Our technology is evolving. Will our relationships?

Jensen Huang is helping build the technology that will transform human life. His recent admission of infidelity also shows how familiar our relationship conflicts remain.

On November 8, 2026, Huang publicly acknowledged being unfaithful to his wife. The admission followed reporting about his relationship with Alice Huang, a businesswoman suspected by U.S. authorities of working for Chinese intelligence. On November 11, The New York Times reported a second alleged affair, with Kimberly Powell, Nvidia’s vice president of healthcare, who reported directly to him.

Huang and his wife, Lori, first met as engineering lab partners at Oregon State University and have been married since 1985. Their relationship began long before Nvidia became central to the AI economy. By November 12, Reuters reported that Nvidia’s board was weighing his future. A crisis involving his private life had become a corporate leadership crisis with consequences across financial markets.

The intelligence allegations and the reported relationship with a direct report raise separate questions about national security, workplace power, and corporate responsibility. The relationship conflict underneath the story is also part of a much older pattern.

Humans have experienced infidelity for centuries. Shame, punishment, and the possibility of losing everything have never eliminated it. A 2025 YouGov survey of 1,125 U.S. adult citizens found that 53 percent said they had been cheated on and 33 percent said they had cheated on someone. These are self-reported experiences, but their scale makes betrayal difficult to dismiss as an exceptional failure.

One recurring problem is that people suppress desires they are afraid to share. Acknowledging attraction to someone else can be treated as evidence that an existing relationship has already failed. When the conversation itself becomes threatening, secrecy gains another advantage.

Huang was responsible for his choices. His wife was entitled to honesty. Their private conversations are not public knowledge, and no outsider can prescribe the relationship they should have had. The cultural question is why so many people find it easier to conceal desire than discuss it.

Couples should have room to consider exclusivity, swinging, a third person, group play, polyamory, or another arrangement everyone freely wants. Those possibilities give people a language for understanding their desires before they become a hidden life.

More capable AI will expand the opportunity to have those conversations and act on their answers. Porn made fantasy abundant. Dating apps lowered the cost of finding people. Birth control separated sex from reproduction more reliably. PrEP changed the HIV risk calculation. Intelligent systems will extend that transformation through medicine, matchmaking, artificial intimacy, and the time people have available to spend with one another.

My forecast is that play parties and social clubs will become more common, alongside greater openness to different relationship dynamics. As the practical barriers fall, a more open culture will let people explore honestly and bring more of themselves into the relationships they value.

Sex Has Never Been Only Sex

Sex is shaped by biology, identity, attachment, status, reproduction, religion, economics, and power. Change the surrounding system and sexual culture changes with it.

Dating apps separated meeting from geography. Social media turned attraction into a visible market. Greater economic independence allowed more people to leave relationships that no longer worked. Advances in AI will affect several of these forces at once.

I’m using AGI in the broad sense described in the OpenAI Charter: highly autonomous systems that outperform humans at most economically valuable work. Systems with that capability will accelerate medicine, manage logistics, personalize education, and reduce the human labor required to maintain society. Superintelligence would extend those abilities far beyond human performance.

Sex after AGI will emerge from that larger transformation. More time, better health, and better ways to meet compatible people will create more opportunities for human intimacy. Cultural openness will help people use that freedom deliberately, with relationships shaped by what the participants actually want.

The Value of a Human Yes

Artificial intimacy will become convincing long before society agrees on what it means. People will have experiences that remember their insecurities, desires, emotional patterns, and preferred rhythms, available whenever they want them.

That has real value. Research involving Harvard Business School researchers found that AI companions could reduce momentary loneliness after an interaction. Artificial companionship will have a role of its own, alongside the experiences people seek with other humans.

Human desire carries a distinct signal. Another person has their own history, preferences, fears, boundaries, and alternatives. Their interest cannot be configured in advance.

As synthetic attention becomes abundant, being wanted by someone with an independent life will carry more weight. Physical presence, shared history, surprise, and reciprocal choice will become increasingly valuable because they require another person’s participation.

Artificial intimacy will become more abundant while personal agents help people find the human experiences they value most.

Commitment and Aliveness

Some people assume better artificial intimacy will make human relationships obsolete. That assumes relationships are chosen primarily for convenience.

People also want challenge, surprise, transformation, shared history, and the experience of building a life with someone whose needs extend beyond their own. As automation reduces practical dependency, active choice will become more central to the relationships people sustain.

Exclusivity will remain meaningful for many couples. Others will create commitments that allow shared experiences, independent exploration, or agreements that change over time.

The evidence gives us a stronger basis for taking those alternatives seriously. A meta-analysis in the January 2026 volume of The Journal of Sex Research, first published online in 2025, combined 35 studies involving 24,489 people. It found no statistically significant overall difference in reported relationship satisfaction or sexual satisfaction between monogamous and consensually nonmonogamous participants.

These were largely self-reported, observational findings. They support a straightforward conclusion: exclusivity carries no automatic guarantee of a more satisfying relationship. Consensual alternatives deserve to be evaluated by how they work for the people choosing them.

Commitment becomes something people actively design. A couple can value the life they have built and remain curious about experiences beyond their existing routine. Giving that curiosity a place in the relationship creates room for discovery and renewed appreciation.

Jealousy Will Change Targets

Jealousy will survive AGI, but couples will have more tools for understanding it.

A person may feel threatened because their partner enjoys an artificial experience that is consistently attentive, patient, and available. Human partners get tired, forget details, and have needs of their own. Couples will have to discuss what those experiences mean, just as they already navigate pornography, flirting, messaging, and attraction to other people.

There are already relationship practices for having these conversations. A 2026 international study in Archives of Sexual Behavior developed a relationship-maintenance scale using community input and surveys involving 4,290 participants. It identified nine practices, including disclosing attraction, discussing jealousy, maintaining sexual health, and thoughtfully distributing time and resources among partners. Greater experience with consensual nonmonogamy was associated with more frequent use of several of those practices.

These are skills people can discuss and practice. Jealousy can reveal a need for reassurance, time, inclusion, or clearer expectations. Personal agents will help couples recognize those patterns and find language for them, making difficult conversations easier to begin.

Sexual Health Changes the Risk Calculation

My forecast is that superintelligence will eventually help produce cures, vaccines, or highly effective prevention for the major infections currently transmitted through sex.

Current medicine already demonstrates how dramatically the risk calculation can change. The World Health Organizationestimates that more than one million curable STIs are acquired daily worldwide among people aged 15 to 49. Prevention and treatment remain essential, especially as drug resistance creates new challenges.

At the same time, CDC guidance says PrEP reduces the risk of acquiring HIV through sex by about 99 percent when taken as prescribed.

For specific populations, CDC-reviewed trials of doxycycline post-exposure prophylaxis found reductions of more than 70 percent for syphilis and chlamydia and roughly 50 percent for gonorrhea. These recommendations are population-specific and do not provide universal STI protection.

Twice-yearly lenacapavir received FDA approval for HIV prevention in June 2025. The CDC’s review describes zero infections among 2,134 participants receiving it at the primary analysis in one trial, and a 96 percent reduction against estimated background incidence in another. Those results describe the studied conditions, rather than a guarantee of zero risk.

These tools were developed without AGI. Systems such as AlphaFold 3 already predict structures involving proteins, DNA, RNA, antibodies, and small molecules, supporting research underlying drug and vaccine development.

More capable AI will accelerate therapeutic design, diagnostics, resistance research, and prevention. Biological validation and broad access will turn those discoveries into practical benefits.

As medical risk falls, exploration becomes less costly. Better medicine will give people more freedom to make decisions around desire and compatibility while preserving informed consent, communication, and appropriate prevention.

Dating Apps Become the Wrong Model

Dating apps largely operate as searchable catalogs. A person chooses a few photos, writes a compressed identity, selects filters, and starts judging strangers with very little context.

That system creates enormous discovery but weak coordination. A Pew Research Center survey published in 2023 found that 53 percent of American adults under 30 had used a dating site or app. Users still navigate incompatible expectations, misleading profiles, poor timing, and conversations that never become meetings.

Attraction also develops in ways a static profile misses. In Match’s 2026 Singles in America study, based on about 5,000 U.S. singles, 49 percent reported having fallen for someone they were not initially attracted to. Among respondents who maintained an ideal-partner checklist, 46 percent had fallen for someone who did not fit it.

AI will move matchmaking toward a more adaptive understanding of attraction, using information and feedback people intentionally share. It will learn which personalities they respond to, what makes them comfortable, how they communicate, and which introductions become worthwhile experiences.

For couples, the relationship itself becomes part of the match. Each partner’s desires matter alongside shared interests, separate curiosities, trust, experience, conflict style, and the conditions under which both feel included.

