Artificial General Intelligence

Context

"Income increasingly flows to those who own computational resources rather than those who provide labor."

Sueyon Kim writes:

"Professor Restrepo defines AGI as “a state in which all economically valuable work currently performed by humans can be accomplished using computational resources.” AGI thus represents more than technological superiority in specific domains—it marks a critical inflection point where algorithms and computing power combine to replace production activities across the entire economy. Restrepo projects that the drivers of economic growth will shift from population expansion and labor inputs to the rate at which computational resources scale.

This transformation transcends mere technological progress—it constitutes a fundamental economic restructuring. While industrial-era productivity gains emerged from labor force expansion, AGI- era growth derives from processing larger datasets and scaling computational capacity. As long as computational capacity keeps expanding, growth can continue in spite of population decline.

This economic realignment fundamentally transforms the determination of wages. Compensation no longer reflects human productivity but rather the cost of replication—the expense of performing identical work with artificial intelligence. Any given occupation must prove that it is difficult to replace with AI in order to retain substantial economic value.

Consequently, income increasingly flows to those who own computational resources rather than those who provide labor."

(Source: Taejae Future Consensus Institute <World Research Trend> Vol.42 I 2025-11-21)

Description

"The term AGI is meant to distinguish itself from tradition AI or narrow AI, of the preprogrammed and austere variety. Cruise control and chess playing software are examples of narrow AI. The goal of General AI is to create a thinking machine, one that can understand patterns in the world and in itself, while learning and acting accordingly. Ben Goertzel's et al. work in the company, Novamente, has shown progress toward this goal, teaching virtual pets in Second Life to play fetch using observation and other learning techniques. Goertzel's work is currently at the infantile stage, described as an autonomous agent with simple associations between words and objects, actions and images, and the basic notions of time, space, and causality.[2] Once AGI is at the intellectual level of a Da Vinci or Einstein and beyond it can then be taught and learn virtually anything a human can more effectively and accurately than a human ever could. To say that AGI, once developed, could teach others a thing or two, may be a significant understatement. Of recent, this discipline has displayed more substantial involvement. The first conference on Artificial General Intelligence attracted over a hundred developers, presenters, and enthusiasts to discuss the many aspects of the field—a strong signifier of what is to come. In an interview with Ben Goertzel at a Singularity Institute conference, it was mentioned that an AGI could be produced in as little as five years, given that a concerted effort is made."

(http://www.effortlesseconomy.com/)

Discussion

Two Transition Pathways: Gradual Adjustment Versus Sudden Disruption

Suyeon Kim:

"Professor Restrepo distinguishes between two scenarios for the AGI transition. The first is the “compute-binding transition” in which algorithms exist, but a lack of computational resources prevents full automation. Under this scenario, automation proceeds gradually, giving workers time to transition to new occupations.

The second is the “algorithm-binding transition” in which there is an abundance of computational resources, but algorithms for specific tasks remain undeveloped. When algorithmic breakthroughs occur, wages in affected sectors collapse abruptly and jobs disappear. Labor markets move discontinuously and in a volatile manner, and entire occupational categories could become obsolete overnight, which drives a rapid expansion in inequality.

Societies with a rapid technology adoption rate, such as Korea, have a higher probability of following the latter pathway. This calls for preemptive policy development and institutional frameworks that are capable of matching the pace of technological change—a warning that demands continued emphasis.

Computational Resource Owners Will Capture Most Income: Universal Basic Income and Other Fundamental Measures Required

On Restrepo, continued:

"The projection that labor’s share of income will approach zero transcends mere statistical observation—it spells wholesale economic restructuring. Professor Restrepo treats computational resources as new factors of production, comparable to land or capital. In AGI economies, growth depends on the speed at which computational capacity accumulates, and whoever owns these resources will capture the lion’s share of income. In other words, future wealth distribution hinges on who controls infrastructure such as GPUs, semiconductors, and data centers.

Restrepo proposes Universal Basic Income and public ownership of computational resources as tentative solutions. One approach involves taxing computational infrastructure revenues and redistributing these funds across society, while the other treats computational resources as public goods under collective governance. These are categorically different from conventional welfare policies, and can be viewed as a kind of institutional architecture for a new economic order."

(Taejae Future Consensus Institute World Trend Research vol42_251121)

More Information

• Pascual Restrepo, “We Won’t Be Missed: Work and Growth in the AGI World,” in Ajay K. Agrawal, Anton Korinek, and Erik Brynjolfsson (eds.), The Economics of Transformative AI (University of Chicago Press, 2025), chap. 9. This research was presented at the NBER “The Economics of Transformative AI” conference in September 2025, subsequently published as NBER Working Paper No. 34423 in October of the same year, and is scheduled for inclusion as Chapter 9 in The Economics of Transformative AI to be published by University of Chicago Press.

More:

1. Artificial General Intelligence Research Institute, at http://www.agiri.org/wiki/Main_Page
2. Interview with Ben Goertzel at http://www.singinst.org/media/interviews/bengoertzel
3. Open Cognition Project