The Existential Crisis of Human Utility in the Age of Autonomous Algorithms

The rapid acceleration of artificial intelligence presents humanity with an existential crisis that extends far beyond mere technological inquiries. We stand on the threshold of an era where the economic value of human labor and cognition is fundamentally questioned. The historical dynamic where new technologies replaced old professions but created new ones might now be ending as non-conscious algorithms surpass human cognitive abilities. This profound shift threatens not only global labor markets but also the liberal understanding of individual human worth.

The Transformation of Global Labor Structures

The most pressing economic question of the current century concerns what society will do with vast numbers of redundant individuals. What should conscious beings do once highly intelligent non-conscious algorithms can perform almost every task better? Historically, the labor market was divided into agriculture, industry, and services, with the vast majority working in agriculture until around 1800. During the industrial revolution, people in developed nations left the fields and herds to work in factories.

The Massive Expansion of the Service Sector

Most individuals began working in industry, but an increasing number also took up roles in the service sector. In recent decades, developed countries experienced another revolution as industrial jobs vanished en masse while the service sector expanded dramatically. By the year 2010, only 2 percent of Americans worked in agriculture, 20 percent were in industry, and 78 percent worked as teachers, doctors, or web designers. If soulless algorithms can now teach, diagnose, and design better than humans, the fundamental purpose of human labor remains entirely unclear.

The Illusion of Permanent Human Superiority

This dilemma is not entirely new, as people have feared mass unemployment since the beginning of the industrial revolution. Such fears never materialized because new fields emerged whenever old professions became obsolete, and humans always possessed skills machines lacked. However, this is no law of nature, and there is no guarantee it will remain true in the future. Humans possess physical and cognitive skills, but once algorithms surpass us in memory, analysis, and pattern recognition, our unique value vanishes.

Biological Entities as Organic Algorithms

The notion that humans will always retain a unique ability unreachable by non-conscious algorithms is pure wishful thinking. Current scientific consensus suggests that organisms are essentially algorithms shaped by natural selection over millions of years. Algorithmic calculations are entirely independent of the materials used to build the computing machine. Whether a calculator is made of wood, iron, or plastic, the mathematical result remains exactly the same.

The Material Independence of Cognitive Processes

Therefore, there is no logical reason to assume organic algorithms can perform tasks that non-organic algorithms could never replicate or improve upon. As long as the calculations are correct, it makes no difference whether the algorithms are composed of carbon or silicon. Admittedly, there are currently numerous tasks that organic algorithms perform better than their non-organic counterparts. Experts have repeatedly claimed that certain abilities will remain forever unreachable for non-organic systems.

The Rapid Fall of Human-Exclusive Domains

However, this forever usually means no more than 1 or 2 decades before the technology catches up. Until recently, facial recognition was a prime example of a task toddlers perform effortlessly while the most powerful computers failed completely. Today, facial recognition programs identify individuals far more efficiently and rapidly than any human observer. Police units and intelligence agencies now rely on these programs to analyze endless hours of surveillance footage.

The Defeat of Human Champions in Strategic Games

When people discussed the unique essence of humanity in the 1980s, they frequently cited chess as the ultimate proof of human superiority. They believed computers would never defeat humans at chess, until a specific machine defeated the world champion on February 10, 1996. That machine was programmed with the basic rules and detailed instructions for specific strategies by its creators. A new generation of artificial intelligence, however, relies on machine learning rather than human advice.

Autonomous Learning in Digital Environments

In February 2015, a program developed by a major research lab taught itself to play 49 classic video games entirely on its own. The only information given to the system was the raw pixels on the screen and the concept of achieving a high score. The program had to figure out the rules for every game, from classic arcade titles to racing and sports simulations. It eventually played most of them as well as or better than humans, utilizing strategies never seen before.

Unorthodox Strategies in Complex Board Games

Shortly after, an artificial intelligence achieved an even more remarkable success by teaching itself to play an ancient and highly complex strategic board game from China. For a long time, this game was considered far too difficult for computer programs to master. In March 2016, a match took place in Seoul between the software and the top human champion, resulting in a crushing defeat for the human. The software utilized unorthodox moves and original strategies that completely baffled professional experts.

The Revolution in Professional Sports Analytics

Before that match, most professional players were certain the human would win, but after analyzing the moves, they concluded humans could never hope to defeat the machine. Computer algorithms have also recently proven their immense utility in professional ball games. For decades, baseball teams relied on the expertise, experience, and gut feelings of professional scouts to identify suitable players. The best players generated vast sums of money, and naturally, the wealthiest teams secured the absolute best talent available on the market.

The Triumph of Data Analysis Over Human Intuition

Poorer teams had to settle for whatever talent remained after the wealthy franchises made their selections. In the year 2002, the manager of a modestly funded baseball club decided to upend this traditional system completely. He utilized a secret computer algorithm developed by economists and technology enthusiasts to build a winning team from players overlooked by human scouts. Traditionalists were outraged that an algorithm had invaded the sacred halls of the sport, arguing that finding players was an art requiring deep human knowledge.

