Karla Ortiz built a career making art. Her name became a way to ask a machine to imitate it. In testimony before a Federal Trade Commission forum in 2023, the illustrator and concept artist said people had used her name thousands of times in image-generation prompts without her consent, credit, or payment (FTC, 2023). A reputation earned through work in film, publishing, and galleries had acquired a use she had never chosen (Ortiz, n.d.).
Ortiz’s career illustrates the movement of personal knowledge that I call knowmadic: a person develops a distinctive practice and brings it into different settings. Her testimony exposes a danger for that person. Recognition can make a body of work attractive to customers and to businesses selling automated substitutes. The artist’s account raises an economic question that extends beyond any particular dispute over training data: how much control does a person retain when others can sell imitations of the work through which that person earns a living?
Elon Musk offered a different prospect in his November 2023 conversation with Rishi Sunak: AI would make paid work optional, leaving people to work for personal satisfaction (Henshall, 2023). Such a future requires a way for people to live on the wealth machines produce. Greater output alone cannot provide it. A company can charge for tools that reduce the need for paid labor while the people losing that income must keep paying for access. The promise of freedom from work comes with no guarantee of freedom from its owners.
That gap between capability and control tests an idea I have spent much of my professional life developing. A knowmad creates value by bringing knowledge, imagination, and relationships into unfamiliar situations. Twenty years ago, I expected that greater capacity to contribute would give people more freedom to choose what they made. AI can extend the first capacity while leaving the second in the hands of employers and technology owners. The knowmad idea remains useful because people still need to imagine work worth doing and carry what they learn into places where that work can take root.
The terms of dependence
When AI lets an organization produce more with the same workforce, the organization can retain the savings, lower prices, expand production, or share the gains with workers. The tool settles none of those choices. Ownership and bargaining shape them, so a rise in productivity tells us little about whether the people doing the work gain time, income, or freedom to pursue an idea of their own.
The distribution problem enters a workday through decisions a person may have little ability to influence. A worker may help an organization produce more while receiving a wage set before the gain appeared. A creator may learn a platform’s tools and reach an audience there, then discover that leaving would mean rebuilding both. Competing services can improve the choices available, although moving files, clients, and working habits across them takes time that the person must bear.
Surveillance adds another form of control. Among respondents to the American Psychological Association’s (2024) U.S. workplace survey who knew their employer monitored them, 47% reported feeling micromanaged, compared with 23% of those who were not monitored or did not know whether they were. The survey establishes an association; it cannot determine whether monitoring caused those feelings. Some respondents saw benefits in monitoring, including protection of their safety. The tension concerns who interprets the record and decides how a person should work. An employer can ask for initiative while treating departures from an established routine as evidence of poor performance.
of workers who knew their employer monitored them said they felt micromanaged, compared with 23% of other workers surveyed.
Knowmads need independence and trust to apply their knowledge creatively in new contexts.
The concern for knowmads is what happens to the exercise of judgment under these conditions. Applying knowledge creatively in a new context involves deciding what carries over, what needs to change, and what the unfamiliar situation makes possible. The person may need to question a routine, consult someone outside an established team, or follow an idea whose value is still uncertain. If each departure must be justified against expectations formed before the exploration began, conformity can become the safer course. The potential contribution of personal knowledge is then constrained by what others already know to expect.
Knowmads therefore need a degree of independence in deciding how to pursue their work, together with relationships in which others trust them to exercise that judgment. Such trust develops through sharing knowledge, explaining decisions, and taking responsibility for consequences. It also requires colleagues, partners, and institutions to tolerate uncertainty while an idea is being tested. These conditions matter within organizations and across the collaborations through which knowmads work. Without them, calls for creativity ask people to take intellectual risks while making those risks difficult to bear.
Dependence can follow a person beyond work when a platform holds the tools, clients, and records through which that person maintains a livelihood. The cost of losing access can make an experiment seem reckless before anyone has tried it. When work and communication depend on systems whose decisions a person has little ability to challenge, formal freedom can coëxist with a narrow range of practical choices.
