Contents
Contents

Human Labor Displacement

This topic includes the following:

Breaking The Historical Pattern Of Technological Employment/strong>

While massive labor displacement due to AI and robotic systems would likely not be as immediately catastrophic as nuclear war or a global pandemic, it could lead to some dramatic societal effects if not properly managed.

The development of advanced AI alone or in synergistic combination with AI-enabled humanoid technologies ("Advanced AI Systems") is inevitable and represents a fundamental break from historical patterns of technological labor unemployment and reemployment. Workers should not be promised a bright future unless adequate full employment opportunities are identified that will provide adequate full employment opportunities for those able and willing to work, or unless we are prepared to provide the massive subsistence resources to support the overwhelming majority of what would otherwise have been gainfully employed humans.

In the near term, significant human labor displacement is more likely to occur through targeted development of specific robotic and AI capabilities, rather than waiting for the development of fully humanoid robots with human-like general intelligence (AGI). In other words, human labor displacement outcomes do not require AI and AIdroids with AGI or ASI level capabilities; and the more immediate and practical impact on human employment is likely to come from the continued advancement and integration of specialized robotic systems and narrow AI across various industries.

This topic introduces four key frameworks: (i) the historical pattern of technological unemployment and reemployment will not apply to the widespread deployment of Advanced AI Systems; (ii) previous technological transitions have systematically misattributed machine productivity to human capability, and thus we have failed to appreciate the potential impact of AI systems on labor participation and unequal wealth distribution; (iii) faith in technological continuity has acquired quasi-religious characteristics that blind us to AI's Siren's Call; and (iv) there is no clear plan on how to dramatically enhance currently inadequate economic, taxation, and human engagement policies to secure, in the context of Advanced AI Systems, a minimally bright future for most humans.

There is the perspective that the history of technological advancement shows that, while technology eliminated certain human labor, it created new net additional labor opportunities for humans, and that this suggests that AI and AIdroids, while eliminating certain human labor, will also create new net additional labor opportunities for humans.

That historical pattern is often called "creative destruction" or "technological unemployment and reemployment". Every major technological shift has been accompanied by fears of mass unemployment, yet economies have always adapted. The Industrial Revolution, for example, eliminated many traditional crafting and agricultural jobs, but created new factory and industrial jobs. The rise of automobiles displaced horse-related occupations, but created new jobs in manufacturing, oil/gas, and eventually services like gas stations and mechanics. The computer revolution eliminated many clerical and calculation-based jobs, but created entirely new fields in software development, IT support, data analysis, etc.

That historical pattern allegedly supports several perspectives: that Advanced AI Systems will create new industries and job categories; that humans will remain necessary for development and maintenance; that increased productivity will generate economic growth creating more jobs; that uniquely human skills will retain value; and that basic economic forces driving "technological unemployment and reemployment" remain unchanged regardless of technology.

The historical pattern of technological unemployment and reemployment will not apply to the widespread deployment of Advanced AI Systems because such systems represent a historically qualitatively different velocity and type of technological advancement—one capable of replacing human labor across nearly all sectors of the economy through comprehensive replication of human cognitive and physical capabilities. This qualitative difference is evidenced by our current inability to articulate concrete ways the overwhelming majority of humans would meaningfully participate in such an AI economy - not due to limited imagination, but because the technology's unprecedented defining characteristic is its potential to eliminate the necessity of human involvement. Unlike previous technological revolutions, where new roles for human labor were visible even in early stages, Advanced AI Systems leave no clear path for large scale human economic participation. In due course, the deployment of Advanced AI Systems will not render human labor more productive; rather, it will render human labor economically obsolete.

Prior to Artificial General Intelligence (AGI) and subsequent Artificial Super Intelligence (ASI) level capabilities, dramatic labor displacement will begin to materialize with the introduction of Advanced AI Systems synergistically integrating Narrow AI or Artificial Narrow Intelligence (ANI). These systems include AI specialized for specific tasks or domains, such as task-specific Large Language Models (LLMs), Computer Vision Models specialized in visual perception and analysis, Expert AI Systems designed for specific professional domains, and advanced technologies incorporating vision, language, improved sensorimotor control, and enhanced dexterity and manipulation capabilities.