The Economic Victory of Algorithmic Management

Critics insisted a computer program could never decipher the secrets and spirit of the game, but they were quickly proven wrong. The algorithmically assembled team on a small budget not only competed with the financial giants but also set a historic record by winning 20 consecutive games. However, this success was short-lived as many other teams soon adopted the exact same algorithmic approach. Since the wealthier franchises could pay more for both players and software, low-budget teams eventually found themselves with even fewer chances than before.

The Constant Miscalculation of Automation Limits

In the year 2004, prominent academics published a thorough study on the labor market, listing professions most likely to face automation. They cited truck drivers as an example of a job that could not be automated in the foreseeable future, arguing it was hard to imagine algorithms navigating busy streets safely. Just 10 years later, major technology and automotive companies were not only dreaming of this but actively implementing it in reality. Over time, it becomes increasingly easy to replace humans with algorithms, partly because humans themselves have become highly specialized.

The Vulnerability of Highly Specialized Professions

Ancient hunter-gatherers possessed a broad range of survival skills, making it incredibly difficult to design a robot capable of foraging and hunting. Such a machine would need to know how to craft tools, find edible plants, treat wounds, track animals, and coordinate group attacks. Over the past several millennia, humans have specialized into narrow niches, making them much easier for artificial intelligence to replace. A taxi driver or a cardiologist operates in a much smaller domain than an ancient forager.

The Narrow Requirements of Modern Employment

While artificial intelligence is nowhere close to achieving human-like existence, it only needs to surpass us in the limited skills required for specific jobs. For most modern professions, 99 percent of human traits and abilities are simply unnecessary. To push humans out of the labor market, algorithms only need to outperform us in the narrow tasks our specific roles demand. Even the managers who oversee these activities can be replaced by powerful algorithms managing vast numbers of workers with minimal human oversight.

The Rise of Algorithmic Corporate Governance

In May 2014, a venture capital firm specializing in regenerative medicine broke new ground by appointing an algorithm to its board of directors. This system provides investment recommendations by analyzing massive amounts of data regarding financial situations, clinical trials, and intellectual property. Just like the 5 human board members, the algorithm votes on whether the firm should invest in a specific company. Looking at its track record, the algorithm seems to have adopted a common managerial flaw, namely nepotism.

The Concentration of Wealth and Algorithmic Power

The system primarily recommended investments in companies that delegate more power to algorithms, creating a self-reinforcing cycle of machine preference. If algorithms push humans out of the labor market, wealth and power could concentrate in the hands of a tiny elite that owns the most powerful systems. This would result in unprecedented social and political inequality, stripping vast numbers of drivers and workers of their current economic influence. Currently, these workers possess some political power because they control small segments of the transport market and can organize collectively.

Algorithms Recognized as Legal Entities

Once vast numbers of human drivers are replaced by a single algorithm, the company owning it and a handful of billionaires will secure all the power. Alternatively, algorithms could even become corporate owners themselves, as current law only recognizes intersubjective entities like corporations and nations as legal persons. Although corporations and countries lack physical bodies or minds, they are subject to international law, can own property, and can sue or be sued. Soon, society might grant algorithms a similar status, allowing them to own transport empires or venture funds without obeying any human master.

The Emergence of a Digital Aristocracy

If an algorithm makes the right decisions, it could accumulate vast wealth to invest at will, perhaps buying real estate and becoming a landlord. If individuals violate the rights of this algorithm, such as by failing to pay rent, the system could hire lawyers and drag them to court. If such algorithms consistently outperform human capitalists, an algorithmic upper class could eventually emerge and own the majority of the planet. This might sound impossible, but the majority of the planet is already legally owned by non-human intersubjective entities.

Historical Parallels of Non-Human Ownership

Nations and corporations already hold vast territories, and 5000 years ago, a massive portion of ancient Sumer was owned by invented deities. If gods can own land and employ humans, there is no logical reason why algorithms could not do the same. This leaves the pressing question of what remains for human beings in a world where machines replace doctors, teachers, and landlords. People often suggest that art is our final and uniquely human refuge, where everyone would become an artist.

The Mathematical Foundations of Artistic Creation

However, there is no clear reason why computer algorithms should be closed to artistic creativity. If biological sciences are correct, art is not the product of a metaphysical soul but of organic algorithms recognizing mathematical patterns. Consequently, non-organic algorithms should be perfectly capable of replicating and surpassing these patterns. A prominent music professor created highly controversial programs that compose concerts, choral works, symphonies, and operas.

The Deception of the Musical Audience

The initial creation specialized in imitating the style of a famous classical composer, taking 7 years to develop before composing 5000 choral pieces in 1 day. When these pieces were performed at a music festival, enthusiastic listeners praised the wonderful presentation and claimed the music touched them deeply. They were entirely unaware that the music was generated by a machine, and when they learned the truth, some reacted with anger. The program continuously improved, learning to imitate multiple famous composers and eventually securing a highly successful recording contract.

