#jevons paradox

[unitedfrontvarietyhour]

"The question, in brief, is whether democracy and freedom are values to be preserved or threats to be avoided. In this possibly terminal phase of human existence, democracy and freedom are more than values to be treasured; they may well be essential to survival."

- Noam Chomsky

Happy Earth Day.

(Pt.1)

[angelsaxis]

Interesting read.

[forexmastertrader]

Deepseek, NVDA и магията на математиката: какво наистина се случва?

Deepseek, NVDA и магията на математиката: какво наистина се случва? Въведение Събитията от вчера разтърсиха сектора на изкуствения интелект (AI), като повечето компании в тази индустрия претърпяха значителни спадове на цените на акциите си. Сред на��-засегнатите бяха гигантите, които досега се възприемаха като непоклатими в лицето на технологичните промени. Пазарът реагира бурно на новината за…

[miloalli14]

nvidia stock

[babyenemychild]

Why the Chiefs’ Chris Jones Was Crying on the Sidelines During Their AFC Championship Win

READ MORE

[collapseofindustrialcivilization]

William of Ockham and the Collapse of Complexity: A Razor's Edge for the End Times

The Man Who Cut Through the Noise In the 14th century, a Franciscan friar named William of Ockham wielded an intellectual tool so sharp it still slices through modern delusions: Ockham’s Razor. His principle—“Entities are not to be multiplied beyond necessity”—was a rebellion against medieval scholasticism’s tangled webs of abstraction. As the Church fractured under rival popes—each justifying…

[link-layer]

The AI Efficiency Paradox

Understanding Jevons Paradox

Jevons Paradox occurs when technological progress increases the efficiency of resource use, but the rate of consumption of that resource rises due to increasing demand. The core mechanism is simple: as efficiency improves, costs decrease, making the resource more accessible and creating new use cases, ultimately driving up total consumption.

In the 1860s, economist William Stanley Jevons made a counterintuitive observation about coal consumption during the Industrial Revolution. Despite significant improvements in steam engine efficiency, coal consumption increased rather than decreased. This phenomenon, later termed "Jevons Paradox," suggests that technological improvements in resource efficiency often lead to increased consumption rather than conservation. Today, as artificial intelligence transforms our world, we're witnessing a similar pattern that raises important questions about technology, resource usage, and societal impact.

 The AI Parallel

Artificial intelligence presents a modern manifestation of Jevons Paradox across multiple dimensions:

 Computational Resources

While AI models have become more efficient in terms of performance per computation, the total demand for computational resources has skyrocketed. Each improvement in AI efficiency enables more complex applications, larger models, and broader deployment, leading to greater overall energy consumption and hardware demands.

 Human Labor and Productivity

AI tools promise to make human work more efficient, potentially reducing the labor needed for specific tasks. However, this efficiency often creates new demands and opportunities for human work rather than reducing overall labor requirements. For instance, while AI might automate certain aspects of programming, it has simultaneously increased the complexity and scope of software development projects.

 Data Usage

As AI systems become more efficient at processing data, organizations collect and analyze ever-larger datasets. The improved efficiency in data processing doesn't lead to using less data – instead, it drives an exponential increase in data collection and storage needs.

 Implications for Society and Technology

The AI manifestation of Jevons Paradox has several important implications:

 Resource Consumption

Despite improvements in AI model efficiency, the total environmental impact of AI systems continues to grow. This raises important questions about sustainability and the need for renewable energy sources to power AI infrastructure.

 Economic Effects

The paradox suggests that AI efficiency gains might not lead to reduced resource consumption or costs at a macro level, but rather to expanded applications and new markets. This has significant implications for business planning and economic policy.

 Social Impact

As AI makes certain tasks more efficient, it doesn't necessarily reduce human workload but often transforms it, creating new roles and responsibilities. This challenges the simple narrative of AI leading to widespread job displacement.

 Addressing the Paradox

Understanding the AI efficiency paradox is crucial for developing effective policies and strategies:

Resource Planning: Organizations need to plan for increased resource demands rather than assuming efficiency improvements will reduce consumption.

Sustainability Initiatives: The paradox highlights the importance of coupling AI development with renewable energy and sustainable computing initiatives.

Policy Considerations: Regulators and policymakers should consider Jevons Paradox when developing AI governance frameworks and resource management policies.