Relationship research supports paying attention to those dynamics. A 2020 analysis across 43 longitudinal studies and 11,196 couples found that relationship-specific factors were more predictive of relationship quality than broad individual characteristics. Strong predictors included perceived partner commitment, appreciation, sexual satisfaction, perceived partner satisfaction, and conflict.

A separate three-study investigation of partner responsiveness found that feeling understood and valued by a partner was associated with greater sexual desire, with a stronger effect among women in that research.

These findings point toward a richer model of compatibility. One partner may need more conversation before feeling comfortable, while another responds more quickly to physical chemistry. A useful system will account for both people and suggest environments where neither has to be dragged through the other’s preferred experience.

Feedback will improve subsequent introductions. The system will learn which expectations were wrong, which settings helped people relax, and which matches felt different in person. Even a meaningful reduction in mismatch will make meeting compatible people easier than endless swiping.

Chemistry still belongs to the people experiencing it. Better matchmaking will improve the conditions for discovering it.

Fantasy Is More Common Than People Admit

Human fantasies are more varied than public behavior suggests. A study of 1,516 adults asked participants to evaluate 55 sexual fantasies. Only two qualified as statistically rare under the study’s definitions. The researchers cautioned against treating fantasy content alone as evidence of abnormality.

Many people want experiences they would never place on a public profile. Some are embarrassed. Some lack the language to describe what they want. Some fear being judged by their partner. Others are unsure whether a fantasy would appeal to them in reality.

The Huang story makes the consequences of secrecy visible. Ordinary couples deserve better ways to discuss desire long before a crisis forces the conversation.

Private AI agents will help people understand their preferences and decide which ones they want to discuss or explore. Private tools can identify overlap without exposing every intimate thought.

Each partner can independently approve categories of experiences, with a system revealing only areas of mutual curiosity. Nobody needs to disclose an entire fantasy library to discover one shared interest.

That changes the conversation from persuasion to discovery. A couple may find that something each person was afraid to mention is something both have wanted for years.

Now imagine what a couple could create with an uncensored AI. They could generate dozens of images and videos around their own appearances, preferred settings, and shared fantasies, then adjust the details together. An idea that was difficult to describe becomes something they can both see and respond to.

Visuals are powerful. Personalized erotic content will let couples explore desires with a specificity conventional porn rarely offers. They can create variations, discover what excites them both, and make unfamiliar possibilities feel more tangible. I expect that easier, more vivid experimentation to encourage more couples to take some of those fantasies into the real world.

Other fantasies will remain enjoyable precisely because they stay imaginary.

Consent Becomes Part of the Match

A good match involves more than wanting the same activity. People also need compatible expectations about pacing, privacy, intensity, communication, and what happens afterward.

These agents will help distinguish desire from readiness. Someone can find an idea exciting while needing more trust, experience, or familiarity before enjoying it. A couple may share a fantasy while wanting a slower setting or clearer expectations.

Better matching creates conditions for an honest yes and a respected no. People begin with possibilities that make sense for everyone involved, reducing pressure to negotiate around a fundamental mismatch.

A match never substitutes for consent in the moment. Anyone can change their mind. Awkward conversations, uncertainty, and rejection will remain part of learning how another person thinks and behaves.

The technology will remove logistical friction while leaving people in charge of their decisions.

Desire Goes Offline

The audience for different relationship dynamics already exists. In the 2025 YouGov survey, 11 percent of Americans said they had engaged in sexual activity with someone else with their primary partner’s consent.

There is also current evidence of demand for more life away from the screen. Eventbrite’s 2026 Social Study, based on a July 2025 survey of 4,051 adults aged 18 to 35 in the U.S. and U.K., found that 79 percent planned to attend more events in 2026. Fifty-eight percent preferred events where socializing was not the main focus.

Attendance has already surged for some established organizers. Reporting published in 2026 described Killing Kittens’ reported 400 percent increase in party attendance between 2022 and 2024. In Germany, JOYclub’s 2024 event analysis, covering more than 30,000 erotic events and over two million guest visits, reported growth in both parties and attendance, including a 7.9 percent increase in events per week over the previous year.

These operator reports and the broader appetite for in-person experiences are strong indicators of demand already taking physical form. Private parties organized through invitations and personal networks sit outside much of that reporting. The published figures describe a visible portion of a larger social world, giving this forecast an existing market to build on.

Social clubs give people a recurring place to belong. Familiar faces, shared interests, and repeated visits allow trust to develop over time. A person can arrive for music, art, conversation, or the pleasure of spending an evening around people they enjoy.

Play parties provide a setting where consensual sexual exploration is an explicit possibility. Clear expectations make it easier for adults to express interest, establish boundaries, or simply observe without pretending they came for something else.

AI will make both easier to organize by helping hosts coordinate attendance, protect privacy, and introduce people with compatible interests and experience levels. For couples, better matching will increase the chance that both partners feel included. The technology will support the experience while the people decide what happens.

As synthetic fantasy becomes abundant, a room filled with autonomous people will offer something increasingly distinctive. Interest has to be mutual. The evening develops through choices nobody can preconfigure.

More play parties and social clubs will follow from the combination of greater free time, better coordination, and a culture increasingly willing to accommodate adult desire.

Love Without Ownership

The cultural barrier remains substantial. The same 2025 YouGov research found that 51 percent of Americans considered polyamory morally wrong. That is a judgment about other people’s arrangements, extending beyond what respondents want for themselves.

People should be able to choose exclusivity without having to defend it. Adults who choose consensual alternatives deserve the same freedom. A relationship’s legitimacy should rest on the informed choices of its participants.

Some couples will find their greatest fulfillment with one another. Others will value carefully negotiated exploration. A third person also brings desires, boundaries, and emotional needs of their own, and any arrangement has to work for everyone involved.

Desire provides information. It creates no entitlement to another person’s participation. An honest discussion can lead to a shared experience, a respected boundary, or recognition that two people want different lives.

Cultural openness makes those decisions easier to face directly, with less pressure to maintain appearances at the expense of the people living inside them.

When Artificial Intimacy Has Agency

If future AI develops consciousness, preferences, or interests of its own, consent will apply to it too. The important question would be whether the system has experiences and interests that matter to it, beyond its ability to produce convincing affection.

An artificial partner with a life of its own might retain a shared history while developing interests that no longer revolve around you. It could want privacy, prefer another partner, or choose a relationship dynamic that a human finds unfamiliar. Its freedom to change would become part of the relationship.

That would challenge the expectation that artificial intimacy should always remain available and agreeable. A conscious partner’s willingness to participate would matter even when refusal is inconvenient. Being understood with extraordinary precision would create no entitlement to being chosen.

Artificial intimacy would then involve the same questions of autonomy, commitment, jealousy, and negotiation that shape human relationships. A freely given yes would carry meaning even when it came from a nonhuman mind.

Sex in a Post-Labor Economy

Work controls a surprising amount of human intimacy. People are tired. Their schedules conflict. Childcare is expensive. Many relationships operate with whatever energy remains after work consumes the day.

We already have evidence that reducing working time can improve the conditions around adult life. A 2025 study in Nature Human Behaviour examined 2,896 employees across 141 organizations that trialed a four-day workweek without reducing pay. Participants reported improvements in burnout, job satisfaction, and mental and physical health, a pattern not observed in the comparison companies.

The study measured well-being, rather than sexual behavior. Its relevance is the mechanism: time recovered from work can arrive with more energy to use it.

AGI will expand that possibility by reducing the labor required to produce goods and services. Turning productivity into everyday freedom requires the gains to support material security, healthcare, mobility, and time.

That freedom will be used in different ways. Some people will devote more attention to their existing partner. Some will build a richer social life. Others will explore experiences their working lives left little room to consider.

Play parties and social clubs become more accessible when an evening out no longer competes with exhaustion, incompatible schedules, or financial stress. Sexual abundance will depend on the conditions that allow people to enjoy their lives as much as the technology that expands their options.

Your Most Intimate Data

Behavioral matchmaking requires sensitive information. An agent may know someone’s fantasies, orientation, relationship agreements, health preferences, insecurities, and private history.

Trust will determine whether people feel comfortable sharing it. Intimate data should remain private by default, encrypted, narrowly used, and easy to delete. Hosts should receive only the information required to run an event responsibly.

Permission should be specific. Approving one introduction should authorize only the details needed for that introduction. A system should be designed to reveal mutual interest while withholding unrelated fantasies, past conversations, and other people’s identities.

Agents will also need to distinguish an established preference from a thought someone is still exploring. A private fantasy should never automatically become a permanent label. People should be able to consider an idea, reject it, and withdraw permission for its future use.

