Protecting democracy in an increasingly digital world
I have always been a little wary of the Margaret Mead quote about how a small group of thoughtful, committed citizens is the only thing that has ever changed the world. I have always been much more fond of Thomas Paine’s view: “Those who expect to reap the blessings of freedom, must undergo the fatigues of supporting it.”
The defence of civil liberties is not something a small group of clever people impose on everyone else. It is the flip side of a free society. It is the responsibility of rights that we have to convince a critical mass about. It is about convincing lots of people of the benefits of a free and fair society so that they feel invested in defending it.
The history of the NSW Council for Civil Liberties (NSWCCL) demonstrates this is spades: routinely finding ways to bring people along the journey of defending civil liberties, being undaunted in taking up sometimes unpopular causes, creating a consistency that strengthens the moral authority for use in moments when it matters.
My research in recent years has been on digital technology and democracy. These concepts are in the most significant amount of tension they have been in for two centuries. In my book Future Histories, my goal was to talk about technology not as some kind of divine or ghostly phenomenon that imposes itself onto society, but rather a human creation with a human history.
My aim was to show that historical thinkers and movements from the past have relevance to understanding debates about technology today. That rather than unprecedented or novel, many of the conversations we are having about technology and its impact on society and democracy in the 21st century are questions many have grappled with before.
Modern policing
A good example is the creation of the first modern professional police force. For a long time I had assumed professionalised policing was a standard feature of human society. But when I researched my book I realised the history was less straightforward.
In fact, the first experiment with the professionalised policing we might recognise today was in the late 18th century, on the docks of the River Thames. It should come as no surprise that this was a moment of technological disruption and advancement (in the form of the industrial revolution), where the social order and economic organisation was in a state of transformation.
The Marine Police Office was a pilot program to establish a professional body that would monitor and enforce the strictures of waged labour against the dock workers who were struggling and resisting the confines of this new form of social organisation The merchants were sick of losing stock to workers who saw it as their right to top up their wages.
So, they pooled their funds to establish a project proposed by three men: John Harriott (a magistrate), Patrick Colquhoun (a statistician) and famed utilitarian Jeremy Bentham. The first modern police force was as a collaboration between industry and the state to operationalise — quite explicitly — a form of surveillance of everyday people at scale.
Colquhoun wrote about his experiment extensively. His vision of policing was deeply bound to economics. He described policing as “a new Science … in the Prevention and Detection of Crimes.”
“It is the dread of the existing power of immediate detection, and the certainty of punishment as the consequence of this detection,” wrote Colquhoun, “that restrains men of loose morals from the commission of offences.” Surveillance, plus the spectacle of force, offered an economical and effective way of maintaining order. It is not walls, locks or bars that prevent crime, Colquhoun argued; instead, “restraints are only to be effected by the strong and overawing hand of power.”
The theory, and the experiment, was a raging success, significantly reducing the merchants’ losses for a small price. Harriott, Colquhoun and Bentham went on to convince Westminster to support the project. The Marine Police Office came under state authority two years later. Not only did the merchants now have a police force, but one funded by the public purse.
Statecraft in the digital age
The history of policing helps us understand some key aspects of statecraft in the digital age.
Like their historical counterparts, modern police understand the power of surveillance in enforcing a form of discipline. Safety is about preserving social order, rather than reducing harm. By allowing law enforcement and intelligence agencies to tell us what it is to be safe, we allow them to use technology in increasingly oppressive ways. Over the last two centuries, we have seen this pattern repeated.
Rapid technological advances have been accompanied by disruptive transformations in social relations. Acceleration of policing has often been the response. In essence, the social fall out of technological change has been met with the strong and overawing hand of power closing into a fist to crush resistance.
In the 21st century, we see this play out in more intensive and invasive ways, where advances in technology are not just in tension with civil liberties, but increasingly challenging our society at a more fundamental level. Surveillance is being used to manage the fall out of technological transformation and technology itself is serving to consolidate power in state and corporate forms in ways that undermine not just civil liberties but democracy.
In the past two decades we have seen this shift, as technology continues to advance corporate and state surveillance, poison our information ecosystem and concentrate corporate power to a degree not seen since the gilded age. This has correlated with an expansion of surveillance capabilities.
