Although China’s response to the latest curbs was swift and seemingly strong, experts told Ars that China’s response to Biden’s last round of tariffs was relatively muted. It’s possible that this week’s ban on exports into the US could also be a response to President-elect Donald Trump’s threat to increase tariffs on all Chinese goods once he takes office.
Analysts warned Monday that new export curbs could end up hurting businesses in the US and allied nations while potentially doing very little to block China from accessing US tech. On Tuesday, four Chinese industry associations seemingly added fuel to the potential fire threatening US businesses by warning Chinese firms that purchasing US chips is “no longer safe,” Asia Financial reported.
Apparently, these groups would not say how or why the chips were unsafe, but the warning could hurt US chipmaking giants like Nvidia, AMD, and Intel, the financial industry publication closely monitoring China’s economy forecast said.
This was a “rare, coordinated move” by industry associations advising top firms in telecommunications, autos, semiconductors, and “the digital economy,” Asia Financial reported.
As US-China tensions escalate ahead of Trump’s next term, the tech industry has warned that any unpredictable rises in costs may end up spiking prices on popular consumer tech. With Trump angling to add a 35 percent tariff on all Chinese goods, that means average Americans could also end up harmed by the trade war, potentially soon paying significantly more for laptops, smartphones, and game consoles.
Google isn’t alone in eyeballing nuclear power as an energy source for massive datacenters. In September, Ars reported on a plan from Microsoft that would re-open the Three Mile Island nuclear power plant in Pennsylvania to fulfill some of its power needs. And the US administration is getting into the nuclear act as well, signing a bipartisan ADVANCE act in July with the aim of jump-starting new nuclear power technology.
AI is driving demand for nuclear
In some ways, it would be an interesting twist if demand for training and running power-hungry AI models, which are often criticized as wasteful, ends up kick-starting a nuclear power renaissance that helps wean the US off fossil fuels and eventually reduces the impact of global climate change. These days, almost every Big Tech corporate position could be seen as an optics play designed to increase shareholder value, but this may be one of the rare times when the needs of giant corporations accidentally align with the needs of the planet.
Even from a cynical angle, the partnership between Google and Kairos Power represents a step toward the development of next-generation nuclear power as an ostensibly clean energy source (especially when compared to coal-fired power plants). As the world sees increasing energy demands, collaborations like this one, along with adopting solutions like solar and wind power, may play a key role in reducing greenhouse gas emissions.
Despite that potential upside, some experts are deeply skeptical of the Google-Kairos deal, suggesting that this recent rush to nuclear may result in Big Tech ownership of clean power generation. Dr. Sasha Luccioni, Climate and AI Lead at Hugging Face, wrote on X, “One step closer to a world of private nuclear power plants controlled by Big Tech to power the generative AI boom. Instead of rethinking the way we build and deploy these systems in the first place.”
OpenAI hopes to convince the White House to approve a sprawling plan that would place 5-gigawatt AI data centers in different US cities, Bloomberg reports.
The AI company’s CEO, Sam Altman, supposedly pitched the plan after a recent meeting with the Biden administration where stakeholders discussed AI infrastructure needs. Bloomberg reviewed an OpenAI document outlining the plan, reporting that 5 gigawatts “is roughly the equivalent of five nuclear reactors” and warning that each data center will likely require “more energy than is used to power an entire city or about 3 million homes.”
According to OpenAI, the US needs these massive data centers to expand AI capabilities domestically, protect national security, and effectively compete with China. If approved, the data centers would generate “thousands of new jobs,” OpenAI’s document promised, and help cement the US as an AI leader globally.
But the energy demand is so enormous that OpenAI told officials that the “US needs policies that support greater data center capacity,” or else the US could fall behind other countries in AI development, the document said.
Energy executives told Bloomberg that “powering even a single 5-gigawatt data center would be a challenge,” as power projects nationwide are already “facing delays due to long wait times to connect to grids, permitting delays, supply chain issues, and labor shortages.” Most likely, OpenAI’s data centers wouldn’t rely entirely on the grid, though, instead requiring a “mix of new wind and solar farms, battery storage and a connection to the grid,” John Ketchum, CEO of NextEra Energy Inc, told Bloomberg.
That’s a big problem for OpenAI, since one energy executive, Constellation Energy Corp. CEO Joe Dominguez, told Bloomberg that he’s heard that OpenAI wants to build five to seven data centers. “As an engineer,” Dominguez said he doesn’t think that OpenAI’s plan is “feasible” and would seemingly take more time than needed to address current national security risks as US-China tensions worsen.
OpenAI may be hoping to avoid delays and cut the lines—if the White House approves the company’s ambitious data center plan. For now, a person familiar with OpenAI’s plan told Bloomberg that OpenAI is focused on launching a single data center before expanding the project to “various US cities.”
Bloomberg’s report comes after OpenAI’s chief investor, Microsoft, announced a 20-year deal with Constellation to re-open Pennsylvania’s shuttered Three Mile Island nuclear plant to provide a new energy source for data centers powering AI development and other technologies. But even if that deal is approved by regulators, the resulting energy supply that Microsoft could access—roughly 835 megawatts (0.835 gigawatts) of energy generation, which is enough to power approximately 800,000 homes—is still more than five times less than OpenAI’s 5-gigawatt demand for its data centers.
Ketchum told Bloomberg that it’s easier to find a US site for a 1-gigawatt data center, but locating a site for a 5-gigawatt facility would likely be a bigger challenge. Notably, Amazon recently bought a $650 million nuclear-powered data center in Pennsylvania with a 2.5-gigawatt capacity. At the meeting with the Biden administration, OpenAI suggested opening large-scale data centers in Wisconsin, California, Texas, and Pennsylvania, a source familiar with the matter told CNBC.
During that meeting, the Biden administration confirmed that developing large-scale AI data centers is a priority, announcing “a new Task Force on AI Datacenter Infrastructure to coordinate policy across government.” OpenAI seems to be trying to get the task force’s attention early on, outlining in the document that Bloomberg reviewed the national security and economic benefits its data centers could provide for the US.
In a statement to Bloomberg, OpenAI’s spokesperson said that “OpenAI is actively working to strengthen AI infrastructure in the US, which we believe is critical to keeping America at the forefront of global innovation, boosting reindustrialization across the country, and making AI’s benefits accessible to everyone.”
Big Tech companies and AI startups will likely continue pressuring officials to approve data center expansions, as well as new kinds of nuclear reactors as the AI explosion globally continues. Goldman Sachs estimated that “data center power demand will grow 160 percent by 2030.” To ensure power supplies for its AI, according to the tech news site Freethink, Microsoft has even been training AI to draft all the documents needed for proposals to secure government approvals for nuclear plants to power AI data centers.
On Wednesday, the Supreme Court tossed out claims that the Biden administration coerced social media platforms into censoring users by removing COVID-19 and election-related content.
Complaints alleging that high-ranking government officials were censoring conservatives had previously convinced a lower court to order an injunction limiting the Biden administration’s contacts with platforms. But now that injunction has been overturned, re-opening lines of communication just ahead of the 2024 elections—when officials will once again be closely monitoring the spread of misinformation online targeted at voters.
In a 6–3 vote, the majority ruled that none of the plaintiffs suing—including five social media users and Republican attorneys general in Louisiana and Missouri—had standing. They had alleged that the government had “pressured the platforms to censor their speech in violation of the First Amendment,” demanding an injunction to stop any future censorship.
Plaintiffs may have succeeded if they were instead seeking damages for past harms. But in her opinion, Justice Amy Coney Barrett wrote that partly because the Biden administration seemingly stopped influencing platforms’ content policies in 2022, none of the plaintiffs could show evidence of a “substantial risk that, in the near future, they will suffer an injury that is traceable” to any government official. Thus, they did not seem to face “a real and immediate threat of repeated injury,” Barrett wrote.
“Without proof of an ongoing pressure campaign, it is entirely speculative that the platforms’ future moderation decisions will be attributable, even in part,” to government officials, Barrett wrote, finding that an injunction would do little to prevent future censorship.
Instead, plaintiffs’ claims “depend on the platforms’ actions,” Barrett emphasized, “yet the plaintiffs do not seek to enjoin the platforms from restricting any posts or accounts.”
“It is a bedrock principle that a federal court cannot redress ‘injury that results from the independent action of some third party not before the court,'” Barrett wrote.
Barrett repeatedly noted “weak” arguments raised by plaintiffs, none of which could directly link their specific content removals with the Biden administration’s pressure campaign urging platforms to remove vaccine or election misinformation.
According to Barrett, the lower court initially granting the injunction “glossed over complexities in the evidence,” including the fact that “platforms began to suppress the plaintiffs’ COVID-19 content” before the government pressure campaign began. That’s an issue, Barrett said, because standing to sue “requires a threshold showing that a particular defendant pressured a particular platform to censor a particular topic before that platform suppressed a particular plaintiff’s speech on that topic.”
“While the record reflects that the Government defendants played a role in at least some of the platforms’ moderation choices, the evidence indicates that the platforms had independent incentives to moderate content and often exercised their own judgment,” Barrett wrote.
Barrett was similarly unconvinced by arguments that plaintiffs risk platforms removing future content based on stricter moderation policies that were previously coerced by officials.
“Without evidence of continued pressure from the defendants, the platforms remain free to enforce, or not to enforce, their policies—even those tainted by initial governmental coercion,” Barrett wrote.
Judge: SCOTUS “shirks duty” to defend free speech
Justices Clarence Thomas and Neil Gorsuch joined Samuel Alito in dissenting, arguing that “this is one of the most important free speech cases to reach this Court in years” and that the Supreme Court had an “obligation” to “tackle the free speech issue that the case presents.”
“The Court, however, shirks that duty and thus permits the successful campaign of coercion in this case to stand as an attractive model for future officials who want to control what the people say, hear, and think,” Alito wrote.
Alito argued that the evidence showed that while “downright dangerous” speech was suppressed, so was “valuable speech.” He agreed with the lower court that “a far-reaching and widespread censorship campaign” had been “conducted by high-ranking federal officials against Americans who expressed certain disfavored views about COVID-19 on social media.”
“For months, high-ranking Government officials placed unrelenting pressure on Facebook to suppress Americans’ free speech,” Alito wrote. “Because the Court unjustifiably refuses to address this serious threat to the First Amendment, I respectfully dissent.”
At least one plaintiff who opposed masking and vaccines, Jill Hines, was “indisputably injured,” Alito wrote, arguing that evidence showed that she was censored more frequently after officials pressured Facebook into changing their policies.
“Top federal officials continuously and persistently hectored Facebook to crack down on what the officials saw as unhelpful social media posts, including not only posts that they thought were false or misleading but also stories that they did not claim to be literally false but nevertheless wanted obscured,” Alito wrote.
While Barrett and the majority found that platforms were more likely responsible for injury, Alito disagreed, writing that with the threat of antitrust probes or Section 230 amendments, Facebook acted like “a subservient entity determined to stay in the good graces of a powerful taskmaster.”
Alito wrote that the majority was “applying a new and heightened standard” by requiring plaintiffs to “untangle Government-caused censorship from censorship that Facebook might have undertaken anyway.” In his view, it was enough that Hines showed that “one predictable effect of the officials’ action was that Facebook would modify its censorship policies in a way that affected her.”
“When the White House pressured Facebook to amend some of the policies related to speech in which Hines engaged, those amendments necessarily impacted some of Facebook’s censorship decisions,” Alito wrote. “Nothing more is needed. What the Court seems to want are a series of ironclad links.”
Enlarge/ New energy vehicles are being loaded into containers for export at Taicang Port and Taicang International Terminal in Suzhou, Jiangsu Province, China, on April 26, 2024.
Photo by Costfoto/NurPhoto via Getty Images
President Joe Biden is expected to levy new 100 percent tariffs targeted at specific Chinese industries, including electric vehicles, on Tuesday. The announcement follows growing calls from automakers, unions, and bipartisan efforts in Congress to address the problem of China unfairly subsidizing its own industries to undermine foreign competitors.
Why are Chinese EVs so cheap?
The Chinese government has been giving its green industries heavy direct subsidies for some time now, far in excess of those handed out by US or European governments. For EV makers like BYD, this has meant billions of dollars a year, in addition to the consumer-facing tax benefit for car buyers, similar to how EV sales are incentivized in the US.
Brands like BYD have concentrated on making their cars cheaper to build—only using one windshield wiper instead of two, for example—but also through vertical integration. Other than Tesla, automakers in the US, Europe, Japan, and Korea instead rely heavily on multiple tiers of suppliers, most of whom supply parts to more than one automaker.
That has allowed Chinese automakers to sell their products in foreign markets at prices no one else can hope to compete with, undermining local industries in the process. This has been most relevant in Europe, where Chinese automakers like BYD and MG have already set up shop. Last year, 1 in 5 EVs sold in Europe were made in China; this year, it’s expected this number will rise to 1 in 4.
Chinese car imports to the US are already subject to an additional 25 percent import tariff on top of the 2.5 percent tariff that applies to any car imported to the US. And Chinese brands have yet to enter the US market. If enacted this week, the new 102.5 percent tariffs would apply to Polestar and Lotus, both of which currently build their US-market EVs in China. But that doesn’t mean the industry isn’t terrified.
“If there are no trade barriers established, they will pretty much demolish most other car companies in the world,” said Tesla CEO Elon Musk in January.
“If you cannot compete fair and square with the Chinese around the world, then 20 percent to 30 percent of your revenue is at risk,” said Ford CEO Jim Farley in February.
It probably goes without saying that the United Auto Workers also thinks protecting the US auto industry is worthwhile. “The transition to cleaner technologies cannot be used to intensify the global race to the bottom through offshoring and low wages. We need to see movement by the administration to protect these jobs. The nascent EV industry needs tariff protections—otherwise we are going to be awash in imports. The stakes of the transition are high for American workers,” the union said in a statement in March.
This year, senators on both sides of the aisle—most recently Sherrod Brown (D–Ohio)—have called for a ban on Chinese EV imports. And pressure from the US Trade Representative has seen the Mexican government promise not to offer incentives to Chinese EV makers looking to establish a beachhead inside the United States-Mexico-Canada Free Trade Agreement.
The White House has announced the “first government-wide policy to mitigate risks of artificial intelligence (AI) and harness its benefits.” To coordinate these efforts, every federal agency must appoint a chief AI officer with “significant expertise in AI.”
Some agencies have already appointed chief AI officers, but any agency that has not must appoint a senior official over the next 60 days. If an official already appointed as a chief AI officer does not have the necessary authority to coordinate AI use in the agency, they must be granted additional authority or else a new chief AI officer must be named.
Ideal candidates, the White House recommended, might include chief information officers, chief data officers, or chief technology officers, the Office of Management and Budget (OMB) policy said.
As chief AI officers, appointees will serve as senior advisers on AI initiatives, monitoring and inventorying all agency uses of AI. They must conduct risk assessments to consider whether any AI uses are impacting “safety, security, civil rights, civil liberties, privacy, democratic values, human rights, equal opportunities, worker well-being, access to critical resources and services, agency trust and credibility, and market competition,” OMB said.
Perhaps most urgently, by December 1, the officers must correct all non-compliant AI uses in government, unless an extension of up to one year is granted.
The chief AI officers will seemingly enjoy a lot of power and oversight over how the government uses AI. It’s up to the chief AI officers to develop a plan to comply with minimum safety standards and to work with chief financial and human resource officers to develop the necessary budgets and workforces to use AI to further each agency’s mission and ensure “equitable outcomes,” OMB said. Here’s a brief summary of OMB’s ideals:
Agencies are encouraged to prioritize AI development and adoption for the public good and where the technology can be helpful in understanding and tackling large societal challenges, such as using AI to improve the accessibility of government services, reduce food insecurity, address the climate crisis, improve public health, advance equitable outcomes, protect democracy and human rights, and grow economic competitiveness in a way that benefits people across the United States.
Among the chief AI officer’s primary responsibilities is determining what AI uses might impact the safety or rights of US citizens. They’ll do this by assessing AI impacts, conducting real-world tests, independently evaluating AI, regularly evaluating risks, properly training staff, providing additional human oversight where necessary, and giving public notice of any AI use that could have a “significant impact on rights or safety,” OMB said.
OMB breaks down several AI uses that could impact safety, including controlling “safety-critical functions” within everything from emergency services to food-safety mechanisms to systems controlling nuclear reactors. Using AI to maintain election integrity could be safety-impacting, too, as could using AI to move industrial waste, control health insurance costs, or detect the “presence of dangerous weapons.”
Uses of AI presumed to be rights-impacting include censoring protected speech and a wide range of law enforcement efforts, such as predicting crimes, sketching faces, or using license plate readers to track personal vehicles in public spaces. Other rights-impacting AI uses include “risk assessments related to immigration,” “replicating a person’s likeness or voice without express consent,” or detecting students cheating.
Chief AI officers will ultimately decide if any AI use is safety- or rights-impacting and must adhere to OMB’s minimum standards for responsible AI use. Once a determination is made, the officers will “centrally track” the determinations, informing OMB of any major changes to “conditions or context in which the AI is used.” The officers will also regularly convene “a new Chief AI Officer Council to coordinate” efforts and share innovations government-wide.
As agencies advance AI uses—which the White House says is critical to “strengthen AI safety and security, protect Americans’ privacy, advance equity and civil rights, stand up for consumers and workers, promote innovation and competition, advance American leadership around the world, and more”—chief AI officers will become the public-facing figures accountable for decisions made. In that role, the officer must consult with the public and incorporate “feedback from affected communities,” notify “negatively affected individuals” of new AI uses, and maintain options to opt-out of “AI-enabled decisions,” OMB said.
However, OMB noted that chief AI officers also have the power to waive opt-out options “if they can demonstrate that a human alternative would result in a service that is less fair (e.g., produces a disparate impact on protected classes) or if an opt-out would impose undue hardship on the agency.”
China is still finding ways to skirt US export controls on Nvidia chips, Reuters reported.
A Reuters review of publicly available tender documents showed that last year dozens of entities—including “Chinese military bodies, state-run artificial intelligence research institutes, and universities”—managed to buy “small batches” of restricted Nvidia chips.
The US has been attempting to block China from accessing advanced chips needed to achieve AI breakthroughs and advance modern military technologies since September 2022, citing national security risks.
Reuters’ report shows just how unsuccessful the US effort has been to completely cut off China, despite repeated US attempts to expand export controls and close any loopholes discovered over the past year.
China’s current suppliers remain “largely unknown,” but Reuters confirmed that “neither Nvidia” nor its approved retailers counted “among the suppliers identified.”
An Nvidia spokesperson told Reuters that the company “complies with all applicable export control laws and requires its customers to do the same.”
“If we learn that a customer has made an unlawful resale to third parties, we’ll take immediate and appropriate action,” Nvidia’s spokesperson said.
It’s also still unclear how suppliers are procuring the chips, which include Nvidia’s most powerful chips, the A100 and H100, in addition to slower modified chips developed just for the Chinese market, the A800 and H800. The former chips were among the first banned, while the US only began restricting the latter chips last October.
Among military and government groups purchasing chips were two top universities that the US Department of Commerce has linked to China’s principal military force, the People’s Liberation Army, and labeled as a threat to national security. Last May, the Harbin Institute of Technology purchased six Nvidia A100 chips to “train a deep-learning model,” and in December 2022, the University of Electronic Science and Technology of China purchased one A100 for purposes so far unknown, Reuters reported.
Other entities purchasing chips include Tsinghua University—which is seemingly gaining the most access, purchasing “some 80 A100 chips since the 2022 ban”—as well as Chongqing University, Shandong Chengxiang Electronic Technology, and “one unnamed People’s Liberation Army entity based in the city of Wuxi, Jiangsu province.”
In total, Reuters reviewed more than 100 tenders showing state entities purchasing A100 chips and dozens of tenders documenting A800 purchases. Purchases include “brand new” chips and have been made as recently as this month.
Most of the chips purchased by Chinese entities are being used for AI, Reuters reported. None of the purchasers or suppliers provided comments in Reuters’ report.
Nvidia’s highly sought-after chips are graphic processing units capable of crunching large amounts of data at the high speeds needed to fuel AI systems. For now, these chips remain irreplaceable to Chinese firms hoping to compete globally, as well as nationally, with China’s dominant technology players, such as Huawei, Reuters suggested.
While the “small batches” of chips found indicate that China could still be accessing enough Nvidia chips to enhance “existing AI models,” Reuters pointed out that US curbs are effectively stopping China from bulk-ordering chips at quantities needed to develop new AI systems. Running a “model similar to OpenAI’s GPT would require more than 30,000 Nvidia A100 cards,” research firm TrendForce reported last March.
For China, which has firmly opposed the US export controls every step of the way, these curbs remain a persistent problem despite maintaining access through the burgeoning black market. On Monday, a Bloomberg report flagged the “steepest drop” in the value of China chip imports ever recorded, falling by more than 15 percent.
China’s black market for AI chips
The US still must confront whether it’s possible to block China from accessing advanced chips without other allied nations joining the effort by lobbying their own export controls.
In October 2022, a senior US official warned that without more cooperation, US curbs will “lose effectiveness over time.” A former top Commerce Department official, Kevin Wolf, told The Wall Street Journal last year that it’s “insanely difficult to enforce” US export controls on transactions overseas.
On top of that activity, a black market for chips developed quickly, selling “excess stock that finds its way to the market after Nvidia ships large quantities to big US firms” or else chips imported “through companies locally incorporated in places such as India, Taiwan, and Singapore,” Reuters reported.
The US has maintained that its plan is not to ensure that China has absolutely no access but to limit access enough to keep China from getting ahead. But Nvidia CEO Jensen Huang has warned that curbs could have the opposite effect. While China finds ways to skirt the bans and acquire chips to “inspire” advancements, US companies that have been impacted by export controls restricting sales in China could lose so much revenue that they fall behind competitively, Huang predicted.