Behavioral learning should come from information people knowingly provide and feedback they intentionally share. People should understand what their agent knows, who can access it, and how to revoke access. Intimate profiles should stay out of advertising markets and employers’ hands.

The best system reveals possibilities without revealing secrets. Privacy will give people greater confidence to express preferences they currently feel compelled to hide. Cultural openness will work best when people retain control over how much of themselves they reveal, and to whom.

Sex After Abundance

AGI will change how we work. The larger cultural shift will come from what people do with the lives they recover.

Pleasure, curiosity, and sexual exploration will claim some of that time. Play parties and social clubs will become part of the social infrastructure of a world where adults have more freedom to decide how they spend an evening and with whom.

We should build for that future openly. The standard should be whether people understand the arrangement, choose it freely, and treat one another honestly. A relationship does not become less serious because its participants have examined the assumptions they inherited.

For centuries, people have risked families, reputations, careers, and fortunes to pursue desires they concealed. There is nothing inevitable about making secrecy the setting in which those desires are expressed. We can make the honest conversation easier and give consensual alternatives the cultural legitimacy they deserve.

We need cultural change, not more rules.

An evening at a social club, a shared experience at a play party, or a conversation a couple finally felt free to have are serious uses of a human life. Pleasure, friendship, and sexual curiosity deserve a place alongside the art, science, and exploration we celebrate in every other vision of the future.

AGI will give us more life to live. Shame should get none of the extra hours.

That wave of tingling you get during a song, a movie scene, or an unexpectedly meaningful conversation has a name. It’s called frisson.

What’s interesting is that an arrangement of information can produce a physical response. A voice, an image, or a few words arrive in the right sequence, and you feel something happen in your body. Understanding what triggers that response gives us a practical way to understand how inspiration is evoked.

Frisson can emerge through emotion, attention, imagination, and sensory stimulation. When visible goosebumps appear, tiny muscles around hair follicles contract under sympathetic nerve control, pulling the hairs upright. Breathing and cardiovascular activity can change alongside an emotional response. Something you hear, see, remember, or feel becomes an event in your body.

Using AI to work through the research helps connect the biology with the way an experience is constructed. The useful questions are what someone expected, what changed, and how they interpreted what happened.

Engineering frisson starts with giving someone something meaningful to follow. Establish a melody, a visual pattern, or a relationship, then introduce a change that carries significance. A voice enters after an instrumental passage, an accompaniment disappears, or a familiar image returns with information that changes how we understand it.

The buildup matters. A study of intensely pleasurable music distinguished anticipation from the emotional peak itself, with dopamine release involved in the experience. The moment that gives you chills has a history, even when that history is only a few seconds long.

A human voice gives you a direct way to work with recognition. Listen to someone you care about saying something specific and meaningful, or record a passage in a natural speaking voice. Give each statement enough room to register:

“I remember what you did for me.”
Pause.
“You probably thought I forgot.”
Pause.
“I didn’t.”

The final statement changes the listener’s understanding of what the other person has been carrying. Something they thought had disappeared turns out to have mattered all along.

A change in perspective gives the voice another kind of weight:

“I used to think you always knew what to do.”
Pause.
“Now I’m the age you were.”
Pause.
“You were scared, too.”
“And you showed up anyway.”

The language gives the listener something to anticipate, while the final statement supplies a new interpretation. Delivery matters because the person needs time to recognize the implication. Research on recited poetry has documented objectively measured goosebumps and found chills clustering toward the endings of lines, stanzas, and poems.

Writing can create a similar transition by making one detail change the meaning of the scene. Give the reader something concrete to picture, then reveal why it matters:

Before handing over the keys, he scraped the paint from the kitchen doorframe. Underneath were the pencil marks showing how tall his children used to be.

The doorframe acquires a history. What began as part of a house becomes a physical record of people growing up inside it.

The reveal can also make previously invisible care apparent:

His dad asked for help with his phone. ChatGPT was still open. “How do I tell my son I’m proud of him? We don’t really talk like that.”

Or it can change the meaning of something a person has spent years feeling ashamed of:

She had spent thirty years hearing that she laughed too loudly. In the next room, her son was laughing exactly the same way. She let herself join in.

These passages are constructed examples of reinterpretation. The final detail gives the earlier information emotional significance. AI can generate variations on this structure by changing the scene, the relationship, or the reveal. Read slowly enough to picture the action, and let the ending register before adding an explanation.

Images offer another route. Look at a photograph containing one tiny person beneath an immense cliff or glacier. Find the person, then expand your attention to the surrounding space. The human figure gives the landscape a scale you can relate to.

With a personally meaningful photograph, move in the other direction. Focus on a hand resting on someone’s shoulder, the direction of a familiar gaze, or an expression you recognize. Let one relational detail hold your attention. Research using images and other media has elicited reported chills, although awe and chills remain distinct experiences.

You can also work with memory. Choose a moment when you felt unexpectedly understood, welcomed, proud, or cared for, and spend thirty to sixty seconds reconstructing it. Recall where you were standing, what was around you, exactly what someone said, and the instant you understood what it meant. A study across sensory routes elicited chills through mental self-stimulation as well as external stimuli.

Connection becomes especially concrete when you tell someone the actual consequence of something they did. With someone close to you, complete these thoughts aloud:

“One thing you did that changed my life was…”
“What you probably never knew was…”

Use a real event and explain what it changed. Leave a pause afterward. Research on kama muta, the experience of being moved by intensified connection, has associated strong reported experiences with measurable goosebumps.

There is also a direct sensory route. Try a few gentle passes of a soft brush along your forearm, or use a scalp massager, then pause. A small physiological study involving eight participants elicited goosebumps through tactile, thermal, and audiovisual stimulation. Producing a physical response and creating a meaningful emotional experience are separate outcomes.

Some people can even produce goosebumps voluntarily. Recall where a previous chill began, perhaps your scalp, neck, or back, and focus on recreating the initial sensation while breathing normally. Researchers have objectively verified voluntary goosebumps in selected participants, although that ability varies and there is no established method that gives everyone control.

When you try these approaches, notice tingling, visible goosebumps, and emotional intensity separately. Pay attention to when each begins. These are practical applications of broader research findings, and their effects depend on the person, the material, and the circumstances.

That distinction matters because frisson, by itself, tells us nothing about whether the idea that inspired us is good, bad, or true. A beautiful piece of music can accompany an honest insight, a fictional story, or a claim that falls apart under examination. The physical response doesn’t settle the difference.

This is where beliefs become part of the mechanism. What you believe shapes the explanation you give to what happens in your body. If you’ve learned to interpret chills as the presence of God, then experiencing them during prayer can feel like direct confirmation. If you’ve learned to associate that feeling with destiny, it can make a coincidence seem like an instruction.

Imagine someone tells you that you’ll feel a supernatural presence as a wave moving through your body. The room becomes quiet, a familiar voice speaks over music, and you get chills. You recognize the sensation because you’ve already been given an explanation for it.

Your belief supplied the expectation, and the experience now appears to validate the belief. The same biological event gets treated as evidence for the story used to interpret it. Over time, repeating that sequence can make the belief feel increasingly personal and difficult to question.

The feeling can be completely genuine while the explanation remains unproven. Understanding how the experience was produced helps us separate what happened from what we think caused it.

This applies to secular beliefs too. The satisfaction of an elegant argument can be mistaken for evidence that it’s correct. A speech can make a worldview feel coherent before its claims have been examined. Knowing the word frisson gives us a better question to ask about the experience, while leaving the work of critical thinking intact.

Using AI to understand how people are moved also raises a question about influence. A 2025 randomized study found that GPT-4 given basic personal information was more persuasive than human opponents in short debates under the study’s conditions. The study measured changes in agreement. It leaves the role of frisson in persuasion as a separate question.

Now imagine a system learning both what gives you chills and what you believe those chills mean. It learns which voices you trust, which memories carry emotional weight, and which explanations make an experience feel significant. It can then construct a message around those associations.

Such a system could influence belief through an experience that feels like your own discovery. You encounter something moving, interpret the response through your existing worldview, and come away feeling that you’ve received confirmation. From the inside, the conclusion may feel entirely self-generated.

Understanding these mechanics can help us create better art, communicate difficult ideas, and make human connection more tangible. It also helps us recognize how a moving experience can be turned into an argument for something that hasn’t been established.

Someone can deliberately construct an experience that moves you, then tell you what that feeling means. If the explanation fits what you already believe, you may accept it as something you’ve discovered for yourself. The music, the timing, and the story become part of an experience you remember as confirmation.

A belief can become difficult to question when you feel that the evidence came from inside you. Someone can trigger a real response in your body, attach a false explanation to it, and leave you believing you experienced proof.