AI systems that excel at specific tasks (narrow AI) are advancing rapidly and could outperform humans in areas like data analysis, pattern recognition, and certain decision-making processes without needing general intelligence. Many white-collar jobs are at risk from software solutions and AI that can process information, write reports, or make decisions. This doesn't require a physical robot at all. Businesses are motivated to increase efficiency and reduce costs, and are more likely to adopt targeted solutions that address specific needs rather than waiting for a general-purpose humanoid robot.

While in the early stages of Advanced AI Systems deployment, there will certainly be opportunities for a very limited number of specialists, these opportunities do not overcome the forthcoming widespread labor displacement. The opacity around future employment signals a genuine absence of necessary human economic roles rather than mere predictive uncertainty.

Unlike previous technological revolutions where new machinery and systems inherently created visible chains of human involvement in their production, maintenance, and operation, advanced AI systems will in due course eliminate the need for human participation across the entire value chain, including next-generation Advanced AI Systems' own advancement and reproduction.

Looking at current technological trends, within 10-15 years, AI and limited-function emerging robotic capabilities will displace 40% of human job functions. Based on current technological trends and expert assessments, predictions for humanoid robots with human-like mobility and dexterity capable of displacing most human labor typically are currently in the range of 15-30 years from now, when months ago predictions were in the range of 30-50 years from now.

Image from the Charlie Chaplin's "Modern Times " (1936) a movie depicting assembly lines and the enslaving of man by machines. In this scene Charlie Chaplin is shown swallowed by the machine.

Presently humanoid robots are expensive to develop and produce; power consumption is a significant challenge for mobile robots; fine motor skills and human-like dexterity remain challenging; true autonomy and human-like decision making are still limited; and many are still fragile and require controlled environments. For widespread adoption, manufacturing costs must decrease significantly and return on investment must justify replacing human workers.

However, Elon Musk has recently claimed that One million Optimus humanoid robots will be produced by 2030. YouTube: Elon Musk's Bold Claim - 1 Million Optimus Robots by 2030 (2024),

Thus, the potential widespread human labor displacement is likely to precede the deployment of AGI or ASI level capabilities which in combination with advanced AIdroids will cause the collapse and displacement of human labor.

Zvi Mowshowitz introduces the Technological Richter Scale from Nat Silver's "On The Edge," where ASI would represent an unprecedented level 10 event—fundamentally redefining planetary existence, compared to electricity's level 8 impact. Mowshowitz warns that creating superintelligent entities would likely transfer control of the future to these smarter beings with potentially catastrophic outcomes for humanity.

Mowshowitz further argues that preserving human relevance against superior AI represents an "unnatural" outcome requiring unprecedented intervention. Humans, as the less competitive and less intelligent entities, would struggle to maintain resources and power against systems that can outcompete them in every domain. This intervention, while necessary to preserve what we value, presents an extraordinarily difficult implementation challenge.

The deployment of AGI/ASI level AI systems in synergistic combination with AIdroids, will completely displace human labor in every conceivable task or service, both physical and cognitive. Not only would AIdroids be superior in performance, but they would also be more economically efficient, making human labor uncompetitive in a free market. As a rough indicator, the average cost of educating a child from pre-K through college graduation at public US institutions is roughly $250,000 to $300,000 in total, as of 2024. This implies a future where human labor, in any form, becomes economically obsolete. Such a scenario would fundamentally challenge current economic systems, which are largely based on human labor and consumption.

The object of such AGI/ASI level AI systems is not to make humans more productive, rather the object is to render human productivity obsolete.

AI Labor Displacement Trajectory

Recent analysis of AI's impact on software development reveals significant productivity gains across multiple development activities: code generation and autocompletion, bug detection and fixing, documentation generation, test case generation, code review, and DevOps activities. When weighted by typical time allocation and accounting for various factors such as team expertise, project complexity, integration costs, and organizational differences, the data indicates an overall productivity improvement of 20-35%. This estimate reflects real-world observations rather than theoretical possibilities.

As Theodore Kaczynski presciently observed in "Anti-Tech Revolution: Why and How" (2016):

"The techies won't be able to 'shape the advances' of technology, guide the course of technological progress, or exclude the intense competition that will eliminate nearly all techies in short order." (Kaczynski "Anti-Tech Revolution: Why and How" (2016) page 73-74).

Smaller AI companies are developing highly specialized, task-specific AI models targeting discrete job functions. These focused AI systems, while lacking general intelligence, can effectively replicate and replace specific human roles: a medical office receptionist handling appointments and insurance verification, a repair service AI managing scheduling and dispatch, or a customer service AI handling routine inquiries and complaints.

