As President Donald Trump’s approval rating hit a new low, he turned once again to the art of redrawing the world map. With the stroke of a pen, the President sought to erase over 400 years of cartographic history by renaming Lake Ontario as “Lake America” through executive order. Trump’s unilateral action requires that the U.S. Board on Geographic Names update its databases to “reflect the renaming of the Lake and remove all references to Lake Ontario.”

Trump’s executive order applies to all U.S. federal maps, documents, and other communications. However, experts suggest that Trump can’t force other countries, international organizations, private mapping companies, or even U.S. state governments to use the new name. Canada’s Prime Minister Mark Carney has already responded in no uncertain terms that Canada will retain the original name of Lake Ontario “today and forever.” New York Governor Kathy Hochul also rejected the use of the name “Lake America” on New York state maps.

As two geographers who have spent decades studying political toponymy, or the politics of place naming, in both the United States and Canada, we are dismayed by the careless nature of Trump’s impulsive use of place renaming as a form of political rage baiting. 

Renaming Lake Ontario is part of a larger pattern of using place naming to promote the Trump brand and his “America First” ideology. From the very outset of his second presidential term, Trump launched the so-called “Golden Age of America” by announcing that the Gulf of Mexico would be renamed the “Gulf of America.” This has now been followed with “Lake America,” and Trump even mused about possibly renaming the Atlantic or Pacific Ocean, we presume to something along the lines of “American Ocean” or “Ocean of America.”

Over the past year, Trump’s obsession with naming places has given rise to a new term—toponymic narcissism—which refers to the condition of being obsessed with naming places after oneself.  

In many respects, Trump tends to approach the world map much like the Greek mythical figure of Narcissus viewed a body of water: as an opportunity to admire the reflection of his own self-image.

The cost of this narcissistic approach to controlling and changing place names is that it obscures how these names should be shared symbolic resources that serve the broader public and not just the ambitions, grievances, or political feuds of a single individual.

The conventional process of naming geographical features along the U.S.-Canada border involves bringing a formal proposal to the U.S. Board on Geographic Names and the Geographical Names Board of Canada, along with their state and provincial counterparts on both sides of the border. There is generally an extensive consultation process to ensure all geographical naming authorities are on the same page before moving forward with a name change. Yet Trump has thrown all of this out the window simply to rage-bait a U.S. ally into submission.

While the standard place naming process is not perfect, it at least establishes an institutional procedure for review, consultation, evidence gathering, and consideration of competing claims before a geographic name is changed. By contrast, what we are witnessing under Trump 2.0 is a unilateral naming by decree or whim with seemingly no public discussion or real government consideration of impacts and consequences. 

It is clear to us that Trump’s renaming of Lake Ontario is symbolic political theater aimed at diverting our attention away from the fallout of his trade war with Canada. Yet symbols matter. Place naming is a world-making practice that shapes the very foundations of our geographical imaginations and how we come to know and engage with the world.

There is a risk in dismissing Trump’s cartography of mass distraction as a frivolous symbolic tactic, since it can have real consequences for what is taught in classrooms, reconciliation efforts with Indigenous peoples, and the badly needed repair of relations between the United States and Canada.

If there is any hope to be found in the cartographic carnage that Trump is unleashing on the world map, it is that a future president can just as easily reverse these name changes in an attempt to restore America’s world image.

Recently, three events related to the U.S. Treasury bond markets have drawn public attention. For one, Japan sold some of its U.S. Treasury holdings to support the yen, and Treasury Secretary Scott Bessent intervened in the currency/debt markets to negate some of the resulting market pressures. Second, U.S. bond yields, especially at the long end, have risen alongside dollar weakness under the weight of an increased supply of dollar debt and weakening demand for it. And third, Secretary Bessent announced that the Treasury will purchase U.S. bonds, though its capacity to do so is limited.  While most people are inclined to view these as passing events, they are symptoms of a serious debt problem that appears to be progressing into a more advanced stage. 

In my book How Countries Go Broke: The Big Cycle, I laid out a template for understanding what happens when a country continuously spends more than it takes in, accumulating debt and debt service payments that rise relative to incomes. My perspective is that of an experienced global macro investor, and my understanding of this dynamic, which I will now explain, was what led me to anticipate the 2008 Great Financial Crisis and the European debt crisis that followed. 

