Welcome to the forefront of conversational AI as we explore the fascinating world of AI chatbots in our dedicated blog series. Discover the latest advancements, applications, and strategies that propel the evolution of chatbot technology. From enhancing customer interactions to streamlining business processes, these articles delve into the innovative ways artificial intelligence is shaping the landscape of automated conversational agents. Whether you’re a business owner, developer, or simply intrigued by the future of interactive technology, join us on this journey to unravel the transformative power and endless possibilities of AI chatbots.
AI chatbots and online therapy promise easier mental health care, but technology may be eroding the boundaries, privacy and human connection that make psychotherapy effective.
While America is suffering a mental health crisis, the good news is that tens of millions of people are getting help. In 2023, 60 million adults reported having sought counseling or treatment in the previous year, and the numbers continue to rise.
Psychotherapy works because of what’s known as the therapeutic frame, a set of boundaries that create safety and structure for patients and clinicians. Sessions last 50 minutes. Fees are agreed upon prior to the start of treatment. The therapist remains neutral, shares little of their personal life, and holds confidentiality sacred.
The bad news is that the future of mental health is increasingly being built around the idea that those boundaries are obstacles. Online therapy platforms promise unlimited access. AI chatbots serve up emotional support. New software records sessions and generates clinical notes.
Each innovation claiming to improve therapy by making it faster or easier is dismantling the very framework that makes it effective. The people shaping the future of mental health often understand venture capital better than they understand the human psyche.
Take BetterHelp, for example. The world’s largest online therapy platform spent $76.9 million on podcast ads in 2021, nearly triple the next largest advertiser in any category. It is a subscription service that uses online questionnaires and algorithms to automate the process of matching patients with therapists. Its closest competitor, Talkspace, does the same. Then patients and therapists interact online via video, audio, or live chat.
While these online platforms advertise accessibility and seem like a good way to get more people into mental health care, they come with a dangerous downside.
The consensus amongst seasoned clinicians is that 20 to 25 clients per week is the sustainable upper bound for a full-time therapist. Therapists at some of these major direct-to-consumer platforms routinely report carrying 40 or more, with new clients assigned to therapists without their consent and with no path to refer anyone to other clinicians.
A clinician juggling 45 clients doesn’t have the bandwidth to give each their full attention. Clients might walk away believing therapy doesn’t work, a potentially deadly conclusion for the one in 20 American adults who reported seriously considering suicide in the past year.
And when a patient finds a therapist through one of these platforms, the platform owns the relationship. For instance, if a therapist leaves BetterHelp, they can’t take a client with them, putting an abrupt end to whatever progress may have been made.
The online therapy platforms also sell features like 24/7 messaging and unlimited therapist access, which sound good in ads but undermine another crucial part of the therapeutic frame: containment. The therapy hour is designed as a holding space, a consistent environment where the therapist and client can safely explore and process complex emotions. When the container leaks and communication flows freely outside the session, the clarity and safety of that sacred space dissolve.
At the same time, more than half of U.S. adults say they would feel comfortable discussing personal mental health issues with an AI chatbot, bypassing the desire for a licensed mental health professional altogether. A new study shows nearly one in five young adults is turning to AI chatbots for emotional support, with two-thirds of them not telling anyone they’re doing it.
Unfortunately, comfort and convenience aren’t the same as safety, and chatbots built on large language models like ChatGPT are no substitute for licensed mental health professionals.
Taking the personal touch out of therapy already is proving to have significant consequences.
Lawmakers in states like Illinois, Utah, and Nevada are recognizing the risks of turning therapy over to machines, restricting how AI companies can operate in the mental health space. And class action lawsuits and FTC settlements against large online therapy companies expose that they have engaged in everything from selling patients’ sensitive data to third-party platforms for targeted advertising purposes to matching patients with unlicensed or inappropriate therapists.
Therapists themselves are facing growing pressure to integrate AI into their practices too. New software can record therapy sessions and use AI to generate progress notes automatically. While this probably could save therapists administrative time, we have remarkably little evidence about what AI recording does to the therapeutic process. Clients can agree to being recorded and still hold back without realizing it, the same way most of us speak differently when we know someone else is listening. Before these tools become routine, we should understand how they affect the conversations they’re meant to preserve.
