The Uncertainty Beneath the Headlines

A week ago, I wrote The Council of Hope, Fear and Jealousy while much of the world’s attention was fixed on the confrontation between the United States and Iran. The headlines have since moved on, as they always do, although the consequences continue to travel quietly across borders.

People living close to the battlefield measure uncertainty through physical danger and survival. Millions of others encounter its consequences in different ways: through higher living costs, volatile energy prices, economic insecurity and difficult decisions made around kitchen tables rather than negotiating tables.

The lingering sense of uncertainty stayed with me as I travelled in recent months through Tokyo, Nairobi, Dubai and New Delhi. Each city possessed its own rhythm, culture and pace, yet the conversations I encountered shared a remarkable familiarity.

I spent more time listening than speaking. Shopkeepers spoke about customers. Entrepreneurs searched for capital. Taxi drivers talked about fuel prices. Parents worried about education, while young professionals searched for opportunities that might offer them a more secure future.

Very few people were discussing artificial intelligence, semiconductor policy or geopolitical rivalry. Their concerns were immediate and deeply human. They wanted stable employment, affordable living, healthy families and the confidence that tomorrow might offer more opportunity than today.

Those conversations reminded me that the view from the street often looks very different from the view presented on conference stages. Technology may reshape the future, but most people experience the future through the ordinary circumstances of daily life.

Two Chapters of the Same Story

A few weeks later, I spent time with several former multinational corporate executives who had chosen to retire before reaching sixty. During their careers, they had lived inside organisations where discussions revolved around growth targets, market share, acquisitions and quarterly performance.

I expected those familiar themes to continue, even after retirement. Instead, I found myself listening to reflections about health, grandchildren, ageing parents, friendships and purpose.

Success had quietly changed its meaning. The dashboards, presentations and boardroom conversations that had once defined their professional lives had given way to questions about time, family and how best to use the years still ahead of them.

Shortly afterwards, I met younger people preparing to enter that same corporate world. Their conversations carried a different energy. They spoke about careers that had not existed a decade ago, businesses without borders and technologies advancing faster than universities could redesign their courses.

They were ambitious, adaptable and optimistic, although uncertainty was never far away. More than one observed that the future would demand a degree of maturity from today’s leaders that young people did not always see around them.

Listening to both generations, I realised I was hearing two chapters of the same story. One group was discovering what mattered after achievement. The other was wondering what achievement itself might look like in a world being reshaped by technology.

The distance between those conversations was measured less by age than by where each generation stood along life’s journey. One was looking back at the promises of success. The other was looking forward and asking whether those promises would still hold.

Two Visions of Artificial Intelligence

While these conversations unfolded quietly across homes, cafés and city streets, another conversation was taking place inside boardrooms, research laboratories and government ministries.

Much of the public discussion surrounding artificial intelligence before the World Artificial Intelligence Conference in Shanghai revolved around companies and the individuals leading them. Elon Musk and xAI, Sam Altman at OpenAI, the Amodei siblings at Anthropic and Google’s continuing advances dominated headlines. Funding rounds, frontier models, benchmark scores and corporate valuations became the language through which progress was measured.

Artificial intelligence was increasingly presented as a contest of corporate capability.

Shanghai introduced a noticeably different vocabulary. President Xi Jinping spoke less about individual companies and more about institutions, international cooperation and national development. The establishment of the World Artificial Intelligence Cooperation Organization, supported initially by 29 countries, signalled China’s intention to frame artificial intelligence as part of an emerging international order rather than simply another commercial technology.

The emphasis shifted from founders to governments, from products to governance and from corporate competition to national capability.

The contrast was difficult to ignore. In the United States, the most visible AI narrative remains predominantly entrepreneurial and corporate. China’s official narrative is more national and institutional. These are not absolute distinctions: American government policy plays an important role in technological development, just as Chinese private companies remain essential sources of innovation. The two systems place their narrative and strategic weight in different places.

Across the Pacific, the United States continues to draw much of its strength from entrepreneurial energy, private investment and the remarkable ability of companies to innovate at extraordinary speed. China increasingly speaks through long-term planning, state capacity and institutional coordination.

These are more than competing technology strategies. They represent different ways of organising progress, distributing authority and imagining the future.

The Quarrel Around the Machines

Listening to these competing narratives, I found myself paying less attention to the machines themselves and more attention to the conversation surrounding them.

Public debate increasingly resembles a quarrel around the machines, although the machines themselves remain silent. Governments debate standards. Companies compete for talent and investment. Investors measure opportunity. Media narratives amplify each breakthrough as though the next model alone will determine the future.

Artificial intelligence has become the language through which nations express strategic ambition and corporations pursue influence. It has also become a screen upon which societies project their anxieties about power, employment, security and decline.

Much quieter questions remain in the background. Every advanced model depends upon vast networks of data centres requiring electricity, water, land and resilient transmission systems. Semiconductor supply chains stretch across continents. Governments announce governance frameworks while still wrestling with implementation.

Questions surrounding infrastructure, funding, education, regulatory capacity and public trust receive far less attention than the release of the next frontier model, although they may ultimately shape the success of artificial intelligence far more profoundly.

There is also a more fundamental question: how will the benefits of that success reach those at the bottom of the economic pyramid?

The Measure of Progress

As I reflected on the conversations from Tokyo, Nairobi, Dubai and New Delhi, one observation kept returning to me. None of the people I met asked which company would build the world’s most capable model.

They wanted to know whether they could build a business, educate their children, find meaningful work and retire with dignity. Their questions have remained remarkably consistent even as the technologies surrounding them evolve at extraordinary speed.

The longer I sat with those conversations, the more I felt that the real transition taking place was larger than technology alone. Artificial intelligence is undoubtedly testing the capabilities of machines. At the same time, it is testing the resilience of institutions, the maturity of leadership and the ability of societies to translate extraordinary innovation into ordinary human progress.

A model may achieve extraordinary results on a benchmark while the society around it struggles to provide reliable electricity, useful education or economic security. A country may lead in computing power yet fail to persuade its citizens that technological progress is improving their lives.

The ultimate measure of artificial intelligence may therefore lie not only in what the technology can accomplish, but in whether institutions can direct that capability toward human purposes.

What the Mirror Reveals

When I think back to these past few months, I remember very little about benchmark scores or product announcements.

I remember the retired executive searching for purpose beyond success. I remember the young graduate wondering where opportunity might lead. I remember parents quietly calculating household expenses while imagining a better future for their children.

Those faces have stayed with me far longer than the specifications of any model.

A mirror has never been responsible for the image it reflects. Its quiet purpose is simply to reveal what is already standing before it.

Artificial intelligence may become one of the most remarkable technologies our civilisation has ever created. Yet the more enduring question concerns something far older than technology itself.

As we look into that mirror, we are also looking at our institutions, our priorities, our ambitions and our capacity for wisdom. The reflection before us is not only the future of the machine.

It is the future we are choosing for ourselves.

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In this econVue/Hale Strategic panel, David Johnson, Marta E. Wosińska, and Shannon Morfin examine why America’s medicine supply chain is fragile — and what it would take to make it resilient.

Panel Recap

While rare earths have been in the spotlight, another critical supply chain is also at risk in the current geopolitical environment: medicines.

The panel examined vulnerabilities in pharmaceutical quality and supply in the US, and the broader policy and economic forces that have left critical medicines and medical devices increasingly exposed to disruption — with potential consequences for almost every American family.

The discussion explored the history and current role of foreign dependence, including China, but also moved beyond a simple “China risk” frame. The panelists emphasized that America’s pharmaceutical vulnerabilities are product-specific, market-specific, and often buried upstream — in key starting materials, active pharmaceutical ingredients, sterile injectables, antibiotics, hospital drugs, and other medical inputs.

