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Sam Altman, CEO of the AI giant OpenAI, expressed confidence in a podcast episode that the company will be the first to achieve AGI or artificial general intelligence. When host Adam Grant, an author and a psychologist, asked Altman about an unpopular opinion in AI, the latter replied, “That it’s [AI] not gonna be as big of a deal as people think, at least in the short term. Long term, everything changes.”
“I kind of genuinely believe that we can launch the first AGI, and no one cares that much,” Altman added.
He predicted that 20 minutes after AGI is achieved, everyone will think about what they will have for dinner that night.
Moreover, Altman also believes that the company’s models are smarter than him in “almost every way”, but this doesn’t impact his life.
Altman’s thesis points towards the fact that in the short term, AI models don’t matter much, and only the long-term effects will change the course of humanity.
“You and I are living through this once-in-human history transition where humans go from being the smartest thing on planet earth to not being the smartest thing on planet earth.”
This certainly opens up a lot of interesting takes on how humans may navigate an AI-driven future and economies.
“Eventually, I think the whole economy transforms. We’ll find new things to do. I have no worry about that,” Altman added.
So are we not to worry as well?
‘We Always Find New Jobs’
While Altman admitted that some jobs will disappear, he added that humans will always find new things to do.
Several big names in the industry approach an AI-dominated future using a similar, optimistic thought process. Take Anthropic CEO Dario Amodei, for instance. In an essay, he said, “I think it is very likely a mistake to believe that tasks you undertake are meaningless simply because an AI could do them better.”
He also said that people may begin to greatly enjoy activities that produce no economic value. He added that people will still be able to achieve a sense of accomplishment by spending years attempting some very difficult task without wanting to reap the economic benefits that come with it.
“The fact that an AI somewhere could, in principle, do this task better and that this task is no longer an economically rewarded element of a global economy doesn’t seem to matter very much to me.”
He further said that even in tasks where AI can do 100% of the things better, humans may possess an advantage if machines are economically inefficient.
Amodei also believes that one area where humans are likely to maintain a relative or even an absolute advantage is their presence in the physical world. However, he admits that AI will eventually become effective and so cheap that the arguments no longer apply.
“At that point, our current economic setup will no longer make sense, and there will be a need for a broader societal conversation about how the economy should be organised,” he added.
Vinod Khosla, a veteran entrepreneur in Silicon Valley, believes that AI could create a world where a “small elite” will thrive and the rest will face economic problems. AI will create new jobs we cannot currently conceive of,” he said, adding that it will eliminate most professions that people pursue to support their needs and lifestyles.
However, he is confident that smart interventions, such as income distribution, minimum living standards, and strategic legislators, can lead to solutions.
“I believe these interventions are achievable because Western capitalism is achieved with the permission of democracy and its voters. If we correctly handle this phase shift, AI will generate more than enough wealth to go around, and everyone will be better off than in a world without it,” Khosla said.
Sam Altman Loves UBI
Interestingly, Altman has also explored the cure for the very problem he created. He is the biggest proponent of Universal Basic Income (UBI), and he’s been vocal about it since 2016, well before the advent of generative AI.
He backs a research group called OpenResearch, which studied the effects of unconditional cash transfers of $1,000 per month to around 1,000 American individuals with an income of approximately $30,000 a year.
The study found that the cash led to increased spending on basic needs and that “recipients worked less, but remained engaged in the workforce and were more deliberate with job searches and employment choices”.
“Recipients had greater agency to make decisions that worked best for their lives and to prepare for the future, from moving neighbourhoods to expressing interest in new business ventures,” the report further stated.
However, cash did not mean everything, and it wasn’t able to address challenges such as chronic health conditions, childcare, or housing costs. Of course, OpenResearch acknowledges such challenges, but implementing UBI is a completely different problem.
Will UBI be More Difficult to Achieve Than AGI?
Anton Korinek, a professor of economics at the University of Virginia, said in a research study that, unlike wealth distribution mechanisms that compensate “losers” within a country, there isn’t a well-established global institution for large-scale wealth redistribution across different countries.
“Addressing this issue would require unprecedented levels of international cooperation
and potentially the development of new global economic governance structures to share the benefits of AI more equitably across nations,” Korinek said.
He also said that monetary policies will face new challenges, especially in understanding the relationship between unemployment and inflation.
“Traditional measures of labour market slack may become irrelevant for inflation dynamics. Instead, new indicators of economic capacity utilisation, such as the intensity of capital use, may emerge,” he added.
Korinek also said that sources of government revenue would have to shift from labour to other bases, such as capital driven by AI assets or new sources of taxes that capture AI-generated economic activity. “Key challenge will lie in reimagining macroeconomic policy for an era where AGI, rather than human labour, becomes the primary driver of economic growth and fluctuations.”
Thus, it isn’t just engineers or AI safety researchers who will have a lot of work to do. “Economists have a crucial role in preparing for the age of AI,” Korinek predicted. “Furthermore, our [economists’] understanding of market dynamics and regulatory frameworks can inform the design of effective governance structures for AI.”
That said, if UBI has its challenges, Altman also proposes universal basic computing (UBC) as a long-term and sustainable alternative to UBI.
“Imagine owning part of the productivity, like a slice of GPT-7 compute, which you could use, donate, or resell—transforming access into empowerment,” Altman said.