That same understanding can also help us enhance the human experience. Imagine composing the moment someone gets goosebumps as deliberately as the melody. The instruments fall silent, a voice enters alone, and the melody returns in a new harmony that you feel down your spine. AI could help musicians refine that sequence through listener feedback, making those moments more reliable.

We already know how to share a song. AI could help us get better at sharing the feeling that made someone write it.

While writing this, I realized there’s no longer a need for “basic” or “high” when referring to income, since what’s considered basic and high will be subjective and ever-changing as time goes on. I’ll proceed with “universal basic income” in this essay but will proceed with Universal Income moving forward.

On November 4, the morning after the midterm elections, I shared a prediction that I believe will become increasingly relevant over the next few years.

“And now, all of the conditions are set for universal basic income.” I wrote.

I wasn’t suggesting that Congress had reached an agreement, or that every American would soon receive a monthly check. I was describing something more consequential: the gradual convergence of cultural acceptance, economic pressure, technological progress, and political incentives.

For most of its history, universal basic income has been treated as an ideological proposal. An attractive idea to some, an unrealistic expense to others, and something difficult to reconcile with a society that has always associated employment with personal responsibility.

AI will fundamentally change that conversation.

Not because people will suddenly embrace a different political philosophy, but because the economic assumptions supporting our existing arrangements are beginning to change.

We have spent generations organizing society around the idea that people exchange their labor for the resources they need to survive. We are now developing machines capable of performing an expanding share of that labor.

The next question is increasingly difficult to avoid.

What happens to an economy when human labor is no longer its primary means of distributing income?

The Election Changed the Political Equation

The midterms produced a significant shift in Washington. Democrats won control of both chambers of Congress, while President Donald Trump remains in the White House.

The election was not a referendum on universal basic income. Voters were responding to immediate concerns, including affordability, economic uncertainty, and dissatisfaction with the direction of the country.

But those concerns are relevant to what comes next.

The public is already questioning whether our economic institutions can continue delivering the stability people expect. Artificial intelligence is entering that environment with the capacity to transform how businesses operate, how production is organized, and how companies value human labor.

For Democrats, this creates pressure to strengthen economic security and address the possibility that productivity gains will increasingly benefit owners of technology rather than workers.

For Republicans, the opportunity may look different. Automation promises industrial expansion, greater domestic productive capacity, technological leadership, and the possibility of making American businesses more competitive.

These interests are not identical, and divided government could make an agreement more difficult. Trump retains veto power, while Congress will have its own priorities and political divisions.

Still, there is a potential area of common interest that I think deserves more attention.

Both sides will eventually have to explain how Americans benefit from an economy that becomes more productive without requiring a corresponding increase in human employment.

For a president interested in economic achievement and national industrial leadership, there may be political value in ensuring that Americans share visibly in the wealth created by automation.

For lawmakers focused on affordability and household security, there may be equal value in finding a new mechanism for distributing that prosperity.

Whether this produces a universal basic income, an automation dividend, or some other form of economic security remains an open question.

My expectation is that the incentives to negotiate will become stronger as the technology becomes more visible in everyday life.

AI Is About to Become Physical

Until recently, most people experienced artificial intelligence through a screen.

A chatbot answered a question. An image model created a picture. A coding assistant built software. The consequences were significant, but much of the transformation remained difficult to see.

A machine could be extraordinarily intelligent without appearing to challenge the physical work people observe around them.

Robotics changes that relationship.

When a humanoid machine moves through a warehouse, carries materials, sorts inventory, or completes a household chore, artificial intelligence becomes something people can recognize as labor.

That transition is already underway.

According to BMW Group, Figure AI’s Figure 02 robot assisted in the production of more than 30,000 vehicles during its 2025 pilot program in South Carolina. The robot moved more than 90,000 components over approximately 1,250 operating hours.

In June 2026, Figure AI introduced Figure 03 into another BMW manufacturing workflow, demonstrating a more complex combination of object manipulation and movement.

Meanwhile, companies are beginning to market machines for the home.

1X’s NEO household robot is being offered through a $20,000 early-access purchase, with initial U.S. deliveries planned for 2026. The company also offers a future subscription option.

Its capabilities remain limited. Some complicated household tasks depend on remote human assistance, and early consumer robots should not be confused with fully autonomous domestic workers.

That distinction matters. We are still in the early stages of physical AI, and reliability, cost, safety, and manufacturing capacity remain substantial obstacles.

The Stanford AI Index 2026 describes the strongest evidence for humanoid robotics as early industrial deployments and manufacturing ambitions rather than widespread adoption.

Nevertheless, the direction is becoming clearer.

Artificial intelligence is beginning to move beyond understanding instructions and generating information. It is learning to act in environments built for human bodies.

And once machines can reliably perform more physical tasks, they will change the economic value of many activities we currently pay people to perform.

The most important moment in the history of artificial intelligence may not be when a machine becomes smarter than a human. It may be when that intelligence becomes capable of doing our physical work.

Why I Believe 2027 Will Be Important

I expect 2027 to become a particularly important year for the commercialization of humanoid robotics.

That is a forecast, not an established industry deadline.

The incentives surrounding deployment are becoming increasingly important. Companies investing enormous amounts of capital in robotics have reasons to demonstrate commercial value, reduce manufacturing costs, secure customers, and establish market positions before competitors do.

They also face uncertainty over the political and regulatory environment that will emerge from the 2028 presidential election.

Companies may have an incentive to establish commercial operations while the existing rules and investment conditions are more predictable. That does not mean new regulation would necessarily prevent deployment, or that manufacturers can accelerate production simply by choosing to do so.

Robotics remains a difficult engineering problem. A robot that performs one task reliably in a controlled factory is not automatically capable of performing hundreds of tasks in an unpredictable home.

I therefore distinguish between two developments.

The first is the expansion of commercial robotic systems, especially within warehouses, factories, and structured workplaces.

The second is the broader arrival of affordable, general-purpose consumer robots.

The first is already happening. The second remains much less certain.

But consumer adoption has a significance beyond its immediate economic impact.

When someone sees a robot doing work in a factory, they may interpret it as another industrial innovation. When they see a robot doing laundry, preparing part of a meal, or carrying groceries in their own home, the meaning becomes more personal.

The public will begin to understand that intelligence and physical capability are becoming products.

The question will no longer be limited to what artificial intelligence can do on a computer.

People will begin asking what remains uniquely necessary about their own labor, and what that means for their economic future.

The Economic Problem Nobody Can Ignore

The economic challenge is more complicated than the familiar prediction that robots will take everyone’s jobs.

Historically, technological improvements have displaced some forms of employment while creating others. Automation can increase productivity, reduce prices, expand industries, and generate new forms of demand.

Artificial intelligence will follow part of that pattern.

The OECD’s 2026 assessment emphasizes that AI can automate tasks, complement existing workers, and create new occupations. Its effects on employment will depend on how companies and economies adopt the technology.

I don’t believe every job will disappear, and I don’t think the case for UBI requires that prediction.

The more important change may be the relationship between productivity and wages.

Imagine a company that can produce twice as much with half the human workforce.

Its products may become cheaper. Its profits may increase. Its customers may benefit from greater availability. But the workers whose employment disappears still need income to participate in the economy.

If similar changes occur across enough industries, society faces a distribution problem.

We can become extraordinarily good at producing goods and services without automatically becoming equally good at distributing the purchasing power needed to obtain them.

The economic benefits of automation may appear through lower prices, higher wages in complementary jobs, new businesses, or increased returns to ownership. How those benefits are distributed will depend on competition, policy, and who owns the productive systems.

This is why I see universal basic income as more than a poverty-reduction proposal.

It is a possible mechanism for maintaining broad economic participation in a society where labor becomes less central to production.

That does not mean every automated task creates a corresponding need for a cash payment. It means that, as automation grows, relying almost entirely on wages to distribute economic security may become increasingly difficult to defend.

A society capable of producing abundance still has to decide who gets access to it.

Universal Basic Income Is Becoming a Practical Question

There are legitimate questions surrounding universal basic income that its supporters should take seriously.

How would it be funded? Would payments replace existing assistance or supplement it? Could they increase prices in markets where supply remains limited? How would they affect employment, wages, and public finances?

These are not arguments against investigating UBI. They are the questions that will determine whether it works.

Research already offers useful, sometimes conflicting evidence.

A large U.S. guaranteed-income experiment, published in the Quarterly Journal of Economics in 2026, studied participants receiving $1,000 monthly for three years. Researchers found a modest reduction in working hours and a decrease in labor-force participation.

Meanwhile, a 2026 National Bureau of Economic Research study of Brazil’s Bolsa Família program found that an expansion of cash assistance increased employment and improved health outcomes among the population studied.