The larger conclusion was clear: pharmaceutical supply-chain resilience is not only a healthcare issue. It is a national resilience issue.

What We Learned

One of the panel’s strongest themes was the distinction between branded and generic drugs.

“Branded and generic drugs are really two different planets.” — Marta E. Wosińska

Branded drugs dominate the public conversation about prices and innovation. But many of the most serious supply-chain vulnerabilities are in generic drugs — especially low-margin hospital workhorse medicines such as sterile injectables, antibiotics, oncology generics, anesthetics, IV fluids, and other essential inputs.

The panel also explored the economic roots of these vulnerabilities. In a market where purchasers reward the lowest price, no one clearly pays for redundancy, quality systems, reserve capacity, or resilient manufacturing.

“Nobody in the supply chain truly internalizes the harm that results from shortages.” — Marta E. Wosińska

David Johnson placed the issue in the broader context of US healthcare economics, arguing that the problem is not simply lack of spending, but distorted incentives.

“We spend enough money. We just don’t get the results.” — David Johnson

Shannon Morfin emphasized that resilience cannot be solved with vague calls for “more manufacturing.” The system needs the right capacity for the right products, supported by the right financing and operational visibility.

“A facility that makes medical gloves cannot solve a shortage for penicillin.” — Shannon Morfin

Why This Matters

China’s role in the pharmaceutical supply chain is not limited to finished pills. According to Rosemary Gibson’s 2026 Senate testimony, China controls roughly 90 percent of the global supply of certain key starting materials — the chemical inputs used to make active pharmaceutical ingredients, or APIs. APIs are the components of medicines that produce the intended therapeutic effect.

That vulnerability extends beyond generics to the broader medicine supply chain, including antibiotics, hospital drugs, injectables, and medical devices.

But the panel also made clear that China is the clearest example of a broader resilience problem. Supply chains can be disrupted by war, export controls, pandemics, earthquakes, cyberattacks, port closures, plant shutdowns, quality failures, or natural disasters. The question is whether the United States has enough visibility, redundancy, and capacity to withstand a serious disruption.

Panelists

Lyric Hughes Hale is editor-in-chief of econVue and founder of the Hale Strategic Resources Initiative, a nonprofit research organization focused on critical resources, supply chains, and national resilience. She moderated the panel.

David Johnson, economist and CEO of 4sight Health, a Chicago-based advisory company working at the intersection of healthcare strategy, economics, and innovation.

Marta E. Wosińska, PhD, Senior Fellow at the Center on Health Policy at the Brookings Institution.

Shannon Morfin, CEO and Founder of LifeScienceX, focused on life-science, pharmaceutical, CDMO, and healthcare infrastructure, including capital formation and resilient manufacturing capacity.

Additional Reading and References

Recommended by Marta E. Wosińska

The Economics of Generic Drug Shortages: The Limits of Competition
American Economic Association backgrounder on how intense price competition in generic-drug markets can contribute to shortages, underinvestment, and supply-chain fragility.

The Economics of Generic Drug Shortages
Brookings summary of the economic puzzle of generic-drug shortages and policy interventions for a more resilient U.S. generic-drug supply.

When Medicine Supply Chains Become Weapons: China’s Leverage and How the U.S. Should Respond
Brookings analysis of China’s role in pharmaceutical supply chains, upstream dependence, and policy options to reduce strategic vulnerability.

When Cheap Becomes Fragile: How the Race to the Bottom in Generics Undermines Manufacturing Quality and What to Do About It
Brookings testimony on the relationship between generic-drug economics, manufacturing quality problems, and shortages.

Prescription Drug Shortages and Supply Chain Reliability
Brookings resource page collecting Wosińska’s work on drug shortages, pharmaceutical tariffs, DEA-related constraints, compounding, GLP-1s, generic-drug economics, and supply-chain reliability.

Recommended by Shannon Morfin

Rosemary Gibson, Testimony before the U.S. Senate Special Committee on Aging, “Foreign Dependence: How China Captured America’s Drug Supply”
Gibson’s March 11, 2026 testimony focuses on US dependence on China for medicines and the critical upstream inputs used to make them. She emphasizes that generic medicines are the “workhorse” of the US healthcare system and states that China controls approximately 90 percent of the global supply of key starting materials used to make APIs in generic drugs.

Testimony Gibson 03

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Gordon G. Chang, Testimony before the U.S. Senate Special Committee on Aging, “Foreign Dependence: How China Captured America’s Drug Supply”
Chang’s testimony frames pharmaceutical dependence as a national-security issue and argues for a mix of onshoring, public subsidies, and market incentives. He cites China’s monopolies or near-monopolies in pharmaceuticals, dependence on Chinese APIs and key starting materials, and the importance of generic drugs in US prescription volume.

Testimony Chang 03

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Ted Yoho, DVM, Testimony before the US Senate Special Committee on Aging, “Foreign Dependence: How China Captured America’s Drug Supply”
Yoho’s testimony emphasizes quality, inspection, and safety concerns related to foreign-manufactured medicines and pharmaceutical inputs, including the challenges of oversight when production has moved offshore.

Testimony Yoho 03

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Related Hale Strategic Analysis

Audrey Levisay, “Fragile by Design: How the IV Fluid Crisis Exposed America’s Sterile Injectable Drug Shortage Problem — Part 1”
Hale Strategic’s first article in a series on the fragility of America’s medical supply chains. Levisay begins with the 2024 IV fluid shortage, a crisis triggered by Hurricane Helene but rooted in a deeper problem: the lack of redundancy and resilience in the production of essential medical products.

Policy and Preparedness Background

Pandemic and All-Hazards Preparedness Act of 2006
This law strengthened the federal public-health emergency preparedness and response framework, including the role of the Assistant Secretary for Preparedness and Response, medical surge capacity, hospital preparedness, and the Strategic National Stockpile:

Pahpa Plaw 109publ417 (1)

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Strategic National Stockpile and Strategic API Reserves
The panel’s discussion of resilience also points to the distinction between emergency stockpiles of medical countermeasures and broader supply-chain capacity for essential medicines, including APIs, key starting materials, and other upstream inputs. A central policy question is whether stockpiles are designed merely to store products or to support a functioning, replenishable resilience system.

About the Hale Strategic Resources Initiative

Hale Strategic Resources Initiative

The official site of the Hale Strategic Resources Initiative, and the HSRI newsletter, supporting economic security and resiliency with a special focus on the American Midwest.

By Lyric Hughes Hale

Editor’s Note: In this VuePoint, Kathleen Graham examines one of the most under-appreciated costs of the AI era: the rising burden of verification. As generative AI makes images, documents, voices, and even institutional records easier to manipulate, trust itself becomes a form of economic infrastructure. Graham’s central insight is that AI does not simply reduce the cost of producing information; it also raises the transaction cost of determining whether information is genuine. The question is no longer simply whether AI can produce more content or accelerate analysis, but whether companies, markets, courts, and individuals can still verify what is real.

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“Trust, but verify” is a Russian proverb that became famous globally when President Ronald Reagan made it his signature phrase in discussions with Soviet leader Mikhail Gorbachev during the negotiations that led to the 1987 signing of the Intermediate-Range Nuclear Forces Treaty. When Gorbachev once asked why Reagan repeated the phrase at every meeting, Reagan replied, “I like it.”^[1]

Many others have agreed. The phrase has endured because it captures a standard method for working effectively with others: one could place reliance on the character, ability, strength, and truthfulness of another person, while also verifying that the person, the promise, and the promised action were genuine at every step of an agreement.