 Looking Forward

As AI technology continues to evolve, the implications of Jevons Paradox become increasingly relevant. The challenge lies not in preventing the paradox – which may be inherent to technological progress – but in managing its effects responsibly. This requires:

- Investment in sustainable infrastructure to support growing AI resource demands

- Development of policies that account for rebound effects in resource consumption

- Careful consideration of how efficiency improvements might reshape rather than reduce resource usage

The parallels between historical patterns of resource consumption and modern AI development offer valuable lessons for technology leaders, policymakers, and society at large. As we continue to push the boundaries of AI capability, understanding and accounting for Jevons Paradox will be crucial for sustainable and responsible technological progress.

[consciousenergies-blog]

The Energy Freedom Paradox: A Mathematical Proof for ElectroDynamic Socio-Economics

Author: Diadon Acs Date: 13/9/2024  Open-Science Publication Conscious.Energy Abstract: The Energy Freedom Paradox (EFP) posits a complex interplay between energy availability, socio-economic development, individual perception, and societal well-being. This paper presents a mathematical formulation of the EFP, integrating key concepts from physics, economics, and information theory. Our model…

[dejoe]

Will Energy Efficiency Actually Lead to Energy Savings?

For years, governments around the world—whether in the EU, North America, or beyond—have set ambitious goals to improve energy efficiency as a primary solution to combating climate change and reducing resource consumption. From policies promoting energy-efficient appliances to standards for renewable energy adoption, the hope is that improving efficiency will lead to less energy use and lower emissions.

But what if all this focus on efficiency might actually be doing the opposite? What if, instead of reducing energy consumption, increasing efficiency leads to more demand for energy? This paradox, known as Jevons' Paradox, challenges the very idea that technological advancements alone can reduce our environmental footprint.

At its core, Jevons' Paradox is a counterintuitive economic phenomenon: as technological improvements make the use of a resource more efficient, overall consumption of that resource can actually increase.

Imagine a fuel-efficient car. You save money on gas, so you drive more. This "rebound effect" undermines the very efficiency gains you sought. Jevons' Paradox highlights this: making something easier or cheaper to use often leads to increased use, not decreased.

It also creates new product categories. Take for example LEDs. By being 6x efficient LEDs have created Electronic Billboards leading to higher usage, erasing all the gains elsewhere.

In other cases it makes the resources affordable that it opens it up to a new class of consumers, thereby increasing consumption. For example air travel. By making flying more efficient, the price would be decreased, thereby leading to more travel.

While making technology more efficient is an important piece of the puzzle, we must also reconsider how we approach resource use on a larger scale. By combining efficiency with smarter policies, behavioral changes, and reforms, we can move toward a more sustainable future.

[xenokhi]

The Planet Is Dying Because the Rich Don’t Care.

Checking out Greensky and got so angry that I had to write it out...please tell me you guys actually understand this and it is just the rest of the world that needs to clue in.

Everyone’s talking about the damages of AI and treating Teslas like they’re going to reverse climate change.

They won’t. They’re distractions. Shiny, expensive, high-tech distractions that let the real problem off the hook. To move a conversation from the real issue.

Let’s talk about who’s actually killing the planet. Because it’s not you. It’s not me. It’s not your neighbor who forgot to recycle their almond milk carton.

************************************************************************

-----The richest 1% of the global population emit more carbon than the bottom 66% combined.

That’s right. While you’re stressing over paper straws and reusable grocery bags, billionaires are flying private jets from conference to conference to talk about how to fight climate change.

Source: https://www.oxfam.org/en/press-releases/carbon-emissions-richest-1-percent-more-double-emissions-poorest-half-humanity

-----The U.S. military is the world’s biggest institutional polluter.

It uses more fossil fuels than entire countries. It’s not regulated by the Paris Agreement. No one talks about it.

Source: https://watson.brown.edu/costsofwar/files/cow/imce/papers/2019/Pentagon%20Fuel%20Use%2C%20Climate%20Change%20and%20the%20Costs%20of%20War%20Final.pdf

-----100 companies are responsible for 71% of all global industrial emissions since 1988.

You read that right. One hundred companies. Chevron, ExxonMobil, BP, Shell and they knew what they were doing.

They didn’t stop. They funded climate denial.

Source: https://www.cdp.net/en/press-releases/new-report-shows-just-100-companies-are-source-of-over-70-of-emissions

-----EVs don’t fix this.

Most electricity still comes from fossil fuels (60% in the U.S.) Lithium mining destroys ecosystems and drains water from Indigenous lands. Rich countries just export pollution to the Global South

Electric cars might reduce your footprint, but they’re still built on extractive systems. And guess what? The richest 1% will just buy more of them. More land, more energy, more mining.

