Last week both Google and Apple updated their maps to accommodate Trump changing the United States Geological Survey’s recognized name for Lake Ontario to “Lake America”. Just as with Trump’s fiat renaming of the Gulf of Mexico back in the first days of his 2.0 administration, Google and Apple are showing the same names to the same people, by region. Here are the names you now see for Lake Ontario, based on what region your device is set to:

• United States: “Lake America”
• Canada: “Lake Ontario”
• Everywhere else in the world: “Lake Ontario (Lake America)”

This is exactly the same as their joint solution to the Gulf of Mexico renaming — the U.S. sees “Gulf of America”, Mexico sees “Gulf of Mexico”, and the rest of the world sees “Gulf of Mexico (Gulf of America)”.

Here is the solution I strongly believe Google and Apple should follow:

• United States: “Lake America (Lake Ontario)” and “Gulf of America (Gulf of Mexico)”
• Everywhere else in the world: “Lake Ontario” and “Gulf of Mexico”

There is no reason to show these new Trump-dictated names anywhere outside the U.S., even putting them in parentheses. There is no reason to show only the actual traditional names exclusively for users in Canada (for Lake Ontario) and Mexico (for the Gulf). Treating Canada and Mexico as special cases only makes sense if they’re part of some sort of dispute over the names. They’re not. The names of these two bodies of water are not contentious. There is no long-simmering debate about them, like there is with Denali/Mount McKinley in Alaska. The one and only country on the planet with a crackpot kook-ridden government that claims these bodies of water have new names is the United States; the only country that should see the new names is the United States.¹

So, I disagree with how Google and Apple have chosen to handle these re-namings. But it is correct that users in the United States do see the new names.

Here’s Andy Ihnatko, at his eponymous website:

We all have every right to be upset. Google’s receiving plenty of flak over this move (as is Apple; Apple Maps now shows “Lake America,” reportedly after being pressured directly by Trump). I dislike Google’s and Apple’s choices, but I can’t personally fault them.

That said, Trump’s move is clearly meant to antagonize Canada during a volatile period in our relations. He’s throwing gasoline on a tariff fight that’s already creating uncertainty and suffering among vulnerable businesses and consumers on both sides of what was once an impeccably peaceful border. Google and Apple didn’t need to move so damned quickly. I wish they’d deferred the name change long enough for things to cool down a little. Doing so would have avoided creating the perception of handing one side a swift, validating victory.

I doubt a cooling-off period would help. Wounds don’t feel better when they’re reopened after healing. It’s best to get it over with. Applying the change to Google and Apple Maps while the GNIS database ink is still wet at least serves to remind who made this change and why. And whose change it rightfully is to make.

This is a bitter pill for some to swallow. What a lot of people want is for Google and Apple to just ignore the U.S. government’s official new names. E.g., to pick just one high-profile pundit, here’s Kara Swisher regarding Google (“quislings”) and Apple (“craven”, “pathetic”). But I suspect, quite strongly, that the people who profess to be the most angry at Apple and Google for going along with this change are the same people who would argue most strongly that Goliath tech companies and mega-billionaires wield too much anti-democratic power and influence.

It’s not coherent to argue that Google and Apple should decide which names to put on their maps only when you want them to ignore the names from the official government database. Neither Google nor Apple are going to sell their maps apps, but it’s not outlandish to think that in some alternative universe, one or more of the leading maps app might be owned by, say, Elon Musk or Larry Ellison. Would the people who want Apple and Google to ignore the official names from the GNIS support the same stance if the two leading maps apps were owned by SpaceX and Oracle instead? Obviously they would not.

What we want is a system where geographic names are determined democratically, by voting. And that is the system we in fact have. Trump won. The Department of the Interior has the power to change these names. If you’re angry that their official names in the United States are now Lake America and Gulf of America, stay angry that Trump won the 2024 election. Stay angry that our president continues to debase his office and embarrass our nation. Directing your anger at Google and Apple for reflecting that change is shooting the messengers.

But this is why I find it embarrassing that both Google and Apple are foisting these absurd names on the rest of the world, even if only between parentheses. These names are nonsense, and they are Americans’ nonsense to deal with.