Today, that standard is under pressure. With the advent of generative AI, images, documents, voices, videos, and other materials can now mimic actual people and their creations with extraordinary precision. It is increasingly difficult to know whether what one is seeing, hearing, or reading is real — or a deepfake. Hany Farid, one of the world’s leading deepfake experts, has recently warned that even he can no longer reliably distinguish between real and manipulated media created by sophisticated generative AI models.^[2]

The questions now become unavoidable: How does one trust in a world where the real and the manipulated version of the real appear identical? How does one verify in a world where the real and the manipulated version of the real appear identical? The distinction matters because only the real person, institution, or system can deliver what was promised. In economic terms, AI is not only changing what can be produced; it is changing what must be verified before people, firms, and institutions can act.^[3]

It is useful here to distinguish between manipulation and persuasion. Merriam-Webster defines a deepfake as a digital image, video, voice, or other material that has been convincingly generated or altered to misrepresent someone as doing or saying something that was not actually done or said.^[4] The American Psychological Association (APA) defines manipulation as behavior designed to exploit, control, or otherwise influence others to one’s advantage.^[5] Misrepresenting what someone said or did is manipulation.

Persuasion is different. The APA defines persuasion as an active attempt by one person to change another person’s attitudes, beliefs, or emotions about an issue, person, concept, or object.^[6] Persuasion may try to change someone’s mind, but it does not require falsifying reality. Manipulation does.

This article first provides examples of what generative AI models are now producing and why they raise urgent questions about verification. It then turns to ways individuals, companies, and institutions can begin to verify in this new AI era so that trust can be rebuilt. The uncomfortable reality is that moving through this period may require more work, more caution, and more time than earlier methods of verification required.

However, our current situation is not the first era in which technological disruption, disasters, political realignment, and social confusion have made it difficult to distinguish what is true from what is false. The 1930s brought rapid technological change — turbojet engines, commercial aviation, frozen foods, radio as mass media, sound films, color films, stereophonic sound, trans-Pacific flight, airmail across the Atlantic, and the first regular high-definition television service.^[7]

At the same time, the world endured the Dust Bowl, severe famines in the Soviet Union and China,^[8] catastrophic floods in China, and the Great Depression. Major political realignments also occurred with the rise of the Nazi Party, the Spanish Civil War, the founding of Saudi Arabia, Gandhi’s movement in India, and the wars between China and Japan.^[9]

It was an era in which the world felt topsy-turvy. Groucho Marx captured this mood in Duck Soup with the line, “Who are you going to believe, me or your own eyes?” The joke worked because people understood the dilemma: should one trust one’s own perceptions, or accept another version of reality offered by someone else?^[10]

That dilemma is very close to the situation that we face now at the beginning of the AI era. Once again, we must do the extra work of critical thinking,^[11] scrutinizing information, and refusing to accept appearances at face value. Ronald Reagan said, “The future doesn’t belong to the fainthearted; it belongs to the brave.”^[12]

We choose to be brave...and here are some ways to rebuild the habits and systems that allow us to verify.

The New Verification Burden

The scale of AI-generated content is already enormous. A Graphite/Originality.ai study found that by late 2025, 52% of newly published online articles were AI-generated, up from roughly 10% in late 2022.^[13] Ahrefs independently found that 74.2% of 900,000 newly created web pages contained AI-generated content. The “50/50 split” has become the new normal. AI content growth may have plateaued as a share of new web content, but total content production is still rising. There is simply more of everything.^[14]

The consequences are not abstract. AI-generated mushroom-foraging guides on Amazon have reportedly contained potentially lethal misidentifications.^[15] AI medical advice proliferates without peer review. AI-generated political imagery — from fabricated campaign images to false disaster photos — can spread faster than fact-checkers can respond.

When visual evidence becomes unreliable, democratic participation suffers. Real musicians and artists lose royalties to AI content stuffing. Human writers compete with AI content farms. Major institutions risk credibility damage when hallucinated content is published under their name, as happened when the Chicago Sun-Times published a summer reading list in which 10 of 15 recommended books were AI-generated hallucinations.^[16]

The psychological effects are also significant. A 2026 Malwarebytes report on AI scams found that nearly 9 in 10 people say they can no longer tell what is real from AI.^[17] The result is a persistent unease: the “black box effect” of not knowing whether what one is encountering is authentic.^[18]

The corporate repercussions are already visible. The Spring 2026 issue of Chicago Booth Review was titled “Going Deep Inside the AI Revolution.” Its introduction page gives several dramatic recent examples: X CEO Linda Yaccarino resigned in July 2025 after the platform’s Grok chatbot produced pro-Hitler and antisemitic messages; McDonald’s hiring chatbot exposed the personal information of 64 million job applicants after researchers discovered that anyone could access a test administrative account by typing “123456” as the password; Lenovo’s AI-powered customer-support chatbot gave unauthorized access to support systems after a malicious prompt instructed the AI to ignore its own security protocols.^[19] Adding to the concern, Matt Robinson’s article in that same issue explores how “our understanding of how AI ‘reasons’ is startlingly limited.”^[20]

The Chicago Booth Review editors of that edition posed the question: “AI is a technology created by people and driven by human knowledge, yet we do not fully understand how it works. If something goes wrong — if a chatbot provides dangerous answers, overshares sensitive data, stores information improperly, or behaves deceptively — how can we ensure that AI is safe to deploy?”^[21]

There are financial repercussions as well. Companies are increasing their AI budgets, but many are still seeing lackluster productivity gains while computing power and usage costs rise, as revealed by a 2026 Bain & Company survey.^[22] A Sage/IDC survey of 2,275 senior financial decision-makers found that finance leaders are spending nearly 13 hours a week validating AI-generated outputs.^[23] Verification is expensive. AI can create more work than it saves. Trust (or the lack thereof), not capability, may become the primary constraint on AI adoption.

There are also legal risks. AI transcription, meeting-summary, screen-recording, and collaboration tools can create unintentional digital paper trails. These records may expand what is discoverable in litigation or accessible to regulators. In 2023, 62% of global general counsel reported new issues related to collaboration platforms, chat apps, file shares, and cloud systems at work.^[24]

Courts are also confronting numerous AI-generated legal errors, including a case in which lawyers on both sides submitted briefs to the court that relied on AI-generated filings containing fabricated citations, resulting in the judge dismissing the case, sanctioning the lawyers on both sides, and barring two of them from the court for two years.^[25]

Finally, there are resource and infrastructure risks. Every AI query incurs costs: chips, data centers, electricity, water, copper, and other critical inputs.^[26] AI detectors can help, but they are imperfect, especially for shorter texts.^[27] McKinsey’s 2026 State of AI Trust report found that security and risk concerns remain the top barrier to scaling agentic AI, while active mitigation lags behind risk awareness across nearly every AI risk category.^[28]

Together, these scenarios are creating the new verification tax burden. AI may reduce the cost of producing content, analysis, and synthetic media, but it also raises the cost of knowing what is real.

Trust Is Economic Infrastructure

Trust is not soft and it is not new. Trust is economic infrastructure.

Societies and individuals with higher levels of interpersonal trust consistently outperform their lower-trust counterparts on economic and institutional measures. Higher trust is associated with stronger economic growth, better institutions, lower transaction costs, higher investment rates, and more reliable contract enforcement.^[29]

Participation in financial markets depends heavily on generalized trust. Collaboration and governance are easier when parties do not have to rely on lengthy contracts, expensive enforcement, and constant suspicion.^[30]

Economists have long understood this connection. Nobel Laureate Kenneth Arrow famously observed that “virtually every commercial transaction has within itself an element of trust, certainly any transaction conducted over a period of time.”^[31]

University of Chicago Professor Ronald Coase’s pioneering papers—The Nature of the Firm in 1937^[32] and The Problem of Social Cost in 1960^[33]—led to his receiving in 1991 the Nobel Prize for Economics, for “his discovery and clarification of the significance of transaction costs…[in] the functioning of the economy.”^[34]

Nobel Laureate Oliver Williamson built on Coase’s research by proving that “institutions are susceptible to analysis,” which can be performed by (1) Keep it simple, by focusing on the main issue; (2) Get it right, which “includes translating economic concepts into accurate mathematics with further operations correctly performed and verified;” (3) Make it plausible, by “describing human actors in (reasonably) veridical ways and maintaining meaningful contact with the phenomena of interest (contractual or otherwise);” (4) Derive refutable implications from the veridical human actors descriptions—i.e., “their cognitive, self-interestedness, and feasible foresight respects” and then “submitting this data to empirical testing.”^[35]

Arrow, Coase, Williamson, and other new institutional economists have proven why transaction costs matter: when the costs of search, bargaining, monitoring, and enforcement rise, the result is that markets, firms, and humans change their behavior accordingly.^[36]

AI-generated uncertainty imposes a direct economic burden on transaction costs, because it causes transaction costs to rise due to the the increased need for verification.