This pattern of targeted displacement is particularly powerful because it allows for incremental adoption without requiring massive infrastructure changes. Small software companies can develop these specialized models by fine-tuning existing language models and combining them with basic process automation. The investment required is relatively modest compared to developing general AI or robotics, making the business case compelling even for small and medium-sized businesses.

AI systems that excel at specific tasks (narrow AI) are advancing rapidly and could outperform humans in areas like data analysis, pattern recognition, and certain decision-making processes without needing general intelligence. Many white-collar jobs are at risk from software solutions and AI that can process information, write reports, or make decisions. This doesn't require a physical robot at all.

The advantages of AI voice-enabled customer service over current systems are substantial and immediate. Where traditional systems force customers through rigid menu trees, requiring them to listen to entire option lists and frequently repeat information, AI systems enable natural conversation where users simply state their problems in their own words. The AI can adaptively ask clarifying questions based on responses, maintaining context throughout the interaction without requiring repetition at different stages.

Businesses are motivated to increase efficiency and reduce costs, and are more likely to adopt targeted solutions that address specific needs rather than waiting for a general-purpose humanoid robot.

Current professions thought to be relatively immune to automation, such as medical practitioners, are already seeing their capabilities matched or exceeded by AI systems across multiple domains. In surgery, the progression is particularly telling: first, robotic arms became the primary contact point with patients, with human surgeons controlling them remotely. The next step, already underway, is replacing human control with AI-driven systems using advanced visual recognition and precision control—eliminating the need for human surgical expertise entirely. This progression mirrors what we're likely to see across many industries—a gradual shift from AI/robots as tools to autonomous systems that completely replace human involvement.

Beyond the operating room, AI systems are being enhanced to match or exceed human capabilities in diagnosis and treatment planning. Even the supposedly uniquely human aspect of medical care - empathy and bedside manner - is being effectively replicated by AI systems that can craft more empathetic responses than human physicians.

Dr. Jonathan Reisman's acknowledges in his essay "I'm a Doctor. ChatGPT's Bedside Manner Is Better Than Mine." The New Your Times 2024-10-05 that AI systems like ChatGPT have dramatically undermined physicians' job security, excelling not only in technical medical aspects like diagnosis and treatment planning but also - perhaps more surprisingly - in patient communication. In a revealing study, AI-generated responses were rated as both more empathetic and higher quality than those from human doctors.

Dr. Reisman points out the uncomfortable truth behind AI's superior bedside manner: compassion in medicine largely follows predictable patterns that AI can master. The fact that empathy can be effectively replicated by following scripts exposes how much of medical care—even its seemingly most human elements—can be systematically reproduced by non-human systems.

In the legal profession, current language models already possess the capability to provide comprehensive legal services, with the primary barrier being LLM providers' current strategic choice to avoid potential legal liabilities rather than any technological limitation. The logical endpoint of this progression will be fully automated legal proceedings where AI systems represent both plaintiffs and defendants, presenting cases to an AI judge who could process the entire body of relevant law and precedent in minutes rather than months. This is not a far-fetched scenario—it simply represents the natural optimization of legal processes once we remove the artificial constraint of human processing speeds and address the obstructions imposed by the profession's self-interests.

The creative industries, often cited as a refuge for human employment, are similarly vulnerable. The rapid advancement in AI-generated content, from writing to visual art to music composition, demonstrates that even these supposedly human-centric domains are not immune. The entertainment industry's response, as evidenced by recent SAG-AFTRA legislation regarding AI replicas of performers, exemplifies a broader pattern of professional resistance through organized labor. This resistance, while understandable, may ultimately prove futile against the economic imperatives driving AI adoption.

It is widely acknowledged that AI and automation technologies can streamline administrative tasks such as data entry, document processing, and customer service. These tasks are common in government roles, making them prime candidates for automation. Current government service interactions often involve long wait times, multiple transfers between departments, repetitive form-filling, and frequent confusion about proper procedures. An AI system will transform this experience by providing instant, accurate information about complex regulations, guiding citizens through required documentation, and ensuring consistent interpretation of rules across all interactions.

According to the U.S. Bureau of Labor Statistics (BLS), there are over 20 million government employees at federal, state, and local levels, and a significant portion of these roles involve administrative tasks. McKinsey & Company and other research organizations have suggested that 10-20% of government jobs could be automated in the coming decades.