Because I am now at a stage in life in which I want to pass along what I have learned, I wrote the book and am sharing this article in the hope that it will help people and policymakers deal with this issue well. 

How the mechanics work 

The debt dynamics of governments are analogous to those of individuals and companies with two important differences. First, when the demand for debt falls short of the supply, governments can create money through their central banks and hand it out to make it easier to pay debt (which also lowers the value of their money). Second, governments can get money from others through taxes. 

Throughout history, governments have tended to accumulate more and more debt until one or both of the following classic big debt cycle dynamics occur, leading to bad returns of debt assets and financial market crises.

First, debt service payments grow relative to incomes until they crowd out spending. Think of credit as being like blood in the economy's circulatory system. When credit circulates well and is used productively, it generates income that can service the debt that created it, which is healthy. But when debt service grows faster than the income needed to pay for it, debt-service costs accumulate like plaque in arteries, gradually crowding out other spending until eventually there is a financial heart attack. That is now happening in the U.S., but the U.S. isn’t alone. The United Kingdom, the European Union, China, and Japan all face too much debt relative to income and fiscal imbalances their governments haven’t solved.

Second, the supply of debt to be sold becomes much greater than the demand for it. As a country’s debt-service burdens grow, those who already hold a lot of the debt become less willing to buy the large amounts of new debt being offered and/or to roll over their maturing debt. Some holders even become more inclined to sell their debt holdings. At the same time, in cases when there are big capital and trade wars resulting from big geopolitical conflicts, history shows that fears of financial sanctions can hurt demand. When demand falls while supply is rapidly increasing, that causes interest rates to rise and credit growth to be curtailed. Credit and economic problems also typically occur, and there is often the "printing " of money and credit, which devalues it. In either case, that is bad for bonds. All these things are now occurring for the U.S., which adversely affects its government supply-demand balance.

The Big Debt Cycle degenerative process that follows these dynamics can easily be seen and understood by studying historic cases across many countries and is as predictable as demographic changes. Anyone who has studied monetary history should know that all monetary orders have eventually broken down, and it was this dynamic that led to the declines of previous reserve currencies and the empires behind them, most recently the British and, before that, the Dutch. Yet the process is not well understood and typically ignored until it is too late because, like unhealthy practices such as smoking and eating fatty foods, it takes place over a long time—typically over about a lifetime of around 80 years. The exact timing of the financial/economic heart attack is not easy to predict until the final symptoms appear. In my 2025 book, I estimated that it would take place in 2027, give or take two years. So far, the progression has been consistent with my estimates. It is certainly time to understand and pay attention to these dynamics. 

Just like the progression of symptoms with a disease, this degenerative process is observable and measurable. Rising debt burdens, weakening debt demand, increasing monetization, and deteriorating central-bank balance sheets can all be used as indicators of where in the cycle the process is and what is likely to happen. 

More specifically, the key red-flag indicators to watch out for are:

1. Government debt-service costs rising relative to government revenue to unacceptably squeeze out spending. 

2. The supply of government debt becoming too large relative to demand for it, causing long-term interest rates to rise faster than short-term rates.

3. The government treasury shortening the maturity of its debt sales to reduce the supply of bond sales.

4. The currency weakening, particularly relative to hard asset storeholds of wealth such as gold.

5. With a further lag, higher interest rates hurting the prices of other investment assets like stocks and real estate, and, after another lag, hurting the economy and creating credit problems.

6. Central banks "printing" money and credit, purchasing bonds, and guaranteeing debt. 

7. Central Banks incurring large losses and monetizing their own debt. 

8. Late in the cycle, governments adopting more extraordinary measures to manage the growing mismatch between their debt offering and debt service obligations and their available financing. These measures can take the form of: shutting down banks or forcing bank mergers because the banks' losses and lack of liquid funds make fully paying their depositors' withdrawals impossible; unusual financial supports for systemically important companies; the establishment of capital controls to prevent money from leaving the country; and the outlawing of hard asset monies such as gold.   