Technology absolutely has a place in mental health. It can help connect people with care, improve scheduling and billing, and make treatment more accessible. But when we hand over the intimate, human work of therapy to AI or prioritize efficiency over depth, we risk losing what makes therapy transformative.
Therapy’s power lies in its slowness, its privacy, and its humanity, and those qualities can’t be coded into an algorithm or outsourced to AI. If we continue to treat psychotherapy as another system to optimize, we will optimize away the very things that make it work.
A licensed psychotherapist, Paul Fugelsang is the founder and executive director of Open Path Psychotherapy Collective, which has helped more than 160,000 clients in need access affordable care through a network of 36,000 therapists across the U.S. and Canada.
Megan Cornish, LICSW, is a licensed clinical social worker, clinician advocate, and consultant to behavioral health companies.
While America is suffering a mental health crisis, the good news is that tens of millions of people are getting help. In 2023, 60 million adults reported having sought counseling or treatment in the previous year, and the numbers continue to rise.
Psychotherapy works because of what’s known as the therapeutic frame, a set of boundaries that create safety and structure for patients and clinicians. Sessions last 50 minutes. Fees are agreed upon prior to the start of treatment. The therapist remains neutral, shares little of their personal life, and holds confidentiality sacred.
The bad news is that the future of mental health is increasingly being built around the idea that those boundaries are obstacles. Online therapy platforms promise unlimited access. AI chatbots serve up emotional support. New software records sessions and generates clinical notes.
Each innovation claiming to improve therapy by making it faster or easier is dismantling the very framework that makes it effective. The people shaping the future of mental health often understand venture capital better than they understand the human psyche.
Take BetterHelp, for example. The world’s largest online therapy platform spent $76.9 million on podcast ads in 2021, nearly triple the next largest advertiser in any category. It is a subscription service that uses online questionnaires and algorithms to automate the process of matching patients with therapists. Its closest competitor, Talkspace, does the same. Then patients and therapists interact online via video, audio, or live chat.
While these online platforms advertise accessibility and seem like a good way to get more people into mental health care, they come with a dangerous downside.
The consensus amongst seasoned clinicians is that 20 to 25 clients per week is the sustainable upper bound for a full-time therapist. Therapists at some of these major direct-to-consumer platforms routinely report carrying 40 or more, with new clients assigned to therapists without their consent and with no path to refer anyone to other clinicians.
A clinician juggling 45 clients doesn’t have the bandwidth to give each their full attention. Clients might walk away believing therapy doesn’t work, a potentially deadly conclusion for the one in 20 American adults who reported seriously considering suicide in the past year.
And when a patient finds a therapist through one of these platforms, the platform owns the relationship. For instance, if a therapist leaves BetterHelp, they can’t take a client with them, putting an abrupt end to whatever progress may have been made.
The online therapy platforms also sell features like 24/7 messaging and unlimited therapist access, which sound good in ads but undermine another crucial part of the therapeutic frame: containment. The therapy hour is designed as a holding space, a consistent environment where the therapist and client can safely explore and process complex emotions. When the container leaks and communication flows freely outside the session, the clarity and safety of that sacred space dissolve.
At the same time, more than half of U.S. adults say they would feel comfortable discussing personal mental health issues with an AI chatbot, bypassing the desire for a licensed mental health professional altogether. A new study shows nearly one in five young adults is turning to AI chatbots for emotional support, with two-thirds of them not telling anyone they’re doing it.
Unfortunately, comfort and convenience aren’t the same as safety, and chatbots built on large language models like ChatGPT are no substitute for licensed mental health professionals.
Taking the personal touch out of therapy already is proving to have significant consequences.
Lawmakers in states like Illinois, Utah, and Nevada are recognizing the risks of turning therapy over to machines, restricting how AI companies can operate in the mental health space. And class action lawsuits and FTC settlements against large online therapy companies expose that they have engaged in everything from selling patients’ sensitive data to third-party platforms for targeted advertising purposes to matching patients with unlicensed or inappropriate therapists.