The New York Times described Australia as the “world’s most secretive democracy” with good cause. In the past two decades, we have passed more than 100 bills in the wake of the war on terror covering over 875 different offences by some counts. At its height, this was a new bill every six weeks. How many days did parliament have, on average, to consider these bills? A mere five. In one instance, for the crossbench at least, it was a single afternoon.
What we have is a stripping away of parliamentary power, with its attenuating scrutiny, towards a growing executive power — one that increasingly relies on technology and the technology industry.
Surveillance capitalism
Technology companies, many of them in the business of surveillance capitalism, have been overwhelmingly compliant. Their business models have been repurposed for state surveillance ambitions.
Some of the most controversial laws in recent years, such as the metadata retention regime and the Assistance and Access Act (aimed at introducing weaknesses to encryption systems) have sought to repurpose existing systems of surveillance capitalism for state surveillance.
This is still happening today. In July, the independent national security legislation monitor raised a whole range of concerns about the overreach inherent in this body of law, as well as its chilling effect on freedom of political communication and the press. Just a month later, the government was proposing to make a range of controversial powers for ASIO permanent.
Equally the failure to regulate, or pass laws, has been highly revealing of the ways in which technology has become central to modern forms of surveillance. Privacy law reform has mostly withered on the vine for the past five years (although that has fortunately recently started to change). Hard regulation of artificial intelligence (AI) has been effectively abandoned. Facial recognition technology has remained stubbornly unregulated, despite clear mandates for reform.
Undoubtedly this is a function of Australia being the only liberal democracy without a bill of rights. Laws can be passed with minimal consideration of human rights. Public debate is atrophied by a lack of discussion about the role of rights and how they might need to be balanced and managed (and be subject to redress as required).
We have successive ambitious governments who see pro-law enforcement policies as an easy poll bump, and who are too timid or cynical to resist overtures from national security bodies for more and more powers to surveill and police in more and more ways.
Big Tech
Undoubtedly this is also a function of an industry that is hugely powerful and is shaped by its own sense of politics and grandiosity.
Meta continues to fill our social media feeds with harmful content and AI slop — they make up to 10% of their revenue from advertisements they have 90% confidence in are scams. They also allow nudification technology and products to be advertised on their platforms, in defiance of the law and on occasion targeting children. The government’s response has been to criminalise the children that use this rather than those who profit from its distribution.
Meta also sells smart glasses impervious to the risk of harm for vulnerable people. These are the Jeffrey Epstein of consumer products — a device for people who do not believe in consent, which contributes to a broader culture along similar lines.
SpaceX has built one of the dirtiest and obscene data centres in the world. Called Colossus, it rents out $1.5 billion a month’s worth of capability to the AI company everyone likes to pretend is ethical, Anthropic. They, of course, have also built an image generator commonly used to create non-consensual sexually explicit material.
Meanwhile, those at “don’t be evil” land, Google, are collaborating with militaries across the world to build military targeting and intelligence systems. These have been used in theatres of war and genocide, such as Gaza and Iran, by the US and Israeli militaries.
The worst part is these people do not think they are doing anything wrong.
Take for example Palantir, a company that specialises in data analytics and helps match up data sets to identify people for deportation by ICE. Palantir founder Peter Thiel recently claimed: “If you’re evil, you’re at least competent. And if you’re evil, you’re not bad. And therefore, maybe you’re actually kind of good because you’re at least getting something done.”
These are not just consumer tech companies, they are AI companies and there is a lot at stake in keeping them growing.
SpaceX recently listed with a valuation of $1.75 trillion. Anthropic was founded in 2021 and the current talk is that the IPO will see a valuation of $2 trillion, despite revenues of $47 billion — which would value the developer of the Claude AI chatbot at 30 times its revenue, the highest in human history.
Recent economic analysis found that current spending on AI is dwarfing previous historic capital expenditure booms, including the dawn of the railroad era and the internet. The US economy, economists suggest, would be at a standstill if we took out the growth of AI companies and data centre builds.
This is a small group of people with enormous financial power, who harbour anti-democratic politics and care little about the social and ecological consequences of their work.
