DecafQuest

Taking philosophy back to the marketplace

Ontologically Different: AI, Work, and What It Means to Be Human

October 11, 2026 · Mahmoud Rasmi

Contents

This reflection is based on the monthly Tech Leaders Salon discussion, where we discuss books on topics including philosophy, strategy, management, and leadership. The salon is co-hosted with Laksh Raghavan as part of his Cyb3rsyn Community. If you’re interested in joining the conversation, you can learn more about the discussion group here. In September, we discussed Daniel Susskind’s A World Without Work.

From Past Disruptions to the AI Era

What does a world without work look like, and how ought we to deal with it at a policy and governance level? These are some of the questions Daniel Susskind’s A World Without Work addresses. Susskind surveys the impact of technological innovation and task automation on human employment, drawing an important distinction between past technological disruptions and current AI-driven ones.

Technological advancements are usually met with mixed reactions, ranging from extreme advocates and early adopters to an opposing pole of skeptics and opponents. Underlying this spectrum are justifiable arguments about how technology improves our lives and drives economic growth on the one hand, and concerns over how the changing landscape could lead to job loss, impacting the livelihoods of many people by rendering their craft or profession obsolete or redundant on the other.

Susskind argues that in the past, the social and existential anxieties triggered by automation proved to be unfounded because machines augmented human labor, increased production at scale, and almost always created new jobs. His main argument is that this pattern doesn’t quite hold in the AI era because technology will slowly take on not only routine tasks, but also non-routine tasks, complex activities, and cognitive work.

Due to the paradigmatic shift in AI development, we seem to have managed to develop machines and systems that mimic human reasoning, relying on big data to carry out tasks like driving, medical diagnosis, legal analysis, writing, mathematical and data analysis, software development, and more.

The more complex and sophisticated this technology becomes, which seems to work without relying on human-like consciousness, the more task encroachment spans manual, cognitive, and affective domains, leading to human displacement. As a result, there exists a possibility that with AI, more people will find themselves without work.

Automation in the age of labor always led to more growth and an increase in the size of the “economic pie,” with these gains being redistributed in society as more jobs were created, new skills were in demand, wages increased in certain sectors, and so on.

Susskind argues that although AI will continue to expand the size of the economic pie, solving the problem of production, it will break the link between economic growth and job creation. It will slowly replace humans without creating jobs at the same rate as before. As a result, capital will be concentrated among the few AI labs that own the means of production. A minority would also partake in this economic pie because they have the relevant skills required to keep things working, but the great majority would find themselves without work due to the absence of demand.

Society will be confronted with three major problems: inequality of wealth distribution, the concentration of power, and a lack of purpose and meaning due to job loss. Susskind writes:

Technological unemployment, in a strange way, will be a symptom of that success. In the twenty-first century, technological progress will solve one problem, the question of how to make the pie large enough for everyone to live on. But, as we have seen, it will replace it with three others: the problems of inequality, power, and purpose.

Technological progress brings prosperity, but AI will cause three problems that we have to deal with. Susskind dedicates the third part of the book to examining these problems and suggesting potential solutions that require coordinated action from policymakers, governmental and private institutions, and society as a whole.

Education, Wealth, and the Big State

In the short term, the best way to tackle these problems is by rethinking our educational system, changing what and how we teach to adapt it to the demands of AI. This includes offering an interdisciplinary curriculum aiming to cultivate both technical and soft skills to equip people with the abilities needed to thrive in routine and non-routine jobs. The concept and aim of education ought to change too, from merely a stage we go through early in our lives to acquire knowledge and skills to a lifelong learning process where we continuously alternate between periods of learning and work to adapt to changing market demands and the latest technology.

Revamping education merely offers a short-term antidote. In the long run, when work grows scarce and technological unemployment turns more structural, inherent to the new AI world, it yields a society without work. In such a world, Susskind argues that societies must aim to construct a Big State that shares asset ownership with private corporations (some sort of citizens’ wealth fund) and taxes high earners and corporate profits, redistributing the income via a Conditional Universal Basic Income scheme. The scheme would require citizens to engage in community and meaningful work, contributing to the overall well-being of society, especially since paid labor would have largely receded.

To counter the high concentration of power among big tech companies, instead of nationalization, Susskind calls for the creation of a new agency that would develop a framework to help regulators identify when power is being misused by these firms. The new body would include a host of political theorists, philosophers, lawyers, and subject-matter experts auditing AI-related transparency issues, big tech political influence, algorithmic bias, and other emergent alignment-related problems.

To address the loss of meaning and purpose in a status-driven world that has come to equate success with grit, hard work, and income level, the government would have to introduce deliberate leisure policies to incentivize people to explore their curiosities. This would shift their focus from paid employment to contributions toward the common good, like volunteer work, caregiving, and charity, and to more personal leisure activities for their subjective pleasure and self-fulfillment. In cases where some people might still aim to pursue a more disciplined routine, the government would also create state-supported programs to help them find a more fulfilling role.

The adequacy of Susskind’s policy recommendations and solutions is highly debatable for many reasons, the most notable of which is the uncertainty underlying the future of an AI-driven world. The argument that the AI revolution is unlike previous tech disruptions has some merit.

We might be able to forecast which jobs may be directly affected by AI, but it is quite difficult to foresee in what way the technology will change the job landscape, political and legal systems, and social values.

Despite this, positing the scenario of a world without work, even if only hypothetical, is still well worth the exploration. By thinking and having conversations about the potential problems arising from such transformative technology, we can imagine various creative solutions and strategies to potentially navigate uncharted territory and prepare for the worst-case scenario.