9. The process reaches a breaking point when debt service crowds out essential spending, bond supply overwhelms demand and pushes interest rates higher, or central-bank money creation becomes excessive and undermines the value of the currency. 

In all these scenarios, bondholders do poorly until debt and currency values are devalued enough to restore demand or the debt is restructured. Quite often these cycles end with a return to hard currencies and hard monetary policies to reestablish confidence in debt as an attractive, real-returning asset.  

That is the typical Big Debt Cycle. 

The U.S. situation in a nutshell 

To understand the U.S. position today, imagine that you are running a big business called the U.S. government.

This year, revenue will be roughly $5.5 trillion, while expenditures will be approximately $7.5 trillion, resulting in an anticipated deficit of nearly $2 trillion. Spending therefore exceeds income by roughly 40%. At the same time, federal debt held by the public is approximately $32 trillion, or about six times annual revenue and $240,000 per American household. Interest expenses alone are approaching $1 trillion per year, roughly 20% of revenue and about half the annual deficit.

In addition to interest payments, roughly $10 trillion of maturing principal must be refinanced. As a result, total debt-service requirements today amount to roughly $11 trillion, or about twice annual revenue.

That’s the current situation.

Looking forward, it appears most likely that things will get worse, and I estimate that projected deficits will cause the federal debt to rise to roughly $55 to $60 trillion over the next decade, requiring an additional $25-$30 trillion of debt sales. If that occurs, debt-service burdens will continue rising while increasing pressure is placed on investors to absorb ever-larger supplies of government debt assets. In addition, similarly large increases in debt and equity in supply in the U.S. private sector and in other countries that have to fund their increasing military and other expenditures will greatly add to the overall supply of debt and other financial assets.   

My 3% three-part solution

The proposed solution that I laid out in my book was to stabilize the government's debt and debt ratio to roughly 3% of GDP through a balanced combination of spending restraint, increased tax revenue, and lowered real interest rates (which would happen naturally with improved debt fundamentals). All three changes are necessary because relying excessively on any one of them would create severe and unnecessary economic pain because the adjustment would be too great. Based on my analysis, spending reductions and revenue increases of roughly 5% relative to current plans, combined with interest rates approximately 1% to 1.5% points lower than otherwise expected, would substantially reduce future debt-service costs from current projections. Lower financing costs, stronger asset prices, and improved economic activity would also support government revenues.

History shows that this kind of solution is possible. The most comparable U.S. example occurred between 1991 and 1998, when the budget deficit was reduced by roughly 5% of GDP while economic outcomes remained favorable. But because of the lack of dealing with this debt issue earlier and the resulting current level of indebtedness, plus the increased needs for capital to fund AI and military expenses, we may be past the point of no return. 

What this means for investors 

For investors, the lesson is not to try to predict the exact timing of the next debt crisis. Timing such events is a challenge for even the most experienced investors. Instead, what’s important is to recognize the long-term implications of excessive indebtedness and to diversify broadly across countries and asset classes, favoring balance-sheet strength, and be cautious about concentrating heavily in long-duration debt assets. Assets that are not government liabilities, such as gold, can provide useful diversification when governments are monetizing debts and depreciating their currencies.

Even though these debt dynamics have occurred repeatedly throughout history and are logical, they still surprise people. The key is recognizing them early enough to act before they become unmanageable. The warning signs are measurable, and the necessary adjustments are obvious based on the lessons of history. The question is whether political leaders and policymakers will understand this and act while they still can—and whether you and others will protect yourselves if they don't act. 

Data center companies “dug their own grave,” Texas Governor Greg Abbott said Sunday, and “that’s why they got the backlash they deserve.” Nine months ago, Abbott crowned Texas the epicenter of AI development, alongside Google executives announcing a $40 billion investment in the state. 
Pennsylvania’s Josh Shapiro, a Democrat who actively recruited Amazon’s $20 billion commitment to his commonwealth, made a similar U-turn days earlier, signing an executive order he calls the “nation’s strictest guardrails” on data centers: no more fast-track permits, no nondisclosure agreements, and no state permit review until developers make binding commitments to community standards.