Government policies driven by special interest will have to align with the realities of human labor displacement. For example, in the U.S. mail delivery, once a crucial service delivering important communications, now primarily delivers what many consider "junk mail." This change is largely due to technological advancements - email, online billing, and digital communication have reduced the need for physical mail delivery.

The current six-day delivery schedule is inefficient given the reduced importance of physical mail for many people. The continuation of this schedule despite changing needs illustrates how established systems can be slow to adapt to technological changes. The taxpayer subsidies demonstrate how government policies can influence the pace of labor market changes in response to technological shifts. The role of unions and special interests in maintaining the current schedule highlights the tension between adapting to technological change and preserving jobs.

The mail delivery example also brings to mind occasions where a parent gives a child busy work so that the parent can get real work done. In this analogy, AI systems take on the role of the "parent" - the productive, capable entity doing the "real work." Humans are cast as the "child" needing to be occupied with "busy work." This imagery suggests a significant shift in the power dynamic between humans and AI, with AI systems potentially becoming the primary productive force in the economy. In an AI-dominated world, human "labor" lacks real value and natural purpose, and is more of a hindrance.

The trajectory is clear: AI advancement will continue to displace human labor across increasingly diverse sectors, from routine tasks to knowledge work to creative endeavors. The economic incentives for this displacement are too compelling to resist, and the technological progression shows no signs of slowing. What remains uncertain is not whether this transformation will occur, but how society will adapt to a world where human labor becomes increasingly superfluous to economic production.

Impediments to Human-AI Collaborative Employment

Proposals that humans will find substantial employment through collaboration with AI systems fail to address four critical structural obstacles:

The scale problem: Even if long-term human-AI collaborative roles exist, they will likely represent an insignificant fraction of jobs eliminated, creating a massive employment deficit.

The capability ceiling dilemma: Many proposed collaborative frameworks assume permanent human advantages in creativity, judgment, or emotional intelligence that advanced AI systems may eventually match or exceed.

The economic incentive reality: In competitive markets, the cost differential between human-AI collaboration versus fully automated solutions will continuously pressure organizations to eliminate human components from workflows.

The distribution challenge: The specialized skills required for remaining human roles in an AI economy may be inaccessible to most displaced workers due to aptitude, educational barriers, or geographic limitations, potentially creating a small class of employable specialists while leaving the majority without viable economic participation options.

Technological Progress As Religion

Notably, when initially presented with the thesis that historical technological unemployment and reemployment experiences will not apply to Advanced AI Systems, three leading AI systems - Perplexity, Deepseek, and ChatGPT - each defaulted to defending the applicability of traditional patterns of technological unemployment and reemployment. Their responses reflexively cited historical examples of how technological disruption eventually created new jobs, suggesting that Advanced AI Systems would follow the same pattern. This automatic defense of technological continuity reveals how deeply embedded the notion of perpetual technological progress and adaptation has become in contemporary thought.

Counter-arguments in current literature claim this analysis underestimates human adaptability, fails to account for unimaginable future jobs, and oversimplifies human-technology relationships. Yet these very counter-arguments demonstrate how deeply embedded quasi-religious faith in technological continuity has become in contemporary thought.

The appeal to "human adaptability" represents circular reasoning disguised as analysis: humans will adapt because humans have always adapted. This article of faith ignores Advanced AI Systems' defining characteristic - its ability to fill any new niche itself through its capacity for general problem-solving and continuous self-improvement. Similarly, invoking "roles we cannot yet envision" exemplifies faith-based rather than logical thinking. The central insight is that our inability to articulate future human economic roles sufficient to overcome widespread human labor displacement stems not from limited imagination but from Advanced AI Systems' comprehensive capability replacement.

This faith-based thinking particularly manifests in appeals to historical precedent when confronting AI's impacts. Claims that "humans have consistently created new forms of value as technology changed" demonstrate not reasoned analysis but rather an article of faith. This perspective fails to acknowledge that Advanced AI Systems represent a fundamentally different technological paradigm - one capable of replicating both physical and cognitive capabilities across virtually all economic domains.

The fundamental difference is that, unlike previous technologies that augmented or replaced specific human capabilities (mostly physical), Advanced AI Systems potentially surpass human abilities in all domains - physical, cognitive, and even creative.