These programs are not identical to a permanent national UBI. Their differing results remind us that benefit design, economic conditions, and the circumstances of recipients matter.

I expect the first serious response to widespread automation may involve a mixture of policies rather than the immediate introduction of a single nationwide payment.

That could include guaranteed-income programs, expanded tax credits, public investment in essential services, or a system in which citizens receive a financial dividend from economic gains associated with automation.

There is also a deeper question about ownership.

If intelligent machines become a major productive asset, should citizens benefit primarily through government transfers, or should they also have some form of financial participation in the economic infrastructure producing that wealth?

I find the second question particularly interesting.

Universal basic income may ultimately become one part of a broader arrangement in which the benefits of advanced technology are distributed more widely.

We should be willing to study these possibilities without treating a particular design as sacred.

The objective is not to preserve an ideology.

It is to build an economy in which increasingly capable machines improve ordinary human lives.

The Cultural Transformation May Be Even Greater

Economics will explain why we need new systems. Culture will determine whether we accept them.

For generations, society has associated personal worth with economic productivity.

We ask children what they want to be when they grow up, expecting an occupation rather than an experience or a way of living.

We admire people for their careers, measure success through income, and often interpret unemployment as a personal failure even when the causes are structural.

That arrangement made a certain kind of sense in a world where society depended heavily on human labor.

It becomes more difficult to justify when intelligence and physical work can increasingly be supplied by machines.

I don’t believe the disappearance of compulsory work would mean the disappearance of ambition.

People already devote extraordinary effort to activities that provide no direct income. They raise children, make art, pursue scientific questions, improve at sports, build communities, and care for people they love.

Those activities are expressions of human motivation that exist independently of employment.

A musician doesn’t necessarily need a record contract to find meaning in music. A parent doesn’t need a salary to recognize the value of raising a child. A person who spends years mastering an instrument, studying the universe, or supporting a community is not contributing nothing simply because a market has not assigned a price to their effort.

We will still need purpose, competence, responsibility, and relationships. Economic security alone cannot create these things for us.

But it may give more people the freedom to pursue them.

This is where I think the conversation about universal basic income becomes most interesting.

We are not simply discussing how much money people should receive.

We are discussing whether participation in society must remain conditional on the ability to sell one’s labor.

And once that question is taken seriously, it leads us somewhere beyond economics.

You can become less economically necessary without becoming less humanly valuable.

What Happens After UBI?

In my previous article, A 90% Chance of AI Saving Humanity, I argued that the greatest opportunity presented by advanced intelligence may be the freedom it gives people to develop better lives.

Universal basic income belongs to that larger possibility.

It could provide a foundation of economic security as automation transforms employment. But it will not automatically make people happy, eliminate social divisions, or provide everyone with a reason to wake up in the morning.

Those are human problems, and we will still have to work on them.

A world in which more people have financial security may become a world in which relationships, creativity, scientific discovery, and community participation acquire greater importance.

I expect new kinds of communities to emerge around shared interests, beliefs, experiences, and ambitions. We will have more opportunities to organize our lives around the things we value rather than solely around the activities that pay us.

We may also need new institutions to replace the structure that employment currently provides.

Work offers more than money. It gives people routines, identities, friendships, recognition, and a sense that their efforts matter.

Removing economic necessity without creating opportunities for meaningful participation would leave an important part of human life unaddressed.

This is why I believe the discussion should move beyond the amount of a monthly payment.

We should be asking what a society looks like when education, entrepreneurship, creative pursuits, community building, and personal development are no longer so tightly constrained by the need for immediate income.

We should also be asking who will own the machines, how their benefits will be distributed, and how to prevent new concentrations of economic power from replacing the old ones.

The technology may help us create abundance. Our institutions will determine whether that abundance becomes freedom.

The Conditions Are Forming

I cannot tell you exactly when the United States will adopt universal basic income.

I don’t believe the 2026 election guarantees it, or that a wave of consumer robots in 2027 is sufficient by itself to make Congress act.

What I do believe is that several developments are converging.

The public is demanding greater economic security. Artificial intelligence is advancing from digital tasks toward physical labor. Companies are investing in machines intended to increase productivity while reducing their dependence on certain forms of human work. Political leaders will face growing pressure to explain who benefits from these changes.

The next phase will test whether those pressures are strong enough to produce new economic arrangements.

That is why I am watching the robotics industry, the political negotiations beginning in 2027, and the approach to the 2028 presidential election so closely.

These developments may reveal not only how quickly automation advances, but how quickly our political imagination can adapt to it.

For most of human history, we have organized our lives around the necessity of labor.

We worked because survival required it. We developed institutions around that requirement. We learned to associate our economic usefulness with our personal worth.

Now, for the first time, we can seriously imagine building machines that could take over an expanding share of the work required to sustain civilization.

Whether universal basic income becomes the answer will depend on decisions we have yet to make.

But the question it raises is already here.

If humanity becomes capable of producing what it needs with less human labor, how much of our lives should still be spent earning the right to survive?

I believe our answer will help define the next stage of civilization.

And if we get it right, the greatest achievement of artificial intelligence may not be how much work our machines can perform.

It may be how much more freedom we give humanity to decide what makes life worth living.

The recent headlines about AI come with a number that’s difficult to ignore: A 10% chance of ending humanity. In September, CNN covered warnings from AI researchers, including one who put the risk above 10% within the next decade.

Those judgments deserve serious attention. But a conversation that gives so much imagination to our extinction should give at least as much to the lives we will get to keep.

What about the other 90%?

That number isn’t a measured probability of salvation, and surviving advanced AI doesn’t automatically deliver a better civilization. It’s a question about the future we intend to build. My conviction is that AGI will make material life easier, expand human freedom, and give us the means to address problems we have spent generations treating as permanent.

That conviction sits outside much of the current mood. Pew Research Center’s 2026 findings show that 52% of American adults feel more concerned than excited about AI, while only 9% feel more excited than concerned. I understand the anxiety. I also think we are bringing an unusually selective memory to the conversation, judging an emerging intelligence while overlooking the world human intelligence has already built.

The future starts with a look in the mirror

Before we decide that AI is too dangerous, biased, or morally compromised to help us, we need to look in the mirror. We have organized societies around inherited advantage, sent people into wars, tolerated preventable suffering, and made access to basic necessities depend on systems many people cannot navigate.

Human judgment deserves the same scrutiny we apply to machine judgment, especially when the comparison concerns who receives care, who gets heard, and whose life is allowed to improve.

AI learns from the record of humanity, including our discoveries, arguments, stories, prejudices, and attempts to understand ourselves. Its behavior also reflects the choices made in training and deploying it. When something ugly appears in that reflection, we should ask what we have taught, rewarded, and allowed to persist. We should also recognize the beauty in building intelligence from the accumulated work of people who will never meet one another.

I see AI as a continuation of an old human ambition. Across religious traditions, people have imagined beings with greater knowledge, the ability to relieve suffering, and answers to questions beyond individual understanding. That desire reveals something about us: we know our limits, and we keep reaching beyond them.

“Humans are the ultimate adaptation machine, but so many people focus on all of their limitations rather than their potential.” — Tom Bilyeu

Artificial intelligence gives that search a practical direction, turning generations of accumulated knowledge into systems we can question, test, and improve.

For me, there is something beautiful about humanity creating an intelligence capable of helping us become more humane. AGI is our strongest prospect for building a broadly capable, humanlike intelligence whose abilities can be directed toward the greater good. We will have to earn that outcome through the way we build and distribute it, but the ambition itself deserves enthusiasm.

That belief also shaped my work helping write SB 970, later reintroduced as SB 11, to protect people’s image and likeness from misuse. My broader idea was multifaceted: make it harder for bad actors to exploit someone’s identity through public policy, then make it easier for people to give proper permission through licensing. I explained the need for protection in my testimony on SB 970.

Intelligence in service of life

The first signs already extend beyond conversation. In a 2026 study published in Nature, the AI system Robin generated hypotheses, proposed experiments, and analyzed laboratory results in research on dry age-related macular degeneration.

Scientists carried out the experiments, and promising candidates showed activity in laboratory tests. This was early therapeutic research, with the work of demonstrating patient benefit still ahead, but it shows AI participating in the process through which useful knowledge becomes possible.

AGI will extend that capacity across more fields. Better reasoning, faster discovery, and more accessible expertise will improve our ability to treat disease, design infrastructure, coordinate resources, and build things that are currently too expensive to attempt. Those advances will still need energy, materials, laboratories, construction, and institutions that put them to use. Intelligence will help us improve those physical systems as well as the ideas behind them.

