AI and the American Future: Toward a Thriving Social Contract
A Public Learning Project of The People’s Commission on Technology and the American Future
An Editor’s Note from Moonshot Press
Moonshot Press is a human-led, AI-augmented publication. This article was written and edited by Shimon Waldfogel, MD, with artificial intelligence used to support research, questioning, synthesis, and editorial development. Shimon retains responsibility for the final judgments and published text.
AI collaborators used in developing this article: [list only the models actually used].
Coauthors with ChatGPT 5.6 Sol, Claude Opus 5
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Imagine a billing specialist in a mid-sized healthcare company. For fifteen years, she has known the intricate rules that determine what insurers will pay, how to correct an error before it becomes a denial, and how to help a patient understand a bill that makes no sense to them.
Her work is not glamorous. Much of it is repetitive. Some of it is frustrating. But she is good at it. People come to her when a problem seems impossible. Her job gives shape to her week, a group of colleagues who know her name, a reason to leave the house, money to help support her family, and the quiet satisfaction of being useful to people who need help.
Then the company installs an AI system that can process most claims, identify likely errors, and generate patient explanations in seconds.
At first, the change feels like relief. The system takes over tedious tasks. It reduces backlogs. It may even spare patients some of the confusion and delay that made the old system so difficult.
But after several months, the company decides it needs fewer specialists. The remaining workers are assigned to supervise the system, manage exceptions, and meet higher productivity targets. The work becomes less predictable. Her judgment matters less. Her role narrows. She begins to wonder whether the competence she spent years developing still has a place.
Nothing in this story requires us to be against technology. The new system may genuinely improve care. It may reduce costs. It may free some workers to focus on the human problems machines cannot resolve.
But it raises a question that lies beneath almost every public argument about artificial intelligence:
If a machine can do part of a person’s job, what exactly is at risk—and what, if anything, has been gained?
That question is larger than employment statistics. It is larger than whether a particular company hires or lays off workers this year. It reaches into how people understand their place in the world, how communities remain connected, and what democratic society owes its members when the conditions of work change.
Before we can decide what AI should do, we need to ask what work has been doing for us.
More than a paycheck
For most adults, paid employment has been the institution through which many essential goods are bundled together.
A job provides income. That is obvious, and it is indispensable. Income determines whether people can afford housing, food, healthcare, childcare, transportation, and the ordinary security required to plan a life.
But work has often provided much more.
It gives the day a shape. It creates routines and expectations. It asks people to develop skill, exercise judgment, solve problems, cooperate with others, and become reliable in the eyes of colleagues and customers. It can connect effort to result: I learned something difficult; I did it well; someone depended on me; my work made a difference.
Work can also confer standing. When people meet, one of the first questions they often ask is, “What do you do?” The question may be clumsy, but it reflects a deep habit of social life. Occupation has become one way people explain who they are, what they know, and how they contribute.
That arrangement has never been fair or complete. Many jobs are monotonous, unsafe, poorly paid, or degrading. Many forms of vital work—raising children, caring for elders, maintaining a household, volunteering, organizing a neighborhood, supporting a friend through illness—are unpaid or underrecognized. Many people have been excluded from stable, dignified employment by discrimination, disability, immigration status, geography, or the simple accident of being born into a community with too little opportunity.
Still, for millions of Americans, paid work has been the principal place where income, identity, structure, relationships, and contribution come together.
When that bundle breaks apart, a person can lose much more than a wage.
Work, employment, contribution, and human worth
The distinction among these terms matters.
Human worth is not earned through a job. A person who is unemployed, disabled, retired, caring for family, studying, grieving, or unable to work has no less dignity than a person with a prestigious title or a high salary.
Work is broader than paid employment. It includes care, service, learning, craft, creative effort, civic responsibility, and the daily labor of sustaining other people and communities.
Employment is a particular arrangement: an institution that exchanges labor for income and, at its best, also supplies relationships, recognition, benefits, structure, and a path of development.
Contribution is the experience of being needed by others. It is the sense that something one does matters beyond oneself.
A healthy society should not make a person’s right to dignity depend on whether an employer needs them. But neither should it dismiss the real losses people experience when work disappears or becomes hollowed out.
The public conversation sometimes offers a false choice. Either we preserve every existing job, or we accept that technology will make many jobs unnecessary and assume people will be fine if they receive an income.
Neither answer is adequate.
Some jobs should change. Work that is dangerous, degrading, or needlessly tedious should not be preserved simply because it is familiar. If AI can reduce paperwork that keeps nurses from patients, lessen repetitive administrative work, make a small business more viable, or help a teacher adapt instruction to a child’s needs, those are gains worth welcoming.
But income alone cannot automatically replace everything a job provided. A monthly payment may help a family survive. It does not by itself create a community of practice, a sense of mastery, a reason to get up in the morning, or confidence that one has something valued to offer.
The question is not whether every old job must remain. The question is whether people will retain meaningful ways to belong, contribute, learn, care, and exercise agency in the world around them.
The conditions of coherence
The medical sociologist Aaron Antonovsky devoted his work to a deceptively simple question: not only what makes people ill, but what helps them remain healthy under conditions of stress.
His answer centered on what he called a Sense of Coherence. People are more resilient when life is experienced as:
Comprehensible — The world makes enough sense that I can understand what is happening and why.
Manageable — I have, or can gain access to, the resources needed to meet life’s demands.
Meaningful — My effort is worth making; I have reason to invest myself in the challenges before me.
These are not luxuries. They are conditions that help people navigate uncertainty without becoming overwhelmed by it.
Good work can support all three.
A worker whose effort leads to visible results may experience the world as more comprehensible. A job can provide wages, training, colleagues, credentials, and routines that make life more manageable. A person whose skills help others may experience meaningfulness: I am capable. I am useful. My contribution matters.