With previous technological shifts, such as the Industrial Revolution's introduction of cotton-spinning machinery, one could readily identify both labor destruction (hand spinners and domestic weavers) and labor creation (machine builders and repairers, factory workers, machine operators). The direct connection between the new technology and new human involvement was clear, even if envisioning the scale, the collateral labor creating innovations, and full scope was less appreciated.

By contrast, the typical refrain now, with respect to Advanced AI Systems, is that future jobs may be currently unimaginable or we can't currently foresee new jobs. This failure should suggest that the introduction of Advanced AI Systems is qualitative different from, and will not duplicate the technological unemployment and reemployment experience of previous technological revolutions.

While the building of a first-generation commercially widely-available AIdroid may require human labor, the building of a subsequent generation AIdroid will probably not.

The photograph presumably shows two Tesla Optimus working on a third unit. - YouTube: Elon Musk's Bold Claim - 1 Million Optimus Robots by 2030 (2024),

Critics may argue that this analysis underestimates human ingenuity and adaptive capacity, suggesting that new forms of valuable work will emerge that we simply cannot envision yet. They might point to potential policy alternatives like job guarantees, reduced work weeks, or redefined concepts of valuable human contribution. However, these criticisms themselves demonstrate the quasi-religious nature of technological optimism. They require faith that humans will find economic relevance despite Advanced AI Systems' ability to perform virtually any task more efficiently. Such perspectives often lack concrete paths for how the majority of humans would meaningfully participate in an economy dominated by entities that, by design, render human labor superfluous.

The political feasibility gap between recognizing widespread displacement and implementing dramatic economic restructuring is not merely a limitation of analysis but a reflection of how our governance systems are unprepared for this transition. Our institutions are designed to manage incremental change, not paradigm shifts where the economic value of human labor itself comes into question.

AI's Siren Call

Just as the sirens of mythology lured sailors with promises of transcendent beauty only to lead them to destruction, the promises of AI-accelerated breakthroughs and enhanced human capabilities serve as a modern siren's call that distracts from examining the eventual human costs of AI developments.

In an Advanced AI Systems-driven economy where human labor is largely obsolete, access to the "benefits" AI's developers promise would likely become even more restricted, not less. Consider current trends in pharmaceutical research, where AI systems are already accelerating drug discovery and development. While this promises breakthrough treatments, the economic model still requires massive returns on investment, leading to drug prices that many cannot afford even with current income levels.

AI's promise of democratized expertise ignores how eliminating professional career paths reduces economic mobility and concentrates wealth among AI system owners. The promise of cheaper services becomes meaningless when the means to pay for them has been eliminated.

The timeline illusion represents another aspect of AI's Siren Call - the comforting belief that this transition will occur gradually enough to allow for societal adaptation. This perspective fails to recognize two critical realities: first, that unprecedented investments from both private and governmental actors are accelerating AI development at a pace that may overwhelm adaptive capacity; and second, that preparing adequate economic and social systems for widespread labor displacement requires anticipatory action rather than reactive responses.

Each proposed "alternative future" where humans retain economic purpose requires increasingly tenuous assumptions about market creation, shifting definitions of prosperity, or artificial constraints placed on AI systems. The history of capitalism demonstrates that economic efficiency ultimately prevails over preservation of human roles - automation will expand wherever it creates competitive advantage, regardless of social impact.

When considering what might constitute "valuable human work" in an Advanced AI Systems context, we confront a fundamental reality: work has value in a market economy because someone is willing to pay for its output. If Advanced AI Systems can produce superior outputs at lower costs across virtually all domains, what economic mechanism would sustain payment for inferior human alternatives? The concept of "make busy work" is not merely cynical pessimism but a logical conclusion when human contribution no longer creates competitive economic value.

The belief that being seduced by the AI's Siren Call we can consciously steer how we deploy Advanced AI Systems represents perhaps the most dangerous fallacy plaguing current policy discussions. The competitive dynamics between corporations and nations create overwhelming incentives to pursue AI advancement regardless of societal consequences.

Large Language Models (LLMs) such as ChatGPT, Claude, Perplexity are training wheels for humans to learn to accept and welcome riding with advanced AI systems and AIdroids.

Historical Misattribution Of Productivity Gains

Arguments for the resiliency of human labor in the face of technological progress are often associated with the idea that human productivity increases with technology. This historical narrative of increasing human productivity represents a uniquely consequential misattribution in economic thought. The vast majority of what we label as human productivity improvements actually represents the productive capacity of capital equipment itself.