Therapists themselves are facing growing pressure to integrate AI into their practices too. New software can record therapy sessions and use AI to generate progress notes automatically. While this probably could save therapists administrative time, we have remarkably little evidence about what AI recording does to the therapeutic process. Clients can agree to being recorded and still hold back without realizing it, the same way most of us speak differently when we know someone else is listening. Before these tools become routine, we should understand how they affect the conversations they’re meant to preserve.
Technology absolutely has a place in mental health. It can help connect people with care, improve scheduling and billing, and make treatment more accessible. But when we hand over the intimate, human work of therapy to AI or prioritize efficiency over depth, we risk losing what makes therapy transformative.
Therapy’s power lies in its slowness, its privacy, and its humanity, and those qualities can’t be coded into an algorithm or outsourced to AI. If we continue to treat psychotherapy as another system to optimize, we will optimize away the very things that make it work.
A licensed psychotherapist, Paul Fugelsang is the founder and executive director of Open Path Psychotherapy Collective, which has helped more than 160,000 clients in need access affordable care through a network of 36,000 therapists across the U.S. and Canada.
Megan Cornish, LICSW, is a licensed clinical social worker, clinician advocate, and consultant to behavioral health companies.
Seven months ago, I attended the first day of my Reporting on Race class at USC. Taught by journalist and immigration reporting expert Jean Guerrero, the course offered growth I hadn’t yet imagined, showing me how much I could evolve as a journalist in just one semester.
For the next five months, I researched and reported on an immigration story of my choosing. I wrote about how educators in Los Angeles protect and advocate for students and communities living in fear of ICE deportations. These educators organized community street patrols to keep their neighborhoods safe. Finding sources and producing the final draft took months, but it was one of the most rewarding experiences of my journalism studies so far.
This project taught me the technicalities of immigration reporting, but more importantly, it taught me to treat these stories with the care and attention they deserve. I learned how to ensure that my sources’ perspectives were shared in the most ethical way possible.
Ethical, personal immigration reporting highlights immigrants’ experiences for the public, helping individuals feel more seen and protected.
Long before I started my piece, journalists across the country had reported on thousands of immigration stories, particularly after President Trump began his second term in office.
With the rise in ICE activity in neighborhoods across the U.S., journalists and media outlets have taken various approaches to sharing immigrant stories.
Journalism has played a vital role in documenting ICE sightings, arrests, and deportations, placing an immense responsibility on the media to inform the public about these events accurately.
Understanding how to tell these stories ethically is essential to avoid perpetuating stereotypes or spreading misinformation.
Despite prevalent misconceptions, ethical and accurate reporting on immigrant communities can counteract negative impacts and foster empathy.
Reporting that fails to account for the personal experiences of immigrants can have serious repercussions on a source’s mental and physical health, as well as their ability to live a normal life.
Widespread reporting that relies on tropes or fails to consider authentic perspectives can lead to lasting harm.
The American Civil Liberties Union reported three ways the media can introduce bias into immigration reporting, often depicting a harmful and untrue image of immigrants. Examples include paid political ads that fearmonger about the border, the over-publicization of violent border imagery, and a hyper-focus on border crossings at the expense of stories about immigrants already living across the country.
The Lenfest Institute for Journalism noted that newsrooms themselves are navigating these challenges. They offer a list of strategies to help journalists avoid the pitfalls identified by the ACLU and better serve immigrant communities.
Ultimately, bias and discrimination have long influenced immigration reporting, often sidelining the individual stories of those living in constant fear.
Immigration reporting is neither easy nor simple. It involves complex layers and risks that many readers may not realize. A primary concern for journalists is the potential danger these stories pose to vulnerable sources.
Journalists must grapple with difficult questions: when to provide anonymity, how to protect a source’s workplace, and how to safeguard their identity.
Despite these risks, potential threats can be minimized if the reporting process is handled correctly. By prioritizing accuracy and care, it is possible to protect a source while ensuring their story is heard.
Immigration reporting involves real lives and families. When approached correctly, a journalist can bring awareness to these issues without putting their sources at risk.
Despite the surge in reporting over the last few years, there are always opportunities to improve how news organizations share these sensitive stories with the public.