When a Texas Republican and a Pennsylvania Democrat pivot to the same position in the same week, it becomes clear that the politics of data centers have shifted. Like everything else in AI, sentiment is moving at an extraordinary pace. Even the AI industry’s biggest winner recognizes the need for change. The tech sector needs to “do a much better job working with the communities,” Nvidia CEO Jensen Huang said this week. 

While shifting or walking back public statements never looks good, leaders are simply listening to voters’ demands. The truth is that leaders across the political spectrum are pivoting on data centers for a simple reason: they want their communities to actually benefit. The best ones are listening to citizens’ concerns while constructively raising the bar for the data center industry—not cutting them off. 

The costs and benefits of data centers

Seven in ten Americans tell Gallup they oppose a data center in their own community, more opposition than a nuclear plant draws. The primary complaint started with electric bills. PJM’s independent market monitor attributes 63% of the region’s 2025/2026 capacity price increase to data center load, roughly $9.3 billion recovered from customers across 13 states in a single year, causing household bills to rise 1.5% to 5% this summer.
The countervailing benefits are just as measurable. In Loudoun County, Virginia (often referred to as known as the "Data Center Capital of the World”), data centers supply as much as 31% of local revenue by the state legislature’s audit count, and the county has banked a $119.7 million stabilization fund against any downturn. The facilities also pay blue-collar wage premiums of 10% to 64% over comparable employers, the venture firm Andreessen Horowitz finds in Indeed postings data. The Dallas Fed has reported that skilled concrete workers, who typically make $28 to $32 per hour, are earning $45 per hour and a $150 per diem on data center jobs. And in July, the National Federation of Independent Business found that small-business optimism is at its highest levels in a year, crediting AI investment in chips and the structures that house them with spillover business opportunities.

The fight over data centers, meanwhile, has become a social and political flashpoint and, at times, embellished beyond what the record supports. Some backlash is earned. Most jobs promised are temporary. Resource demands are massive, and draining when mismanaged. Speculators have gamed interconnection queues and incentive programs, while both developers and policymakers have done a poor job communicating to the public. We heard these concerns from over 50 mayors leading cities that span the U.S. during our annual Yale Mayors College in March. 

Done well, though, these projects are a once-in-a-generation development opportunity for places ranging from underused farmland to urban brownfield sites. As Huang explained it: “This is the first time in probably the last century that we’re able to invest in sustainable energy, invest in improving our energy grid, securing our energy supply, reducing the cost of energy across the country.”

Local and federal responses

Opposition to data centers tends to concentrate at the county level because costs pool locally while benefits disperse. A county absorbs the water draw, the noise, the land conversion, and a share of the regional capacity bill. The compute serves users elsewhere, and the returns accrue to shareholders nowhere nearby. Every serious policy response attempts to move some portion of that diffuse benefit back to the community bearing the concentrated cost.

The responses span a diverse spectrum. New York paused state environmental permitting on large data centers for at least one year, pending a statewide study—the only statewide pause in effect, for now. Texas ordered an audit of every project in its grid queue, and the state’s grid operator paused new data center connections until the audit is complete. Maine’s legislature passed the first statewide construction moratorium this spring, only for Governor Janet Mills to veto the bill and create an advisory council to write standards instead. More broadly, 27 states advanced large-load legislation this year, with California, Ohio, and Utah enacting laws that exceed the industry’s voluntary ratepayer pledge to the White House.

 At the federal level, Washington continues to accelerate. A July 2025 executive order fast-tracked federal permitting, and a December preemption order, whose promised list of invalid state laws has yet to appear, expressly preserved state authority over “AI compute and data center infrastructure, other than generally applicable permitting reforms.”

Beneath the surface, the two sides are searching for a shared premise: the buildout must take the form of a mutually beneficial, transparent partnership. The public is already there. In Morning Consult polling commissioned for our June CEO Summit, 55% of Americans view data centers as a community benefit, while 69% call the backlash justified, the clearest indicator of an electorate searching for better terms, not fewer projects. 

“Don’t ban—raise the bar, ask for more,” suggests Chris Crosby, CEO of Compass Datacenters.