China is another country with ridiculous geographic dogma. China demands that Taiwan, which is an independent free nation, be falsely labelled as a province of China. Apple Maps reflects that policy — within China. It doesn’t label Taiwan as “(Province of China)” on maps outside China. Bullshit inside parentheses is still bullshit. Less seriously but more preposterously, the Chinese government also insists that the obscure Diaoyu Islands, subject of a long-running territorial dispute with Japan, be drawn larger than they actually are on maps. Apple Maps dutifully renders those inflated false island sizes to users in China. It doesn’t show them to users anywhere else in the world — not even as dotted outlines. Chinese users see Chinese government dogmatic nonsense; no one else does.

So too it should be for U.S. government dogmatic nonsense. Spreading the nonsense to the rest of the world only makes it more embarrassing.

Neither Google nor Apple claim to be cartographic editorial authorities. I do not think we should want them to be. Other non-governmental institutions do claim to be independent authorities. The Associated Press has stuck to their guns even in the face of losing its White House press pool seat over their refusal to adopt the “Gulf of America” name. And then there’s Wikipedia, whose reputation, integrity, popularity, and independence haunt the right wing. From Politico, last week:

Other platforms will soon follow, a senior administration official told Politico on Tuesday. “We got Lake America changed on Google Maps, and many other maps are changing in a couple days. And Wikipedia is going to change as well,” said the official, who was granted anonymity to speak frankly.

As of Wednesday, Wikipedia was still using the original names of both the Gulf of Mexico and Lake Ontario, while noting that Trump had signed orders to rename them.

Regarding this, Molly White noted:

A Wikipedia editor put it well: “You almost want to pat them on the head and say ‘Yes, of course it will’ in the same way you’d tell a small child that Santa Claus will be delivering their presents.”

It’s Labor Day, so here’s a post about how human labor is alive and well in the age of AI.

I live in San Francisco and hang out with a lot of tech people, both in the AI industry and outside of it. And one thing that almost everyone I know here believes is that AI’s main economic effect is to displace humans from their jobs. Most people don’t have concrete arguments for why this should be true; it’s just an article of faith. The conventional wisdom is pretty well summed up by the first line of this tweet:

In fact, AI companies themselves have spent years talking about how their inventions are going to render large swathes of humanity economically obsolete — an odd marketing pitch, perhaps, but one that seemed to reflect their honest expectations.

A lot of times, San Francisco tech people are out of step with the general public. This time, though, the public seems to agree. A recent Ipsos poll found that most Americans expect AI to compete with human workers more than it complements them. And Pew finds that this belief has even strengthened in recent years:

So basically, most people think AI is a job-killer. And yet somehow, this job-killer keeps stubbornly refusing to kill jobs. In the aggregate, the labor market is about as healthy as it’s ever been. The prime-age employment rate — the single best indicator of how many Americans have jobs — continues to hover near all-time highs:

Of course, there are lots of other things going on in the labor market right now besides AI. But most of those things — tariffs, the Iran war, etc. — are bad for employment. It’s not easy to identify some sort of positive shock that is canceling out the job-killing effects of AI.

Or maybe it is, if the shock is AI itself. Theoretically speaking, automation can create jobs just as easily as it can destroy them. Here are Acemoglu and Restrepo (2019), explaining the various ways that technology can affect the demand for labor:

Automation [can be bad] for labor because of a displacement effect—as capital takes over tasks previously performed by labor…

[A]utomation technology also increases productivity, and via this channel, which we call the productivity effect, it contributes to the demand for labor in non-automated tasks…

[T]he displacement effect of automation has [historically] been counterbalanced by technologies that create new tasks in which labor has a comparative advantage. Such new tasks generate not only a positive productivity effect, but also a reinstatement effect—they reinstate labor into a broader range of tasks and thus change the task content of production in favor of labor. The reinstatement effect is the polar opposite of the displacement effect and directly increases the labor share as well as labor demand. [emphasis mine]

In other words, automation can do three basic things. Yes, it can replace people and take their jobs. It can also make them more productive, which can both create jobs and destroy them.1 And, crucially, automation can create new jobs for people to do. Power looms replaced master weavers, but they created jobs for technicians and engineers to make the power looms work. The internet automated much of the work of travel agents, but created jobs for web designers. And so on.

People who think of AI as a job-killer might not have thought of the second and third of these. Or they may have thought of them, but simply assumed they’re not a big deal. Anecdotally, a lot of tech people think that AI will keep substituting for more and more tasks until A) productivity increases just increase the demand for AI, and B) there are no new tasks left for humans to do. AI detractors, meanwhile — like Daron Acemoglu himself — often simply assume that new tasks created by AI will be “bad tasks” like misinformation and cybercrime that hurt the economy instead of helping it.