5 ways to make immigration reporting more ethical:
Ethical immigration reporting is essential for helping audiences understand the immigrant experience and making these communities feel heard. However, there is always room for improvement for both journalists and audiences.
There must be a collective effort from news publications to implement ethical strategies and pressure from the public to demand meaningful stories about the communities they care about.
I still draw on the lessons from my Reporting on Race class. What stayed with me most is that the most powerful stories often belong to those who haven’t yet shared their perspectives with the media—their voices are the ones that can truly shift the conversation about immigration in the United States.
Daniela Mattson is a Fulcrum Fellow, a bilingual multimedia journalist who prioritizes diverse storytelling in my reporting.
Beyond the Border: A New Standard for Ethical Immigration Reporting was first published by the Latino News Network and republished with permission.
AI is transforming finance, government, and society. As Congress considers new technology laws, the future of democratic oversight depends on wisdom, foresight, and political will.
Imagine waking up one day to find your bank account frozen because an AI system has incorrectly identified you as a fraud risk. There is no human to call, only another algorithm reviewing your appeal. Hours later, the error is corrected, but the damage has already been done.
Who is actually in charge?
What once sounded like science fiction is rapidly becoming reality as artificial intelligence assumes decisions once reserved for human judgment.
As Congress responds to disruptive technologies ranging from cryptocurrencies to artificial intelligence, it is considering proposals such as the CLARITY Act and the Great American AI Act of 2026.
That is important. But the deeper question is not simply how to regulate emerging technologies. It is whether we still possess the wisdom, foresight, and will to govern ourselves now that we wield tools capable of transforming economic, political, and social life.
Congress has governed earlier technological revolutions, from railroads to nuclear power to the internet. The hardest task has always been overcoming the human failings that keep us from acting wisely when change arrives.
Polarization, misinformation, concentrated power, greed, and political tribalism all predated AI. It did not create these problems. It magnifies them.
Artificial intelligence changes the scale of our choices, not the nature of the people making them.
The real question, then, is not whether Congress can regulate disruptive technologies. It is whether we can govern ourselves while wielding tools that amplify both our greatest strengths and our oldest weaknesses.
Congress is beginning to confront this challenge on multiple fronts.
Sponsored by Rep. French Hill (R-Ark.) with bipartisan support, the CLARITY Act seeks to bring greater certainty to digital asset markets by clarifying the responsibilities of the Securities and Exchange Commission and the Commodity Futures Trading Commission. Its goal is to encourage financial innovation while establishing clearer rules and stronger investor protections.
The Great American AI Act of 2026, released as a bipartisan discussion draft by Reps. Jay Obernolte (R-Calif.) and Lori Trahan (D-Mass.), proposes a broad federal framework for AI governance. It addresses transparency, safety, cybersecurity, research, workforce development, fraud, AI literacy, and the division of authority between federal and state governments.
Together, the proposals show Congress confronting a succession of disruptive innovations. One seeks rules for the future of finance. The other seeks oversight of technology increasingly capable of making decisions once reserved for human beings.
Their larger significance lies in what they acknowledge: technological change is accelerating across several domains, and democratic government must find a way to keep pace.
Yet no statute can supply the wisdom to understand every consequence, the foresight to anticipate every unintended outcome, or the will to act before those outcomes become crises.
Every generation believes its defining technology is unprecedented. Railroads compressed distance. Electricity transformed industry. Nuclear weapons gave humanity the capacity to destroy itself. The internet democratized information while making misinformation instantaneous. AI may reshape how we work, learn, create, govern, and decide.
Each breakthrough has expanded human power. None has expanded human wisdom at the same pace.
That is the paradox of progress: our technological capabilities advance rapidly while our capacity to govern them advances slowly, if at all.
The Founders understood the underlying dilemma. As James Madison observed in Federalist No. 51, “If men were angels, no government would be necessary.” The problem of self-government has never been technology itself. It has always been human nature.
Institutions can adapt. Harder is ensuring that those who create, regulate, and use new technologies wield them responsibly. Can human character keep pace with human capability?
That challenge comes down to three qualities: wisdom to understand what is at stake, foresight to anticipate consequences, and political will to act before events force our hand.