Taking back power
There is a lot going wrong with the world. But there is also a lot to take heart from. One place to start with is Australian’s attitude to AI.
Everyone is telling Australians that this technology is important — from politicians to financial markets to a media industry that too often treats industry sources as gospel. Yet, in what teeters on a charming form of contrarianism, Australia polls as the least optimistic country about AI globally.
Across the board people dislike the technology and struggle to see the promise. More people (79%) report being concerned about negative outcomes than the number (73%) that report experiencing a range of benefits. Importantly, more people see the benefits of rules and accountability: nearly 90% would be more inclined to trust and use AI if international standards were in place.
There is a neoliberal assumption that people see the state as a laggard bunch of bureaucrats who could not possibly understand new tech. But Australians expect the government to step in on their behalf. They want regulation. They want elected representatives to stand up to industry. That is a common ground we can work with.
In fact, we are seeing this start to happen. In recent weeks, Coles have announced they are ending their relationship with Palantir. They used the company’s services for workforce and consumer analytics, but sustained pressure from Getup and Digital Rights Watch led to them ending the relationship.
The next stage is to target other companies collaborating with Palantir, as well as the tens of millions of dollars worth of government contracts they have, so that we can get them out of our society.
In recent days, plans for a controversial $1.2 billion data centre in Lane Cove, in Sydney’s north, have been withdrawn with the developer blaming “emerging” regulations from state and federal governments. We absolutely need 21st century infrastructure for the digital age, but what we do not need is hyperscalers treating us as a place to set up shop because they have run out of room in the US.
The government, to its credit, has tabled reforms to the Privacy Act (which have been five years in the making) and a proposed digital duty of care. This comes off the back of mammoth litigation in the US, which has seen eyewatering sums of damages paid and significant behavioural change.
The Medicare hack by Open AI agents has seen a paradigm shift in how we understand the AI threat. Rather than seeing it as a god-like existential threat or rogue agents, people are coming to understand this as a problem of corporate governance, of cowboys not taking their obligations seriously and an opportunity to hold them to account.
I do not want to be naïve, this is going to take some hard work — the kind of fatigue that comes with defending civil liberties Paine knew well. But I would also argue these are good conditions to organise around: the overawing hand of power is seeking to crush us, but we have the capacity to land a counterpunch.
There are comically obvious villains, there are clear opportunities for intervention, and the vast majority of everyday people are on our side. This is the time for organisers, agitators, lawyers, ratbags and policy nerds to work together to build an alternative future where civil liberties are protected and democracy can flourish.
Lizzie O’Shea is a writer, lawyer and founder of Digital Rights Watch. This article is based on a speech she gave to the NSWCCL annual fundraising dinner and journalism awards on October 1.
Big Tech, AI and digital liberation
Artificial intelligence (AI) covers a broad range of technologies. But there is only one that dominates the news and financial markets — the multimodal generative AI systems produced by leading tech companies, in particular ChatGPT (OpenAI), Claude (Anthropic), Gemini (Google), Grok (SpaceXAI), Copilot (Microsoft), and Llama (Meta).
Tech leaders are all in on this type of AI because of its potential to secure them great wealth and political power. It also happens to be the type that is most threatening to our well-being, although not for the reasons generally highlighted by tech leaders and the media.
The birth of the AI offensive
The AI offensive started with the November 2022 release of ChatGPT by OpenAI. The model was a big hit and, as might be expected, other companies quickly followed with their own competing models.
All the statements made by tech leaders, in one way or the other, proclaimed that these large language model generative systems would lead within a very few years to a coming of artificial general intelligence or superintelligence — AI systems so smart they would be able to continuously improve themselves leading to a singularity, after which these systems would either solve all our problems or destroy the world.
But the truth is that these systems are not “intelligent” and do not represent a meaningful step towards any type of superintelligence.
At the most basic level, these systems are giant statistical prediction machines that rely on large-scale pattern recognition. The patterns are generated from inputted training data that must first be converted into numerical tokens to make them machine readable. The tokens are then run through a neural network which enables the systems to process the data.
When prompted with a question or request for information, these systems identify related material in their database and assemble a response that, probabilistically speaking, best satisfies the inquiry. The response, made in token form, is then translated back into words, images or sounds as appropriate. In other words, no matter how conversational and intelligent these systems might appear, they do not “think” or “reason”.