Trust saves money. When people observe that behavior is driven by external incentives rather than genuine intent, they update their beliefs about others’ trustworthiness downward. Changed incentives change behavior. Changed behavior changes beliefs. The result can become a self-reinforcing spiral toward distrust, lower productivity, and higher costs.^[37]

A lack of trust affects economic stability through higher transaction costs, reduced investment, lower consumer spending, and the erosion of institutional credibility.^[38] If a counterpart does not trust you, resistance is almost certain.^[39] Businesses thrive on the cumulative trust their stakeholders place in them, as is true of governments.^[40]

Hany Farid has warned that today’s deepfakes have become part of the background of modern life: scammer tools, social-media weapons, video-call impersonations, and voice clones that can mimic a child calling a parent in distress. In this environment, speed is the point. By the time a fake is disproved, the damage is often already done.

Farid emphasizes that much of what we call artificial intelligence is built on human labor: human annotation, human judgment, human selection, and human correction. Human origin matters for education, business, law, and governance. Students are already using these tools. Professionals are already using these tools. The question is not whether AI will be present, but what people need to learn in a world where these tools are always nearby.

He says that what we have lived with for the past 20 years in social-media disinformation is now being amplified by generative AI: more sophisticated bots, fake images, fake video, fake voices, and fake evidence. His advice: if we want a world where evidence still counts, we must rebuild the rules of liability and go after the choke points that make digital deception cheap and profitable.

Farid concludes that the trust infrastructure needs to be rebuilt for the age of generative AI. His view is that the issue extends far beyond social media. Courts must decide how to trust evidence in civil, criminal, and national-security cases. Companies must decide how to trust AI systems embedded in operations. Governments must decide how to trust AI-enabled systems that may eventually touch critical infrastructure.^[41]

Clearly, something fundamental is shifting in society. Decisions made over the next few years will define the future of our economy, of our institutions, and of our quality of life.

Ten Ways to Verify in an AI-Generated World

1. Meet new people in person whenever possible. Verify that the person you met is who they say they are by meeting others who can confirm their identity and background. Do not rely only on online information. When appropriate, establish a safe word, code phrase, or shared fact for future verification. There is an additional benefit from meeting in person: Nicholas Epley, professor of behavioral science at the University of Chicago Booth School of Business and author of Mindwise and A Little More Social, has shown that in-person conversations build connection, relationships, and information-sharing more effectively than online interaction.^[42]

2. Minimize and protect the amount of personal information you keep online. This practice includes checking your information on LinkedIn, Facebook, and other social platforms. The more public information available about you, the easier it becomes for someone to impersonate you or manipulate others using your identity.

3. Do not use the same email addresses or phone numbers for financial accounts and social media. Using different personal, financial, and public-facing contact information (email addresses, phone numbers, etc.) reduces the risk that one compromised source can be used to access another. Double-check long-standing accounts to verify that crucial information hasn’t been used recently on social media.

4. Do not click on links reflexively. Look up the information separately through a trusted source or official website. Carefully double-check logos, company names, and other info provided, especially when these fakes look legitimate and you are in a hurry.

5. If someone you do not know calls you, hang up and call back through a verified number. Use a main number or official contact source whenever possible.

6. If someone you do not know emails you, check them carefully. Confirm through another person or independent channel that the sender is real before responding, sending money, sharing information, or clicking anything.

7. Treat disinformation security as part of cybersecurity. It’s important that organizations focus on whether systems are technically secure and whether inaccurate or manipulated information is leaking into systems, data, decisions, and thought processes. Critical thinking and evergreen premortems are some of the tools that can help expose and minimize disinformation security issues.

8. Include verification costs in AI return-on-investment calculations. AI may improve at computer-science speed, but the production of final products and services still require humans and capital, which operate at different speeds and schedules. AI also does not yet reliably assess overall enterprise risk, set strategy, protect governance, build relationships, or perform business development. These roles remain human strengths. Moreover, AI depends on capital: money, land, energy, data centers, chips, water, rare earth minerals, machines, and robots. These human and capital inputs move at a different cadence from AI and are potential substitutions for AI, sometimes at a lesser overall cost.^[43] To ensure accurate AI cost-benefit analysis, the actual and potential costs of training, monitoring, disinformation risk, legal risk, infrastructure risk, substitution analysis, and contingency planning are necessary elements.

9. Help shape the policies that will rebuild trust. To paraphrase Hany Farid, something is clearly shifting in the world. It is therefore time to think seriously about the future and what appropriate policies are required now. The more input that comes from individuals, businesses, professional associations, universities, and governments, the more likely it is that safeguards for the AI era will cover real-world contingencies.

10. Focus on changing the infrastructure that makes deception cheap and profitable. Farid has described a world drowning in AI slop: fake war videos, fabricated political robocalls, false celebrity endorsements, AI-generated kidnapping scams, fake job applicants, fabricated identities, fake podcasts, ^[44] and manipulated images that spread faster than they can be debunked. Going after individual pieces of content is not enough as the reward mechanism is still in place. The supporting infrastructure that profits from these manipulations should be the target of laws, liability rules, platform responsibilities, and enforcement protocols designed to reduce the incentives now weaponizing generative AI against individuals, companies, and society. Changed incentives do change behavior.

Conclusion

This new AI era can be phenomenal. AI can do repetitive or lengthy work faster, freeing humans to build ideas into reality more quickly. Humans still have sustainable competitive advantages: creative thinking, judgment, relationship-building, values, purpose, and the ability to look around the corner. The “creative leap” — the flash of insight through which a new idea is born — remains deeply human.

Technology can accelerate analysis and clarify uncertainty, but it cannot replace the human purpose, values, and judgment behind decisions. The best path forward is not AI instead of humans, but AI as a trusted adviser: improving the speed, scale, and quality of decisions while keeping humans firmly in charge of the “why.”^[43]

“Trust, but verify” was once a useful rule. In the AI era, the question is harder: how now to verify? The answer will determine the strength of our trust infrastructure and, therefore, the quality and level of our future economic and institutional life.

If the economy is a skyscraper, trust is the steel framework. With brave human effort and AI’s speed, depth, and support, our future economy will stand tall.