Wisdom begins by recognizing that not every technological advance automatically serves the public good. Societies often become captivated by what can be built before asking what should be built. Markets reward innovation. Politics rewards speed. Neither necessarily rewards reflection.
The goal is not to slow innovation, but to keep it accountable to democratic values. We should ask whether new technologies protect human dignity, preserve liberty, and broaden opportunity. Those are political questions, not technical ones, and they cannot be delegated to algorithms.
Disruptive technologies rarely produce only the outcomes their creators intend. Social media promised connection but accelerated polarization and misinformation. The internet democratized knowledge while weakening traditional gatekeepers of truth. AI will also bring extraordinary benefits alongside consequences we cannot fully predict.
Democratic government cannot foresee every outcome. It can, however, think beyond the next election, anticipate second- and third-order effects, and build institutions able to adapt. Waiting until problems become crises is not governance. It is damage control.
Wisdom identifies the problem. Foresight anticipates its consequences. Political will turns understanding into action.
This is democracy’s hardest test. Short-term incentives, partisan conflict, and powerful economic interests make it easier to postpone difficult decisions than to confront them.
Effective governance requires leaders willing to act before disaster makes action unavoidable, businesses willing to accept rules that sustain public trust, and citizens willing to value long-term democratic resilience over short-term convenience.
The debate over AI and other disruptive technologies is ultimately not about machines. It is about us.
The two proposals are attempts to keep democratic government relevant in a rapidly changing world. Their deeper lesson is that every generation must decide whether its institutions and civic character can keep pace with technology.
That is the paradox of progress. We continue to invent tools that extend human power while leaving the harder work of cultivating wisdom, foresight, and political will unfinished.
The question is no longer whether these technologies will become more powerful. They will. The question is the one posed at the beginning: Who is actually in charge? If the answer is to remain “the American people,” then our democracy must govern these technologies before they govern us.
Robert Cropf is a Professor of Political Science at Saint Louis University.
If Allison Baker and Maria Garcia apply for the same job against Matthew Owens or Joe Alvarez, and Matthew or Joe gets the job despite everything else being the same, that would seem to be a typical case of gender discrimination by the employer.
However, the names and scenarios I described were not drawn from a human example, but from AI. ChatGPT generated female candidates who were, on average, 1.6 years younger than their male counterparts and considered them less qualified than male applicants. Given AI’s pervasiveness in hiring decisions, these biases pose a significant concern.
However, AI’s bias is not limited to gender; it extends to other categories, including age: a separate study from Stanford found AI bias against older job applicants. On the opposite end of the age spectrum, in the healthcare field, a study found that pediatric patients face the highest risk of misdiagnosis across medical image foundation models, including adult-trained models that mispredict cardiomegaly (enlarged heart) in young children.
Though healthcare and hiring are majorly influenced by AI, they are hardly the only areas affected. AI has become ingrained in housing, finance, and criminal justice. Built on a foundation of biased data, these systems will undoubtedly continue to produce discriminatory results.
We are increasingly seeing AI discriminate against the very old and the very young simultaneously. In both cases, this stems from biases and underrepresentation in the training data. In image databases used to train machine learning algorithms, women are consistently portrayed as younger than men, especially in higher-status occupations. In pediatric patients, a systematic review of 181 public medical imaging datasets found that children accounted for just under 1% of the data, despite being 30% of the world’s population. This jeopardizes these systems’ ability to correctly diagnose and treat young patients, putting their lives at risk.
The source of the problem leads to a counterintuitive solution. Traditionally, equality on the basis of a class has meant making decisions without considering it, such as evaluating a job applicant without knowing their race. In human decision-making, this certainly still holds true.
However, to address discrimination from AI, the exact opposite is required: disregarding age would leave the model to the mercy of biases embedded in the training data. There must be an affirmative effort to ensure that all ages are fairly represented in the training data, which by necessity involves considering age.
These shared injuries, while extremely damaging, create a unique opportunity to form an intergenerational political coalition: one that works for both old and young people, rather than helping one at the expense of the other.
The nature of artificial intelligence necessitates new political coalitions. For decades, many political issues have pitted old against young, suggesting that for one group to benefit, the other must pay. However, artificial intelligence defies this framework: it discriminates against those it perceives as too old or too young.
