Aaron Kalikawe’s AI-first Cities proposal makes robots the natives of the AI-first Cities and humans the immigrants. Work that can be performed reliably by robots or AI agents would be automated, while tasks that cannot yet be automated would continue to be carried out by humans.
This allows businesses to deploy robots into public spaces more rapidly, much like self-driving cars must operate on public roads to collect real-world data that improves their safety and performance. Similarly, humanoid robots need exposure to real-world environments in order to learn, adapt, and become safer when operating alongside people. AI-first Cities would become city-scale training grounds where humanoid robots learn to operate safely alongside humans and even the wildlife in the Wildlife Parks, including serving as humanoid park rangers responsible for monitoring and protecting wildlife. The faster they learn to coexist safely in real-world environments, the better.
Because robots and AI agents do not receive salaries, the resulting cost savings become additional business profits, which are taxed to generate city revenue. A portion of those city profits is then distributed to citizens as a Universal Basic Income. In effect, people receive the income that would otherwise have been paid as wages to the robots and AI agents performing the work.
With the financial protection of Universal Basic Income in place, automation can proceed at full speed without the fear that displaced workers will lose their livelihoods. Humans would then be free to spend their time much like retirees do after leaving the workforce—pursuing education, entrepreneurship, creative endeavors, recreation, family life, volunteer work, or other personal interests. Looking back, future generations may find it remarkable that people were once required to work simply to earn enough income to meet their basic needs. For much of human history, those who could not find employment often faced severe financial hardship, with few meaningful alternatives.
Yes, training robots without simultaneously transforming your nation’s economic model from dependence on employment income to dependence on Universal Basic Income could create short-term employment at the risk of long-term unemployment.
I support training robots to automate all forms of human labor, provided that the resulting economic gains are taxed and redistributed to citizens through a Universal Basic Income. This would provide people with a more stable source of income—one funded by the productivity of the entire economy rather than by a single employer.
The Solution by Aaron Kalikawe
For policymakers, the writing is on the wall: PLEASE HEED THE WARNING. You need to begin transitioning your economy from dependence on employment income to dependence on Universal Basic Income. The longer you wait, the more chaotic and painful that transition is likely to become. During the transition, governments will need to financially support those who become unemployed while UBI payments are still insufficient to meet their basic needs. The longer the transition is delayed, the greater the number of unemployed people who will require support.
The earthquake has already occurred beneath the ocean—the rise of artificial intelligence. It has triggered a tsunami that could lead to widespread job displacement. The waves have not yet reached the shoreline, and that gives policymakers valuable time to organize an orderly evacuation to higher ground by transforming their economies while most people are still employed. If you wait until the tsunami makes landfall before taking action, it may be too late. The transition to a UBI-based economy will not happen overnight, and governments may no longer have sufficient resources to support a rapidly growing unemployed population during the transition.
Professor Chad Jones discusses the weak links that could slow the high rates of economic growth expected from AI adoption. The danger of only partially automating the economy is that it may produce only modest productivity gains while simultaneously creating political unrest as the economic divide widens between those whose jobs remain unautomated and those whose jobs have been automated.
Weak links that slow economic growth occur wherever humans remain in the loop, particularly when performing tasks that can already be reliably automated by AI. The failure to automate these tasks may stem from a desire to preserve human employment or simply from a lack of awareness that the work can already be automated. In practice, this lack of awareness is one of the biggest reasons businesses fail to automate tasks that are already automatable.
This is one of the reasons my AI economic proposal advocates building entirely new AI-first Cities governed by AI companies with levels of autonomy comparable to Hong Kong and Macau, and contractually obligated to continuously develop AI systems that automate not only commercial activities but governance itself. Building new cities allows businesses to adopt an economic system that requires the automation of every task that can be reliably automated. The governing AI companies would build and maintain the infrastructure that enables businesses to automate their operations easily, including through third-party AI tools.
Humans are often the bottleneck in adopting new AI capabilities because workers require continual training whenever new technologies become available. By contrast, updating an AI model to use a newly released capability the next time it performs a task is relatively straightforward. Even the human brain has limits in its ability to remember every AI capability available for accomplishing a particular task. As AI models rapidly gain new capabilities—and as AI-assisted “vibe coding” accelerates the pace at which those capabilities are developed—it becomes increasingly impractical to expect human workers to remain continuously trained. Humans therefore become the bottleneck: the weak link that prevents AI adoption from keeping pace with technological progress. The result is that increasingly powerful AI models remain significantly underutilized because the people using them cannot keep up with their expanding capabilities.
The promise of AI-driven abundance will only be realized by maximizing automation throughout the entire economy. I do not believe conventional cities have the political will to pursue that level of automation without first protecting workers from the resulting job losses. That is why I propose building new AI-first Cities, where the economy has never depended on employment income and is designed from the outset to be sustained by Universal Basic Income.