Meta’s Mark Zuckerberg drew the same position in his August letter, proposing a community compact of local jobs, investment in schools, and public services, held-down energy prices, and environmental care, backed by a $1 billion fund. When the company told Eagle Mountain, Utah, back in 2018 that it wanted to be a welcomed corporate partner, local public leaders answered, “Well, then we’re going to ask for some things.” And ask they did.

Virginia Governor Abigail Spanberger, whose state hosts more data centers than any other, has taken note and come to define the state’s role as ensuring “our local communities know what they can ask for and what standards they should be setting.” If knowing what to ask for is half the problem, then capacity to execute is the other half. The table often seats a county planning staff of a dozen across from a trillion-dollar counterparty, and that imbalance has unfortunately appeared in lopsided deals negotiated behind nondisclosure agreements.

Yet the smaller side of the table holds more leverage today than it may realize. The industry is desperate to scale and willing to deal. “AI is constrained today by data center capacity, not compute or software,” MARA Holdings CEO Fred Thiel tells us.

In reviewing the tariffs, statutes, audits, agreements, and published commitments behind the American AI buildout and other noteworthy economic development projects for our forthcoming book When Machines Act, we identified those practices that have produced win-win outcomes for all parties. 

Pay full freight, and sign for the total 

Our research suggests that major industry players have already accepted the central demand from communities. Data centers should pay the full grid costs of their own growth, and industry committed to do so when seven of them, from Amazon to xAI, signed the White House ratepayer pledge in March. Anthropic, though not among the signatories, also committed weeks earlier to cover the electricity price increases, transmission lines, and substations its own data centers require. “This should be the expectation across the industry,” the company wrote. Microsoft went even further, telling regulators to set rates high enough so that data center costs do not impact anyone else.

A pledge is only as good as the paper behind it, which is why Google’s Capacity Commitment Framework matters as much as any of them—a structure that includes guaranteed minimums, a security deposit, and cancellation fees a utility can collect. Water has followed the same path from promise to specification. Microsoft is aiming for a 40% improvement in datacenter water-use intensity by 2030, and Meta has pledged to restore double what it consumes in stressed watersheds.

Flexible demand response is another potential lever few contracts have adopted and is one of the cheapest options available. Duke’s Nicholas Institute calculates that if data centers trimmed their peak demand just 1% to 2%, retail electricity prices could fall as much as 2.8%. Utilities build power plants and wires to cover the few highest-demand hours of the year, so a data center that briefly tempers or shifts computing during those hours reduces the amount of new generation and transmission that must be built. The avoided construction flows through regulated rates as savings to every customer. Operators can avoid performance losses—shifting tasks in time or place during peak periods—and save up to $8.00 per megawatt-hour for their contribution.  

Trade tax breaks for assets that last 

Incentives are a different matter, costing taxpayers real money, so the first question for any state is whether a subsidy changes a company’s decision. Georgia’s independent state audit found that the sales-tax exemption changed the siting decision for roughly 30% of data center activity, and while the incentive produced a net fiscal loss of $433 million in fiscal 2025, it also returned $2.86 in economic value across the broader economy per dollar forgone. While critics carry the loss and boosters the multiplier, the audit’s real lesson belongs to neither camp. A state that pays for 10 projects to decide only three should be asking for far more than it does.

A study by the Brookings Institution finds that hyperscale sitings follow power, land, and fiber, meaning subsidies largely pay for what was coming anyway. The smarter deal asks the incoming project to fund assets the community keeps, such as transmission upgrades, roads, and water systems, that compound in value over the long run. 

Compass Datacenters’ Crosby volunteers that rationale himself. On a $5 billion project, spending $100 million on transmission upgrades “makes a lot of sense to me from a real estate perspective.” Taking a page from semiconductor industrial policy—such as Micron conditioning its Central New York megafab on a $500 million community fund shaped by 300 local civic groups—states can require data center operators to seed long-term local endowments. And New Jersey is conditioning AI data center credits on partnerships with in-state universities and startups, converting a tax break into innovation-economy seed capital. 