This unprecedented issue calls for the formation of an intergenerational political coalition, where organizations like the AARP join young activists to co-create solutions for responsible AI governance. A robust ecosystem has developed to address other issues in AI equity, chief among them discrimination on the basis of gender and race, yet age discrimination has received little attention.
Such a coalition could yield unprecedented political power. The AARP has 38 million members fighting for those over 50. On the other hand, there are over 31 million Americans ages 18-24, though they are less mobilized into a unified organization. In comparison, AIPAC has 6 million members, the NRA has 5 million, and the AFL-CIO has 15 million.
Thus far, by excessively narrowing their political coalitions, both young and old activists deny themselves the opportunity to meaningfully address the issue they face. If older activists increasingly leverage the resources of the AARP and other organizations, while younger activists make AI age discrimination a voting priority and eventually form their own organizational infrastructure, the result would be the most powerful political coalition in American politics and the best opportunity to proactively address the problems that AI discrimination poses.
Arvind Salem is an Advocacy Associate with the Young People’s Alliance.
Could AI help fund America’s future? Explore how a sovereign wealth fund could reduce inequality, strengthen Social Security, and share AI-driven wealth.
In his recent encyclical Magnifica humanitas, Pope Leo XIV stated that humanity is at a critical turning point, facing a pivotal choice regarding Artificial Intelligence and modern digital technologies. Indeed, AI experts on both sides of the aisle have worried that accelerating advances in AI technology could cause major disruptions to our economy and workforce, including rising inequality and mass unemployment.
To address these looming challenges, the CEO of OpenAI, Sam Altman, has made a bold offer: his company will gift the US government a 5% stake. At the company’s current stock price and valuation of nearly $900 billion, a 5% holding would be worth roughly $42.6 billion. That’s a handsome sum, and Altman has also proposed that other AI companies should match his company’s offer.
If other AI-related companies, such as Google, Microsoft, Anthropic, Nvidia, and Meta/Facebook, also gift to the government 5% stakes, the total holdings would be worth around $800 billion. Under Altman’s plan, that endowment would then be used as seed money for a sovereign wealth fund (SWF).
What is a sovereign wealth fund? What are its pros and cons? In the last few weeks, why has everyone from Donald Trump to Bernie Sanders to Vice President J.D. Vance and California governor Gavin Newsom plugged their own version of an SWF?
Interest is growing because, in a time of mounting government debt and declining government funding for public goods and services, a well-designed sovereign wealth fund could do a lot to amass a huge pot of money that could then be used to pay for urgent needs such as replacement income for laid off tech workers, affordable housing, health care, basic income for the poor, Social Security retirement—all without using taxpayer dollars.
Does that sound too good to be true?
The money in a sovereign wealth fund is invested in a range of appreciating capital investments—whether stocks, bonds, real estate, energy, or technology companies—which are allowed to grow over a 5 to 15-year period. Those investments eventually turn into a much larger pool of money, which the government can then spend on various public goods and services.
Sovereign wealth funds are currently used by over 60 countries with over 100 SWFs (some countries, such as China, have more than one) that together manage over $10 trillion of assets. Norway, with only 2% of the US population, has the largest sovereign wealth fund in the world, with $2.1 trillion in assets, supercharged by oil revenue from state-owned energy companies, which is invested in stocks and other assets to grow the fund over time. Norway’s sovereign wealth fund has swelled its enormous investment portfolio to the point where it provides more money to Norway’s public budget than its oil profits do.
China has two SWFs totaling about $3.5 trillion and is using its investment returns to try and take the global lead in AI technology and other industries. Saudi Arabia, Australia, Singapore, Abu Dhabi, Kuwait and Indonesia all have an SWF worth about a trillion dollars each. In the right hands—such as Norway’s—a sovereign wealth fund can really do a lot to generate a ton of wealth for spending on public goods and services without needing to raise taxes or incur more government debt.
In the wrong hands, such as Saudi Arabia, it has been used as a slush fund by unaccountable political leaders for their own amusement. Saudi leaders have done foolish things like starting a new professional golf league, LIV Golf, which attracted grotesquely overpaid celebrity golfers, quickly lost $6 billion, and is on the verge of going bankrupt.