But work can also undermine coherence. A job that is insecure, arbitrary, dangerous, humiliating, or impossible to understand does not necessarily create health. Neither does a workplace that treats people only as costs to be reduced or data points to be managed.
This is why the future of work cannot be judged simply by counting how many jobs exist. We need to ask what kinds of work are being created, transformed, or eliminated—and what happens to the people whose lives were organized around them.
AI: liberation, disruption, or both?
Artificial intelligence is not one thing, and its effects will not be one thing.
In one workplace, AI may reduce drudgery. A physician may spend less time documenting a visit and more time listening to a patient. A public-interest lawyer may analyze a large body of records more quickly and devote more attention to strategy and human judgment. A small business owner may use AI to translate materials, draft a marketing plan, organize accounts, or provide better customer service without hiring a large back-office staff.
In these cases, AI can operate as a tool of augmentation. It may increase people’s capacity to do work they consider more skilled, more relational, or more meaningful.
In another workplace, the same technology may remove entry-level roles, concentrate authority in fewer hands, weaken a worker’s discretion, intensify surveillance, or turn a skilled occupation into a narrow task of monitoring a system someone else designed. In those cases, AI may reduce costs and increase output while diminishing people’s ability to exercise judgment, build mastery, or see themselves as contributors.
The difference is not merely technical. It is organizational and political.
Who decides how the technology is introduced? Do workers have a voice? Are productivity gains shared? Does automation remove a burden while preserving the worker’s role, or does it remove the worker’s role while preserving the burden for someone else? Are people given time, training, security, and real choices—or simply told to adapt?
No one can yet answer these questions for every occupation. Predictions about the future of work vary widely. Some analysts expect AI to create new categories of work and raise productivity across the economy. Others expect rapid displacement, particularly in administrative, clerical, and professional roles once considered protected from automation. Both possibilities deserve serious attention.
What is clear is that the outcome will not be determined by AI alone.
What an adequate transition must protect
The familiar response to technological disruption is often one word: retraining.
Learning matters. People should have repeated opportunities to acquire new knowledge, new tools, and new forms of competence throughout life. A society facing rapid technological change cannot rely on a single credential earned in youth to sustain a career for decades.
But retraining is not a complete answer.
It assumes that new jobs will exist in sufficient number, that people can afford the period of transition, that training will lead to genuine opportunity, and that a person’s needs can be reduced to acquiring another marketable skill. Sometimes those assumptions will be true. Sometimes they will not.
A more adequate response must ask at least six questions.
Will people have economic security?
Can they pay bills, care for their families, maintain housing, and weather a transition without catastrophe?
Will people have access to learning and adaptation?
Can they gain useful skills, understand changing technology, and move into work or contribution that is genuinely available?
Will people retain voice and dignity at work?
Are workers consulted when AI changes their roles? Can they question unfair systems? Do they share in the gains their experience and labor help make possible?
Will communities remain capable of supporting one another?
When a local employer changes, contracts, or disappears, are there institutions—schools, libraries, community colleges, unions, faith communities, health systems, civic associations, local governments—ready to help people navigate the change?
Will people have meaningful ways to contribute?
If traditional employment becomes less stable or less central, what institutions will recognize caregiving, service, mentorship, creation, civic work, and other forms of needed contribution?
Will citizens remain able to participate in self-government?
Economic insecurity narrows the time, attention, confidence, and social connection people need to participate in public life. A democratic society cannot afford an economy that leaves large numbers of citizens too precarious, exhausted, or isolated to exercise their voice.
These questions do not yet tell us what policy to adopt. They tell us what a serious policy must be capable of seeing.
An open question for citizens
There is a genuine disagreement here.
One view holds that the best response to AI is to embrace innovation, allow old roles to change, and focus on creating new opportunity. History offers reasons for this optimism. Previous technological transformations disrupted lives but also produced new industries, new professions, greater productivity, and improvements in material well-being.
Another view holds that the current transition may move too quickly, concentrate too much power, and reach too deeply into cognitive and professional work for existing institutions to absorb it. History also offers reasons for this concern. Technological gains have often been distributed unevenly, and communities have frequently borne the costs long before they received any benefits.
Both views contain truths.
The task of democratic citizenship is not to choose between optimism and fear. It is to refuse the false comfort of either one.
We should welcome technologies that expand human capability, reduce needless suffering, and make more room for care, creativity, learning, and contribution. We should also insist that no person be treated as disposable because a machine can perform some of the tasks they once performed.
The question is not whether the future will contain less work, more work, different work, or new forms of contribution we cannot yet imagine.
The question is whether we will build a society in which people remain secure, capable, connected, and needed.
When technology changes the role of human labor, what do we owe one another—not merely so people can survive, but so they can continue to belong, contribute, and flourish?
The next chapter turns to the technology itself: what artificial intelligence can actually do, what it cannot do, and why understanding that difference is essential to shaping the future wisely.
Discussion questions
Which functions of work—income, structure, mastery, belonging, contribution, or civic capacity—are most difficult to replace when a job disappears?
When AI removes repetitive or burdensome tasks, what should employers and workers do to make sure the gain becomes more meaningful human work rather than simply fewer human workers?
If paid employment becomes less stable or less central to adult life, what new institutions might help people experience dignity, security, and the sense of being needed?
Selected foundations for further reading
Aaron Antonovsky, Unraveling the Mystery of Health; Hannah Arendt, The Human Condition; Adam Smith, The Theory of Moral Sentiments and The Wealth of Nations; David Autor, “Work of the Past, Work of the Future”; Daron Acemoglu and Simon Johnson, Power and Progress.