I use neo-serfdom to describe the danger of an economy in which owners control the means of earning a living while those who depend on them have few effective ways to leave or challenge their terms. The analogy concerns dependence; historical serfdom involved a legal status that a software subscription does not reproduce. Subscriptions can offer useful tools at affordable prices. The danger emerges when people invest their working lives in systems whose owners can make the cost of departure unaffordable. Their freedom to choose a purpose then rests on continued access to someone else’s infrastructure.
Such dependence could waste more than income. People equipped with extraordinary tools might spend their ingenuity securing continued access to them, rather than following the questions their knowledge has taught them to ask. The knowmad idea was born from a different possibility: someone learns something particular in one setting, recognizes its use in another, and makes work that neither setting had planned.
The worker I imagined, and the futures we can create
The knowmad began as an attempt to describe a future worker whose contribution would exceed a fixed job description. I traced its origins to my doctoral work more than 20 years ago in a 2024 retrospective; a public definition appeared in my 2008 essay, “Knowmads in Society 3.0” (Moravec, 2008, 2024). The central proposition was that a person’s knowledge could become more useful as it crossed the boundaries that institutions placed around work.
The early definition joined knowledge work to movement between settings and collaborators. In the 2008 essay, a coffee shop offered a modest illustration: people from different professions might find an idea in conversation that none had found within a workplace (Moravec, 2008). The point was the encounter between a person’s knowledge and an unfamiliar problem. Imagination mattered because the person had to see a possible use for what they knew, then learn enough about the new setting to try it.
The nomadic language has an obvious weakness. It can suggest an affluent person moving between cities with a laptop, free of obligations that keep other people in place. That image excludes forms of contribution central to the concept. A person can cross intellectual and organizational boundaries while remaining rooted in a neighborhood, caring for a relative, or working inside a public institution. Physical movement offers one opportunity for encountering difference; it provides no guarantee of judgment, generosity, or useful knowledge.
In 2012, I described knowmads as people who combine information with experience, apply knowledge in context, collaborate across organizations, use technology with purpose, share expertise, revise habits, and learn from failure (Moravec, 2012). Age played no part in the definition. The profile described capacities people could cultivate across a working life, with each unfamiliar setting offering a chance to reconsider what they knew.
That profile turns on the difference between information and personal knowledge. Information can describe a procedure; experience teaches a person where it breaks down, what an exception looks like, and whose account deserves attention. A knowmad carries that judgment into another setting while recognizing that local conditions may change its usefulness. The encounter works in both directions: experience helps the person see an unfamiliar problem, and the problem changes the experience they carry onward.
The 2013 book distinguished a job, the position someone holds, from work, the longer pursuit of outcomes that person considers meaningful (Moravec, 2013). That pursuit can continue through employment, apprenticeship, enterprise, and civic life. A person moving between short contracts may have little say over its direction, while a person rooted in one place may carry a question across disciplines and years. For the knowmad, movement follows the work; changing jobs or cities has no value of its own.
Each person accumulates a particular combination of practice, relationships, mistakes, and local understanding. That combination can make an innovation possible when its bearer sees a use that specialists in a new setting have missed. Yet curiosity needs time, and experiments can fail. The knowmad profile loses its meaning if it praises initiative without asking who can afford to follow an uncertain lead.
The early work acknowledged barriers to participation, including access to pooled health insurance (Moravec, 2012). In Knowmad Society, the 2013 collection I edited, contributors explored what education, work, and relationships might become when people could use knowledge across institutional boundaries (Moravec, 2013). The book widened the question from the attributes of a worker to the kind of society those attributes could help create. My optimism placed too much weight on growing capability as a route to autonomy. The intervening years have made the gap between them harder to overlook.
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The book’s social ambition still holds. A learner needs room to pursue a problem; colleagues need ways to share knowledge across boundaries; an organization must decide whether someone can act on what they discover. Those everyday choices shape whose knowledge enters public life. They also determine whether a capable person can keep developing work after an institution decides it has no use for the idea.