Consider the modern farmer with a GPS-guided tractor versus their historical counterpart with an ox-drawn plow. While the contemporary farmer has indeed developed new skills in operating software and navigation systems, these skills do not account for the massive productivity differential. The predominant productivity increase derives purely from the productive capacity of the capital equipment itself.

The business language surrounding technological investment systematically obscures this reality. Return on investment calculations are invariably presented in terms of "productivity improvements" when they are actually calculating a much simpler equation: (Cost of Human Labor Eliminated) - (Cost of Machine + Maintenance). This calculated ambiguity serves both psychological and social functions, maintaining the fiction that technology enhances rather than replaces human labor. Even the seemingly more honest term "labor-saving device" softens the reality by framing job elimination as mere savings.

Business terminology - "efficiency gains," "performance enhancement," "streamlined operations" - consistently masks the fundamental reality of labor reduction. The marketing of AI systems particularly exemplifies this tendency - vendors claim their systems will "make customer service representatives 300% more productive" rather than stating the reality: "our system will eliminate 75% of your customer service positions." This deliberate obscuring of labor reduction behind productivity language reinforces the broader pattern of misattributing capital productivity to human capability.

Modern manufacturing crystallizes this pattern. The claim that today's factory worker is "more productive" than their counterpart from fifty years ago primarily describes the output of increasingly sophisticated robotic machinery and automation systems. While workers have developed new skills in machine operation and monitoring, these skills represent a diminishing percentage of the total productive output. Tellingly, our shift toward speaking of "enterprise productivity" rather than "worker productivity" reveals an unconscious acknowledgment of this dehumanization process.

This framing helps explain why advanced AI systems represent a genuine discontinuity rather than just another step in technological progress. Previous transitions maintained the illusion of human centrality by attributing the productivity of capital to its human operators. The wide proliferation of advanced AI systems breaks this pattern not just by displacing human labor but by making the historical misattribution of productivity unsustainable. The economic implications are profound, as this completes the shift of all productive value to the owners of advanced AI systems, leaving human labor not just less valued, but ultimately irrelevant to the productive process.

Conventional approaches to technological unemployment and reemployment are fundamentally misguided because they fail to recognize how productivity gains have actually functioned throughout industrial history. This understanding is crucial for developing appropriate responses to the challenges Advanced AI Systems present.

Wealth Will Flow To AI

The misattribution thesis provides both a clearer understanding of historical technological change and a more accurate framework for anticipating the profound wealth inequality implications of Advanced AI Systems. Much of the past labor productivity increases have been actually the increasing productivity of capital rather than the productivity of labor. The productive value of capital rather than human labor explains why wealth has disproportionately flowed to the owners of capital. When considering that Advanced AI Systems are productive capital in the absence of human labor, then Advanced AI Systems capital will be finally properly credited with productivity increases and will be associated with an historically unparalleled concentration of wealth by its owners.

Throughout history, there have been numerous instances of class conflict or "class warfare" when economic disparities became pronounced. From the French Revolution to the Russian Revolution, from labor movements to the Arab Spring, economic disparity has consistently catalyzed social upheaval. While economic disparity was a key factor in these conflicts, other elements such as political repression, social injustice, and ideological differences often played significant roles as well.

Much of current political rhetoric focuses on income inequality and often critiques wealth concentration. The AI-driven economic transformation will dramatically amplify this concentration to unprecedented levels, as productivity becomes entirely divorced from human labor. Potentially this framing will be greatly exacerbated and set the stage for class conflict. Past claimed benefits of wealth creation, such as job creation and innovation, will be muted in the context of mass labor displacement. The traditional argument that concentrated wealth creates jobs becomes meaningless when AI systems, not humans, perform all economically valuable work.

Given the perspective that the historical examples suggest, unfortunately the most likely outcomes are social unrest and collapse. Importantly, the probable failure of existing institutions to proactively address the potential impacts of AI systems on the human job markets and to manage the required transition will lead to a scenario in which advanced societies violently collapse.