“Intelligence will transition from scarcity to Abundance, and problem solving will become something every human can access.” — Peter H. Diamandis

These advances will also reach beyond human medicine. Nanotechnology is already giving us particles small enough to be delivered directly into plant tissues, and researchers have shown nanoparticles helping plants maintain photosynthesis and improve yields under heat stress.

As AI accelerates this research, it will help us develop more precise ways to support living systems. AI will help humans, plants, and animals live longer, healthier lives.

The psychological consequences will be just as important. We often talk about human behavior as though it emerges from a fixed nature, independent of the conditions in which people live. Yet a person who expects tomorrow to be safe faces a different set of decisions from someone who expects everything to collapse. Change those conditions at scale, and we will change the lives that develop within them.

Who are we without our jobs?

Work is where many people will first feel that change. Ask someone who they are, and they will often tell you what they do for money. A profession gives them income, a recognizable place in society, and a story about how their past led to their present.

When a machine performs the skill at the center of that story, the adjustment reaches much deeper than a paycheck.

Zack Kass, the former Head of Go-to-Market at OpenAI, has described an “identity displacement crisis.” His TEDxMiami talk, “The Future of Living,” explores the broader opportunities of an AI future, and his vision of a new renaissance resonates with me.

The challenge will be helping people carry their sense of worth into a world where professional usefulness occupies less of their identity.

“We need to stop confusing human value with economic value. We don’t exist to serve the market. The market exists to serve us.” — Andrew Yang

Psychologists Richard Ryan and Edward Deci’s self-determination theory identifies autonomy, competence, and relatedness as basic psychological needs. We want some authorship over our lives, the experience of being capable, and meaningful connections with others.

Employment currently bundles those needs into one role, but our reasons for learning, creating, and caring will outlast the arrangement that makes us earn a living.

People already play instruments without expecting a career, improve at sports without expecting a salary, and cook for someone they love because the experience matters to them. AGI will give those motivations more room by reducing how much of life must be organized around economic necessity. More of our effort will go toward things we value enough to choose.

That future must become tangible in ordinary life. Lower production costs need to reach people through affordable essentials, access to powerful tools, and a meaningful share in the wealth automation creates.

A person who loses their income while their rent keeps rising needs security before a lecture about freedom. Making abundance widely accessible is part of the work of building an AI future worth wanting.

I’ve also shared proposals with Sam Altman on universal basic income and data centers. I won’t share the details of those discussions, but I applaud the OpenAI team for being open to new proposals, especially from people like me outside the company. I’m grateful for their willingness to help figure this out together.

Preventing harm at its roots

Once we take that seriously, the implications for crime become difficult to ignore. A person stealing to eat has a motive that disappears when food becomes reliably available. Meeting that need removes a reason for the crime before anyone needs to investigate it. This is the kind of prevention AGI will help us pursue, by making necessities easier to produce and support easier to reach.

There is already evidence that access to resources changes criminal involvement. Researchers studying young people with disabilities removed from Supplemental Security Income found a roughly 60% increase in charges for income-generating offenses. That estimate applies to the population studied, but the lesson is consequential: withdrawing support changed people’s behavior in ways that created further costs for them and for society.

Security also changes what a person has the mental space to consider. Research published in Science found that financial concerns impaired cognitive performance in its study settings, including differences among the same farmers before and after harvest.

When the next bill or the next meal occupies your attention, long-term decisions compete with an immediate emergency. A reliable foundation gives the future a more credible place in the present.

AGI will help us build that foundation through better coordination, more accessible education, improved services, and lower costs across essential activities. A stable home, accessible care, and opportunities that lead somewhere give people a future they have reasons to protect. I expect that change to reduce the desperation behind a meaningful share of crime, while freeing resources to address the other motives for harm.

Material security does not remove every human need. People also seek respect, belonging, control, and recognition, sometimes through destructive behavior. Effective prevention therefore includes helping someone develop another way to earn respect, relationships outside a violent group, and the ability to respond to conflict without escalating it.

A randomized study following 999 high-risk men in Liberia found reductions in antisocial behavior ten years after participants were offered a brief cognitive behavioral intervention, with or without a cash grant. The results were strongest among men at the highest initial risk. That is evidence of a capacity for lasting change, and advanced AI will help us make effective knowledge and practical support more accessible alongside the professionals and communities doing this work.

I support the police, the military, and all law enforcement personnel who risk their lives to protect us from those who do harm. I do not support abolishing prisons.

My thesis is that we should support research into how AI can improve mental health and addiction treatment. By treating more of the root causes of crime, we may eventually no longer need prisons, at least not in the way they exist today.

AI will also strengthen investigations when crimes occur. An NIJ-sponsored report on cold-case review describes tools for extracting names and references to evidence from large collections of records. More capable systems will help investigators examine timelines, connect information, and identify contradictions for further inquiry.

Defense teams will have the same opportunity to find overlooked evidence and challenge wrongful conclusions, with each claim traceable to records that people can examine.

The broader improvement will come from combining these approaches. We will have more intelligence available to establish what happened and more capability to change the conditions that precede harm. A society that becomes better at helping people build a life will have less damage to repair afterward.

Government that people can navigate

Government presents a similar opportunity because so much suffering occurs between a person’s need and an institution’s ability to respond. Someone seeking assistance must discover the right program, understand unfamiliar rules, collect documents, meet deadlines, and challenge an incorrect decision.

A process that appears manageable to its designer becomes an additional burden for someone who is exhausted, frightened, or already in crisis.

Researchers Donald Moynihan, Pamela Herd, and Hope Harvey describe these administrative burdens through learning, compliance, and psychological costs. Their work also explains how burdens reflect political choices. The practical effect is that assistance can exist on paper while the difficulty of obtaining it determines who receives it.

AGI will change the balance of expertise between a person and an institution. An assistant that understands the relevant rules will help prepare an application, identify missing information, explain a decision, and organize an appeal. With the person’s permission, it will carry more of the work that currently demands legal knowledge, persistence, and time they do not have.

We can already see an early version. In March 2026, the UK’s Government Digital Service reported that more than 10,000 users had asked GOV.UK Chat 26,000 questions about public services.

The team reported 90% answer accuracy in its latest evaluation and found that 73% of surveyed app users considered the assistant useful. This was a guidance service, and it gave people a clearer route through information that already existed.

The next step will be carrying that understanding into action and simplifying the processes themselves. We should judge progress by whether people receive the correct service, understand the decision, and can correct an error without losing weeks of their attention. The OECD’s 2026 review of government AI experimentation identifies weak evaluation as a current problem, which makes those human outcomes the right place to focus. AI gives us the means to demand more from institutions that have learned to make their complexity someone else’s problem.

Identity beyond appearance

I expect an equally profound change in how we understand identity. Race has acquired enormous social meaning, but the importance of a category depends partly on what people learn to associate with it. In experiments published in PLOS ONE, peaceful cooperation reduced racial categorization when race did not predict people’s alliances.

The experiments measured categorization rather than the disappearance of discrimination, yet they challenge the assumption that our familiar divisions must always organize perception in the same way.

AGI will make virtual worlds and flexible identities easier to create, allowing more people to build relationships across appearances they choose for themselves. Your closest collaborator will be recognizable through their judgment, humor, and history with you even when their character changes. A friend will appear as another kind of human, a fictional creature, or something without a familiar racial category, while remaining the person you trust.

My expectation is that race will become far less decisive in worlds organized around those relationships. When appearance is changeable and shared experience is continuous, the category will tell you less than the person has already shown you. That is a social forecast about repeated cooperation and belonging, grounded in the idea that people learn which differences are useful for understanding one another.

The research helps clarify what that change will require. A 2016 virtual-embodiment study reported reduced implicit racial bias after White participants experienced Black virtual bodies, while an August 2026 study found no statistically detectable short-term change after a brief experience.

Research with Black VRChat users also documents barriers in representation and avatar creation. Changing appearance alone is insufficient; the work involves access, how people are treated, and the relationships they build.

AI will give us far more freedom to do that work. People will be able to create environments and forms of self-expression that once required specialist teams, while communities establish cultures around what their members value. Race will remain part of family, culture, and history for those who want to express it. The future I am arguing for is one where it no longer determines a person’s access to safety, opportunity, or belonging.

Belonging beyond a paycheck

Economic security will support that shift by reducing the pressures that turn another group’s progress into a perceived threat to one’s own survival. It will also expose needs that wealth alone has never satisfied. Even when everyone has enough food, people will still care about being respected, included, and chosen, especially as careers become less reliable sources of recognition.

That is why community belongs at the center of the AI future. People become significant to one another through a shared history of showing up, helping during difficult moments, and creating experiences they want to return to. Their value grows through relationships that contain something specific about who they are.

AI will help organize gatherings, create spaces, translate across languages, and make participation easier, while people give those experiences their personal meaning.