But these assumptions simply might not be correct. AI might be creating lots of new tasks for humans to do. For example, software engineers are writing less and less code themselves. Instead, they’re spending more and more time telling AI to write code — that represents a productivity improvement. But they’re also trying to figure out what code to tell AI to write, making sure AI is writing the kind of code they want, integrating that code into products, and so on. Those are all new tasks. There are also a lot of software engineers working on improving AI itself, and on discovering new applications for AI. Those are new tasks as well.

This helps explain why in the age of Codex and Claude Code, software developer jobs have been increasing as a percentage of total employment:

Anecdotally, organizations that thought they could replace lots of their software engineers with AI ended up having to hire many of them back — sometimes at a premium.

In fact, this is a story we see throughout the economy. Alex Tabarrok recently reported on a Census Bureau survey about AI that’s been running since 2023. The Census Bureau calls companies up and asks them A) how AI affected their total employment, and B) how AI affects the tasks that workers do.

Most companies reported no change in overall employment, which could just be due to inertia. But of companies that did report a change, more reported an increase than a decrease!

And here’s the breakdown by sector:

The story was similar for tasks. Tabarrok writes:

Among firms using AI, 44% say it supplemented or enhanced work an employee already does. Ten percent say it performed a task an employee used to do. Eleven percent say it introduced a task no one had been doing.

Here’s the chart:

Rigorous research, meanwhile, sometimes finds negative effects of AI on labor demand at the industry level, and sometimes not. But at the company level, the evidence is clearer — Kharazian, Simon, and Stevens (2026) find that when companies adopt more AI, they tend to hire humans rather than replacing them. Here’s a blog writeup of their findings:

Ramp Economics Lab

We can finally say AI isn’t killing jobs

Dear Colleagues: The most important economic question of this decade asks how AI will affect jobs. Everyone wants to write that paper. Until now, no one has had the right dataset, so existing research has relied on a combination of guesses, surveys, AI exposure scores, and self-interested punditry. In fact, a recent paper from Stanford said the ideal da…

Read more

2 months ago · 63 likes · 14 comments · Ara Kharazian

And here’s a chart:

Interestingly, they find the same for entry-level jobs — the jobs that people usually identify as being most under threat from AI.

So despite Acemoglu’s skepticism, it looks like for now, the new tasks being created by AI are probably matching or even slightly exceeding the tasks replaced by AI. Of course this measure is “number of companies” rather than “number of jobs”, but the pattern is pretty clear.

The Economist, meanwhile, has a report on how AI is creating jobs, both through the “new tasks” channel and by boosting demand in areas that AI can’t yet touch — physical jobs like construction and HVAC installation. Here’s what they write about the productivity/demand effect:

The Economist estimates that AI has so far created around 1m new jobs in America. That easily exceeds the roughly 200,000 lay-offs attributed to AI since mid-2023, and appears more than enough to offset weaker hiring in many back-office roles. America’s AI infrastructure splurge has created many of them…The Economist tracked five industries at the heart of the data-centre build-out, from electrical contracting to equipment manufacturing. Since 2023 employment in them has risen by roughly 320,000 more than broader…trends would suggest…LinkedIn, a social network for strivers, estimates that nearly half a million data-centre jobs were created between 2023 and 2025 in America, with data-centre technicians and engineers among the most common recent hires…

The scramble for workers is showing up in pay cheques, too. Indeed finds that installation and maintenance jobs at data centres advertise wages about 40% higher than comparable work elsewhere…In the year to June, average hourly earnings rose more than 13% in electrical-equipment manufacturing and nearly 8% among electrical contractors. [emphasis mine]

And here’s what they write about new tasks:

AI is also creating a new class of white-collar jobs. Engineers build the models, data annotators label their inputs and judge their answers, “forward-deployed” engineers adapt them for customers, and newly minted “heads of AI” decide what companies should do with the technology. Some of these roles barely existed until recently. Many are quickly growing in number. Postings for heads of AI, AI engineers and directors of AI have roughly doubled since 2023-24, according to LinkedIn…

Preliminary research by Gad Levanon, chief economist at the Burning Glass Institute…reckons roughly 1% of professional jobs are now “AI jobs”…[P]rofessional occupations closest to the AI boom—engineers, software developers, mathematicians and data scientists…have added roughly 730,000 jobs above trend in recent years[.] [emphasis mine]

What about specific occupations? Technology has certainly destroyed many specific types of jobs over the centuries — there are (basically) no more elevator operators, human telephone operators, or people who do manual typesetting for printing.