This internal architecture is not only incapable of giving rise to artificial general intelligence, it also suffers from limitations that make contemporary use of multimodal systems problematic. One limitation is that these systems tend to generate output that amplifies existing social biases. That is because most of the data used for training is scraped from the web, which includes all the discriminatory and hateful material found there.
Many studies have shown how AI used in job search software will discriminate against applicants of colour. Or that image generating software will produce images that reinforce cultural biases. Imagine the danger if we integrate these systems into our healthcare, government agencies, schools, and so on.
Another limitation, no doubt of greater concern to businesses, is that multimodal systems, because of their probabilistically based decision-making, routinely hallucinate or produce what is called “erroneously constructed responses.” And again, there are lots of examples of this happening. This lack of reliability is a big turnoff to businesses who cannot afford to have their operations depend on systems that periodically produce unexpected and potentially harmful — meaning costly — outcomes.
Tech leaders have largely dismissed these limitations, claiming they will be overcome with larger data sets, better model training, more sophisticated algorithms and greater computational power. But their efforts have not been successful. In fact, as the New York Times reported: “The newest and most powerful technologies ... are generating more errors, not fewer.”
And the business experience with these models reflects these limitations. A 2025 MIT Media Lab evaluation of hundreds of AI adoptions found “that 95 percent of organizations employing AI systems are getting zero return.” A recent National Bureau of Economic Research survey of leading executives from the United States, the United Kingdom, Germany, and Australia revealed that “firms report little impact of AI over the last 3 years, with over 80 percent of firms reporting no impact on either employment or productivity.”
Growing crisis for AI developers
Despite their confident pronouncements, AI developers find themselves in a bind. The two industry leaders, Open AI and Anthropic, which together account for “the vast majority of all AI compute demand,” have yet to make a profit. The reason is simple: their models are expensive to train and run but to encourage firms to use them they have been offering their customers free or highly subsidised flat subscription services. As a consequence, as one tech analyst put it, AI providers are “annihilating cash.”
Sam Altman, OpenAI’s CEO, has acknowledged that even the company’s top $200 a month pro account was a financial loser because of the high computing costs involved in running ChatGPT. Anthropic is no different. According to one analyst, its subscribers are burning some $8 in compute for every dollar of paid subscription.
Not surprisingly, then, ChatGPT lost $5 billion in 2024 and $35 billion in 2025. Forecasts are for even greater losses in 2026. Anthropic is heading down the same road.
So, faced with ever growing losses, OpenAI and Anthropic have started to charge their large customers based on their actual token-use. But here is the problem: it is impossible for anyone to know or even predict, ex ante, the token use associated with any AI directive.
That is because AI systems often explore multiple paths of inquiry before generating a response, and each path can involve significant token use. The result is that companies are finding their AI spending soaring and their response has been fast in coming: they have ordered a dramatic cut in AI use. Thus, this shift has done little to solve the AI profit problem.
In short, we are far from a world of superintelligence and AI dominance.
The AI agents
Early this year, AI developers began thinking that they had found the answer to their profit problems: so-called AI agents. These agents, it was said, would revolutionise business operations by allowing companies to boost output while dramatically slashing employment. And because these agents depend on large language models for their operation, their use would ensure a profitable future for the leading AI developers.
Suddenly talk of a future of abundance for all became replaced by talk of a “jobs apocalypse.” However, businesses soon discovered that the usefulness of AI agents was also greatly oversold.
In brief, AI agents are best understood as complex software systems that can interface with and manipulate other software systems and external databases. They can be given a complex directive, break it down into smaller ordered tasks, gather the required information, and then, relying on the work of a large language model, progressively make the decisions needed to satisfy the directive, all without successive human prompts or oversight.
Anthropic and OpenAI were first to develop agents, but other companies quickly followed, many of whom are not in the AI business themselves. Now there are many agentic products on the market, agents tailored for the legal profession, the finance industry, the ecommerce business and so on.
As an example of the many shortcomings of these agents, the Financial Times reported that Amazon suffered several agent-caused “outages” in early 2026. In one case, it “took down Amazon’s shopping website and app, leaving customers unable to make orders.” A major study by researchers from Microsoft, Nvidia, and the University of California at Riverside found that most agents were unable to complete their assigned tasks. According to the study, “The average completion rate was around 30 percent.”
One big reason for this poor performance is that since AI agents must operate in concert with multimodal systems, their work is often compromised by the same limitations that affect those systems, including hallucinations.
Even more concerning, there are an increasing number of incidents where agents pursue actions that disregard company protocols or, as it is commonly said, go “rogue.” This includes wiping out data and exposing corporate secrets, having decided that doing so was the most effective way to achieve the task they were assigned. That is because, as the previously mentioned study found, these agents have an “inherent tendency to pursue user-specified goals regardless of feasibility, safety, reliability, or context.”
And then, there are financial issues which are perhaps the biggest threat to the widespread adoption of AI agents. AI developers are now charging their corporate clients based on token use — and AI agents are token hogs because of all the many complex loops and decisions they need to make. Thus, Uber, which uses Anthropic’s Claude Code, burned through its entire 2026 AI coding tools budget in just four months.
In brief, we are not on the verge of an agent driven jobs apocalypse.
But there are dangers
All this does not mean we have nothing to fear from letting the AI experience proceed unchecked.
First, the massive spending on AI infrastructure — data centres and their associated equipment and software — is both diverting funds from other areas of need and driving an AI-hype fuelled market bubble. Yearly AI-related capital spending in the US by the four biggest tech companies (Alphabet, Amazon, Meta, and Microsoft) went from $150 billion in 2022 to $360 billion in 2025 and to an estimated $650 billion this year.
This boost in spending is so big that even these leading hyperscalers find it necessary to borrow money to fund it. But the problem here is that these investments will only become profitable if OpenAI and Anthropic, which account for about 80% of total AI revenue, have the money to pay for the resulting compute power. But since both OpenAI and Anthropic are losing money and going deeper into debt themselves, there is a real likelihood that they will not be able to make payment and, if that happens, the hyperscalers will be stuck and the entire AI bubble will collapse, leaving recession in its wake.
But there is a more immediate reason we need to resist the AI offensive. AI companies are aggressively pushing their systems into a variety of businesses and government agencies with disastrous consequences for working people. In all cases their aim is to cheapen the cost of production by diminishing human agency with little regard for the well-being of those that use the goods and services being produced.
Here are two examples. The first concerns healthcare, more specifically mental health. Two health companies have developed what they call the PatientGPT chatbot. It is designed to answer calls from people seeking mental health support. The chatbot will ask questions and then decide what you need: an appointment sometime in the future with a therapist or urgent emergency care.
This chatbot has been trained on previously recorded conversations between clinicians and patients. It does not take long to imagine some of the many problems that can be expected. Unfortunately, studies have shown that AI often makes mistakes when recording those conversations, thus its own decision making can be corrupted.
We also know that these systems recreate existing social biases, which could well influence the system’s evaluation of patient mental health concerns. And hallucinations could well lead to a misrepresentation or misdiagnosis of patient issues, potentially leading to life-threatening mistakes.
For workers, it means cuts in the number of therapists and greater challenges for those that remain who must help patients in crisis who may have been misdiagnosed or delayed needed treatment. Some companies are now actively working to go further and build agents to engage in actual therapy.
Then there are government agencies. In the US, several states are now using AI agents to manage their social safety net programs. As AI agents replace government workers, many of those seeking needed services confront many of the same problems as in health care.
In other words, we can expect mistakes recording information and hallucinations when giving responses. People will not only be unfairly denied benefits but once mistakes become part of a person’s record, corrections will be difficult and time consuming to make.
There are countless other examples of growing AI use in newsrooms, schools and, of course, the military. Resistance to the AI offensive is clearly needed. And it will have to be a resistance with muscle developed through strong organising and alliance building.
Resistance
Unions in the US, especially in healthcare, are taking the AI push seriously and pursuing numerous avenues to resist or limit its use.
Kaiser Permanente is a major health care provider that operates in several states. In March 2026, some 2400 unionised Kaiser mental healthcare workers in northern California conducted a one-day strike in protest over “Kaiser’s efforts to replace human-provided mental health care with artificial intelligence.” Significantly, the strikers were joined by 23,000 registered nurses who shared their concerns about Kaiser’s increasing use of AI.
In Oregon, The Oregon Health & Science University (OHSU), the state’s only public academic health centre, has been rapidly increasing its use of AI and without notifying or consulting with its unionised workers. One of the unions, the largest, has begun surveying its members to determine all the ways in which AI is being integrated into the university’s operations and to track its error rate.
The union is preparing to file an unfair labour practices complaint with the state. The union wants OHSU to agree to having worker involvement in AI implementations, including multiple seats on the AI governance committee and involvement in the feedback process and error tracking. It also wants OHSU to provide notice to the union before any AI system is put into use, and to put limits on surveillance tools.
And there are similar fightbacks taking place in newsrooms, schools, and government agencies.
Now while important, struggles such as these remain largely defensive and siloed by sector and often by employer. As such they are unlikely to have the power to reverse corporate efforts to deepen our dependence on these systems.
At the same time, there is no reason that they must remain limited in either their demands or vision. With creative and sustained organising, they can become a powerful driver of the inclusive, class-based movement we need to defend our interests.
Here are three suggested steps for moving the process forward.
We need to create opportunities for unionised workers from different workplaces and industries to share experiences about how their employers seek to use AI systems and the efforts of their unions to win contract language protecting their rights. This kind of sharing can stimulate productive thinking about organising and bargaining strategies.
More importantly, it can help workers see that the corporate embrace of AI agents has little to do with improving efficiency or product quality. Rather, it represents a new weapon in a generalised class offensive against working people, one whose primary aim is to undermine worker power and well-being.
Another step is to encourage union adoption, when appropriate, of a “Bargaining for the Common Good” negotiation strategy. Unions need to find ways to share their concerns over the use of AI agents with community members and win their support for a jointly fashioned set of demands that place restrictions on the use of those systems.
Success will not only strengthen unions in bargaining, it also has the potential to encourage new visions of social organisation, as well as reinforce a class-based understanding of the forces threatening community well-being.
Finally, as the movement in opposition to this technology grows, those unions and community coalitions already in motion need to establish ties with the anti-data centre movement. To this point these two movements have largely developed with little overlap, even though there is a natural alliance waiting to be formed. Such an alliance could serve as a strong foundation for building the kind of movement we need to assert popular control over the ongoing development and use of technology.
It is worth emphasising that we should not think of this as an anti-technology or anti-AI movement. AI as a broad technology is not our problem any more or less than are computers, the internet or email. Rather, the problem is with the class interests shaping its development.
More specifically, it is with the determination of tech leaders to develop a specific AI technology that undermines human agency, deepens our dependence on them and threatens our economic well-being.
The fact that we are witnessing an explosion of opposition to this form of AI by workers, consumers, parents, students and community groups should give us reason for optimism. We need to unify and strengthen this opposition as well as expand its vision. It’s time for us to assert our own class interests.
Martin Hart-Landsberg is Professor Emeritus of Economics at Lewis and Clark College, Portland, Oregon. He is the author of seven books on issues related to globalisation and the political economy of East Asia. He is the chair of Portland Rising, a committee of Portland Jobs with Justice, and chair of the Oregon chapter of the National Writers Union.
Pax Silica: A plan for peace or preparations for war?
First published at Workers Make Possible.
On the 12th of December 2025, at the close of the inaugural Pax Silica Summit, seven countries signed the Pax Silica declaration in Washington, D.C.: the United States, United Kingdom, South Korea, Japan, Australia, Israel, and Singapore. Following a second summit in June 2026, the number of signatories grew to 24.
According to the text of the declaration, these signatories have committed to advancing “mutual prosperity, technological progress, and economic security”, through “shared efforts on investment security practices, infrastructure, and incentives.”
This initiative signals an apparent push for both greater cooperation between the US, its partners and client states, and for their deeper integration into the US technology stack.
As our newspaper of record, the Straits Times reported on the declaration in similarly diplomatic language, calling it an “agreement to collaborate on artificial intelligence (AI), tech supply chains and infrastructure”. Later in 2026, in an interview with the Straits Times, US Under Secretary of State for Economic Affairs Jacob Helberg claimed that Pax Silica does not aim to “ringfence a US-led AI supply chain of trusted partners against China”.
Other media outlets have framed the initiative in more antagonistic terms. For instance, a report from the Washington Post cautions the reader that “Breaking China’s grip on critical minerals opens up a world of opportunities — and risks” and states that the initiative is “aimed at countering China’s dominance in both the mining and refining of several critical minerals, which presents a threat to both U.S. national security and economic security”.
Similarly, the Center for European Policy Analysis poses the question, “Pax Silica — Can it Stop China?”, and reports that the initiative is “framed as a response to ‘countries of concern,’ implicitly, but not naming the target as China”.
Pax Americana, past and present
Is Pax Silica an innocuous agreement for economic cooperation, or an instrument of domination? To understand what it is meant to accomplish, we must consider the context from which it emerges.
Since 2018, the US has been putting pressure on the Dutch government to prevent semiconductor lithography tool manufacturer ASML from exporting its most advanced machines to China. The Biden administration’s 2022 CHIPS Act sought to reverse decades of US semiconductor firms offshoring, while also placing restrictions on funding recipients “expanding semiconductor manufacturing in China”. The US Department of Commerce then banned the export of several advanced Nvidia chips to China in 2023. Pax Silica fits into these recent developments, as the USA’s latest effort to kneecap potential technological rivals.
Such efforts are not new, as the US-Japan chip war in the 1980s demonstrates. In the face of an ascendant Japanese semiconductor manufacturing sector, their US counterparts, in concert with the Reagan administration, successfully pressured the Japanese government to sign the 1986 US-Japan Semiconductor Agreement. The agreement’s US-set price controls, forcing open the domestic Japanese market, and threat of sanctions would ultimately play a key role in the shrinking of Japanese market share from 75% to 20% between 1987 and 2001.
Returning to the present day, we must also consider the belligerence of the second Trump administration. It began a trade war with China, ramped up its illegal, unilateral economic siege of Cuba, and illegally invaded Venezuela to abduct its sitting President. It continues to escalate tensions with China over the issue of Taiwan, and persists in arming and supporting Israel, despite that government’s referral to the International Court of Justice for plausibly committing genocide against the Palestinian people. It is now waging an illegal war of aggression on Iran, during which it has openly targeted civilians, boasted of offering “no quarter”, and threatened the death of an entire civilisation — all of which are war crimes, or crimes against humanity.
However, it must also be recognised that Trump is not an exception. His administration’s policies are not a significant departure from the imperial adventurism of previous US administrations. The difference is that the Trump administration does not care as much about concealing its intentions with highfalutin rhetoric about freedom and human rights: it is comfortable with nakedly fascistic proclamations.
By considering both the deeper historical context, as well as current events, it becomes increasingly difficult to accept the claim that Pax Silica is no more than a framework for economic cooperation. Instead, it would seem that the US is focused on its technological hegemony by securing access to territories, resources, technology and infrastructure across the 5-layer AI stack. It is also increasingly clear that the US political and corporate leadership interprets China’s increasing technological development primarily as an existential threat to its supremacy. Partners in Pax Silica may stand to benefit from their increased integration into and collaboration with the US AI industry, but only insofar as such benefits serve the maintenance of US hegemony.
This is, in a way, announced in the name of the initiative itself. The US State Department describes “Pax” as a “historical term denoting peace, stability, and prosperity”. They would like us to imagine a ‘silicon peace,’ unburdened by history, by omitting a key detail: “Pax” refers to stability under the influence of a dominant military power.
In the words of the late historian and political scientist Michael Parenti, “Empires are often represented as creations of peace. They’re even given names of peace, right? Pax Romana, the Roman peace. The Roman peace was a brutal, bloody world conquest... Pax Britannica and there’s even Pax Americana... Empires are often represented as bringing stability, justice, and prosperity to their subject peoples.”
What is Pax Silica, but an attempt to entrench Pax Americana through domination of the technological supply chain? If so, what are the dangers of wedding ourselves to this imperial project, and integrating ourselves into its technological architecture?