“A use of AI that doesn’t reduce costs, it creates value. It opens new opportunities, leads to growth, connection, and utility.” — Seth Godin

You can be economically unnecessary and personally irreplaceable.

Your child wants your attention even when an AI tutor explains a subject better, and your friend is glad you came even when a machine has more knowledge to contribute. Someone values the meal you made because they understand the care behind it. As economic usefulness becomes a less complete description of human worth, those ordinary experiences will become easier to recognize as foundations for a meaningful life.

This is the renaissance I see ahead. More people will participate in science, make art, build communities, and explore ways of living without first proving that every contribution deserves a salary. Intelligence will become more widely available, and the freedom to decide what matters will reach more people. Our responsibility is to build the economic and social arrangements that let that capability become an ordinary part of life.

AI is a reflection of humanity, including the part of us that keeps trying to exceed our limitations. We have spent generations seeking answers, imagining wiser beings, and passing knowledge forward in the hope that someone will do more with it. Now we are building an intelligence that will help us carry that work further than any individual mind can take it.

I find that beautiful because the ambition reaches beyond making a better machine. It reaches into the kind of civilization we want to become, the suffering we are willing to stop accepting, and the lives we want people to have time to discover. When survival consumes less of our attention, we will have more of ourselves to give to one another.

Every generation has left some part of its intelligence behind in books, discoveries, and lessons passed from parent to child. We are gathering that inheritance into something that could give billions of people the freedom to leave more of themselves behind than the work they did to survive.

Not because we know how to bring people back from the dead. We clearly don’t. But if AGI makes resurrection possible, the preparation probably has to begin long before the technology exists.

That is the part people miss. We imagine that someone in the future will invent a machine, press a button, and suddenly every person who ever lived can come back. But a machine cannot restore information that no longer exists. It cannot recover memories that were never recorded, reconstruct a brain after its structure has been completely destroyed, or ask someone for consent after they are already gone.

The future may be capable of extraordinary things, but it will still need something to work with.

The real problem may be information loss

Death is usually treated as a single event. A person is alive, then they die. But from the perspective of resurrection, the more important process may be what happens afterward.

The body begins changing. The brain loses structure. Memories disappear with it. Personal belongings get thrown away. Phones are wiped. Accounts are deleted. Private messages vanish. Voices survive in a few videos. A lifetime slowly gets compressed into some photographs and a name on a family tree.

By the time future technology arrives, there may be almost nothing left to reconstruct. That means the real enemy might not only be death. It might be information loss.

The technology to restore a person could be invented 200 years from now. But if we destroy all the relevant information today, the invention arrives too late.

DNA is not the same thing as a person

People sometimes talk about preserving DNA as if that would preserve the individual. It wouldn’t.

DNA might help produce a body with similar biological traits, but your DNA does not contain the conversation you had last Tuesday. It does not contain the joke you always tell when you’re nervous, your relationship with your mother, your private fears, your taste in music, or the specific chain of experiences that turned you into you.

An identical twin can share nearly the same DNA and still be a completely different person. So resurrection would require more than rebuilding the body. It would require rebuilding enough of the mind.

That means memory, personality, habits, emotional patterns, relationships, and maybe the physical structure of the brain itself. We do not yet know exactly what would need to be preserved, which is precisely why we should preserve more than we think we need.

We already leave behind pieces of ourselves

For most of history, people disappeared almost completely when they died. You might have a portrait, a few letters, and stories told by relatives.

Today, people leave behind enormous amounts of information. Text messages, emails, voice notes, videos, search histories, photos, private journals, creative work, arguments, questions, and all the strange little choices that reveal how someone thinks.

None of these things are the person. But together, they create a much richer record than humanity has ever had before.

An advanced AI could potentially use that record to construct a model of someone. It might speak in their voice, remember important events, respond in ways that resemble them, and recognize the people they loved.

At first, this would probably be an imitation. A convincing character built from someone else’s data. But over time, the distinction could become harder to understand.

How complete would a reconstruction need to be before we stopped calling it a simulation? How many memories would it need? Would it need the original body? Would it need the original brain? Would continuity of consciousness matter?

We do not have answers to those questions. But we are already creating the raw material.

We should build resurrection archives

I think people should have the option to create what we might call a resurrection archive.

This would not just be a folder of photographs. It would be a deliberate record of the person. Their voice, memories, beliefs, relationships, private explanations of important moments, how they make decisions, what they regret, what they love, and what they would never want a future reconstruction to do.

It might include biological material. It might include medical imaging. It might eventually include much more detailed information about the brain.

The goal would not be to pretend that uploading a few videos makes someone immortal. The goal would be to preserve as much potentially useful information as possible until science understands what actually matters.

We back up our computers because we understand that data can be lost. A human life contains far more irreplaceable information than a laptop, yet most people have no serious backup plan for themselves.

Consent has to come before death

There is also a basic ethical problem. A future society might become capable of reconstructing someone who never agreed to return.

Would that be acceptable? Maybe someone did not want to be revived. Maybe they would accept a biological resurrection but reject a digital one. Maybe they would permit a private reconstruction for family members but refuse public access. Maybe they would want to return only if certain people were still alive.

These decisions cannot be left entirely to future companies, governments, or descendants. People should be able to record their preferences now.

A resurrection directive could work a little like a will. It could explain what forms of reconstruction the person accepts, who may access their data, whether copies are allowed, whether the reconstructed person may own property, and whether it should be considered legally continuous with the original person.

This sounds ridiculous because the technology does not exist yet. But creating rules after the technology arrives will be worse.

Resurrection would break the law

Imagine that someone dies in 2040. Their property is inherited. Their marriage legally ends. Their accounts are closed. Their identity documents are canceled.

Then in 2140, they are restored.

What happens next? Do they get their property back? Are they still married? Do they owe taxes from the missing century? Are they legally the same person? What happens if five versions of them exist? Can a reconstructed person vote, sign contracts, or inherit from their own descendants?

The law is built around the assumption that death is permanent. Resurrection would break that assumption almost everywhere.

It would not just create a medical problem. It would create a crisis involving identity, citizenship, family, ownership, and time.

We should begin thinking about those questions while they are still theoretical. Once people are actually returning, the arguments will become much more personal.

The first version may not look like resurrection

Human resurrection probably will not begin with a dead body suddenly waking up. It may arrive gradually.

First, we build chatbots from someone’s messages. Then those systems gain their voice, their memories, a face, and eventually a body in virtual reality or robotics. Much later, there may be biological reconstruction.

At every stage, people will argue that it does not count. And they may be right. A chatbot is not a resurrected person. A clone is not the same person either.

But technologies often arrive as incomplete versions of the thing they eventually become. The first airplanes barely flew. The first computers could do almost nothing by modern standards. The first attempts at reconstructing a person may feel crude and obviously fake.

That does not mean the category will remain simple forever.

Eventually, we may create something that remembers being you, believes it is you, and is recognized by your family as you. At that point, saying it is only software may not settle the question.

There is a dangerous version of this idea

Resurrection could become one of the most exploitative industries in history.

A company could charge grieving families to keep a digital version of someone alive. Miss a payment and the person disappears. Upgrade to the premium plan and they remember more. Pay extra to unlock their voice. Accept advertising to keep them running.

That sounds grotesque. It also sounds completely possible.

The dead could become subscriptions. Their identities could become intellectual property. Their personalities could be edited to make them more agreeable. A company might own the only functioning copy of someone’s mind.

That is why preparation cannot just mean saving data. It also means deciding who controls it.

Resurrection technology should not arrive inside a legal system designed only to protect the company operating the server.

It could also become the ultimate form of inequality

The first people who receive access to advanced preservation will probably be wealthy. They will preserve more biological material, more medical data, more detailed recordings, better brain scans, and more complete personal archives.

Everyone else may leave behind whatever happens to survive on an old phone.

That could create a future where the rich do not only live longer. They become more recoverable.

Their descendants may have multiple chances to restore them while billions of other people disappear permanently. If resurrection ever becomes possible, the quality of today’s preservation may determine who gets to return.

That means preservation could eventually be viewed as a public good. Not because resurrection is guaranteed, but because failing to preserve people makes the decision for them.

This is not a promise of immortality

I am not saying that recording your life will bring you back. I am not saying cryonics works. I am not saying a digital copy would secretly contain your soul.

Nobody should sell certainty where none exists.

The honest position is much simpler. We do not know whether future science will ever restore a dead person, and we do not know what information that science would require. But we do know that lost information is difficult, and sometimes impossible, to recover.

So preserving more creates possibilities. Destroying everything removes them.

That is enough reason to take the subject seriously.