And yet in recent decades, we haven’t seen as much of this sort of occupational destruction. For example, a lot of people thought the internet would kill travel agents. And while the industry was hit hard, there are still plenty of travel agents left:

The reason is probably that the job of “travel agent” is much more flexible and “messy” than older types of jobs like elevator operator; travel agents do a whole lot of different tasks, so they’re harder to replace than people who just stand there and press a button. That makes modern jobs harder to replace entirely.

It’s a good bet that AI will eventually make some occupations obsolete. But so far, despite awe-inspiring progress in model capabilities, it’s extremely hard to find occupations that have seen significant replacement by AI. Top AI researchers who famously predicted the end of human radiologists saw their predictions get confounded. Truckers, too, are doing just fine.

The most impressive example might be translators. It seems pretty obvious how AI could replace human translators, and yet it hasn’t done so yet:

Here’s a chart:

If you could go back to 2022, and tell people that in four years, AI would be solving frontier math problems, but we’d still have the same number of people working as translators, how many would have believed you?

It turns out that it’s very natural for people to overestimate the degree to which AI will take their jobs. Hartley et al. (2026) have a really excellent paper called “Job Loss Fears in the First Years of Generative Artificial Intelligence”. Here’s a thread explaining the paper’s findings.

Basically, the authors find that fear of AI job replacement is extremely common:

And they find that the more people’s jobs are exposed to AI, the more they think their jobs are about to be replaced:

In fact, the more of their day people spend using AI at work, the more they’re afraid of being replaced!

And yet when the authors looked for a correlation between AI exposure and actual job loss, they found…absolutely nothing. People’s fears simply haven’t come true yet.

What’s going on? The authors hypothesize that people who use AI more start to understand its ability to replace the tasks they do at work. But as we keep finding, replacing tasks isn’t the same as replacing jobs. People keep finding new things to do in their roles at work — sometimes things AI can’t do yet, but often things that couldn’t even be done until AI made them possible!

It seems like we’re uncovering a consistent human blind spot here: People don’t actually know how they produce value at their jobs. Modern jobs are much more than a simple collection of tasks — they are pieces of a complex machine that produces value in ways that an individual worker often doesn’t even see.2 So when AI comes along and starts replacing people at various tasks, it just ends up making them more valuable as pieces of their corporate machines.

How long that situation will persist, of course, is an open question. AI leaders are starting to realize that it might take a very long time for the full effect of their inventions to be felt:

This is why the AI companies’ recent messaging pivot — many now say that AI will create jobs rather than destroying them — may be honest, rather than a cynical marketing ploy to calm public outrage.

But then there’s the question: Can this situation persist indefinitely? No one knows, of course. But my bet is that while many occupations will eventually be mostly replaced by AI, humans will still have plenty to do. I’ve argued that in order for AI to start replacing human jobs wholesale, it’ll have to get much more agentic — which will make it inherently more unreliable from a human point of view. So I predict that humans will always have jobs keeping AI agents on track.

Even if I’m wrong, though — even if the AI job apocalypse does eventually come — it doesn’t seem like it’s coming soon, and it certainly isn’t here right now. Everyone keeps thinking that AI is a job killer, and AI keeps on refusing to be what everyone expects.

Happy Labor Day!

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When Paul St. Louis voted as a juror in 2017 to convict Frederick Turner for his role in a methamphetamine dealing ring, St. Louis had no idea that prosecutors would stack the charges in such a way that Turner, a first-time offender, received a 40-year mandatory minimum sentence.

The judge presiding over the trial declared Turner's sentence "excessive" and "wrong," but had no choice but to impose it. Less than a year later, Turner, 38, was found dead in his cell at a high-security federal prison in Colorado.

Ever since, St. Louis has been haunted by Turner's death, and the knowledge in hindsight that there may have been more he could have done in his role as a juror.

"If I could go back in time, and if I knew Frederick faced 40 years, I would vote to acquit him," St. Louis said in a new jury-education campaign launched this week by the Cato Institute, a libertarian think tank. "I could have asked what sentence would be imposed. I could have drawn my own conclusions if no one would answer. And I could have voted my conscience."