About the Author

Footnotes

^[1] National Air and Space Museum, Smithsonian. (n.d.). INF Treaty Signing - Trust, But Verify. Air and Space Museum. https://airandspace.si.edu/multimedia-gallery/inf-treaty-signing-trust-verify

^[2] Saslow, E. (2026, June 14). The world’s leading deepfake expert no longer trusts his own eyes. https://www.nytimes.com/2026/06/14/us/ai-deepfake-hany-farid.html [paywall]. Reprinted: (2026, June 16). https://www.seattletimes.com/nation-world/the-worlds-leading-deepfake-expert-no-longer-trusts-his-own-eyes/

^[3] Catalini, C., Hui, X., Wu, J. (2026, February 25). Some Simple Economics of AGI. General Economics (econ.GN). https://doi.org/10.48550/arXiv.2602.20946

^[4] Merriam-Webster. (n.d.). Deepfake. In Merriam-Webster.com dictionary. https://www.merriam- webster.com/dictionary/deepfake

^[5] American Psychological Association. (n.d.). Manipulation. In APA dictionary of psychology.https://dictionary.apa.org/manipulation

^[6] American Psychological Association. (n.d.). Persuasion. In APA dictionary of psychology. Retrieved July 10, 2026, from https://dictionary.apa.org/persuasion

^[7] Johnston, M. (2025, November 12). Timeline of the 1930s. Encyclopedia Britannica. https://www.britannica.com/topic/Timeline-of-the-1930s

^[8] Herre, B., et al. (2025, March). Famines. Our World in Data. https://www.ourworldindata.org/famines

^[9] Forgeard, V. (2024, April 6). 1930s Timeline: Key Moments from a Transformative Decade. BrilliantIO.com. https://brilliantio.com/1930s-time-line

^[10] Thoughts in Harmony. (2024, August 1). Decoding Groucho Marx’s quote: Who are you going to believe, me or your own eyes? https://rhodetrips2110.wordpress.com/20204/08/01/decoding-groucho-marxs-quote-who-are- you-going-to-believe-me-or-your-own-eyes-from-duck-soup

^[11] Critical Thinking. In Wikipedia. https://en.wikipedia.org/wiki/Critical_thinking.

^[12] Ronald Reagan Quotes. (n.d.) The future doesn’t belong to the fainthearted. Reagan Foundation. https://www.reaganfoundation.org/ronald-reagan/quotes/the-future-doesn’t-belong-to-the-fainthearted-it

^[13] SlopDetector. (2026, February 12). The rise of AI slop. https://slopdetector.org/blog/rise-of-ai-slop

^[14] Law, R., Guan, X., & Soulo, T. (2025, May 19). 74% of new webpages include AI content. Ahrefs. https://ahrefs.com/blog/what-percentage-of-new-content-is-ai-generated

^[15] Mollman, S. (2023, September 3). Mycologists warn of life or death consequences as foraging guides written with AI chatbots crop up on Amazon. Fortune. https://fortune.com/2023/09/03/ai-written-mushroom-hunting- guides-sold-on-amazon-potentially-deadly/

^[16] Rosenblatt, K. (2025, May 21). Chicago Sun-Times admits summer book guide included fake AI-generated titles. NBC News. https://www.nbcnews.com/tech/tech-news/chicago-sun-admits-summer-book-guide-included-fake- ai-generated-titles-rcna208325

^[17] Malwarebytes. (2026, June). Face value: How AI is reshaping trust, identity, and scams. Malwarebytes. https://malwarebytes.com/ai-scams?utm_source=iterable&ut

^[18] Jones, P. (2026, January 2). The psychology behind our anxiety toward black box algorithms. Psy Post. https://www.psypost.org/the-psychology-behind-our-anxiety-toward-black-box-algorithms

^[19] Weitzman, H. & Lambert, E. (2026, Spring). Going deep inside the AI revolution [Editorial]. Chicago Booth Review. https://www.chicagobooth.edu/review/spring-2026

^[20] Robinson, M. (2026, Spring). Can we break open AI’s black box? Chicago Booth Review. https://www.chicagobooth.edu/review/spring-2026

^[21] Weitzman, H. & Lambert, E. (2026, Spring). Going deep inside the AI revolution [Editorial]. Chicago Booth Review. https://www.chicagobooth.edu/review/spring-2026

^[22] Heric, M. , Doddapaneni, P., & Debarre, A. (2026, June 1). Your AI budget is growing. Your returns aren’t. Here’s why. Bain & Company. https://www.bain.com/insights/your-ai-budget-is-growing-your-returns-arent-heres-why/

^[23] Permenter, K. (2026, June). The emerging economics of AI in finance. IDG-Sage. https://blog.insightful.accountant.com/sage-releases-idc-whitepaper-emerging-economics-of-ai-in-finance

^[24] Dinzeo, M. (2024, August 12). AI tools creating digital paper trails that could haunt companies in court. ALM Law. https://www.law.com/corpcounsel/2024/08/12/ai-tools-creating-digital-paper-trails

^[25] Tangermann, V. (2026, June 11). Furious judge cancels entire trial after finding out lawyers on both sides used AI. Futurism. https://futurism.com/artificial-intelligence-judge-cancels-trial

^[26] Brown, M. (2026, Summer). How many questions can the world afford to ask AI? Chicago Booth Review. https://www.chicagobooth.edu/review/summer-2026

^[27] Jabarian, B. & Imas, A. (2026, Spring). Data points: Do AI detectors work well enough to trust? Chicago Booth Review. https://www.chicagobooth.edu/review/spring-2026

^[28] Asaftei, G. & Roberts, R. (2026, March 25). State of AI trust in 2026: Shifting to the agentic era. McKinsey. https://www.mckinsey.com/capabilities/tech-and-ai/our-insights/tech-forward/state-of-ai-trust-in-2026- shifting-to-the-agentic-era

^[29] Grun von Jolk, R. (2026, May 5). The economics of trust. Psychology Today. https://www.psychologytoday.com/us/blog/maximizing-relationships-and-happiness-in-life/202604/the- economics-of-trust

^[30] Kalish, I., Wolf, M., & Holdowsky, J. (2021, May 20). The link between trust and economic prosperity. Deloitte. https://www.deloitte.com/us/en/insights/topics/economy/connecting-trust-and-economic-growth

^[31] Leblang, D., Smith, M., & Wesselbaum, D. (2022, November). The effect of trust on economic performance and financial access. Economics Letters, 220; 110884. https://doi.org/10.1016/j.econlet.2022.110884

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^[34] The University of Chicago Law School. (n.d.). A Nobel Winner. https://www.law.uchicago.edu/lawecon/coaseinmemoriam/nobel

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^[36] Menard, C. & Shirley, M.M. (2025). Handbook of New Institutional Economics (2nd ed., pp. 1-21). Springer. https://doi.org/10.1007/978-3-031-50810-3_4

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❝ We could change the chessboard in the same way that fracking did for US oil and gas production.”
— Heidi Crebo-Rediker

🎙️ Episode Details

Guest: Heidi Crebo-Rediker
Topic: Securing American Critical Resources
Host: Lyric Hughes Hale, Editor-in-Chief of econVue
Producer: Sam Fu
Recorded: Thursday, July 9, 2026 | 48 minutes

Episode Overview

In this episode of The Hale Report, I speak with Heidi Crebo-Rediker, senior fellow at the Council on Foreign Relations and one of the country’s leading voices on geoeconomics, economic security, and economic statecraft.

Heidi served as the first chief economist at the US Department of State, advising two secretaries of state on the intersection of economics, finance, diplomacy, and national security. Her career began with Russian area studies at Dartmouth and work on the Soviet economy during the period of perestroika — an early experience that shaped her understanding of economics not only as markets, but as power.

Our conversation centers on her new Council on Foreign Relations Special Report, co-authored with Mahnaz Khan: Leapfrogging China’s Critical Minerals Dominance: How Innovation Can Secure US Supply Chains.

The scale of the problem is easy to miss. Rare earths are not a large market. They are a small market sitting underneath very large systems.

In an earlier econVue piece, I noted that the entire global rare earth market was estimated at only $19.5 billion, while US rare earth imports from China were only about $170 million. Yet China’s October 2025 export restrictions helped trigger roughly $1.5 trillion in equity losses, while US-listed rare earth firms gained about $33 billion in market capitalization.

That is the paradox at the center of this episode: a tiny visible market can create enormous hidden dependence.

