The idea of a guaranteed income for all has been floating around for centuries, its popularity ebbing and flowing with the passing tide of current events. While it is still considered by many to be a radical concept, proponents of a universal basic income (UBI) no longer see it only as a solution to poverty but as the answer to some of the biggest threats faced by modern workers: wage inequality, job insecurity – and the looming possibility of AI-induced job losses.
Elon Musk, at the recent Bletchley Park summit, said he believed “no job is needed” due to the development of AI, and that a job can be for “personal satisfaction”. Economist and political theorist Karl Widerquist, professor of philosophy at Georgetown University-Qatar, sees it differently.
“Even if AI takes your job away, you don’t necessarily just become unemployed for the rest of your life,” he says. “What happens is you go down in the labour market, you start crowding the lower-income professions.”
Widerquist believes, at least in the short term, that the growth of AI will push white-collar workers into the gig economy, and into other forms of poorly paid, insecure work. Such a shift in the workforce would, he fears, drive down wages and conditions, while increasing inequality.
A UBI policy in response to AI and automation would address the failure of employers to distribute the spoils of economic growth – propelled, at least in part, by automation – fairly among workers, says Widerquist.
Some go further still, pointing to UBI as a dividend due to workers for their role in the development and dissemination of knowledge used to train AI models such as ChatGPT. “Why,” asks Scott Santens, editor of website Basic Income Today, “should only one or two companies get rich off of the capital, the human work, that we all created?”
If, in the future, workers do find themselves made redundant by automation and unable to secure new positions, UBI offers a similarly promising option, says Loek Groot, associate professor of economics of the public sector at Utrecht University.
In a study conducted by Groot and fellow researchers in the Netherlands between 2017 and 2019, unemployed individuals who were previously in receipt of social assistance were given a basic income. The study indicated increased participation in the labour market. This was not solely due to the financial support provided by UBI, but to the removal of conditions – and sanctions for failing to fulfil said conditions – traditionally imposed on job seekers, says Groot.
Specifically, participants who were exempt from obligations to find and accept work were more likely to secure a permanent contract – in contrast with the type of insecure work highlighted by Widerquist.
While UBI experiments do not generally show that the policy encourages workers to entirely leave the labour market, higher payments have led to some people reducing their working hours. This, Groot says, should not be considered a bad thing. “Why try to push everyone into paid work, if you can objectively see that there are not enough jobs around?” he asks. “Why not give people who have good alternatives the opportunity to reduce work, or not work at all, and cash in the basic income?”
“Good alternatives” include the opportunity to upskill or retrain. It’s also possible that the policy could redefine what society has historically considered work. Caregivers – predominantly women – could be remunerated for traditionally unpaid labour, such as raising children or caring for elderly relatives.
In Kenya, the world’s largest UBI scheme has been providing almost 5,000 people with a payment of about 75 cents (62p) a day since 2017. Organised by GiveDirectly and funded by donations, the experiment will run for 12 years. Tavneet Suri, a member of GiveDirectly’s research team and professor of applied economics at Massachusetts Institute of Technology, says she has so far seen some surprising results.
“We do see people leaving low wage jobs,” she says. “They are going and starting businesses, and the businesses are doing great because there’s money around.” This unexpected wave of entrepreneurship has also had a positive impact on those taking jobs that pay wages, as a shrinking of the available workforce has led to an increase in salaries.
“In a developing country, if we see a 20% increase in businesses, that’s people who are going to pay taxes,” says Suri. “Because farmers [who make up a high percentage of Kenya’s workforce] are not taxed in general, suddenly you have a bunch of people showing up in tax brackets, and they’re buying stuff. And one of the biggest pieces of revenue for the government is actually sales tax.”
Suri and her colleagues also report that workers have not left the labour market, and that local economies have been boosted by increased buying power. Despite this, Suri is cautious. In a country where poverty remains far more pressing for workers than automation, she says a government-backed UBI programme must be shown to be truly beneficial before being seriously considered.
For countries where automation is a greater concern, Rosanna Merola, a macroeconomist and researcher at the International Labour Organization, has considered a very different approach: a robot tax. In a 2022 research paper, Merola described the possibility of taxing companies that replace workers with robots in order to fund a UBI as “philosophically appealing”, if currently unrealistic.
“At this stage, proposals on how to implement a robot tax in practice remain very nebulous,” she says. “Legislators are likely to deal with the complexity of defining what constitutes a ‘robot’ and how to tax it. The distinction between a machine and a robot or between a computer program and AI is still not clear.”
Despite this, Merola does believe that the concept of a robot tax could be extended to apply to AI in more recognisable forms – large language models such as ChatGPT, for example. She suggests that companies that use AI to automate tasks, make decisions or perform services might be subject to taxes on the profits or revenue generated through AI-driven processes. Or, governments might tax the collection, processing or sale of data on which AI heavily relies, with a portion of this revenue used to mitigate the technology’s impact on displaced workers.
Joe Chrisp, a researcher at the University of Bath’s Universal Income Beacon, feels that conversations surrounding automation in work can sometimes resemble a “counsel of despair”. Crisp does believe that a UBI could deliver positive outcomes for workers, but describes himself as a “friendly sceptic”.
While some argue that AI could drive workers into the gig economy, and that a UBI could help to lift them out, Chrisp says that such a policy risks “facilitating the proliferation of these types of jobs, rather than incentivising people to find more stable work”.
And, on the topic of a possible UBI model, he is once again sceptical, describing even the most modest proposals as likely to require large increases in taxation, and therefore as “difficult to sell”.
Research from thinktank Autonomy shows a modest UBI scheme would probably require higher contributions from the most well-off, but would not result in a net increase to taxation. “That model is effectively cost neutral, and would halve child poverty and pensioner poverty,” says Will Stronge, director of research at Autonomy. “But I think it wouldn’t be high enough to achieve some of the more expensive cultural changes.”
Chrisp agrees that in the medium term, there must be a strategy to help workers to secure new roles in a changing economy. And, in the shorter term, a safety net for those same workers must be found. However, he is not convinced that a single policy could provide the solution to an issue as complex as the impact of AI on work.
“Personally, that vision of a UBI providing lots of people who can’t find any job in the labour market with a secure income indefinitely, I find that quite depressing,” he says. “Capitalist economies are very good at continuing to generate things that people can do to earn a wage, it’s just a question of whether those are good jobs or not – and that we can’t really know.”