Write the rules before the applications arrive 

Seed capital compounds only where the rules were written before the arrival of the applications. Eagle Mountain set expectations first and approvals second. Meta spent roughly $100 million on roads and electrical service before construction, backed a creek restoration project the city expects to return 476 million gallons of water a year, and granted more than $1 million to local schools and nonprofits. The company is carrying that playbook forward to Hyperion, its largest campus yet, in Richland Parish, Louisiana, where it has pledged more than $1 billion for local roads, water, and wastewater systems and funded data center trade scholarships for every parish high school graduate—and where surging parish tax receipts funded $50,000 teacher bonuses this year.

Yet both campuses also carried confidentiality and nondisclosure agreements that cast a shadow over the goodwill earned from community investments. Data centers need to deal transparently and operate openly, since closed-door agreements breed suspicion even when the terms are generous.

Public verification, therefore, matters as much as a pledge to a long-term partnership. The city of Lancaster, Pennsylvania, publicly posted its full agreement with a data center consortium, secured the obligations with a letter of credit, and bound the counterparties to the land, all while granting no city tax breaks. Georgia’s audit process exists because of a requirement from a 2024 transparency statute. New York attaches a uniform per-megawatt host fee to large renewable projects—a renewable-siting design that data center statutes could borrow—and researchers studying the first twenty projects under the law found the fee became a floor that communities negotiated above. From another parallel case, Massachusetts addresses the root of the asymmetry by allowing the gaming commission to require casino applicants to pay the host community’s legal expenses. In policy, the standards embraced by Spanberger provide communities with the knowledge of what to ask for and how to ask for it well.

How a state sequences these tools matters as much as which it selects. States must build the accountability layer first, requiring disclosure, published agreements, and scheduled audits before offering a single incentive. The negotiated package of local benefits that Lancaster and Eagle Mountain modeled (host community frameworks) and the rate design that binds a data center to the full grid costs the industry has pledged (cost-coverage tariffs) should then pair local benefits and ratepayer protection as one package. Any incentive that follows needs to be conditioned on a “but-for test” fortified with a proportional clawback instrument, and only then should states pilot novel concepts such as flexible demand response and ownership stakes that give host communities equity in the projects themselves.

An effective state framework

Ultimately, we have found that four universal principles govern an effective state framework:

• Commitment prior to permitting: Binding community and grid compacts must precede site approvals.

• Proportionality: Infrastructure and community asks must scale directly with peak megawatt demand.

• Enforceable security: Pledges must be backed by letters of credit, escrow reserves, or parent-company guarantees.

• Statewide baseline floors: Establish statewide statutory floors to prevent developers from regulatory arbitrage across county lines.

A year ago, data center developers and their backers spent little to no time on policy. Today, some, Crosby among them, are spending as much as 80% of their time on it. As he put it: “Our social license is at risk, and we have to figure that out as an industry.”

Willingness, at times, has even outrun the law’s ability to receive it. Compass Datacenters offered the Texas Public Utility Commission $100 million toward transmission upgrades but was refused because existing law did not permit the entity to accept the funding. The mismatch captures the moment. The moment is moving faster than the rules that govern, and that pace obliges data center owners and developers to work closely and transparently with the states, localities, and communities that host their projects.

When managed properly, we believe these facilities can be monumental opportunities for the towns that attract them. The buildout, in Huang’s words, “is going to re-industrialize the United States.” If the trend persists, however, the moment could be lost to neighboring nations that do embrace them, such as border towns like Tijuana, Mexico. Even more, the demand underneath them carries national weight, too, as the buildout will help decide whether America leads the AI race with China or falls behind. What remains is establishing enforceable terms that let both sides meet in the middle, so the communities hosting the infrastructure of the AI era also hold a durable share of what is built in their backyards.

In 1937, Aldous Huxley ominously warned in Ends and Means: “Technological progress has merely provided us with more efficient means for going backwards.” As communities across the nation and across parties come to embrace this neo-Luddite resistance to data centers, some developers are listening, learning, and hopefully acting.

With research assistance from Frankie Reichman and Zander Jeinthanuttkanont.

I don’t expect anything of my friends that I don’t expect of myself.