The nonpartisan initiative, Your Verdict Counts, aims to educate jurors on three things the Cato Institute says they should know but are rarely, if ever, told: that jurors have the right to decide if a law is unjust or being applied unjustly, the right to ask what the consequences of a conviction will be, and the right to vote their conscience based on those factors without fear of punishment.

"Jurors are not just called to go in and check boxes and determine if somebody technically violated the law," says Matthew Cavedon, director of the Cato Institute's Project on Criminal Justice. "Their job is to use their conscience and their sense of justice, to figure out whether somebody deserves to have their lives, their liberty, or their property denied. That's a completely different task than the one that judges and lawyers often insist is all that a jury is supposed to do."

In addition to the website, the Cato campaign will include a series of in-person events in Richmond, Virginia. Cavedon said the Cato Institute chose Richmond for the initiative because Virginia allows convicted defendants to ask to be sentenced by a jury, rather than a judge—a rare if not wholly unique feature of its criminal justice system. Richmond also has a particularly zealous defense bar.

The act of acquitting or refusing to indict a criminal defendant based on moral objections to the laws or charges in question, regardless of whether the defendant is technically guilty, is commonly called "jury nullification," and it's a controversial subject in the legal profession.

As George Mason University law professor Ilya Somin wrote at The Volokh Conspiracy in 2018, nullification undermines the rule of law in a system where the criminal codes are more or less uniformly applied, but in the real world it has become, unfortunately,  "a counterweight to the enormous discretionary power already wielded by government officials."

The Cato campaign conspicuously avoids the term nullification, which Cavedon says gives a rebellious shade to a proper and traditional check on government overreach.

It's more important than ever for juries to exercise that power, the Cato Institute argues, because juries so rarely can anymore. A Pew Research Center report found that in 2018, only 2 percent of federal criminal cases went to trial. Lengthy mandatory minimum sentences give prosecutors so much leverage over defendants that turning down a plea deal and going to trial becomes an irrationally risky choice. Defendants who turn down plea deals and get convicted, such as Turner, get hammered at sentencing, a phenomenon that criminal justice advocates call the "trial penalty." The result is that the constitutional right to trial has largely vanished.

The Cato Institute argues that emboldened juries would be a safeguard in a justice system that has mostly taken away judges' ability to consider individual defendants at sentencing.

However, although jurors can't be punished for voting their conscience, it's practically verboten to talk about inside courthouses. Attorneys are usually barred from talking about nullification with juries, and doing so can be grounds for a mistrial.

In 2019, a divided 2nd Circuit Court of Appeals panel chastised a federal judge who complained about an overzealous prosecution and said the case before him "call[ed] for jury nullification."

Over the years, activists have even been arrested and convicted on jury tampering charges for handing out flyers about nullification outside courthouses, leading to First Amendment lawsuits. In 2022, the 2nd Circuit ruled that a New York man's free speech rights were violated when he was arrested outside a Bronx courthouse for doing so.

Despite courts' deep uneasiness with the concept, the Cato Institute argues that there is a long and strong tradition of American juries using their power to resist unjust laws and charges, from the acquittal of Peter Zenger in a famous 1735 libel case to northern juries' refusal to convict defendants of aiding fleeing slaves under the Fugitive Slave Act.

Likewise, Reason's Damon Root wrote in 2018 on the originalist case for jury nullification, finding that there's "good evidence that many 18th and 19th century Americans understood juries to possess the lawful power to reject guilty verdicts when the jurors believed the underlying law was unconstitutional."

The concerns that motivated those Americans, Cavedon says, are much the same as today's.

"There's such a feeling in America today that government is distant, and that especially lawyers and judges are just part of the elite class, making decisions without the good sense of the people. That's been a concern all throughout American history, and the jury is supposed to be the antidote," Cavedon says. "The jury is literally government by the people, and we have lost something in shifting the most important function of the government, criminal punishment, to behind closed doors, to negotiations between lawyers, to a quick sign-off by a judge. That is not the freedom and the democratic order that we were promised."

The post The Right to Trial is Vanishing. Could Bolder Juries Save It? appeared first on Reason Magazine.

This month, there will be over 400 Chinese officials in New Delhi—more than double the previous delegation in 2019—to discuss the future of Sino–Indian relations. For China, those relations have never been more favorable; India’s position on the world stage has declined, though not in ways caused by China, making the prospect of resumed and increased trade between the two nations increasingly likely.