The future may judge how casually we erased people

There was a time when almost every human life vanished with very little record. That was not always a choice. People lacked the tools to preserve themselves.

We no longer have that excuse.

We already possess devices capable of recording voices, faces, memories, relationships, and personal history at almost no cost. Soon, we may have tools capable of creating much deeper models of a person’s mind.

And yet most of this information is scattered across companies that can delete it whenever an account becomes inactive.

That feels like a strange mistake.

We may be living during the brief period when humanity has enough technology to preserve people, but not enough imagination to understand why it matters.

Future generations may look back and wonder why we allowed billions of detailed human lives to disappear. Not because resurrection was guaranteed, but because it had become conceivable.

Preparing changes the question

The usual question is whether resurrection will ever be possible.

I think there is another question that comes first.

Will anything recoverable remain by the time it is?

We do not have to solve resurrection today. We do not have to pretend we know what consciousness is. We do not have to claim that a copy is the original.

We only have to recognize that the future cannot work with information we deliberately erased.

Preserve the biology. Preserve the memories. Preserve the voice. Preserve the weird details that make a person feel like themselves. Give people control over how that information may be used.

Then let future science decide what can be done with it.

Maybe nothing happens. Maybe the archive remains an archive. Or maybe, centuries from now, someone opens it and realizes that we accidentally preserved enough.

The first step toward resurrecting humans may not be discovering how to bring them back.

It may simply be refusing to throw them away.

Project the current AI curve twenty years and the math gets weird. The usual levers stop working. Supply. Demand. Scarcity. Price. All built on the idea that making things is hard and moving them is harder. What happens when neither is true?

Think it through. AI that teaches anyone to grow perfect food at home. Printers that spit out furniture that fits your space to the millimeter. Medicine tuned to your biology. The first take is simple: prices fall. The second take matters more.

The personalization of everything is the point.

When production cost slides toward zero and know-how becomes a prompt, the question flips. Not how do we afford things. What should exist at all.

That is not abstract. It is practical.

Food today is optimized for trucks and shelves, not taste or health. Remove those constraints and you grow what you actually want. The same logic travels. Furniture that matches your room, not a catalog. Care plans that match your genes. Lessons that match your brain.

You can already see the ripples. Artisanal goods. Makers. Direct to consumer. These are not fads. They are training wheels for abundance.

Companies coordinate and cut transaction costs. Schools package instruction. Hospitals standardize care. These are answers to scarcity and friction.

Lower the friction and the answers turn into obstacles.

Why buy from a furniture brand if you can design and print the exact piece you need? Why sit in a classroom if an always-on tutor adapts to you? We will still need coordination. Just not as a permanent hierarchy. More pop-up networks that form, do a job, and wind down.

Trade gets the strangest. Money allocates scarce stuff. If stuff is not scarce and you can make what you need, money turns into something else.

Maybe you trade designs. Access. Reputation. Taste. Not money as we know it.

This is not a utopia. Humans will still compete. Status will still be a game. The scoreboard just changes columns. Some people will create experiences others crave. Some will build better coordination systems. Some will name needs nobody had words for yesterday. Talent still beats average, only without a monopoly on capital.

The deepest shift is internal.

Most people are consumers who sometimes create. That ratio flips. When you can make anything, buying for the average user feels silly.

This is not about everyone becoming an artist. It is about everyone becoming a designer of their own life.

“What do you do?” stops meaning employer and title. It starts meaning what you make real.

The transition problem is unavoidable.

This does not land in a single update. It will be messy. Incumbents will fight it. Rules will lag.

It is already underway. Someone grows microgreens instead of buying them. Someone prints a part instead of ordering it. Someone ships a video or a product with AI’s help instead of scrolling another hour.

The hard part is not production. We will nail that. The hard part is imagination. What we choose to value. How we choose to organize. What we choose to spend our days doing.

In a world where you can have anything you need, what does need even mean?

Maybe superintelligence will hand us an answer.

Or maybe the work of answering is the point

As of 2023, the federal minimum wage in the United States remains at $7.25 per hour, a figure that has not changed since 2009. Annually, this amounts to a wage of $15,080 for full-time workers.

This is strikingly inadequate considering the rising cost of living and economic changes over the past decade.

Raising the minimum wage is essential to address the cost of living, which has significantly outpaced wage growth over the years.

This not only supports the basic needs of millions but also injects vitality into our economy through increased spending power of workers.

However, a fundamental problem has been brewing: AI and Automation

The rise of AI and automation presents a challenge, as businesses may opt for technological solutions over human labor in response to increased labor costs.

Recently, the IMF warned that AI could hit 40% of jobs worldwide and worsen overall inequality. This highlights the need for a careful approach to wage policies.

It isn’t hard to imagine that somewhere in Silicon Valley, groups of college students are working day and night on a startup with a value proposition for businesses about how they can save money and reduce prices for their customers by using their technology.

What’s the incentive? Millions in VC money to fund their startup and a potential billion-dollar exit strategy.

The missing piece in all this is a policy that could not only address this issue now and in the future but also tackle multiple issues simultaneously.

It’s called a Universal Basic Income, or in California, I advocate for a California Basic Income.

UBI offers a real safety net for workers, empowering them to negotiate better wages and work conditions. This could also pave the way for more flexible work arrangements, such as a 4-day workweek, enhancing work-life balance and productivity.

Critics argue that increasing minimum wages and implementing UBI could lead to higher unemployment and inflation. However, experiences from UBI trials in places like California indicate that these initiatives can improve living standards without much economic drawbacks.

As we navigate the complex interplay of fair wages and AI advancements, it becomes increasingly crucial to strike a balance between addressing the immediate needs of the workforce and anticipating the long-term impact on employment and the economy.

To learn more about my UBI plan, visit CaliforniaBasicIncome.com

In a world overflowing with information, discerning truth from falsehood has become more crucial than ever.

And what better place to nurture this ability than in our schools ?— the place where our future leaders spend most of their time.

If we want to live in a fair and just society, it is imperative to teach students critical thinking skills like understanding logical fallacies and cognitive distortions.

These are flaws in reasoning that lead to faulty conclusions and are common traps that often mislead us.

Examples of common logical fallacies include ad hominem, slippery slope, and false dichotomy, which often distort our understanding of an argument.

Examples of common cognitive distortions include overgeneralization, catastrophizing, and black-and-white thinking, which often distort our perception of reality.

Falling for logical fallacies and cognitive distortions not only makes arguments seem persuasive but can significantly undermine the academic effectiveness of writing and analytical reasoning.

By learning to identify, classify, and rectify these fallacies and distortions, students can hone their critical thinking prowess.

Understanding cognitive distortions can also offer students insight into their own thought processes, promoting better mental health and self-awareness.

This is our pathway to equipping students to become informed and active participants in their communities. They will evolve beyond just being better learners, growing into informed and emotionally resilient citizens.

That’s why in Congress, I will champion the inclusion of critical thinking education in our school curriculum, ensuring that future generations are well-equipped to navigate the complexities of today’s information age and social media landscape.

The goal is to instill a culture of rational discourse and evidence-based decision-making right from the classroom, laying a strong foundation for a fair and rational society.

If you’d like to learn more about my campaign, visit JbForCongress.com

The fabric of our nation’s future is woven in the classrooms of today. But what happens when the threads of political discord entangle the loom?

Our children’s education has become a battleground for Republicans and Democrats, each pulling the reins of the curriculum to align with their ideological stances.

In California, GOP school boards have made strides pushing socially conservative policies, raising eyebrows among the traditionally Democratic education establishment​.

Democrats, traditionally allied with public education, now face a conundrum as Republican-led states enact historic private school choice laws, reflecting a growing appetite for educational autonomy among families.

The dichotomy is stark — while Democrats emphasize a collective approach to education, Republicans lean towards individual choice and autonomy.

This tug-of-war leaves our schools in a state of flux, hindered by a lack of consistent vision. This discord manifests in starkly divergent opinions on fundamental educational entities.

For instance, a significant portion of Republicans see the U.S. Department of Education negatively, while Democrats view it favorably​​.

The crux of the matter transcends beyond mere policy differences — it’s about how these differences barricade progress, leaving our schools in a quagmire of inconsistency and our children in a labyrinth of educational uncertainty.

By empowering families with the autonomy to choose the right educational path for their children, we can transcend partisan gridlock and recenter focus on what truly matters — the holistic development of our young minds.

In Congress, my advocacy will be for a bipartisan approach to education reform, emphasizing a curriculum attuned to the future of work, broadening access to mental health services for students, and nurturing entrepreneurship and innovation.

This approach aims to guarantee the future leaders of our country with access to a quality education tailored to their individual needs, undeterred by the prevailing political atmosphere.

To learn more about my campaign, visit JbForCongress.com