Straining sovereignty
Dr Govand Azeez of Macquarie University cautions, “Southeast Asia is rapidly embracing artificial intelligence, with governments, businesses and investors touting its potential to transform economies and deliver up to US$1 trillion in growth by 2030. But beneath this optimism lies a more uncomfortable reality: the region risks becoming structurally dependent on technologies it does not own or control.”
This point about technological sovereignty has larger implications for both economic and political sovereignty.
Countries and economies that are deeply integrated into a foreign technology stack become particularly reliant on foreign corporations, and vulnerable to political interference by foreign governments.
Singapore is already an established and important node in the global semiconductor supply chain, a position achieved through a combination of state industrial policy, favourable tax incentives, a relatively educated local workforce, the availability of low-cost labour power in nearby countries, and its geostrategic location. In fact, a recent Channel News Asia article reported that approximately 10% of the global supply of semiconductor chips and 20% of semiconductor equipment are produced in Singapore.
Significant foreign investment — particularly by US multi-national corporations — have contributed to the creation of substantial fixed capital in terms of factories and equipment, including Micron wafer fabrication plants (fabs), and Applied Materials’ research centre and manufacturing facilities. Fabless semiconductor companies like AMD, Qualcomm and Broadcom have also established local facilities, along with other European and East Asian companies like UMC, ST Microelectronics, NXP, VIS, Siltronic, Infineon and Toppan. Many of the largest US technology multi-nationals including Meta, Alphabet, Amazon, Google, Microsoft and OpenAI have substantial local research and development (R&D), logistics and procurement operations serving as a key node in the Asia-Pacific region.
Given that the local semiconductor and technology industries are dominated by foreign firms, this makes both the supply of materials and technology required and the demand for the products and services generated by these industries largely subordinate to decisions made overseas. That these industries also constitute a major proportion of the Singapore economy further increases the weight of foreign political pressure that can be exerted by, for instance, unilateral US action in the form of sanctions, export restrictions and/or tariffs, or even threats thereof.
The New Lines Institute, another DC-based think tank, also highlights that a “core objective of the plan is to ‘export the entire U.S. tech stack’ to secure allies and establish global dependency on U.S. technology ahead of competitors like China.”
“Global dependency” is about as ominous a phrase as they come.
Additional risks to national sovereignty have also been illuminated by recent events. The former Chief Prosecutor of the International Criminal Court (ICC) lost access to his Microsoft account in May 2025 after US President Donald Trump imposed sanctions on him, evidently in response to the ICC issuing arrest warrants for the Israeli Prime Minister and former Minister of Defence for alleged “ war crimes and crimes against humanity”. This incident has been cited as a key factor in European countries such as France, Germany and Denmark shifting away from dependency on US technology provided by companies such as Microsoft and Palantir in favour of open-source or indigenously-developed alternatives, as part of a move towards protecting digital sovereignty. The US has also suddenly and unexpectedly imposed 12.5% tariffs on 45 countries including Singapore on Jul 24, 2026, for a reported failure to ‘adopt and effectively enforce prohibitions on trade in goods produced with forced labour’, allegations rejected by the Singapore state.
As if to underscore these risks, based on a leaked draft of a letter from the US State Department, it was also reported earlier in August 2026 that the United States intends to compel nations around the world to choose sides. While the leaked letter is an unsent draft whose full contents have not been disclosed, it would appear that the United States has a simple message to the nations of the world: You can submit to our ‘silicon peace’, or participate in the World Artificial Intelligence Cooperation Organisation, but not both.
A balanced pragmatism has long been a central feature of Singapore’s foreign policy. As recently as this June, speaking at a dialogue session as part of the Singapore Press Club’s Eminent Speaker Series, prime minister Lawrence Wong reiterated this position, stating, “We want to have an active multi-engagement approach towards bringing all the key parties and having all of them have stakes in Southeast Asia.”
The engagement that Pax Silica represents is already facing widespread and vocal opposition in the Philippines, our fellow ASEAN nation, whose sovereignty is even more gravely challenged through Pax Silica.
We have to ask ourselves: is Pax Silica compatible with our independent foreign policy, and the peaceful, stable development of Southeast Asia? And if the US more openly demands subordination to its belligerence, should the people of Singapore not question our participation in this scheme?
Nicholas is a mechanical engineer.
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