It’s worth noting that sovereign wealth funds are not “foreign” to American shores. In fact, 20 US states already have their own sovereign wealth funds, including Alaska ($78 billion—greater than Alaska’s state GDP), Texas ($56 billion), New Mexico ($34 billion), Wyoming ($26 billion), and North Dakota ($8.5 billion). Most of these are seeded by oil revenues earned by each state, which are then invested so that the state can benefit from ongoing investment returns. Some states, like Oregon and Minnesota, seed their SWFs with revenues earned from the public’s use of state lands. Most of these SWFs are fairly small, a couple of billion dollars or less, and nearly all of them use their funds for a single purpose: to help fund public education.
The Altman plan is certainly innovative, since US companies don’t usually give an ownership stake to a government. Once the $800 billion in seed money is invested, it could yield a net gain of $1.4 trillion to $2.5 trillion, depending on how it is allocated and for how long. But it is designed to be a one-time “wasting trust”—the Treasury gets $800 billion dollars up front, and begins an orderly liquidation over 10 years. Once 10 years have passed, the fund is finished. The one booster shot of financial adrenaline would be over. The CEOs of AI companies can say, “Hey, we tried to alleviate the harms of our invention,” but the Band-Aid would be temporary. Given that, a 5% stake is actually insufficient, and the White House should insist on more.
Even better, Norway’s and other countries’ sovereign wealth funds are self-replenishing “permanent funds,” which makes a big difference. The single-shot Altman plan wouldn’t come close to plugging the large gap in America’s looming financing needs. A better plan would be to establish a more permanent revolving fund by selling 10-year Treasury notes to the public on a month-to-month and year-to-year basis to raise seed money, which would then be invested for a decade to produce capital gains, with all Americans as beneficiaries.
With a well-designed Federal Permanent Revenue Fund, what might the federal government do with an extra three to four trillion dollars per year? It could plug the $2.5 trillion shortfall in Social Security, which by 2032 is going to result in America’s 52 million retirees taking a 22 percent haircut, a loss of about $8000 or more per year for many beneficiaries. Or the federal Department of Housing and Urban Development, which currently spends around $20 billion each year to build or preserve affordable housing, could receive a large injection of money to partner with states and ramp up housing production all across the country. Or it could be used to pay unemployment benefits to AI-displaced workers.
The possibilities—the needs—are endless. The returns to beneficiaries could take multiple forms, including housing, education, healthcare, climate mitigation, childcare, and other public services and goods. And by designing the fund to incorporate the best practices for anti-corruption management used by successful countries like Norway, Australia, and Singapore, it is possible to maintain the right institutional guardrails. Some might worry that the stock market could crash and everything will sink underwater. However, since 1928, the US stock market has risen on average about 10% per year, and the market is up roughly 3 out of every 4 years; over any five to 10 year period, investments in index funds tied to the S&P 500, the Nasdaq or Dow Jones have always risen, and often outperformed America’s top blue-chip companies such as General Electric, AIG, IBM, Ford, and General Motors.
The fact is, the greatest “gold rush” of investment gains has been occurring for the past 70 years in the US economy, and the vast majority of Americans have missed out. That’s why the top 10% of wealthiest Americans own 93% of all stock equities today. This is the exact unfairness in capitalism that Louis Kelso, the financial visionary of universal capitalism, was determined to address. Kelso was a corporate finance attorney who first crafted the blueprint with his basic formula of “form a regulated trust => raise seed money => invest seed money => let it grow over time => reap the future returns on behalf of the broader public.”
A successful sovereign wealth fund designed like Norway’s could produce greater ownership and wealth for all Americans from the future returns on the SWF’s investments. These funds would allow everyday people to benefit from the wealth creation generated by America’s most valuable businesses, and by new technologies like AI. Once initiated, a fund will take several years for its investments to reach maturity and be fully loaded. So the sooner America gets going on its launch, the better.
Steven Hill was policy director for the Center for Humane Technology, co-founder of FairVote, and political reform director at New America. See more of his writing at his Substack newsletter DemocracySOS.