The direct import value of rare earth compounds and metals does not capture the real exposure. Rare earths enter the economy embedded in magnets, components, electronics, vehicles, defense systems, turbines, robotics, and industrial equipment. The market price of the mineral does not reflect the systemic cost of losing access.

The report argues that the United States cannot simply out-mine, out-process, or outspend China. Instead, it must use its own strengths — innovation, substitution, recovery, recycling, finance, and allies — to reduce China’s leverage over the minerals that power advanced manufacturing, defense systems, AI infrastructure, robotics, batteries, electric vehicles, wind turbines, and the technologies of the future.

As Heidi explains, the problem is not simply that China mines rare earths. Rare earths themselves are not rare. The deeper choke point is processing, manufacturing, know-how, and the production of permanent magnets — the components that make rare earth dependence matter.

China understood this early. In 2010, China cut off Japan’s access to rare earths and magnets, creating what Heidi describes as a wake-up call for advanced economies. The United States responded by investing in R&D through national labs and research universities. The result, she argues, is that some of those investments are now reaching commercialization.

That is why she sees a possibility for what she calls a “fracking moment” in critical minerals: a technology-driven shift that could change the chessboard, just as fracking changed US oil and gas production.

🎤 Topics and Key Moments

We begin with Heidi’s path into economics: studying the Soviet economy, central planning, and the transformation of post-Soviet Russia. That background gives her a distinctive view of today’s US-China competition, not simply as a trade dispute, but as a contest over economic systems, industrial capacity, and state power.

We then turn to the central question of the report: what does it mean to “leapfrog” China?

For Heidi, leapfrogging does not mean ignoring mining. Traditional mining still matters. But mining and processing projects take years, often decades, to permit, finance, build, and qualify. Innovation may offer faster routes to resilience.

Among the most promising areas:

• Rare-earth-free or reduced rare-earth magnets.
  Materials engineering may allow companies to bypass some of China’s most important choke points rather than simply replicate them.

• Biotech applied to mining.
  Heidi points to examples such as microbes being used to reopen copper mines and extract value from spent mines in cleaner and more commercially viable ways.

• Waste is a strategic resource.
  Mine tailings, e-waste, old batteries, old magnets, hard drives, phones, wind turbines, and other end-of-life products contain strategically valuable materials. The United States often treats these materials as waste and exports them, even though they can feed directly back into China’s supply chain.

As Heidi puts it, if China is restricting access to rare earth elements and magnets, it makes no sense for the United States to export waste streams that contain those very same materials.

The Business Model Problem

One of the hardest questions in the episode is how to make resilience investable quickly and at scale.

Critical minerals are strategically enormous but commercially small. Markets do not automatically pay for national-security resilience. Companies need customers, margins, financing, and predictable demand. If China can use its dominance to lower prices, flood markets, restrict inputs, or make Western projects uncommercial, then innovation alone may not be enough.

That raises the question: do the United States and its allies need price floors, collars, grants, equity investments, offtake agreements, procurement commitments, or other tools to keep non-Chinese capacity alive long enough for innovation to scale?

Heidi’s answer is that this is one area where intervention is warranted because the United States is so far behind and so dependent on China. But the tools must be used with transparency, good governance, and a clear understanding of when and why Washington should become a shareholder, lender, buyer, or guarantor.

Why Allies Matter

This is not only a US problem. Australia, Canada, Brazil, Japan, India, Europe, and others all have roles to play as producers, processors, buyers, financiers, and innovators.

The G7 has already elevated critical minerals as part of the economic-security agenda. NATO is now bringing raw materials into the defense-industrial conversation. Heidi draws a useful distinction: the G7 framework is more civilian and economic, while NATO’s interest is tied to the defense applications of magnets and heavy rare earths.

Both matter. Semiconductors, electric vehicles, robotics, turbines, MRIs, and defense systems all depend on materials whose supply chains have become a quiet fault line in global power.

🔑 Key Takeaways

1. Rare earths are not rare.
   The problem is not scarcity alone. It is processing, manufacturing, know-how, and China’s dominance of the magnet supply chain.

2. China’s leverage is now a tool of economic statecraft.
   Heidi argues that as long as vulnerabilities remain, Beijing’s ability to weaponize export controls and supply-chain dependence will remain a serious risk.

3. Innovation may be faster than traditional mining.
   New materials, waste recovery, recycling, and cleaner processing technologies could scale more quickly than conventional mining projects.

4. Waste is a strategic resource.
   End-of-life products and industrial waste streams may become “America’s next mine.” As Heidi puts it, “The low-hanging fruit is really to scale the waste-based recovery”.

5. The business model still has to work.
   Resilience will not happen unless companies can finance projects, find customers, and survive Chinese pricing power.

6. This could be a fracking moment.
   The United States has changed the global energy landscape before through innovation. Heidi argues that critical minerals may offer a similar opportunity — if we move quickly.

The HSRI Connection

This is also why this issue is so central to the work we are building at the Hale Strategic Resources Initiative — HSRI.

The strategy is increasingly clear, and allied forums can provide the diplomatic umbrella. But implementation requires bringing together groups that do not naturally sit at the same table: scientists, manufacturers, investors, regulators, insurers, defense buyers, communities, and allies.

The question is not whether America can recreate China’s mineral supply chain. The question is whether America and its allies can make China’s chokepoints less decisive.

The Challenge

For decades, globalization rewarded efficiency, low cost, and just-in-time production. Critical minerals reveal the hidden cost of that model. The United States and its allies do not need to become China. But they do need to learn how to organize science, capital, industry, policy, and strategy at scale.

That is the challenge Heidi Crebo-Rediker’s report places squarely on the table, and why this conversation matters now.

🔗 Mentioned in This Episode

• Heidi Crebo-Rediker, Council on Foreign Relations

• Leapfrogging China’s Critical Minerals Dominance: How Innovation Can Secure US Supply Chains - Council on Foreign Relations

• Mahnaz Khan, Silverado Policy Accelerator - Vice President of policy for critical supply chains. She leads the organization’s critical minerals portfolio.

• G7 Critical Minerals Action Plan / Alliance coverage

• NATO Summit Defence Industry Forum — Defence Critical Raw Materials

• NATO multinational project on defence critical raw materials

• Hale Strategic Resources Initiative — HSRI

  ---

About Our Host

Join the Conversation!

Editor’s Note: econVue fellow Saliya Weerakoon reflects on the human emotions that shape decision-making in business, diplomacy and markets. His essay arrives amid new reporting that Iran may be rebuilding suspected nuclear facilities and renewed tensions around the Strait of Hormuz.

Against that backdrop, this lyrical VuePoint calls to mind the 12th-century Persian poem “The Conference of the Birds”. Birds from around the world gather in search of a sovereign who can guide them. Their journey becomes an allegory of human fear, longing and self-knowledge — a fitting image for Weerakoon’s reflection on the invisible council of hope, fear and jealousy that accompanies decisions made under uncertainty.

---

The Limits of Logic

Some of the most important decisions in my life have also been the most difficult to explain.

They involved my family, my business and, more recently, the essays I write. I searched for evidence, listened carefully to competing views and tried to construct rational explanations before arriving at a decision. I sometimes wonder whether those decisions were ever guided by logic alone. Experience seemed to whisper quietly. Intuition occasionally interrupted reason. Hope encouraged one direction, fear questioned another, and jealousy, although less welcome, sometimes revealed itself in unexpected places.

Explaining those decisions to others often proved more difficult than making them. Rational arguments helped me understand my own thinking, although they rarely produced complete agreement around a boardroom table. Over time, I found myself returning to a simple question: if individual lives are seldom guided by logic alone, why should nations be any different?

That question gradually changed the way I observed the world. Boardrooms looked different. Governments looked different. Financial markets looked different. International negotiations also appeared less mechanical than they first seemed. Institutions express themselves through policies, strategies and carefully prepared statements. Behind those institutions, however, sit people carrying memories, ambitions, disappointments, responsibilities and uncertainty.