But lately, I’ve found myself disproportionately annoyed by tiny breaches of friendship etiquette. If I ask a friend to dinner and they say they’re busy without suggesting another date, I feel slighted. If I introduce two friends and they start hanging out without me, I wonder why neither thought to include me. Then I wonder: am I holding my friends to an outdated social code? 

Today, it is common to say “let’s catch up soon” without making plans, leave invitations unanswered, and allow one person to become the permanent initiator. My theory: Technology lets us remain constantly in touch while making the obligations of friendship increasingly ambiguous.

When you think about it, an invitation is more than a logistical question, says Dr. Jeff Katzman, a psychiatrist at Silver Hill Hospital in New Canaan, Conn., who extensively studies human relationships. It’s a small relational bid: something close to, “I’d like to spend time with you. Would you like to spend time with me?” When that second part is missing, we’re left with ambiguity, and we fill in the blanks. 

“From an attachment perspective, we’re continually looking for signals about whether the people we care about are available and responsive,” says Katzman. “When I reach toward you, is somebody there? We also bring our own histories to these moments.”

Someone who has experienced rejection or exclusion may experience the same unanswered invitation quite differently from someone who has generally experienced other people as reliable. Katzman points out that we do our best to infer other people’s minds from very small pieces of behavior. “A text goes unanswered, and the human mind is remarkably good at writing the rest of the story: ‘She doesn't really care about me. He doesn’t want to see me. I’m always the one who tries,’” he explains. 

I have lost a lot of sleep about the idea of social hygiene and the small acts of reciprocity that keep friendships healthy. I was quite surprised when two of my friends in Lisbon reached out to me on the exact same day when I had said to them separately a few months ago that I might be visiting Lisbon for work on that date. The fact that both of them remembered the exact date and reached out to check if I’m in Portugal is a great example of good social hygiene. 

Whenever I make new friends now, I pay close attention. Do they regularly cancel plans at the last minute? Do they have the capacity for investing in a friendship and take on the logistical requirements of keeping an adult friendship alive? It takes roughly 50 hours of time together to move from mere acquaintance to casual friend, 90 hours to go from that stage to simple friend status, and more than 200 hours before you can consider someone your close friend, according to a report published in the Journal of Social and Personal Relationships. Getting to know someone takes a real commitment of time. 

I also think about rejection and what we reasonably owe our friends. “Reciprocity is extremely important, but I don't think reciprocity means symmetry,” says Katzman. Healthy friends don’t need to keep score. “I think of friendship a little like improvisational theater.” One person makes an offer, and the other person receives it and makes an offer back. The contributions don’t have to be identical. They’re building a scene together. One person might initiate more dinners; another might get curious a little more reliably. And at different stages of life—parenting, illness, caregiving, grief, work pressures—one person may carry more of the relationship for a while.

In good improvisation, both people help create the scene. Friendship is similar. We don’t have to say “Yes” to Tuesday night, but somehow, over time, we need to say “Yes” to the relationship. And it’s best if we can let our friends know that, in some way.

“A useful question might be: if I stopped doing all the work of maintaining this friendship, would a friendship still exist?,” asks Dr. Katzman. Sometimes, it may be worth stepping back a bit to see what happens.

When I have done that in the past, a lot of the friendships naturally dissipated, whereas when I look at all the close friendships I have now, it’s the result of mutual effort. It’s pretty similar to playing tennis, where one person hits the ball, and the other person hits it back. Sometimes, one of us drops the ball, but quickly enough it’s picked back up again to continue the game.

At the same time, we should have some humility about how many relationships any person can actively maintain. Former U.S. Surgeon General Dr. Vivek H. Murthy, in his book Together, describes concentric circles of connection: an intimate circle of close friends and confidantes, a larger relational circle of friends and companions, and a much larger collective circle of colleagues, acquaintances, and community. We need all of these kinds of connections, but we can’t maintain hundreds of relationships with the intensity of our closest friendships.

So I took a fountain pen and drew concentric circles in my journal and assigned a circle to every friend, be it close friends or acquaintances. It helped me understand that someone can genuinely value our relationship without having the bandwidth to place us in their innermost circle at a particular point in life. It also helped me assign how much energy I want to spend.

Ultimately, it helped me appreciate my friends for what they are.