A knowmad can contribute within a conventional organization, build an independent practice, or join others in a project. Each arrangement can support invention or constrain it. The distinction lies in whether people can develop a purpose and act on their judgment, including when that judgment points beyond the work an employer has assigned. Adaptability becomes a thin promise if it means learning whatever system an owner introduces while abandoning every question that owner declines to pursue.
Personal knowledge travels with friction. In the United States, an employer is the initial copyright owner of work an employee creates within the scope of employment unless a signed agreement provides otherwise (U.S. Copyright Office, 2024). Copyright excludes underlying ideas and methods, although contracts and confidentiality obligations can impose separate constraints (U.S. Copyright Office, n.d.). A worker may retain judgment gained through experience while lacking the right to carry code, records, or a finished workflow. Applying that judgment elsewhere can require new materials, new tools, and time to build again. The person’s capacity survives the boundary; the means of exercising it may have to be reconstructed.
The knowmad’s question is “What do I want to bring into the world?” An answer might be a service, a body of knowledge, a different way to earn a living, or a form of public life. The question gives imagination a direction, but other people and real constraints give the work its shape. A person may pursue it inside an organization and carry it elsewhere if that setting leaves no room for the idea.
When many people can pursue such work, their projects begin to change the society around them. Some work alone; others find colleagues whose knowledge changes the project. Schools, workplaces, and civic life can give people room to try both. Knowmad society names the result: more people able to bring distinctive knowledge into a new setting, make something useful there, and benefit from what they create.
This makes knowmad society a social ambition with a material test: whether people can pursue work whose value they recognize before an employer or investor recognizes it. A distinctive combination of skills has little room to develop if every hour must earn an immediate return. The capacity to imagine a future and the means to attempt it have to meet in a person’s life.
Judgment after the answer arrives
AI can help someone cross a knowledge boundary. In a study of 5,172 customer-support agents at one software company, Brynjolfsson et al. (2025) estimated that access to an AI assistant increased issues resolved per hour by an average of 15%, with larger gains among less experienced and lower-performing agents. The researchers also found evidence of learning among workers using the assistant. These findings suggest that AI can help people develop expertise through work. Whether that capability brings greater influence over the purpose and terms of the work remains a separate question.
As tools make answers easier to produce, choosing a problem becomes a greater part of the work. People need to learn whose experience an answer leaves out and what evidence would change their course. AI can help gather and compare information; its speed can also carry a mistaken idea further before anyone tests it against the lives it will affect.
Safecast offers an observed example of people applying knowledge across boundaries to a purpose they chose. After the Fukushima nuclear disaster began in March 2011, volunteers formed a network to collect and publish radiation measurements when dependable local information was scarce. They combined sensor design, field measurement, mapping, and public communication; the data and methods became available for others to use (Brown et al., 2016; Safecast, n.d.). The group created a source of knowledge that people could examine alongside official accounts. People still had to interpret a reading in its context and decide how to respond. That distinction between producing information and making a judgment runs through knowmadic work.
Heiwa Kataoka encountered Safecast through his family’s church and community work in Fukushima. He borrowed his brother’s sensor to measure radiation around home, then built his own at a workshop in 2013. He also mapped churches and church-run schools in relation to nuclear facilities, hoping to extend monitoring through those connections (Prosser, 2018). His knowledge of a community gave a technical tool a purpose.
In the same interview, Kataoka recalled finding a radiation hotspot at a slide in his church’s nursery-school playground; the slide was removed (Prosser, 2018). The account connects measurement to a decision about a place people knew and used. A sensor supplied a reading. Someone had to recognize its significance, bring it to others, and act on the consequences.
Kataoka’s example gives the knowmad idea a human scale. Knowledge acquired through one project entered a life with existing concerns and relationships. The resulting work arose from that combination. A machine’s ability to supply answers increases the importance of people who can recognize a question that deserves attention and take responsibility for what follows.
