Artificial intelligence (AI) is poised to transform various aspects of society, but its impact on our economic systems raises critical questions about money and resource distribution. Currently, Australia faces a paradox: while the nation wastes approximately 7.6 million tonnes of food annually—equating to about 312 kilograms per person—around one in eight Australians experience food insecurity, primarily due to financial constraints. This scenario underscores the challenges of ensuring equitable access to resources in an era of technological advancement.
The Economic Implications of AI
The intersection of AI and economics is complex. As economist Lionel Robbins articulated, economics examines the relationship between desires and limited resources. Traditional market systems have relied on the principle of scarcity, whereby prices reflect the balance between supply and demand. However, the advent of AI could disrupt this model by potentially generating abundance, leading to concerns about mass unemployment. If millions lose their jobs due to automation, the question arises: how will individuals earn money and sustain market functions?
The recent economic downturn in Australia, caused not by market failure but by the COVID-19 pandemic, revealed that government interventions—such as increased welfare payments and relaxed means-testing—significantly reduced poverty levels. This outcome suggests that a similar approach could be beneficial in addressing the economic challenges posed by AI. Indeed, the experience prompted discussions around implementing a universal basic income (UBI), which aims to provide all citizens with a guaranteed income sufficient for covering basic necessities.
Universal Basic Income: A Solution or a Band-Aid?
The concept of UBI is not new; it has been debated for decades. Proponents, including researchers from the Australian Basic Income Lab—a collaboration involving Macquarie University, the University of Sydney, and the Australian National University—argue that such a policy could facilitate a smoother transition into an economy increasingly influenced by AI. However, UBI proposals vary significantly, with some merely perpetuating existing wealth inequalities. Elise Klein of Macquarie University and James Ferguson from Stanford University advocate for a UBI that functions not as welfare but as a “rightful share” of the wealth generated by technological and social advancements.
This idea aligns with historical movements advocating for equitable distribution of resources. The early 20th century saw similar debates in Britain, where industrialization created wealth without eliminating poverty, leading to widespread job insecurity. The Luddites, who famously protested against mechanization, highlighted the risks of technological advancement when it comes to job displacement.
Another perspective is proposed by author Aaron Bastani, who envisions a world where advances in technology lead to “fully automated luxury communism.” Instead of simply providing cash payments, Bastani suggests implementing universal basic services, which would ensure access to essential needs such as healthcare, education, and transportation. This approach shifts the focus from individual financial support to the collective provision of services, potentially addressing the inequalities exacerbated by technological change.
The discussions surrounding UBI and universal basic services emphasize that, while AI holds promise for creating a more abundant future, it is not a panacea. The potential for ecological collapse and the concentration of power in the hands of a few technology companies could lead to dystopian outcomes if not addressed. As Peter Frase notes, the future shaped by AI and technology will depend significantly on how societies choose to distribute resources and power.
In conclusion, the rise of AI raises urgent questions about economic structures and the distribution of wealth. As the world navigates this technological revolution, it becomes increasingly important to consider innovative policies that ensure equitable access to resources. As Ben Spies-Butcher, an associate professor at Macquarie University, aptly puts it, “We already have enough food for everyone. We already know how to end poverty. We don’t need AI to tell us.” The challenge lies in leveraging technological advancements to create an inclusive economic model that benefits all.