The Invisible Council

Perhaps civilisation has always been accompanied by an invisible council. Hope, fear and jealousy never cast a vote, sign a treaty or issue a public statement. Even so, they seem to accompany many of the decisions that eventually shape history. They wait quietly beside those entrusted with difficult choices.

Diplomacy Under Pressure

The recent diplomatic exchanges between the United States and Iran encouraged me to think about that possibility once again. Only weeks ago, an interim understanding created cautious optimism. Markets steadied. Commercial shipping through the Strait of Hormuz appeared to move toward gradual normalisation. Governments, investors and businesses briefly allowed themselves to imagine that one of the world’s most dangerous confrontations might slowly move toward greater stability.

That confidence weakened quickly. Military exchanges resumed. Political accusations returned, even as diplomatic channels remained open. New reporting and satellite imagery also raised concerns that Iran may be rebuilding suspected nuclear facilities. The understanding appeared neither fully alive nor completely abandoned. Viewed only through diplomacy, those developments may appear contradictory. Viewed through the psychology of decision-making, they may simply remind us that agreements are negotiated by people before they become documents.

Hope may encourage leaders to begin negotiating because they understand the cost of permanent conflict. Fear may persuade the same leaders to hesitate when compromise appears politically dangerous. Jealousy may quietly influence questions of prestige, influence and strategic advantage. Perhaps all three remain present, even if they never appear in official communiqués.

The Silence Around the Table

During the past few weeks, I found myself listening carefully to friends across different parts of the world. A former J.P. Morgan investment banker remained cautious about predicting financial markets because experience had taught him how quickly certainty can disappear. A Vietnam War veteran viewed the Middle East through memories formed decades ago, reminding me that old conflicts rarely leave the minds of those who lived through them. A Singaporean pioneer in artificial intelligence examined the same events through the language of systems and accelerating technology. An Indian author kept returning to the human story behind the headlines. Their conclusions differed, though each reflected a lifetime of lived experience.

Most importantly, there were many who remained silent. Their silence seemed to speak a different language. Some no longer wished to choose sides. Others appeared tired of reacting to events that felt beyond their control. Silence, I began to realise, may also be a form of judgment.

Walking through ordinary streets offers another perspective altogether. Most people I meet are not thinking about Tehran or Washington. They are thinking about rising living costs, their children’s education, their livelihoods and whether tomorrow will be a little more secure than today. The younger people I meet often express one quiet hope. They believe adults, particularly those entrusted with power, require greater maturity.

Perhaps that observation deserves as much attention as the diplomatic statements.

What Algorithms Cannot Feel

Artificial intelligence has also become part of this changing landscape. Algorithms now interpret shipping movements, commodity prices, satellite imagery, political statements and financial sentiment within seconds. Markets increasingly respond to calculations that no human mind could perform alone. Unlike the people who designed them, algorithms carry neither hope, fear nor jealousy. They simply calculate.

That distinction invites reflection rather than certainty. Algorithms appear remarkably capable of interpreting information. Human beings remain considerably more difficult to interpret. A carefully chosen diplomatic sentence may reassure financial markets while provoking political rivals. The same military action may strengthen confidence in one capital while deepening anxiety in another. Human judgment continues to move through memory, emotion, intuition and experience in ways that rarely follow mathematical precision.

The world itself appears increasingly noisy. Artificial intelligence amplifies narratives before facts have fully settled. Markets interpret political language almost instantly. Public opinion often forms before governments complete their own assessments. Decision-makers are expected to project confidence while operating with incomplete information and carrying responsibilities whose consequences may extend far beyond anything they intended.

Watching the United States and Iran over recent weeks, I found myself thinking less about missiles and memoranda than about the people carrying those responsibilities. A political leader signs a treaty. A military commander authorises an operation. A central banker makes an announcement. A chief executive commits billions of dollars. An investor deploys capital accumulated over decades. Those decisions may appear institutional from the outside, although each is ultimately experienced by a human being navigating uncertainty.

The Human Question

Perhaps that is why I keep returning to the same question. Technology continues changing the instruments through which civilisation operates. Artificial intelligence may transform economies, diplomacy and warfare in ways we are only beginning to understand. Institutions will continue evolving. Markets will become faster. Information will travel almost instantly. The human condition, however, may continue evolving at its own pace.

I do not know whether hope, fear and jealousy explain the world. They do, however, seem to appear repeatedly whenever difficult decisions are made under conditions of uncertainty. Perhaps that invisible council has always been present. It may have sat quietly beside kings and queens, presidents and prime ministers, entrepreneurs and investors, parents and children. It may also be sitting beside us today, listening patiently before the next important decision is made.

That possibility, at least, may be worth reflecting upon.

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❝ A risk of epic proportions.
— Rosemary Gibson, author of China Rx, on US reliance on foreign upstream materials for medicines, quoted in Goldman Sachs’ 2026 Investment Strategy Report

While rare earths have been in the spotlight, another critical supply chain is also at risk in the current geopolitical environment: medicines.

Our panel will examine vulnerabilities in pharmaceutical quality and supply in the US, and the broader policy and economic forces that have left critical medicines and medical devices increasingly exposed to disruption — with potential consequences for almost every American family. The conversation will also examine the history and current role of foreign dependence and how meaningful reforms could improve long-term resilience.

Why this matters

• China’s role in the pharmaceutical supply chain is not limited to finished pills. According to Rosemary Gibson’s 2026 Senate testimony, China controls roughly 90% of the global supply of certain key starting materials — the chemical inputs used to make active pharmaceutical ingredients, or APIs. (APIs are the components of medicines that produce the intended therapeutic effect.)

• That vulnerability extends beyond generics to the broader medicine supply chain, including antibiotics, hospital drugs, injectables, and medical devices.

Panelists

Lyric Hughes Hale is editor-in-chief of econVue and founder of the Hale Strategic Resources Initiative, a nonprofit research organization. She will moderate the panel and off-the-record audience discussion. A replay of the panelists’ remarks will be available to registered participants.

Panelists and participants include industry experts:

David Johnson, economist and CEO of 4sight Health, a Chicago-based advisory company working at the intersection of healthcare strategy, economics, and innovation;

Marta E. Wosińska, PhD, Senior Fellow at the Center on Health Policy at the Brookings Institution and

Shannon Morfin, CEO and co-founder of LifeScienceX, focused on life-science, pharmaceutical, CDMO, and healthcare infrastructure, including capital formation and resilient manufacturing capacity.

👥 REGISTRATION

Date: Friday, July 10 | Time: 12–1 pm (CDT)

Please register in advance for this meeting:

Register

After registering, you will receive a confirmation email containing login information and suggested reading. This event is open to all subscribers.

About the Hale Strategic Resources Initiative:

Hale Strategic Resources Initiative

The official site of the Hale Strategic Resources Initiative, and the HSRI newsletter, supporting economic security and resiliency with a special focus on the American Midwest.

By Lyric Hughes Hale

Editor’s Note: One theme has emerged repeatedly in recent months. Whether writing about Hormuz, AI infrastructure, insurance, healthcare, or monetary systems, I kept re…

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❝ A risk of epic proportions.
— Rosemary Gibson, author of China Rx, on US reliance on foreign upstream materials for medicines, quoted in Goldman Sachs’ 2026 Investment Strategy Report

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❝ A risk of epic proportions.
— Rosemary Gibson, author of China Rx, on US reliance on foreign upstream materials for medicines, quoted in Goldman Sachs’ 2026 Investment Strategy Report

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The Trump-Xi Summit in Beijing May 14-15, 2026

You are invited to an econVue virtual panel discussion on the upcoming Trump-Xi Summit, scheduled to take place in Beijing on May 14–15. The conversation will be moderated by Lyric Hughes Hale.

