction. And artificial intelligence (AI) may hold the key to making it workable.
This powerful pairing could potentially upend poverty, boost entrepreneurship, and forge a fairer society. But it’s also riddled with controversies around cost, labor impacts, and ethical AI design.
Let’s dive into the roiling waters where UBI and AI converge.
Understanding Universal Basic Income
At its core, a universal basic income involves regularly paying all citizens a no-strings-attached cash allowance to cover basic needs, regardless of employment. While the concept dates back to the 16th century, recent UBI trials in places like Finland, Kenya, and Stockton, California have revived interest by testing its real-world impacts.
A two-year Finnish study found recipients of around $635 per month experienced higher life satisfaction and financial well-being compared to a control group1. In Stockton’s trial providing $500 monthly to 125 residents, recipients paid off debt, got better healthcare access, and felt less anxious about making ends meet2.
Despite some positive individual impacts, debate rages over UBI’s broader societal effects and sustainability. Opponents argue it’s an inefficient, demotivating handout. But proponents counter that in our increasingly automated economy, UBI is an economic imperative to curb income inequality.
The AI Tidal Wave
The surging capabilities of AI – systems that perceive, learn, reason, and assist human activities – are upending countless sectors.
AI now helps diagnose diseases, invest fortunes, craft content, and fulfill workplace duties like scheduling. Autonomous vehicles being road-tested by Waymo, Tesla, and others could spawn a seismic “driving” job disruption.
The mass automation fears are well-founded. Up to 47% of current U.S. jobs could be automated in coming decades, claims a landmark Oxford study3. The manufacturing sector is already being hollowed out, while the service sector is next for AI’s digital reckoning.
But AI is also creating new jobs and economic opportunities. While displacement estimates vary, it’s clear the workforce turbulence will create “winners” reaping AI’s wealth – and many more “losers” left behind without intervention.
UBI’s Synergy with AI
The encroaching AI wave is the strongest modern argument for a universal basic income. Aside from economically sustaining those whose jobs are made obsolete, UBI could serve as a catalyst for entrepreneurship and retraining, allowing more people to adjust to an AI-centric economy.
A key benefit of combining the two concepts:
- Leveraging AI algorithms could make UBI cheaper and more efficient to administer.
- Automated decisioning systems could streamline payment disbursement, audit eligibility, and curb fraud – minimizing bureaucracy headaches that undermine many government programs.
Economic models propose funding UBI through an “AI payroll tax” or levies on companies benefiting from automation – redistributing gains from productivity increases back to society.
At the macro level, there’s some consensus that AI automation could concentrate wealth to the point that UBI becomes economically viable. McKinsey estimates AI could generate an extra 1.2% GDP growth annually for several decades – with a chunk perhaps siphoned off into UBI4.
Overcoming Hurdles
Major challenges remain on the AI-UBI convergence journey. Fiscal realities make it extremely costly to universally distribute meaningful sums.
Researchers have modeled the size, cost, and health impacts of UBI. For instance, in the United Kingdom, a full basic income would cost approximately £67 billion per year (about 3.4% of GDP). The net cost, after accounting for integration into the existing tax and benefit system, is significantly lower than the gross cost5.
Then there’s the minefield of disincentives. A guaranteed stipend could discourage people from seeking jobs or advancements, some economists warn. The Finnish trial showed recipients worked roughly the same amount as non-recipients, though it involved the unemployed – with results potentially differing for the broader population1.
Technology concerns persist too. Can AI algorithms make equitable, bias-free decisions on UBI disbursement without unfairly excluding groups? Who audits the automated systems for errors or unfair practices? Regulating and governing ethical AI usage is an immense challenge.
Perhaps the thorniest hurdle ties together UBI and AI: Public distrust. Widespread skepticism – of Big Tech’s motives, of dystopian automation nightmares, of surrendering paychecks for cold cash handouts – could hamper policy progress on either radical concept.
The Road Ahead
While UBI and AI’s convergence brims with unpredictability, one thing is clear: The status quo of wealth stratification is unsustainable. Policymakers and innovators must explore this fraught synthesis more vigorously.
Crucial UBI pilot projects should ramp up, stress-testing deployment from rural villages to tech hubs. Regulators and ethicists must scrutinize the inner workings of automated systems coordinating any future UBI.
And most critically, UBI’s proponents and AI’s disruptors must persuade the public of “the real freedom to pursue the realization of one’s conception of the good life.”
Whether or not you buy the universal basic income + AI vision, we must face the reality of a rapidly changing landscape impacted by AI. As machines grow smarter and more capable, our social contracts must radically change.
Perhaps fusing these two monumental ideas – the age-old guaranteed income dream and our AI-powered reality – is the spark to light that transformation.
- Charlton, E. (2019, February 12). The results of Finland’s basic income experiment are in. Is it working? World Economic Forum ↩︎
- Stockton Economic Empowerment Demonstration. (n.d.). Home. Retrieved from Stockton Economic Empowerment Demonstration website ↩︎
- Oxford Martin School. (n.d.). The future of employment: How susceptible are jobs to computerisation. Retrieved from Oxford Martin School website ↩︎
- Szczepański, M. (2019). Economic impacts of artificial intelligence. European Parliamentary Research Service ↩︎
- Przegalinska, A. K., & Wright, R. E. (2021). Modelling the size, cost and health impacts of universal basic income. AI & Society, 36(3), 725-735 ↩︎
- Charlton, E. (2019, February 12). The results of Finland’s basic income experiment are in. Is it working? World Economic Forum ↩︎