Source: https://www.nature.com/articles/s41467-021-24487-w

-----Efficiency doesn’t mean less. It often means MORE. This is called the Jevons Paradox: when things get more efficient, consumption often goes up.

We’re consuming 4x more materials now than in 1970.

Source: https://www.greenchoices.org/news/blog-posts/the-jevons-paradox-when-efficiency-leads-to-increased-consumption

-----Billionaires emit over a million times more carbon than the average person.

But sure, tell me more about my thermostat.

Source: https://www.oxfam.org/node/21337

************************************************************************

The only real solutions are the ones the rich fear most:

End fossil fuel subsidies

Tax the carbon billionaires

Ban private jets

Invest in Indigenous land rights

Degrowth for the wealthy, not the poor

Global climate reparations

This is not about personal choices. This is about power.

Until we stop chasing trending topics and misinformation to cause conflicts of opinions, we will keep losing time. We will keep losing species. We will keep losing lives.

Climate change is class war. And the side with all the money is winning because we’re busy arguing over compost bins while they’re torching the planet for profit.

[unitedfrontvarietyhour]

"The question, in brief, is whether democracy and freedom are values to be preserved or threats to be avoided. In this possibly terminal phase of human existence, democracy and freedom are more than values to be treasured; they may well be essential to survival."

- Noam Chomsky

Happy Earth Day.

(Pt.1)

[presidentdisastraofgallifrey]

Live-blogging Gallifrey: Ascension

Romana the second she finds herself at home: I am not your President I don’t want to be your President please don’t make me do this again

Sefghkjugfdsw mandatory lockdowns. Imagine that.

Also how long has it been since Pandora? Are they saying there’s been ANOTHER war since then? That line was unclear

“Absolutely without precedent. Well, except for that one time.” That is VERY Time Lord

“Under Romana, things were so much better. A golden age of Gallifrey.” How long has it been?? You all HATED her. And also she started a war and declared herself dictator

She can’t fucking escape this life even when she doesn’t want power lol

Oh I think Leela should get to be a werewolf proper btw. Not just heightened senses but everything else that goes with it

Oh dang, Jevon has Andred’s job now (I had to look him up to be sure but I KNEW i remembered him as one of the guards who was a dick to Leela on alt!Gallifrey and I feel proud I was right)

Non consensual presidency

Ok so this is recontextualizing last episode, but I still think Renaissance is my least favorite so far just for listening to

Oh is it time for Zombie Apocalypse 2: Electric Boogaloo?

Anyone who says “not now, K-9” really deserves what’s about to happen to them

They JUST put her back in power and already everyone is yelling at her what to do. Do they really treat every President like this, or just her?

Do. Not. Give. This. Guy. Your. Codes. He is clearly SO shady

You’d think she’d be better at protecting these after, you know, not giving them to the daleks for twenty years

“But Narvin will have a fit! …which makes it worth it 😏” Amazing

She used to judge how much danger they were about to be in by the Doctor saying “what could go wrong?” “It can’t do any more harm” should NOT be in her vocabulary. You should know better, Madame President

*literally cuts to things exploding*

I need Trey to kiss Leela

Narvin: saves Leela’s life

Narvin five minutes later: But why did you come back for me? 🤔

I don’t feel too bad about Leela being confused by Slyne’s appearance, since Romana did the same thing at first

WAIT THE MATRIX CAN RESET REAL LIVING PEOPLE?? Whose idea was this, that’s such a bad plan!!

Narvin like “I leave you alone for a few hours and you seize power again”

Oh damn Leela. Good for her

This is still ridiculous. Not out of character for time lords of course, but utterly ridiculous. They’re so connected to the matrix it can treat them like a computer in need of a rollback to previous save

I know it’s widely assumed renegades are deleted from the matrix but he just included them. Are the Doctor and Master asleep somewhere too and about to wake up confused? (One with no memory of a current companion, the other stuck mid plan no idea what it was?) Can this set people back to previous regenerations? I HAVE SO MANY QUESTIONS

Sigh. It really is always the daleks

I never thought the exterminating monsters would exterminate MY face! 😧

Let Romana say fuck

I would like to point out that, while as Leela likes to point out none of the time lords are particularly athletic, Romana does seem to get winded the fastest every time they have to run away

And she’s facing the idea of potential dalek torture again, oh this is so delicious

(Also the “they’ll rip it from my mind if they have to” implies she couldn’t resist them again which goes nicely with the idea of her psychic barriers being all messed up)

I know Trey is fake but I like the idea that Romana programmed her to be enough of herself that she is also dealing with dalek trauma

WAIT THE FACT THAT TREY IS FAKE HAS ANOTHER GREAT IMPLICATION: Romana met her before creating her, but she’s not real so it wouldn’t really be a paradox if she regenerated into her…because she thought she was hot

I love Leela and Narvin’s we’re-friends-now dynamic

“It is customary to knock before entering my office” SINCE WHEN MA’AM

Lmao this only works because they expect her be self sacrificial instead of cunning

(She is, of course, both)

This is of course deliciously tragic, but I’m also laughing because this is THREE TIMES now that the matrix has been destroyed or rendered useless in this show

Leela’s right, you dumbass. This is your worst plan ever

Oh I love Narvin being called a weirdo. He is so weird, just not as weird as her his friends

Dfjkhfds he’s going to the Doctor I did NOT see that coming

Oh SHIT genesis of the daleks was directly because of Narvin\

Actually imagining a version of Genesis now where the Doctor got more information, namely that this was about saving Gallifrey his friend he hasn't met yet

Helps to save everyone -> Immediately starts the time war

Ok this hurts. If Narvin could have waited like. An HOUR, it might have all been alright. Gallifrey would be safe and the time war wouldn’t have happened

But this also means that the time war happened directly because of that one time the Doctor didn’t destroy all the daleks. Not indirectly, as in they existed to do it, but directly because of that. Damn! Do you think he knows?

[probablyasocialecologist]

Agricultural intensification under the guise of sparing “wilderness” can lead to greater deforestation and disease spillover. By the Jevons paradox, more efficient extraction and cheapening production can increase resource use and associated environmental destruction overall. Empirical evidence suggests that, with few exceptions, agricultural intensification programs lead to more deforestation, not less. So the specific mode of agriculture matters a great deal in assessing its role in forest destruction, biodiversity loss, and the production of food.

Can agroecology stop COVID-21, -22, and -23? Moving Beyond Capitalist Agriculture

[realcleverscience]

AI and Natural Resources

Continuing on my theme of why I think AI is actually a good thing overall...

Lots of discussion about AI using energy, water, and producing emissions. These are, once again, extremely valid concerns. At the same time, this doesn't mean that AI "isn't worth it". This is because we have to compare those costs against the status quo.

For instance, let's take translation as an example. I work with immigrant populations and know first-hand the communication obstacles that exist, as well as the fact that many agencies still use human translation services (especially for legal or technical writing).

From what Perplexity has informed me, the average human can translate around 5,000 words a day (this may be specifically for writing).

For an AI, that amount of translation might represent 50 queries, totaling 0.145 kWh of electricity, as much as 5 liters of water, and 0.12 lbs of CO2.

What about a human? The average person uses 29.4 kWh per day, 100 liters of water per day (again, the time in which they translate 5k words), and 45 lbs of CO2 per day.

When compared in terms of economic output (again, 5k words translated), we find that humans use around 200x as much energy, 20x as much water, and 300x as much CO2.

And the craziest part: We are measuring in terms of a human day's output of 5k words. The AI can accomplish this in minutes. AI translation is literally hundreds of times more efficient than humans for most situations*. (*Granted, there's still work to be done in this field, particularly for adding more languages.)

This presents a pro and a con:

Pro: Lots more translation! Helps tons of people, including lots of people in other countries or migrants. And it's much more resource efficient.

Con: Even though it's 100x more resource efficient, its use is growing 1,000x, which ultimately means more resource usage, even if it's being used much more efficiently.

Put another way: Let's say some major event happens and the US decides it needs translators. We can either divert workers from other sectors or rely on population growth to "grow" an expanded workforce. To double the number of human translators and translations, we'd need to double the resources (food, paper, lights, co2, homes, etc.) But if we doubled it with AI, we'd only need to add 1-5% more resources (water, energy, co2). AI is an amazingly effective way to reduce costs & promote efficiency, while maintaining or even massively growing output.

The downside is that our appetite/need for AI goods, whether translation services, images, software code, etc, is magnitudes greater than our current, human output. Which means that as these technologies become cheaper and easier to access, much more resources are being used.

But this doesn't mean AI is bad. AI is amazing. Rather, it means we either need to tamp down economic growth (e.g. expect fewer translations, as when it was dominated by human translators; this is not good for people who need those services), reduce resource consumption (e.g. instead of 100x efficiency gains, let's get to 1,000x or 10,000x, which companies are working on), or produce more resources (e.g. expand energy generation, expand *sustainable* water generation, switch to more sustainable materials growth; e.g. bioplastics; which again, companies are working on).

We do have to contend with Jevon's Paradox (as things become more abundant, people just use more of it till it's not abundant) and how that reality butts against our current capitalist system and it's unsustainable practices.

That said, AI is allowing humanity to massively grow its technological advances and economic output with a fraction of the resources it would take to do that with human growth. So we need to do use it responsibly, and push for further efficiencies, but it's undoubtedly a boon for humanity.

p.s. By way of additional context, to make a single hamburger requires 2400 liters of water and emits about 3.1 kg of CO2 - that's nearly 500x as much water and 6.5x as much CO2. For a *single* hamburger.

[mariacallous]

The most powerful people in the United States are obsessed with spending more on artificial intelligence (AI). Besides Greenland and Gaza, President Donald Trump has signaled that he wants total dominance of the technology. Elon Musk wants OpenAI, a leading player, for himself. And OpenAI CEO Sam Altman is aiming for artificial general intelligence, or AGI, which mimics all human capabilities—and he’s pushing for “exponentially increasing investment” to get there.

Even as a hitherto obscure Chinese lab, DeepSeek, has demonstrated a cost- and energy-efficient approach to AI development, the U.S. tech industry has taken the present situation as its own Sputnik moment. Americans have derived all the wrong lessons: spend even more on AI; trust Chinese technology even less; and reach back to analogies from the 19th-century English coal industry to justify the seemingly unjustifiable 21st-century expenditures in AI.

Undeterred by proof that pretty good AI can be produced with a fraction of the planned spending, the major players have responded by upping the ante. Last year, CNBC estimated that AI investments added up to $230 billion; this year, Amazon alone plans to spend $100 billion on AI infrastructure, Alphabet will pitch in $75 billion, Meta’s bill could run up to $65 billion, and Microsoft will spend $80 billion on AI data centers in the fiscal year ending in June, with more to come for the balance of 2025. The so-called “Magnificent Seven” tech companies will now be spending more on capital investment than the U.S. government’s entire budget for research and development across all industries.

This showering of industry spending on AI is happening in the larger context of the U.S. public sector being stripped of people and resources in the name of efficiency. Ironically, a part of the new administration’s so-called efficiency plans involves replacing government civil servants with AI.

Why hasn’t this messianic urge for finding savings hit the private sector, where one would expect competitive market pressures to demand such discipline?

Three forces are in play; collectively, they are locking the U.S. industry into a trap.

A central argument for increased investment is a variant of the Jevons paradox, a theory that dates back to post-Industrial Revolution 1860s but is back in fashion in the proto-AI age.

The English economist William Stanley Jevons had argued that technologies that made more efficient use of coal would only make England’s coal-shortage problem worse by driving up demand for the fuel. The argument is intuitive—with greater efficiency, costs and, therefore, prices fall, triggering more demand and creating the need for more coal to meet the rising demand.

This logic is at the heart of the case that the leading AI players are making. In arguing for more investment, Alphabet CEO Sundar Pichai told the Wall Street Journal that “we know we can drive extraordinary use cases because the cost of actually using it [AI] is going to keep coming down,” while Microsoft CEO Satya Nadella posted on X in January, “Jevons paradox strikes again!” and went on to declare his own intentions to spend more.

There is no doubt that we are still early in our learning about AI’s many uses. But it’s unclear whether the technology’s uneven adoption picture will be improved simply by the availability of cheaper tools. According to a study conducted by Boston Consulting Group, only 26 percent of companies surveyed have derived tangible value from AI adoption, despite all the spectacular advances.

Worse yet, trust in AI has been declining. That trend is likely to persist; with fewer guardrails and regulations coming from the United States, the largest source of AI tools, this will act as a brake on adoption. More than 56 percent of Fortune 500 companies have listed AI as one of the risk factors in their annual reports to the U.S. Securities and Exchange Commission. Overall, business decision-makers have struggled to demonstrate an adequate return on investment in AI so far.

But will cheaper AI unlock greater demand for the technology—along with demand for more data centers and high-end chips in the proportions anticipated by these unprecedented levels of investment?

New frugal AI formulas are already in the market: DeepSeek alone has shown ways to economize on the computing power needed—through, for example, open-source models rather than proprietary ones, a “mixture of experts” technique that splits the AI’s neural networks into different categories, or even resorting to lopping off decimal places on numbers used in calculations.

Despite these new revelations, none of the major AI players have made the case for why they haven’t altered their strategies or R&D budgets. Lower prices alone may not drive up demand for more AI infrastructure, as Jevons’s theory about coal might suggest, and even if they did, there are far cheaper ways to assemble that infrastructure.

With hundreds of billions of dollars at stake, it is unwise to overlook the lessons of numerous earlier technological disruptions, where persistent heavy investments by incumbents led to massive destruction of value. What has frequently happened in these cases is that incumbents ignored the overturning of received industry wisdom by entrants armed with minimal investments but “good enough”—and, often, ultimately better—products.

Consider the examples of Kodak and the emergence of digital imaging, BlackBerry and the rise of the Apple iPhone and the apps ecosystem, Blockbuster being sidelined by Netflix, and so many more.

There is a second factor that is hard to ignore: The major AI players are locked into a mutually reinforcing and collectively binding embrace. Each of the major players has experienced near-term benefits from increasing investments in development. For Google, generative AI is an existential threat to its most lucrative business, its search engine, so the company had no choice but to invest to defend its most precious asset. Moreover, the company reports that 2 million developers are using its AI tools, and its cloud services revenue from AI has grown by billions.

Microsoft’s Azure AI has seen new revenues estimated to be about $5 billion last year, up 900 percent annually, and the company has experienced the number of daily users double every quarter for its AI-aided Copilot. Amazon, too, has earned billions from its AI-related cloud services and in driving operational efficiencies into its online retail businesses. Meta CEO Mark Zuckerberg hopes to be the “leading assistant” for a billion people (whatever that means) and to “unlock historic innovation” and “extend American technology leadership.” More pragmatically, Meta sees demand for data centers growing and wants to be at the forefront of serving that demand.

For Amazon, Google, and Microsoft in the near term, greater AI spending increases demand for their cloud services. Indeed, these companies have been giving each other business and driving up each other’s revenues, which keeps the mutually reinforcing justification for investing going for a while. As long as each player believes that all the others are going to keep investing heavily, it is not in the interests of any individual player to pull back, even if they harbor concerns privately.

In the language of game theory, this devolves into a suboptimal Nash equilibrium—a situation where every party is locked in, and it is not compatible with their incentives to unilaterally break from the industry’s norm.

A third force locking the industry into its flood of investment is the U.S. government and its geopolitical interests. The White House has sent several signals of its intention of ensuring U.S. domination in the AI industry and keeping Chinese technologies away from usurping that position. Tellingly, the ambitious $500 billion Stargate project, a new joint venture for building out AI infrastructure led by SoftBank and OpenAI with several other partners, was announced not in Silicon Valley but in the Roosevelt Room of the White House, just one day after Trump’s inauguration.

Even though DeepSeek surfaced just a few days later and seems poised to make such giant commitments look like overkill, construction of the first Stargate site is already underway in Texas. Vice President J.D. Vance took to the podium at the recent Artificial Intelligence Action Summit in Paris to advance an aggressive “AI opportunity” agenda and—with an obvious reference to China—warn against “cheap tech in the marketplace that’s been heavily subsidized and exported by authoritarian regimes.”

The Trump administration’s approach to championing the U.S. AI industry is one of the few areas where it has taken a page from the previous administration, which had systematically attempted to stymie China by limiting access to high-performance chips. But while the new administration plans via executive order to give the U.S. players free rein to build faster and bigger AI, it reserves the right to selectively make it difficult for companies that do not align with its political agenda. It does so with threats of regulations, lawsuits, or tariffs on key supply chain components.

The emerging rules of play are clear: Companies that fall in line and have strong ties to the administration will be better positioned to make plans without interference from Washington, get government contracts, benefit from federal spending on AI, and negotiate more forcefully with international regulators and other industry players.

Before the bubble bursts, it will be wise for at least one major player to signal a stop to the escalation. The first step to breaking out of a trap is to recognize that you are in one. The second step is to acknowledge that the rules of competitive advantage in your industry may have changed. The third is to have the courage to recognize technology that is “good enough” and defined not by the hardest number-crunching problem that it can solve but by the breadth of problems that it can solve for the largest number of people.

Can even one major player dare to break from the pack and aim not for the splashiest announcement on spending on AI, but for a new goal for the technology? How about aiming to make a meaningful difference to worker productivity—an aspiration that proved so elusive for AI’s predecessor, the internet?

This could offer courage to the others to follow suit and find a different—better—Nash equilibrium of mutual best responses. Now, that would be a real breakthrough.