The meeting comes at a critical moment for US-China relations. Trade tensions, technology restrictions, rare earth dependencies, Taiwan, sanctions, and the widening geopolitical fallout from the Iran conflict are all converging ahead of the summit. Whether the meeting produces a genuine reset or merely a diplomatic pause, markets, policymakers, and allies will be watching closely for signs of how Washington and Beijing intend to manage competition in a more fragmented global economy.

👥 Panelists

Our panel will bring together three sharply informed perspectives on China: Christopher Balding, who spent much of his academic career in the PRC; Brian McCarthy, who analyzes China from a Wall Street and global macro perspective; and Eric Huang, Hale Strategic senior fellow, joining us from Taipei.

Christopher Balding is CEO of Siphtor, a financial data provider based in California, and a senior fellow at the Henry Jackson Society. He spent nine years at Peking University HSBC Business School in Shenzhen and later taught at Fulbright University Vietnam. His work focuses on China’s economy, financial markets, technology sector, and corporate governance. He is widely followed on X as @BaldingsWorld.

Brian McCarthy is the Managing Principal and Chief Strategist of Macrolens LLC. A Harvard-trained economist, he has held senior roles at Alliance Capital, AIG, Barclays, UBS, RBS, and Emerging Sovereign Group, where he managed a China-focused macro hedge fund. He founded Macrolens in 2018 to provide institutional investors with independent research on global macro trends, China, and US-China financial dynamics.

Eric Huang is a senior fellow at Hale Strategic and a recognized expert on US-China-Taiwan geopolitics. He previously represented Taiwan’s Kuomintang Party in Washington, DC, where he worked at the intersection of cross-strait relations, US policy, and Taiwan’s domestic political debate. He is frequently quoted in leading global media, including The Economist, BBC, and Bloomberg. He holds degrees from Johns Hopkins SAIS, Harvard Kennedy School, and MIT.

Lyric Hughes Hale is editor-in-chief of econVue and host of The Hale Report. A longtime observer of the Chinese economy and US-China relations, she will moderate the panel and audience Q&A.

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❝ The unhappy scenario is one in which confidence in the dollar is lost abruptly…I worry about risks to financial stability that could lead to a disorderly migration away from the dollar before adequate alternatives exist.
— Barry Eichengreen

Episode Details

Guest: Barry Eichengreen
Book: Money Beyond Borders: Global Currencies from Croesus to Crypto
Host: Lyric Hughes Hale, Editor-in-Chief of econVue
Producer: Sam Fu
Recorded: Friday, May 1, 2026 | 48 minutes

Episode Overview

Barry Eichengreen joins econVue editor Lyric Hughes Hale on the The Hale Report to discuss his new book, Money Beyond Borders: Global Currencies from Croesus to Crypto. The conversation ranges from ancient coins and Spanish silver to sterling, dollar dominance, gold, stablecoins, and central bank digital currencies. His book spans centuries, from the history of money, to the state of US dollar dominance, and the future of digital money.

Eichengreen does not believe that the dollar is about to be replaced by the euro, renminbi, gold, or crypto. Instead, he warns that geopolitical fragmentation, US debt, sanctions, pressure on Federal Reserve independence, diminished faith in institutions, and new forms of market fragility could erode trust in the dollar system faster than alternatives can develop.

The result would not be a clean transition to a new reserve currency, but a more unstable monetary system, marked by increased reserve diversification, parallel payment systems, digital money, gold accumulation, and echoes of the 1930s.

About Our Guest

Barry Eichengreen is one of the world’s leading economic historians and monetary scholars. He is Distinguished Professor of Economics and Professor of Political Science at the University of California, Berkeley, where he holds the George C. Pardee and Helen N. Pardee Chair. He is also affiliated with the National Bureau of Economic Research and the Centre for Economic Policy Research, and previously served as Senior Policy Advisor at the International Monetary Fund.

He is a regular columnist for Project Syndicate and a past president of the Economic History Association. His most recent book is Money Beyond Borders: Global Currencies from Croesus to Crypto.

🎤 Topics and Key Moments

Money Beyond Borders: Money That Travels
The conversation begins with one of the book’s central ideas: currencies become international through trade before they become tools of finance, from ancient coins to Spanish silver to the US dollar.

The Life Cycle of Global Currencies
Eichengreen discusses whether reserve currencies rise and fall according to a recognizable life cycle, and whether the dollar’s century-long global role is entering a new phase.

The Dollar Under Stress
The dollar remains dominant, but Eichengreen argues that its strength depends on more than markets. It also rests on political stability, rule of law, Fed independence, and alliance trust.

❝ International currency status has economic and financial prerequisites, but it also has important political prerequisites.

Gold, Oil, and War
The conversation explores why central banks are buying gold, how sanctions are reshaping reserve management, and how Eichengreen sees events in the Middle East.

❝ I do think events in the Middle East are dollar negative and renminbi positive.

China, Silver, and Hong Kong
Eichengreen explains why the renminbi lags far behind the dollar, what China’s silver standard period reveals about global money, and why Hong Kong’s dollar peg depends on unusually specific institutional conditions.

Crypto, Stablecoins, and CBDCs
The discussion turns to Bitcoin, stablecoins, tokenized bank deposits, and central bank digital currencies, including Eichengreen’s warning that stablecoins could create new forms of Treasury-market fragility.

❝ We know from history that something that is safe and liquid today can become unsafe and illiquid tomorrow.

Monetary Fragmentation and the 1930s Scenario
The episode’s darkest warning is not that the dollar will be replaced overnight. It is that confidence in the dollar could be lost before alternatives are ready.

❝ The unhappy scenario is one in which confidence in the dollar is lost abruptly.

Policy and Practical Takeaways
To preserve the dollar’s role, Eichengreen argues that the United States must protect Federal Reserve independence, address its fiscal trajectory, maintain institutional credibility, and reassure allies.

Mentioned in This Episode

• Barry Eichengreen, Money Beyond Borders: Global Currencies from Croesus to Crypto
  Eichengreen’s newest book and the focus of the episode.

• Barry Eichengreen, Exorbitant Privilege
  Referenced through the discussion of dollar dominance and the advantages and burdens of the dollar’s global role.

• Federal Reserve Act of 1913
  Discussed in relation to the creation of the Federal Reserve and the early use of the dollar in international trade finance.

• GENIUS Act and CLARITY Act
  The GENIUS Act, signed into law in 2025, created the first federal framework for payment stablecoins, including rules on reserves, redemption, supervision, anti-money-laundering obligations, and sanctions compliance. The related CLARITY Act, still under debate in Congress, addresses the broader digital-asset market structure by clarifying regulatory jurisdiction between the SEC and CFTC.

• Dodd-Frank Act
  Discussed in relation to post-global-financial-crisis regulation, stress tests, and capital requirements.

• Smoot-Hawley Tariff Act
  Referenced as part of the 1930s breakdown in trade and global liquidity.

• Project mBridge
  The cross-border central bank digital currency project involving China, Hong Kong, Thailand, the UAE, and Saudi Arabia.

• Simon Kuznets’s “four kinds of economies” line
  A memorable reference to “developed, developing, Argentina, and Japan,” used to explain Japan’s unusual place in the global economy.

• John Greenwood
  Referenced in connection with the Hong Kong dollar peg. Greenwood is widely associated with the design and defense of Hong Kong’s modern currency board system, which restored the Hong Kong dollar’s fixed link to the US dollar in 1983. In the episode, his views are discussed in relation to the peg’s automatic convertibility and rule-bound credibility, as a comparison to stablecoin protocols.

• Paul Warburg
  Discussed as a central figure in the creation of the Federal Reserve and Eichengreen’s chosen dinner guest.

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