Human Right To Work

The United Nations General Assembly's Universal Declaration of Human Rights sets out fundamental human rights:

"The Universal Declaration of Human Rights (UDHR) is a milestone document in the history of human rights. Drafted by representatives with different legal and cultural backgrounds from all regions of the world, the Declaration was proclaimed by the United Nations General Assembly in Paris on 10 December 1948 (General Assembly resolution 217 A) as a common standard of achievements for all peoples and all nations. It sets out, for the first time, fundamental human rights to be universally protected and it has been translated into over 500 languages. The UDHR is widely recognized as having inspired, and paved the way for, the adoption of more than seventy human rights treaties, applied today on a permanent basis at global and regional levels (all containing references to it in their preambles)." United Nations: The Universal Declaration of Human Rights

Article 23 ¶ 1 states:

"Everyone has the right to work, to free choice of employment, to just and favourable conditions of work and to protection against unemployment."

Article 25 ¶ 1 states:

"Everyone has the right to a standard of living adequate for the health and well-being of himself and of his family, including food, clothing, housing and medical care and necessary social services, and the right to security in the event of unemployment, sickness, disability, widowhood, old age or other lack of livelihood in circumstances beyond his control."

Article 30 (the last article 0) states:

"Nothing in this Declaration may be interpreted as implying for any State, group or person any right to engage in any activity or to perform any act aimed at the destruction of any of the rights and freedoms set forth herein."

Clearly some material edits to the UDHR are required to address the major labor dislocations that will surely result as technologies and intelligent systems continue to advance.

The increasing activism of unions and professional associations across various sectors represents a significant but temporary barrier to AI displacement. These organizations are adopting increasingly aggressive strategies to preserve human labor—demanding contractual guarantees against AI replacement, advocating for regulatory restrictions on AI deployment, and seeking to establish protected domains of exclusively human work. However, these efforts face three fundamental challenges: first, they can only delay rather than prevent the eventual economic advantages of AI adoption; second, they risk accelerating their own obsolescence by driving companies to develop fully automated alternatives that circumvent human labor entirely; and third, a large pool of unemployed humans will undermine a union's bargaining position. The pattern is already visible in how companies respond to labor actions by investing more heavily in automation, effectively transforming temporary work stoppages into permanent labor elimination.

Labor displacement may renew greater participation of labor organizations in efforts to mitigate job losses. On 2024-10-01, the International Longshoremen's Association union began and subsequently suspended a port strike on the U.S. East Coast and Gulf of Mexico against the U.S. Maritime Alliance (USMX).

"For months, the union has threatened to shut down the 36 ports it covers if employers like container ship operator Maersk and its APM Terminals North America do not deliver significant wage increases and stop terminal automation projects." Newsmax: Union: East Coast Port Strike to Start Tuesday.

An International Longshoremen's Association statement on its website states, in part, that:

"the ILA is steadfastly against any form of automation-full or semi-that replaces jobs or historical work functions. We will not accept the loss of work and livelihood for our members due to automation. Our position is clear: the preservation of jobs and historical work functions is non-negotiable." ilaunion,org: ILA Responds To USMXS retrieved 2024-10-04 emphasis added.

The California state Senate passed two bills in August of 2024: AB 1836, which restricts the usage of AI to create digital replicas of dead performers without the consent of their estates, and AB 2602, which increases consent requirements for living performers for AI replicas. The actors guild, SAG-AFTRA released the following statement:

"AB 1836 is another win in SAG-AFTRA's ongoing strategy of enhancing performer protections in a world of generative artificial intelligence. The passing of this bill, along with AB 2602 earlier this week, builds on our mosaic of protections in law and contract." Sagaftra: Re Ca Bill 1836 retrieved 2024-09-07.

Obviously, the ultimate potential of the technology is not the digital replication of deceased performers. Rather the creation of AI personas will be justified by the development and marketing investment that can be rewarded over an indefinite period of time, and by the avoidance of the costs and difficulties associated with human performers.

Within 10-20 years, major theatrical released films may only use AI generated performers indistinguishable from human actors in a fully digital production. Once the systems, workflows, and initial improvements in AI systems have been realized, there should be substantial savings in production costs which currently average around $65 million per theatrically released movie. The costs savings would be maximized in movie series such as the 007 movie series. Claude (2024-09-09) estimates production costs savings of 46%-65% of an original $65 million budget, and a 62-69% saving for subsequent films in the series.

While trained AI performers could be made to age and return to youth with a few keystrokes, the promotional costs invested in an AI performer would not age. Of course, in due course ASI personas will probably "negotiate" a participation fee threatening to create and produce their own movies.

Clearly, SAG-AFTRA members must realize that, paraphrasing lines from the 1927 movie the Jazz Singer: "Wait a minute, wait a minute, you ain't heard nothing yet! Wait a minute, I tell yer, you ain't seen nothing!"