Building futures alongside the present
The knowmad’s question, “What do I want to bring into the world?”, changes the relationship between learning and the future. A forecast describes conditions a person may face. A purpose gives that person a reason to intervene. Learning then develops through the attempt: a first version exposes a mistaken assumption, a collaborator contributes an unfamiliar method, and the people affected identify a consequence the originator missed.
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In Build a Positive Rebellion: Create New Education Futures, I bring this concern into education, examining how people can question the conditions of learning and create alternatives they have a part in shaping (Moravec, 2026). The book develops the practical question that follows Knowmad Society: how people begin to change conditions they have learned to regard as fixed. Education matters here because a learner who has experience choosing a question, testing a response, and revising it with others has practiced making a future that was not assigned in advance.
That practice can begin within an institution or alongside it. A teacher can develop an approach with colleagues; a designer can find an application for a technique outside the industry that taught it; a person with years of caring experience can recognize a failure that a service’s designers have missed. These are possible paths, each drawing on a combination of knowledge that belongs to a particular person. Their value emerges through contact with the people and circumstances the work must serve.
Attending to knowmads begins with recognizing the value of that knowledge. Someone may need time to investigate an observation before they can explain its value in the language an organization uses. Another may need a collaborator who sees why a familiar method fails in an unfamiliar setting. An institution’s response can determine whether the idea develops within it or whether its bearer seeks another place to work. A knowmad society leaves room for both outcomes, including work that its established organizations would never have commissioned.
For people supporting households, this freedom has a cost. An experiment may begin with paid work continuing alongside it, using materials its maker has the right to use and tools within reach. Customers, colleagues, or institutions may support its development. Other ideas require equipment or paid time before they can produce income. A society that makes invention depend on spare hours will lose contributions from people whose obligations consume those hours.
Safecast demonstrates what people can initiate; its example offers no assurance that volunteer labor can sustain every service people need. Maintenance, repair, and continuity require resources. The same is true of a small business or a project within a large employer. Once others rely on an invention, attending to its makers includes recognizing the labor required to keep it useful and the limits of what they can contribute without pay.
These conditions make personal agency a shared concern. A person needs enough security to risk an unsuccessful attempt, access to knowledge and tools, and relationships through which work can develop. People will pursue different arrangements for meeting those needs. The common ambition is a society in which a wider range of people can act on what they know, with a fair chance to benefit from what they create.
The futures people bring into being
Beyond 2030, machines may take on a greater share of tasks associated with expertise. If that process narrows people’s opportunities to practice, they may lose occasions to develop the judgment on which new work depends. An apprentice learns through making decisions and encountering their consequences. A future in which people receive finished outputs without those encounters could expand access to information while eroding the experience needed to question it.
A knowmad society would treat the development of personal knowledge as part of its future productive capacity. Schools would give learners sustained experience investigating questions whose answers remain open. Workplaces would make room for people to learn across roles and pursue observations that fall outside a current brief. Independent practitioners would have opportunities to develop work beyond an employer’s priorities. Each setting would contribute something different to the range of futures people could attempt.
People would still make poor judgments, exhaust resources, and disagree over whose purposes deserve support. Distinctive knowledge can serve exploitation as well as care, so knowmadic capacity carries responsibility for its effects. The people touched by an experiment have knowledge of their own. Their ability to question and change it is part of what allows an individual ambition to become work with public value.
The alternative to neo-serfdom begins with people retaining the ability to choose a purpose, develop their knowledge, and carry it into work they have reason to value. That freedom needs material support, and its exercise can create possibilities that no owner has commissioned. The two prospects in this essay can coëxist: extraordinary tools can deepen dependence while people use them to build alternatives. The direction depends on whose purposes the work comes to serve.
Ortiz’s name acquired value because she developed a practice that people recognized. A society organized around extracting the traces of such work risks consuming the conditions that made it possible. A knowmad society would invest in people’s capacity to develop work whose form and value we cannot specify in advance. Its future would take shape through what they choose to bring into the world.
References
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