Some people do that by letting their imagination run wild through sci-fi fiction, exploring different ideas, like a world without work, and their potential impact on society. Others may do that by offering a more serious philosophical, economic, political, or social analysis. Both approaches are needed not only to help us prepare for an uncertain future, but also to leverage technology to innovate and build a better world for ourselves and future generations.

A Tale of Two Worldviews

There is a caveat, though, one that has become a recurring theme the more I read about AI, whether in general analysis, technical overviews, fiction, or non-fiction books. The deeper I dig into this world, the more confused I become about its implications and what it means for us. The only thing I can be certain about now, in the spirit of Heidegger’s essay on technology, is that new technology often changes the way we perceive and interact with the world.

The possibilities are endless. I do agree with Susskind that AI poses challenges different from past technological revolutions, simply because the discussions around the technology and the underlying perspectives are multifaceted and span different dimensions. As Susskind points out, the debates have shifted from how we can improve production and make our lives easier to broader questions about the possibility that AI can become conscious, perform non-routine tasks, develop affective skills, and make sound judgments.

The answers to such questions and our confidence in how correct these answers are, I think, depend by and large on our beliefs, values, and foundational worldview. For AI labs and venture capitalists, the stakes are high. They want to find a business model that works and brings a decent return on investment. Many AI labs have been burning cash for years without a clear path to profit. Until that changes, they will lean into all forms of marketing and sales hype to increase their market share and survive brutal competition. We are already witnessing some examples of this as some AI companies are invoking existential risk arguments in hopes of slowing down the cash burn, or attempting to secure more regulation and public-sector partnerships.

Outside the commercial realm, debates are centered around questions of value, ethics, transparency, and what it means to be human in an AI world. Will and should AI take our jobs? Can AI create art in the same way humans do? Should AI models and agents be given legal personhood status? Are AI models and what they do fundamentally different from human beings and what they produce?

As I mentioned earlier, I think the answers to these questions are based on and downstream from our values, worldview, and assumptions about the world that we assume are self-evident. Any discussion about AI without clarifying what our assumptions are will only cause more confusion and lead to a dead end. I will give an example that generalizes a bit without taking into consideration any nuances, just for the sake of illustration.

It seems that there are two major different approaches surrounding the AI debate, both ontologically distinct. In other words, both worldviews have different assumptions about what the world is like. On the one hand, there is the engineering worldview. It tends to perceive and understand the universe as a big machine, a stance known as technomorphism.

The more advanced the technology, the more these technological understandings and terms are projected onto the world. At the same time, the projection runs the other way too: the more sophisticated the machines, the more anthropomorphized they become. We talk about the computational universe, neural networks, the software of the brain, opinion dynamics that study human beliefs as though they were fundamental particles, etc.

The main assumption of the engineering worldview is that there is no qualitative difference between technology and humans. They are merely governed by forms, systems, and processes that can be simulated and mimicked, with the results being of equal nature. If we can simulate brain processes and structures, we can simulate consciousness. If we can crack the human creativity code and algorithm, we can produce art at the level of Shakespeare and company.

On the other side of the river is, for the sake of simplicity, the humanistic camp. It assumes that humans are qualitatively different from machines; this view can be based on a religious worldview or a more secular perspective, like that of Kant among others, asserting that humans have an inherent moral worth and dignity, and should be treated accordingly as ends in themselves rather than means to an end.

Since humans are qualitatively different, human imagination, art, literature, creativity, and thought are fundamentally different from those of machines. The latter may be able to mimic and simulate human reasoning and creativity, but they produce just that: a copy that exhibits the same format but is radically, or ontologically, different from human creation.

Whether you find yourself agreeing with one camp or the other is beside the point. Things are fuzzier than this binary distinction, too. But much of the heated debate and disagreement taking place on social media, in the news, and between AI labs, philosophers, policymakers, and politicians is often due to the difference in the assumptions underlying their arguments and conclusions.

These assumptions influence the measures and policy recommendations being presented. If you believe that humans have nothing special about them, and that AI can develop cognitive capacities, then you might think we should pursue a transhumanist agenda, fusing humans with machines as the next logical step in the evolutionary process, accelerating growth, eradicating disease, and abolishing poverty.

If you believe that humans are special and qualitatively different from machines, then you would favor a more prudent approach to technology, ensuring that progress safeguards human moral dignity, values, judgment, and creativity, and that people have the conditions to pursue a purposeful life, especially in a world without work.

Examining Our Assumptions

To address the question of a world without work, therefore, I think it is also important to examine our assumptions about the world, what our values are, what we think it means to be human, and what living a good life looks like for us. In order to do that, at a personal level, I think that there is always going to be value in reading philosophy, fiction, and books that help us think about, examine, and discuss these questions from different perspectives.

The question remains: in a world without work, how will we make ends meet? I have no idea. But maybe instead of a conditional universal income, we need to imagine a new economic system of sorts. In the short run, though, as Susskind suggests, we would be better off if we cultivate our sense of curiosity, build a habit of continuous learning and adaptation, all the while reflecting on our worldview, values, and philosophy. I think this reflective activity will be essential moving forward, to ground and not lose ourselves in a sea of noise and fads in the face of an increasingly accelerated world.

If we could really tell what the future will look like, things would have been much easier, perhaps, or much worse; I am not sure. On that note, I can only recommend a few more books and essays to reflect on and explore these issues further: