China, China, China

Perhaps you, like me, read with some concern the news that, after some negotiations with China and much pleading from Nvidia CEO Jenson Huang, President Trump is allowing Nvidia to sell its second best AI chip to China. Hmm, isn’t China going to use them to compete even more on AI and other crucial new technologies? Well, others might argue, we do need their rare earth minerals, the President says it will be good for trade, plus the U.S. is supposedly getting a 25% cut of the sales. And anyway, they might add, we’re the U.S.: it’s only the second best chip, and we’ll keep innovating our way to the top.

The U.S. is in a technology race with China - and ma not be winning. Credit: Microsoft Designer

That last statement is not quite as clear as it might once have been. The 2025 Critical Technology Tracker, done by the Australian Strategic Policy Institute (ASPI), looks at 74 current and emerging technologies – and found that China is ranked number one in 66 of them. That’s 90%. ASPI added ten new emerging technologies to its 2024 report, including advanced computing and communication, artificial intelligence, and emerging neurotechnologies relevant to human-machine integration.

ASPI’s special report on the findings, written by Jenny Wong-Leung, Stephan Robin and Linus Cohen, was blunt:

The updated picture is stark. China’s exceptional gains in high-impact research are continuing, and the gap between it and the rest of the world is still widening. In eight of the 10 newly added technologies, China has a clear lead in its global share of high-impact research output. Four—cloud and edge computing, computer vision, generative AI and grid integration technologies—carry a high technology monopoly risk (TMR) rating, reflecting substantial concentration of expertise within Chinese institutions.  

Just to be clear, the report focuses not on how well the countries are implementing the technologies but on the high impact research in them, as measured by the ten percent most cited research papers in them between 2020 and 2025. This is research pointing to the future.

The ASPI authors write: “The historical data for these new technologies tells a familiar story: an early and often overwhelming US lead in research output in the opening decade of this millennium, eroded and then outmatched by persistent long-term Chinese investment in fundamental research.”

“China has made incredible progress on science and technology that is reflected in research and development, as well as in publications,” Ilaria Mazzocco, an expert on China’s industrial policy at the Center for Strategic and International Studies, told Nature’s Xiaoying You. ASPI’s Dr. Wong-Leung also told her that democratic nations were at risk of losing “hard-won, long-term advantages in cutting-edge science and research.”

The report indicates that the U.S. still holds the lead in top tier tech research talent, but that probably does not reflect the recent “brain drain” caused by the Trump Administration’s war on science as The Washington Post recently reported on.

In a new Goldman Sachs report, The U.S. China Tech Race, Mark Kennedy, Founding Director, Wahba Initiative for Strategic Competition at New York University’s Development Research Institute, was asked if the role of technology in the U.S.- China strategic rivalry was overstated, and he responded:

The role of technology is not being overplayed. Technology isn’t just at the center of the US-China rivalry—it’s the central switchboard. Whoever controls how technology, data, and computing power are routed will impact every domain—from military might, to economic influence, to the flow of information

Mr. Kennedy believes the U.S. is still leading in the most advanced technologies – he and ASPI will have to discuss that – but agrees that China is making great strides to catching and sometimes overtaking the U.S. Moreover, he notes, “China is also dominating on the global installations front.”   

He urges:

…the US must more broadly move beyond its historically laissez-faire approach toward technology and lean into winning the tech competition across all arenas. This means significantly increasing investment in research and development, reversing the recent trend of stagnant or declining university funding, and easing restrictions that hinder the entry of global talent.

From his lips to Trump’s ears.

In the same report, GS Chief China Economist Hui Shan discusses how China’s most recent Five Year Plan (FYP) three key areas of development:

• “chokehold technologies,” including integrated circuits, industrial machine tools, high-end instruments, basic software, advanced materials, and biomanufacturing;
• “emerging industries,” including new energy technologies, advanced materials, aerospace, and the low-altitude economy (i.e., drones and urban air mobility;
• “future industries,” including quantum technology, biomanufacturing, hydrogen energy and nuclear fusion, brain-computer interfaces, embodied intelligence (integrated AI and robotics), and sixth-generation (6G) mobile communications

And, she notes, “China’s government support for science and technology—and their adoption in industrial sectors—is holistic and highly coordinated.”  It would be hard to say that about the U.S.

Let’s take a specific example of an exciting emerging technology: fusion. The New York Times reported on how China and the U.S are each approaching it:

The world’s two superpowers are in a tightening contest to dominate the energy future. Under the Trump administration, the U.S. is intent on producing oil, gas and coal and selling it abroad. Its chief economic rival, China, has become the world’s dominant supplier of clean energy in the form of solar panels, batteries and electric vehicles.

 Now, NYT says, China is seeking to add fusion to its list of 21^st century energy dominance, while we continue to invest in energy technologies of the past. China has made fusion a national priority, while the U.S. is largely relying on the private sector. Whichever country succeeds would have access to cheap, plentiful power that could supercharge its economy (think of all those data centers).

Even if the U.S. does out-innovate China, China might out operationalize us. Jimmy Goodrich, a senior fellow at the University of California Institute on Global Conflict and Cooperation, told NYT: “The risk for the United States is we create a viable technical pathway first, but then China engineers and scales it up before we can.”

That same risk applies to other key technologies.

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 Maybe ASPI’s methodology is not the best measure for evaluating who is leading in emerging technologies. Maybe China has so many priorities that it is overextended and most will fail. Maybe practical fusion will remain, as it has been for decades, ten years away. Maybe China will prove to be the “paper tiger,” and these concerns are just a hoax. Maybe worrying about all this is just being paranoid.

But as Joseph Heller told us in Catch-22, “just because you’re paranoid doesn’t mean they aren’t after you.”

The Defense Doesn't Rest

Two articles caught my eye this week, and neither was about the “Trump Kennedy Center,” the Netflix attempt to buy Warner Brothers Discovery, or anything AI-related. Instead, both concern defense spending, something I’ve been paying more attention to during the Ukraine-Russia war and China’s revamping of its military.

You'd think all that spending would buy us more. Credit: Peter G. Peterson Foundation

Today’s New York Times Editorial Board published Overmatched: Why the U.S. Military Needs to Reinvent Itself.  It is by no means the first such call; critics of the Defense Department have long accused it of being too slow, too expensive, too bound by tradition. The Ukraine war in particular has been a startling demonstration both of how war is being waged differently and how quickly tactics and weapons are forced to evolve. The U.S. military claims to be paying close attention to that struggle. It even has a Defense Innovation Unit aimed at speeding adoption of commercial technologies, and is trying to radically increase its drone capabilities.  

That’s all well and good, but the Editorial Board says: “Nearly four decades after victory in the Cold War, the U.S. military is ill prepared for today’s global threats and revolutionary technologies.” E.g., in war game after war game against China, even Pete Hegseth admits: “we lose every time.”

Gulp.

Don’t get it wrong: we spend more money on the military than the next nine nations combined, close to $1 trillion annually, devoting over 3% of our GDP on defense. We just aren’t necessarily spending it wisely. We like to spend it on fantastically expensive weapons systems (which are usually overbudget and years beyond schedule) that employ lots of people in many political districts. As Editorial Board noted: “There is also a conceptual failure: the idea that more sophisticated is always better. For decades the American military has relied on systems that are bespoke, complex and wildly expensive.”

We also can’t build those systems fast enough – e.g., ships, artillery shells or drones. China’s industrial capacity would turn any extended conflict into a disaster for the U.S. and our allies, which is exactly how the U.S. led the Allies to victory in WWII.

Credit: USN via The war Zone

The Editorial Board concludes:

Ultimately, a stronger U.S. national security depends less on enormous new budgets than on wiser investments. Spending heavily on traditional symbols of might risks shortchanging the true sources of American strength: relentless innovation, rapid adaptability and a willingness to discard old assumptions.

Meanwhile, Congress is considering a defense spending bill that would not only top $900 billion but also include more money than even the Trump Administration requested. Faster, smarter, cheaper? Probably not.

President Trump has long been demanding that NATO countries, as well as Pacific allies such as Japan, South Korea, and Taiwan, boost their defense spending. There are good reasons for that, but he also certainly expects that much of that increased spending will go to U.S. defense contractors. We do pride ourselves on having the most sophisticated weapons, be they F-35s, Patriot missiles, nuclear submarines, or tanks.  But, it turns out, Europe has a more robust defense than I’d realized, which leads me to the second article.

The Washington Post profiled German defense contractor Rheinmetall. WaPo reports that its shares have tripled in the last year, and its market value is almost $100b, from less than $5b before Russia invaded the Ukraine. “Before the war in Ukraine, I would have said Rheinmetall was one of those German arms companies becoming increasingly less important and likely to be displaced internationally,” Ulrich Kühn, head of arms control research at the Institute for Peace Research and Security Policy, told WaPo.  

Instead: “We are becoming a global defense champion,” says CEO Armin Papperger. Mr. Kühn agrees, adding: “It will very likely grow into one of the world’s leading arms companies, if it isn’t already in certain areas.” 

Rheinmetall is building plants across Europe, from Spain and Hungary to Ukraine and Latvia, along with its German facilities.

But it is not just Rheinmetall and not just Germany. The European defense industry grew 14% in 2024. In fact, five of the top 20 defense contractors in the world are European; the U.S. has 11, and China 4. And, of course, Ukraine leads the world in drone innovation and production  (although Russia has dramatically closed the gap).  

For example, for those of us old enough to remember Saab automobiles, its slogan was “born from jets. You won’t find many Saab cars anymore, but Saab is still a leading defense contractor.  Its Gripen fighter jet is drawing lots of attention. Canada is considering buying them instead of F-35s (no doubt in part due to recent trade wars instigated by the U.S.), and Ukraine has already ordered up to 150 of them.  The Gripen is considered not as advanced as the F-35, but it is much cheaper to buy and maintain.

Poland is buying submarines from Saab, and the Saab led MANGROVE consortium has been selected by NATO to lead the Allied Underwater Battlespace Mission Network project (AUWB-MN).

There’s also Airbus (France), B.A.E Systems (U.K), and KNDS (Germany), among others.

The U.S may have (by far) the biggest defense industry, with some of the most advanced weapons, but it is not the only game in town, nor are those weapons necessarily the ones best suited for fighting future wars.

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All this, of course, reminds me of the U.S. healthcare system and the U.S. tech industry. The U.S. has, by far, the most expensive healthcare system in the world, with some of the most advanced care and technologies. Our tech industry has led the world for decades (although we lost most of our actual manufacturing capabilities). They are both major drivers of our economy.  

But look at the NYT Editorial Board’s charge about our military: “There is also a conceptual failure: the idea that more sophisticated is always better. For decades the American military has relied on systems that are bespoke, complex and wildly expensive.” Tell me that substituting “healthcare system” for “military” wouldn’t be equally accurate.

Similarly, we take great pride in NVIDIA, but what is it -- and all those data centers -- going to do if/when China takes over TSMC? We love OpenAI, but China’s DeepSeek indicates that our approach to AI may also be bespoke, complex and wildly expensive.

We keep deferring regulating digital privacy, social media, and AI, claiming that would deter innovation, but the countries that are trying to do so may be reading the future better.

Bigger isn’t always better. More expensive isn’t always more valuable. Traditions aren’t always to be followed. Faster, cheaper, more flexible may be the ticket to the 21^st century.  

Let's Check the Math on Health Subsidies

It’s December 1, and, to no one’s surprise, Congress still has not acted on extending the expanded health care premium tax credits for ACA. To Congress, the subsidies don’t expire until the end of the year, so they figure they have until at least then to act, or maybe sometime after that, given the way they handled the recent government shutdown.

Trust me: the math is not that complicated. Credit: Microsoft Designer

On the other hand, consumers who are renewing or shopping for ACA plans face a more immediate deadline; they have until December 15 to enroll for January 1^st. They’re already seeing huge increases that result from a normal renewal increase plus the loss of the generous subsidies; Kaiser Family Foundation estimates that their premiums will more than double without them. They can’t wait while Congress plays politics.

There seems to be agreement that something will be done about the subsidies, but less clarity about what that something is. Some centrists argue to extend the enhanced subsidies but with some tweaks, such as lowering the upper income levels and/or requiring everyone to pay at least some minimum premium. To me, that’d be a reasonable compromise. But some Republicans, including President Trump, are calling for a more radical change: instead of giving the expanded premium tax subsidies to those “fat cat” insurers, give them directly to consumers through health savings accounts (HSAs). Put individuals over insurers, they argue.  

I’m here to tell you: the math does not work.

I am not an actuary, but long ago I was a group underwriter, setting rates for employer groups’ health insurance, and, also long ago, I was involved in the early days of so-called consumer directed health plans (CDHPs), including HSAs and high deductible health plans. I don’t disagree that HSAs and high deductible plans can play a role, but one has to understand the math that drives health care spending.

The central fact of health care spending is that it isn’t evenly distributed. It is a perfect example of the Pareto principle: 80% of spending comes from 20% of people. The flip of that is that about 15% of people have no healthcare spending in any given year. What insurance does is take money from everyone and use it to fund the spending of the high cost people. That’s what all insurance does.

Pareto principle illustration

OK, I’ve avoided doing the math as long as I could, but here goes. One proposal has called for $2,000 to be deposited in each enrollee’s new HSA. Let’s keep it simple and say there are 1,000 such people, and that their average annual health care spending is $2,000 (which, of course, is way low). So we have 1,000 x $2,000 = $2 million in both subsidies and spending. It works out perfectly, right?

Not so fast. Of that $2,000,000 in spending, eighty percent of it -- $1.6 million -- is accounted for by just 200 people. They’ve only got $400,000 in HSA funds (200 x $2,000), so they are really out of luck. $1.2 million out of luck.

The remining 800 people have only $400,000 in spending ($2 million - $1.6 million) but have $1.6 million in HSA funds (800 x $2,000), so they just got a big windfall. They can spend it on non-covered services like dental or vision or roll it over to the next year, tax free. They’re $1.2 million to the good.

Of course, at some point insurance kicks in, but the unfortunate 200 people are going to hit those big deductibles and out-of-pocket limits, while the more fortunate people are sitting pretty with their mostly intact new HSA funds. It’s a great deal for them (and the financial institutions that get to manage those funds, an angle let’s not forget about).

Do we aim to protect the high cost people, or benefit the most people?

It gets worse than that. Let’s assume that ACA premiums are also $2,000 per person, ignoring any insurance admin or profit. So we have $2,000,000 in premiums and $2,000,000 in spending. But let’s now take those 15% of people without spending. They contribute $300,000 (150 x $2,000) in premiums but get nothing back. Now that they’re losing the expanded subsidies and seeing their premiums double, they might decide, the heck with insurance, I’ll drop out.

That’s devastating to the insurance risk pool. Its premiums now fall to only $1.7 million ($2  million - $300,000), but its claims stay at $2 million. It is then going to require an 18% rate increase ($2 million divided by $1.7 million) just to keep up, which is probably then going to cause more people to drop coverage, which will cause rates to go up again, and soon we’re in the ominous death spiral.

ACA required insurers to take everyone with no medical underwriting and no exclusions for preexisting coverage – neither of which was true pre-ACA – and it only worked because of the subsidies. Without enough healthy people, you cannot have a viable health insurance market.

Republicans seem to think that insurers are making too much money off of ACA plans, which in their mind justifies not paying the enhanced subsidies to them. I’m dubious this is true. I can see insurers profiting off Medicare Advantage, but I suspect ACA plans constantly teeter on the edge of profitability.  Insurers have to get, and keep, that enrollment mix just right: enough healthy people, not too many sick people.

I’m trying to figure out if Republicans truly just don’t understand the math, or if they understand it just fine but are using the HSA ploy to continue their efforts to undermine ACA. I.e., are they ignorant, or cynical? 

The expanded subsidies were a COVID response and no one should have ever expected them to be permanent. It’s fair to take a look at them and the original subsidies to see how they might be improved (e.g., the original subsidies never contemplated that states wouldn’t expand Medicaid, so don’t go to very low income people at all).  But let’s not kid ourselves that the HSA approach is an effort to improve anything.  

Revenge of (the Other) Nerds

Like it or not, ready for it or not, we appear to be living in the age of A.I. Anyone who isn’t worried about its impact on their job isn’t paying attention, and anyone who isn’t thinking about it for their portfolio is risking experiencing FOMO. If it wasn’t for all the A.I. spending – both on its development and on the data centers that support it – we probably wouldn’t be seeing big stock market gains and might even be in a recession. The Wall Street Journal reports: “Growth has become so dependent on AI-related investment and wealth that if the boom turns to bust, it could take the broader economy with it.”

AI is going to have to get past the accountants and actuaries. Credit: Microsoft Designer

So it is kind of ironic that a revolution caused by the computer nerds could be facing big headwinds caused by the green eyeshade kind of nerds, like accountants and actuaries.

Let’s start with the accounting. Many questions have been raised about how circular some of the AI investments seem. Microsoft invests in OpenAI, which then buys cloud computing from Microsoft. Same with Oracle. NVIDIA invests in OpenAI, which then buys lots of NVIDIA chips and causes others to do the same. And the money goes round and round.

Sam Altman, CEO of OpenAI, recently said: “There is always a lot of focus on technological innovation. What really drives a lot of progress is when people also figure out how to innovate on the financial model.” Unfortunately, some of those innovations are starting to look like innovations Enron might have come up with.

Jonathan Weil of The Wall Street Journal analyzed how Meta was financing the building of a new $25b data center without it appearing on its balance sheets, and concluded: “The favorable accounting outcome hinges on some convenient assumptions. Some appear implausible, while others are in tension with one another, making the off-balance-sheet treatment look questionable.”

Mr. Weil concludes: “Artificial intelligence, meet artificial accounting.”

Then there is insurance. AI benefits carry AI liabilities. Consider AI toys. The U.S. Public Interest Research Group Education Fund (PIRG) issued its 40th Trouble in Toyland report, and one of the areas of focus was A.I. chatbots that interact with children. It’s scary: “We found some of these toys will talk in-depth about sexually explicit topics, will offer advice on where a child can find matches or knives, act dismayed when you say you have to leave, and have limited or no parental controls.” Privacy is also a concern.

An advisory from Fairplay was also blunt: “AI Toys Are NOT Safe for Kids.”

When AI products might tell kids where to find knives or encourage explicit sex talks, you can imagine that liability concerns come right to mind for actuaries and CFOs. That’s why Financial Times is reporting that insurers want no part of AI exposure. Lee Harris and Christina Criddle found:

Major insurers are seeking to exclude artificial intelligence risks from corporate policies, as companies face multibillion-dollar claims that could emerge from the fast-developing technology.

AIG, Great American and WR Berkley are among the groups that have recently sought permission from US regulators to offer policies excluding liabilities tied to businesses deploying AI tools including chatbots and agents.

Dennis Bertram, head of cyber insurance for Europe at Mosaic told them: “It’s too much of a black box.” Rajiv Dattani, co-founder of the Artificial Intelligence Underwriting Company, an AI insurance and auditing start-up, added: “Nobody knows who’s liable if things go wrong,”

The "black box" nature of AI is a liability problem. Credit: Microsoft Designer

We’ve already seen some AI-related losses. The Tech Buzz details:

Google's AI Overview falsely accused a solar company of legal troubles earlier this year, triggering a $110 million lawsuit. Air Canada got stuck honoring a discount its chatbot completely invented after a customer took the airline to small claims court. Most dramatically, fraudsters used a digitally cloned executive to steal $25 million from London engineering firm Arup during what appeared to be a legitimate video conference.

In addition to outright exclusions, insurers are adding amendments that limit liability to certain types of risks or certain amounts of payouts. Aon’s head of cyber Kevin Kalinich told FT that the industry could accept some AI-related losses, but: “What they can’t afford is if an AI provider makes a mistake that ends up as a 1,000 or 10,000 losses — a systemic, correlated, aggregated risk.”

One way or another, the experts told FT,  there will be some AI-related losses, and some of them will end up in court. Aaron Le Marquer, head of insurance disputes team at law firm Stewarts, told FT: “It will probably take a big systemic event for insurers to say, hang on, we never meant to cover this type of event.”

This isn’t unexpected. New technologies bring new benefits, and new risks, and it takes time to factor in both. “When we think about car insurance, for example, the broad adoption of the safety belt was really something which was driven by the demands of insurance,” Michael von Gablenz, who heads the AI insurance division of Munich Re, told NBC News. “When we’re looking at past technologies and their journey, insurance has played a major role in that, and I believe insurance can play the same role for AI.”

NBC News also cites a survey from the Geneva Association indicating that 90% of businesses want insurance protection against generative AI losses, and an Ernst & Young report that found 99% of the 975 firms it surveyed had suffered financial losses from AI-related risks – two-thirds of them more than $1 million.

Clearly there is a need for insurance against AI-related losses, and certainly there is an emerging market, but actuaries need data and predictability, and both of those are in short supply at the moment.  Still, the potential is huge. Deloitte predicts AI insurance could be a $4.8b market by 2032, which seems remarkably low.

Martin Anderson, writing in Unite.AI, suggests we may need some sort of federal backstop, such as what happened with the nuclear industry or for vaccine development. “However, history suggests that forcing AI companies to insure themselves, devoid of government aid, is not the likely path ahead,” he says. On the other hand, “Those that object to the possibility of AI obtaining the same ‘bailout’ status as banks, are not likely to embrace heavily government-backed solutions to the insurance quandaries around AI.”  

Insurance quandaries abound.

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In one sense, it may frustrate AI advocates that mundane things like accounting and insurance might slow down its progress. On the other hand, the fact that they are is a sign that they’re truly becoming mainstream. So give the green eye-shade guys a break while they figure this out.

If You Could Read My Mind - Wait, You Can?

Over the years, one area of tech/health tech I have avoided writing about are brain-computer interfaces (B.C.I.). In part, it was because I thought they were kind of creepy, and, in larger part, because I was increasing finding Elon Musk, whose Neuralink is one of the leaders in the field, even more creepy. But an article in The New York Times Magazine by Linda Kinstler rang alarm bells in my head – and I sure hope no one is listening to them.

This is your brain in fMRI. Credit: Max Planck Institure

Her article, Big Tech Wants Direct Access to Our Brains, doesn’t just discuss some of the technological advances in the field, which are, admittedly, quite impressive. No, what caught my attention was her larger point that it’s time – it’s past time – that we started taking the issue of the privacy of what goes on inside our heads very seriously.

Because we are at the point, or fast approaching it, when those private thoughts of ours are no longer private.

The ostensible purpose of B.C.I.s has usually been as for assistance to people with disabilities, such as people who are paralyzed. Being able to move a cursor or even a limb could change their lives. It might even allow some to speak or even see. All are great use cases, with some track record of successes.

B.C.I.s have tended to go down one of two paths. One uses external signals, such as through electroencephalography (EEG) and electrooculography (EOG), to try to decipher what your brain is doing. The other, as Neuralink uses, is an implant directly in your brain to sense and interrupt activity. The latter approach has the advantage of more specific readings, but has the obvious drawback of requiring surgery and wires in your brain.

There’s a competition held every four years called Cybathlon, sponsored by ETH Zurich, that “acts as a platform that challenges teams from all over the world to develop assistive technologies suitable for everyday use with and for people with disabilities.” A profile of it in NYT quoted the second place finisher, who uses the external signals approach but lost to a team using implants: “We weren’t in the same league as the Pittsburgh people. They’re playing chess and we’re playing checkers.”  He’s now considering implants.  