A key development came in March 2026, when the Indian Union Cabinet amended Press Note 3, a rule in place since 2020 that required government clearance for investment from any country sharing a land border with India (the largest of course being China, which shares a 3,500-kilometer border with India). The removal of this barrier proved its effectiveness by the end of August: investors had brought ₹4,896 crore ($512 million) across 29 projects. This is a proof of concept that cannot be easily ignored.

But the greater significance is in where investment did not come from: China. After relaxing a rule that primarily affected China, investment instead came from Mauritius, Korea, Japan, Singapore, and the United States.

From the two factors—the small inflow, and the source nations—a reasonable conclusion can be drawn: global funds carrying incidental Chinese shareholders had been caught by mistake, and they were now unblocked.

The conclusion that should be drawn is that formal (“hard”) blockages to trade are only ever one part of a greater picture and should be understood alongside the informal (“soft”) blockages. India’s trade problem with China is habitually described as a deficit to be narrowed by negotiation—the lifting of tariffs, increasing market access, joint ventures, and so on. It is better understood as an asymmetry that negotiation cannot alter: India’s constant attempts to address this gap seem to have made it wider.

Bilateral goods trade reached $151.1 billion in the fiscal year ending March 2026, and, of that, imports to India from China were $131.63 billion, the highest India recorded from any country; meanwhile, exports to China were only $19.47 billion. The new fiscal year is following the same trend: June’s deficit alone was $15.3 billion.

What India buys from China falls into roughly four broad categories—electronics, machinery, organic chemicals and plastics—as well as the pharmaceutical agents upon which India’s generic drug industry depends. What India sells in return is very much the raw end of things: ores and slag, mineral fuels, and marine products. Exports have been growing—up 37% in the previous year—but that growth seems less impressive when the actual numbers are considered: from $14 billion to $19 billion.

The Sino–Indian trade profile is not, therefore, one between two comparable advanced economies, but between a supplier and a manufacturer, and because the Indian economy supplies the very items that China exports to India, it becomes a self-reinforcing cycle. As Indian industry grows, and the country becomes wealthier, it will buy more of the products China produces using the very raw materials it has bought from India.

This yawning deficit is, in large part, a product of two of India’s own policies that have pulled in opposing directions.

The first is security-focused: Press Note 3, mentioned above, was first introduced at the very beginning of the COVID-19 pandemic, and was originally aimed at preventing opportunistic pandemic-era acquisitions. As a consequence, hundreds of Chinese investment applications were banned, and business visas for Chinese engineers were subject to layer upon layer of vetting, at the ministerial level. The cost of doing business simply skyrocketed. In a strict sense, it achieved its goal: Chinese direct investment collapsed to a mere $67.34 million between 2021 and 2024.

The second was an industrial policy designed to build a modern industrial base for India at speed. The first industries to benefit from this were the assembly-based industries: phones, appliances, solar panels, and so on. Naturally, these industries are resource-intensive and require more components as they grow; as a result, the trade deficit with China, the main supplier for these components, ballooned from $44 billion in 2021 to nearly $85 billion in 2024 and even further to $112 billion in 2025.

Delhi has been laser-focused on course correction since late 2025. Former cabinet secretary Rajiv Gauba proposed dismantling the visa-vetting system, and shortly after in December the government launched a digital sponsorship platform, simplifying the process and no longer requiring ministerial recommendations. On the FDI side, Press Note 2, which was approved in March and has been in effect since May 2026, automatically processed noncontrolling stakes of up to 10%, while introducing a 60-day approval window for priority manufacturing sectors (including electronics, capital goods, and solar cells).

These are real liberalization efforts, noted approvingly by the Carnegie Endowment, which wrote, “The practical argument for reform was genuine. The system was deterring not just Chinese capital but also legitimate global investment.”

The problem persists, however: the barriers to Chinese investment have been lowered, but Chinese investment has not automatically flowed through.

The forthcoming BRICS summit, held in Delhi from September 12–13, will be a real opportunity for India to address this. Xi Jinping himself will be coming, his first visit to India since 2019, with the aforementioned 400 expected delegates. The size of the delegation speaks to the seriousness of the summit and the potential for both sides (in fact, all BRICS nations) to take advantage of the global trend among manufacturers to pursue a “China Plus One” policy of diversification in response to a fragile global economy.

As it stands, trade will grow between the two nations, because both economies are growing and complement one another. Unfortunately for India, the trade deficit will grow, too, unless some serious rebalancing is made.