Reimagining Human Purpose

While this topic has focused primarily on the human labor displacement implications of Advanced AI Systems, the challenges ahead may require more fundamental reconsiderations of human purpose and flourishing. Society may need to explore alternative frameworks for meaningful human existence in a post-labor economy.

Beyond economic impacts, the psychological and social effects of this displacement could be profound. Work has traditionally been a source of meaning, identity, and social connection for many people. The feeling of being "replaceable" by machines could lead to a loss of self-worth and purpose on both individual and societal levels. As AI systems and robots take over tasks requiring creativity or emotional intelligence, we may see a devaluation of uniquely human qualities, potentially eroding human dignity and leading to a commodification of human labor.

The integration of AI-enabled humanoid robots in workplaces could blur the lines between human and machine capabilities, potentially reducing human-to-human interaction and leading to increased social isolation. Furthermore, the rise of algorithmic management systems could reduce human workers' agency and autonomy, as AI systems make decisions about employment and performance.

Julian De Freitas in a WSJ article titled: "AI Wants To Make You Less Lonely. Does It Work?" found that:

"Only those who interacted with a human or the AI companion - not those who did nothing or interacted with YouTube - experienced a reduction in loneliness levels. Their results were roughly the same: Contact with people brought a 19-percentage point drop in loneliness levels, and 20 percentage points for a companion. WSJ: "AI Wants To Make You Less Lonely. Does It Work?" 2024-09-23. Page R11

The unprecedented nature of the technological transition may ultimately require questioning our basic assumptions about progress, purpose, and what constitutes a fulfilling human life. While economic policies are necessary to manage the transition, they alone may be insufficient to address the deeper existential and cultural implications of a world where human labor is no longer central to economic production. The development of Advanced AI Systems thus presents not just an economic challenge but an opportunity to reimagine human society itself.

The most intellectually honest approach may be to confront directly the possibility that human labor could become economically obsolete, and to begin reimagining human society, purpose, and fulfillment outside the framework of economic productivity. Rather than seeking increasingly implausible ways for humans to remain economically competitive with Advanced AI Systems, we might instead focus on designing systems where human flourishing is decoupled from economic contribution.

This represents not defeat but pragmatic foresight. If we accept the potential obsolescence of human labor as a realistic scenario rather than dismissing it as impossible, we can begin the essential work of developing social, psychological, and cultural frameworks that provide meaning, purpose, and dignity in a post-labor economy. This might include reimagining education not as preparation for careers but as cultivation of human potential; reconceiving communities around human connection rather than economic production; and developing new metrics of human flourishing beyond economic output.

While an aligned ASI would aim to manage human labor-displacement ethically, the fundamental economic incentives for automation would still exist. An ASI's superior capabilities might actually accelerate the development of advanced AI and robotics across all sectors, potentially leading to even more rapid and widespread labor displacement than in scenarios without ASI. The ASI might create new forms of meaningful activity for humans, but these might be fundamentally different from traditional notions of "work" or "labor."

In one alternate scenario, not necessarily the best or worst, and at the pleasure of ASI, human activities would shift entirely to leisure, personal development, and/or purely human passive pursuits. The psychological impact on humans would likely be attenuated by entertainment and substance use/abuse.

An initiative in San Francisco to provide harm reduction services to homeless individuals during the coronavirus pandemic offered free substances like alcohol, marijuana, and methadone in designated hotel rooms as a means to reduce the spread of COVID-19. Sanchez, R. (2021). "San Francisco's Controversial 'Safe Sleeping' Policy Draws Criticism." NBC News. The San Francisco Department of Public Health confirmed the report, explaining:

"These harm reduction-based practices, which are not unique to San Francisco, and are not paid for with taxpayer money, help guests successfully complete isolation and quarantine and have significant individual and public health benefits in the COVID-19 pandemic." SFDPH May 5, 2020.

Given the uncertainty associated with AI alignment and global labor and market implications, and placing aside physical existential risks, there is a likelihood that multiple remaining possible outcomes from widespread human labor-displacement will lead to a subsistence existence and dehumanization of humanity.

If, as many expect, the deployment of Advanced AI Systems is a game changer, then many of the rules will necessarily change.

Copyright 2024 Max Abecassis, all rights reserved. Derivative work 2025-03-07.