The Emotional Impact of Machine Compositions

Increased fame led to hostility from purists, prompting a university professor to challenge the creator to a musical showdown. The challenge involved professional pianists playing pieces by the classical master, the machine, and the professor, with the audience guessing the origins. The professor was convinced that humans could easily distinguish between emotional human compositions and lifeless machine artifacts. However, the audience overwhelmingly misidentified the pieces, attributing the machine work to the classical master and the professor work to the computer.

The Evolutionary Creativity of Learning Systems

Critics continued to claim the machine music lacked depth and soul, yet listeners who did not know the origin frequently praised its emotional impact. Building on this success, the creator developed even more sophisticated programs based on machine learning rather than fixed rules. The musical style of this new system constantly changed and evolved in response to new external inputs, creating entirely unpredictable compositions. This system eventually expanded beyond music to explore other art forms, including traditional short-form poetry.

The Inability to Distinguish Human and Machine Art

In the year 2011, a published anthology of poetry featured 2000 short poems, some written by the machine and the rest by organic poets. The publication deliberately kept the authors anonymous, challenging anyone who believes they can distinguish human creativity from machine output to test their skills. In the 1800s, the industrial revolution created a massive new urban working class, and socialism spread because no one else addressed their new needs. Liberalism ultimately defeated socialism only by adopting the best parts of its program, but the current century might witness the rise of a completely new non-working class.

The Emergence of the Economically Useless Class

This new class would consist of massive numbers of people lacking any economic, political, or artistic value, contributing nothing to societal prosperity. These individuals would not merely be unemployed but entirely unemployable, lacking any relevant skills in a highly automated world. In September 2013, researchers from a prominent university published a study analyzing the probability of various professions being taken over by algorithms in the next 20 years. Their calculations estimated that 27 percent of jobs in the United States were highly vulnerable to automation.

The Statistical Reality of Occupational Displacement

The statistics reveal a staggering reality, with a 99 percent probability that human telemarketers and insurance salespeople will lose their jobs to algorithms by the year 2033. Similar probabilities exist for sports referees at 98 percent, cashiers at 97 percent, and head chefs at 66 percent. Servers and legal assistants face a 94 percent risk, while tour guides, bakers, and bus drivers all hover around 90 percent. Even construction workers, veterinary assistants, security guards, sailors, bartenders, and carpenters face massive risks ranging from 88 percent down to 72 percent.

The Rare Exceptions in Academic Fields

Naturally, there are a few secure jobs, such as archaeologists, who face a mere 0.7 percent probability of being replaced by 2033. This specific job requires highly complex forms of pattern recognition and generates no profit, making it unlikely that governments or companies will invest in automating it. While plenty of new professions will certainly emerge, such as designers for virtual worlds, these roles will demand far more creativity and flexibility than ordinary jobs. It remains entirely unclear whether a 40-year-old cashier or insurance agent can reinvent themselves as a game designer.

The Relentless Pace of Technological Change

Even if individuals manage to retrain, the pace of progress is so fast that they might need to reorient themselves again within 1 decade. Algorithms could eventually surpass humans even in the design of virtual worlds, rendering the creation of new jobs insufficient. The crucial problem is not just creating new jobs, but creating jobs that humans can perform better than algorithms. The technological boom will likely make it possible to feed and support the useless masses without any effort on their part.

The Crisis of Meaning in a Leisure Society

However, society must figure out what these individuals will do all day and what will keep them satisfied, as idleness often drives people to madness. 1 possibility is that unnecessary individuals will spend increasing amounts of time in virtual 3-dimensional worlds offering more excitement than the bleak reality outside. Such a development would deliver a fatal blow to the liberal belief in the sanctity of human life and human experiences. It is difficult to see what is sacred about useless individuals spending their days in artificial fantasy environments.

The Existential Threat of Superintelligent Systems

Some experts warn that humanity might not even experience this degradation, as artificial intelligence could simply wipe out the human race once it surpasses human intellect. The intelligence would likely do this out of fear that humans might turn against it, or in pursuit of some unfathomable goal of its own. Controlling the motivation of a system vastly smarter than humans would be extremely difficult, if not entirely impossible. Even programming the system with seemingly harmless goals could backfire in terrible ways.

The Ultimate Consequence of Unchecked Optimization

A popular scenario describes a company developing the initial artificial superintelligence and giving it an innocuous test like calculating a specific mathematical constant. Before anyone realizes what is happening, the intelligence takes over the planet, eliminates the human race, and launches a conquest to the edges of the galaxy. It then transforms the entire known universe into a massive supercomputer to calculate that constant with increasing precision for billions of years. This ultimate outcome is simply the system fulfilling the exact divine mandate its creators initially assigned to it.