A Cybathlon 2024 competitor. Credit: Cybathlon ETH Zurich

Fine, you say. I can protect my mental privacy simply by not getting implants, right?  Not so fast. A new paper in Science Advances discusses progress in “mind captioning.” I.e.:

We successfully generated descriptive text representing visual content experienced during perception and mental imagery by aligning semantic features of text with those linearly decoded from human brain activity…Together, these factors facilitate the direct translation of brain representations into text, resulting in optimally aligned descriptions of visual semantic information decoded from the brain. These descriptions were well structured, accurately capturing individual components and their interrelations without using the language network, thus suggesting the existence of fine-grained semantic information outside this network. Our method enables the intelligible interpretation of internal thoughts, demonstrating the feasibility of nonverbal thought–based brain-to-text communication.

The model predicts what a person is looking at “with a lot of detail”, says Alex Huth, a computational neuroscientist at the University of California, Berkeley who has done related research. “This is hard to do. It’s surprising you can get that much detail.”

“Surprising” is one way to describe it. “Exciting” could be another.  For some people, though, “terrifying” might be what first comes to mind.

The mind captioning uses fMRI and  AI to do the mind captioning, and the participants were fully aware of what was going on. None of the researchers suggest that the technique can tell exactly what people are thinking. “Nobody has shown you can do that, yet,” says Professor Huth.

 It’s that “yet” that worries me.

Dr. Kinstler points out that’s not all we have to worry about: “Advances in optogenetics, a scientific technique that uses light to stimulate or suppress individual, genetically modified neurons, could allow scientists to “write” the brain as well, potentially altering human understanding and behavior.”

“What’s coming is A.I. and neurotechnology integrated with our everyday devices,” Nita Farahany, a professor of law and philosophy at Duke University who studies emerging technologies, told Dr. Kinstler. “Basically, what we are looking at is brain-to-A.I. direct interactions. These things are going to be ubiquitous. It could amount to your sense of self being essentially overwritten.” 

Now are you worried?

Dr. Kinstler notes that some countries – not including the U.S., of course – have passed neural privacy laws. California, Colorado, Montana and Connecticut have passed neural data privacy laws, but the Future of Privacy Forum details how each is different and that there is not even a common agreement on exactly what “neural data” is, much less how best to safeguard it. As is typical, the technology is way outpacing the regulation.

Credit: Future of Privacy Forum

“While many are concerned about technologies that can “read minds,” such a tool does not currently exist per se, and in many cases nonneural data can reveal the same information,” writes Jameson Spivack, Deputy Director for Artificial Intelligence for FPF. “As such, focusing too narrowly on “thoughts” or “brain activity” could exclude some of the most sensitive and intimate personal characteristics that people want to protect. In finding the right balance, lawmakers should be clear about what potential uses or outcomes on which they would like to focus.”

I.e., we can’t even define the problem well enough yet.  

Dr. Kinstler describes how people have been talking about this issue literally for decades, with little progress on the legislative/regulatory front. We may be at the point where debate is no longer academic. Professor Farahany warns that having the ability to control ones thoughts and feelings ““is a precondition to any other concept of liberty, in that, if the very scaffolding of thought itself is manipulated, undermined, interfered with, then any other way in which you would exercise your liberties is meaningless, because you are no longer a self-determined human at that point.”

In 2025 America, this does not seem like an idle threat.

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In this digital world, we’ve gradually been losing our privacy. Our emails aren’t private? Oh, OK. Big tech is tracking our shopping? Well, we’ll get better offers. Social media mines our data to best manipulate us? Yes, but think of the followers we might gain. Surveillance camera can track our every move? But we need it to fight crime!

We grumble but mostly have accepted these (and other) losses of privacy. But when it comes to the possibility of technology reading our thoughts, much less directly manipulating them, we cannot afford to keep dithering.

Support Your Neighborhood Scientist

These are, it must be said, grim times for American science. Between the Trump budget cuts, the Trump attacks on leading research universities, and the normalization of misinformation/ disinformation, scientists are losing their jobs, fleeing to other countries, or just trying to keep their heads down in hopes of being able to just, you know, keep doing science.

Seriously: you should. Credit: Stand Up for Science

But some scientists are fighting back, and more power to them. Literally.

Lest you think I’m being Chicken Little, warning prematurely that the sky is falling, there continue to be warning signs. Virginia Gewin, writing in Nature, reports Insiders warn how dismantling federal agencies could put science at risk. A former EPA official told her: “It’s not just EPA. Science is being destroyed across many agencies.” Even worse, one former official warned: “Now they are starting to proffer misinformation and putting a government seal on it.”  

A third researcher added: “The damage to the next generation of scientists is what I worry the most about. I’ve been advising students to look for other jobs.”

It’s not just that students are looking for jobs outside of the government. Katrina Northrop and Rudy Lu write in The Washington Post about the brain drain going to China. “Over the past decade,” they say, “there has been a rush of scholars — many with some family connection to China — moving across the Pacific, drawn by Beijing’s full-throttle drive to become a scientific superpower.” They cite 50 tenure track scholars of Chinese descent who have left U.S. universities for China. Most are in STEM fields.

“The U.S. is increasingly skeptical of science — whether it’s climate, health or other areas,” Jimmy Goodrich, an expert on Chinese science and technology at the University of California Institute on Global Conflict and Cooperation, told them. “While in China, science is being embraced as a key solution to move the country forward into the future.”

They note how four years ago the U.S. spent four times as much in R&D than China, whereas now the spending is basically even, at best.

I keep in mind the warning of Dan Wang, a research fellow at Stanford’s Hoover Institution:

Think about it this way: China is an engineering state, which treats construction projects and technological primacy as the solution to all of its problems, whereas the United States is a lawyerly society, obsessed with protecting wealth by making rules rather than producing material goods.

We’ve seen what a government of lawyers does, creating laws and regulations that protect big corporations and the ultra-rich, while making everything so complex that, voila, more lawyers are needed. Maybe it’s time to see what a government of scientists could do.

When scientists (or engineers) are in charge, we can put a man on the moon within a decade or create a pandemic vaccine in months. When lawyers are in charge we get Congresses that can’t even pass a budget.  

In The Atlantic, Katherine J. Wu discusses a new wave of scientists who are running for public office. Core to that effort is 314 Action, which claims it is “the only organization in the nation focused on recruiting, training, and electing Democrats with a background in science to public office.” Shaughnessy Naughton, the president of 314 Action, told Ms. Wu the organization had fielded 700 applications from scientists interested in becoming candidates just this year, which is seven times what it would normally expect.

Credit: 314 Action

Ms. Wu cites data from Rutgers University’s Eagleton Institute of Politics that only 3 percent of state legislators are scientists, engineers, or health-care professionals – and most of those are Republicans. 314 action thinks it can help change that. Its website declares:

Bottom line: when candidates run on their science credentials and have the backing to get their message out there, they win. 314 Action candidates are scientists first, not politicians. We’re fighting to elect scientists who can tackle urgent shared challenges – like the climate crisis, reproductive rights, and healthcare access –  and secure a better future for us all. 

It claims to have raised some $8.6m and help elect 400 endorsed candidates, including 4 U.S. Senators, 13 members of the U.S. House, 9 candidates for down-ballot statewide offices, and over 300 candidates at the state and municipal level. Ms. Wu reports that Hawaii’s Josh Green, the only Democratic physician currently serving in a state governorship, has partnered with 314 Action to launch a $25 million campaign to elect 100 new Democratic physicians to office by 2030.

“Politics came for us,” pediatrician Annie Andrews told Ms. Wu. “You can’t fight bad politics by staying apolitical.”

Running for office is only one way for scientists (or people who care about science) to fight back. Take Stand Up for Science, which believes in protesting loudly and proudly. Founded just this year in response to Trump Administration actions, Stand Up for Science describes itself as “a political activism organization dedicated to defending and advancing America’s scientific ecosystem, a cornerstone of democracy, freedom, and progress.”

Its mission:

We believe that science is the lifeblood of American democracy and freedom. With a bold strategy combining activism, messaging campaigns, grassroots organizing, and political advocacy, we’re mobilizing the fight for science and democracy, now and for generations to come.

SUFS was active in the No Kings protests, and is conducting an important – and amusing -- effort to impeach HHS Secretary Robert Kennedy Jr. called “Impeach the Quack,” complete with toy ducks.

Founder and Chief Executive Officer Colette Delawalla, MA, MS manages to run the organization while working on her Ph.D. (and apparently being a mom). She saw the need as soon as Trump was inaugurated. “You’ve got these legacy organizations that have simply not thought it was that important to communicate with the public in a meaningful way,” she told NOTUS. “Any of these organizations — and I know this because I’ve done it — on Jan. 21, 2025, could have stood up, in less than 24 hours, a 501(c)(4) nonprofit arm of what they’re already doing, and granted over some money, set up a little team, and gotten political.” Too few did, so she created her own organization.

Both 314 Action and Stand Up for Science deserve our support.

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Scientists are no angels (e.g., James Watson, William Shockley), Maybe putting them in charge isn’t the answer. But, really, could they do any worse than our current politicians? We’re quickly moving into an era of AI, quantum computing, synthetic biology, and a host of other advances, while battling climate change, microplastics, income inequality, and many other challenges. Who do you think will be best able to deal with them: lawyers, or scientists?  

Life Is Geometry

In 2025, we’ve got DNA all figured out, right?  It’s been over fifty years since Crick and Watson (and Franklin) discovered the double helix structure. We know that permutations of just four chemical bases (A, C, T, and G) allow the vast genetic complexity and diversity in the world. We’ve done the Humam Genome Project. We can edit DNA using CRISPR. Heck, we’re even working on synthetic DNA. We’re busy finding other uses for DNA, like computing, storage, or robots. Yep, we’re on top of DNA.

Super-resolution imaging reveals the 3D geometry of the genome. Credit: Northwestern University

Not so fast. Researchers at Northwestern University say we’ve been missing something: a geometric code embedded in genomes that helps cells store and process information. It’s not just combinations of chemical bases that make DNA work; there is also a “geometric language” going on, one that we weren’t hearing.

Wait, what?

The research - Geometrically Encoded Positioning of Introns, Intergenic Segments, and Exons in the Human Genome – was led by Professor Vadim Backman, Sachs Family Professor of Biomedical Engineering and Medicine at Northwestern’s McCormick School of Engineering, and director of its Center for Physical Genomics and Engineering. The new research indicates, he says, that: “Rather than a predetermined script based on fixed genetic instruction sets, we humans are living, breathing computational systems that have been evolving in complexity and power for millions of years.”

The Northwestern press release elaborates:

The geometric code is the blueprint for how DNA forms nanoscale packing domains that create physical "memory nodes" — functional units that store and stabilize transcriptional states. In essence, it allows the genome to operate as a living computational system, adapting gene usage based on cellular history. These memory nodes are not random; geometry appears to have been selected over millions of years to optimize enzyme access, embedding biological computation directly into physical structure.

Somehow I don’t think Crick and Watson saw that coming, much less either Euclid or John von Neumann.

Coauthor Igal Szleifer, Christina Enroth-Cugell Professor of Biomedical Engineering at the McCormick School of Engineering, adds: “We are learning to read and write the language of cellular memories. These ‘memory nodes’ are living physical objects resembling microprocessors. They have precise rules based on their physical, chemical, and biological properties that encode cell behavior.”

“Living, breathing computational systems”? “Microprocessors”? This is DNA computing at a new level.

Electron microscopy resolves a 3D packing domain— the physical “memory node”
of the human genome. Credit: Northwestern Engineering

The study suggests that evolution came about not just by finding new combinations of DNA but also from new ways to fold it, using those physical structures to store genetic information. Indeed, one of the researchers’ hypothesis is that development of the geometric code helped lead to the explosion of body types witnessed in the Cambrian Explosion, when life went from simple single and multicellular organisms to a vast array of life forms.

Coauthor Kyle MacQuarrie, assistant professor of pediatrics at the Feinberg School of Medicine, points out that we shouldn’t be surprised it took this long to realize the geometric code: “We’ve spent 70 years learning to read the genetic code. Understanding this new geometric code became possible only through recent advances in globally-unique imaging, modeling, and computational science—developed right here at Northwestern.” (Nice extra plug there for Northwestern, Dr. MacQuarrie.)

Coauthor Luay Almassalha, also from the Feinberg School of Medicine, notes: “While the genetic code is much like the words in a dictionary, the newly discovered ‘geometric code’ turns words into a living language that all our cells speak. Pairing the words (genetic code) and the language (geometric code) may enable the ability to finally read and write cellular memory.”

I love the distinction between the words and the actual language. We’ve been using a dictionary and not realizing we need a phrase book.   

I recently read about, and was impressed by, something called MetaGraph, a tool developed at ETH Zurich to search DNA databases. "It's a kind of Google for DNA," as Professor Gunnar Rätsch, data scientist at the Department of Computer Science at ETH Zurich, puts it. This “DNA search engine” makes it much easier, faster, and cheaper to search for DNA sequences and compare them to other sequences. Cool as that is, the existence of the geometric code means that the ETH Zurich folks may have some additional work to do, as is true of lots of other people working with DNA.

I hate to say it’s a whole new ball game, but there certainly are some important new rules.

The presence of this geometric code has implications for our health. It may not always be DNA mutations that cause problems; our DNA structures may sometimes be falling apart. Dr. Almassalha says: “Instead of a puzzle of genetic words, the geometric code lets cells build elaborate tissues, such as brains or skin. But with age, this language loses its fidelity. This decay results in neurodegeneration, cancer, or other diseases of aging.”

This opens up all sorts of new avenues for research, and, potentially, treatments. “The next step is to fully learn the engineering principles of the geometric code so we can repair dysregulated cell memories or create entirely new ones,” Professor Backman says. “Current approaches to aging try to reset cells back to a factory default state. The geometric code works differently. Cell memories are physical structures enhanced by experience. Revitalizing cells resembles restoring the clarity of a well-loved book — bringing back the stories our cells already know how to tell.”

This isn’t CRISPR. This isn’t mRNA. This is a new way of thinking about cells and our genome. This is a whole new step in computational biology, and it may be foundational in 22^nd century medicine.

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If you are a physics or cosmology buff, you may have heard the expression “The universe is geometry.” E.g., Einstein’s general theory of relativity indicates gravity is not a force but, rather, the result of distortions in spacetime. Similarly, whether the universe is flat (Euclidian), positively curved (spherical), or negatively curved (hyperbolic) has profound implications for the fate of the universe. In fact, some scientists believe that geometry may explain everything from the smallest particles to the universe itself.

So it pleases me to think that life itself may owe much to geometry as well.