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Why do we fall for hype, again and again?

 explanations. We are suckers for the charisma of the huckster. We fear, contextually and primordially, being left behind or left out. We each yearn to believe our future will be better. A lot can also be attributed to cynical opportunism. We hope that by riding the wave of hype we can surf to success. Maybe if we mimic the hyperbolic slop we hear gushing from our silicon overlords, it might make us sound adroit and better equip us to land deals, jobs and opportunities. We invest early, literally and metaphorically, hoping to sell our own speculation to a greater fool.

But in this short essay I want to propose another more theoretical sociological explanation. While hype may consist of lies, exaggeration and bombast, it also appeals to some aspect of each of us that yearns and deserves to 

 of figures Elon Musk or Jeff Bezos profit by building elaborate fantasy worlds, seducing us to believe that they are visionary saviors of humanity working to take us to the stars or to ever greater horizons of human achievement. I am speaking of something deeper and more profound, and frankly quite tragic.

What animates hype, what gives it its attractive spark, is the way it touches (and manipulates) our estranged power as part of a cooperative, storytelling species.

To explain, let me speak for a moment about what makes scams work.

There are, of course, “brute force” scams, the kind that are the equivalent of a mugging, exploiting our shock. Someone calls you claiming to be the tax authority and demands money. Or they tell you your child is in hospital and needs a immediate cash for a transfusion.

: someone entraps you in a fantasy. This kind of scam includes “

,” where a scammer uses a dating website to ensnare someone looking for love and companionship, only to rob them.

What makes catfishers so effective is neither the beautiful images or words of love they send their prey nor the plausibility of the sob story that prevents them meeting in person (a visa problem, a medical emergency, a debt. “Can I send you money?” the target volunteers). What really makes these scams work is the way the story they tell embraces and validates the scammed person.

On such reality TV programs, victims of scams often shamefully confess that the clues were there all along and that the scam was, in hindsight, blindingly obvious. But the victim was enraptured and, like anyone in the grips of infatuation, they ignored the inconvenient evidence. What so captivated them was not the persona of the scammer so much as the character they invited the scammed to play. The scammer and their target, like any two lovers, build a world together with words. The sophisticated scammer is adept at shaping that world so it validates and affirms the scammed 

: kind, romantic, generous, gallant, selfless, trusting and desirable. The scammed individual does not fall in love with the scammer’s fabricated persona, but their own. They help build the fantasy world that now entraps them.

Hence the curious but not uncommon phenomenon of a scammed person seeking out their scammer even 

 the robbery and betrayal has been revealed. They want to regain access to the person even though they know they were caught in a predatory relationship. They want to return to the storyworld which they and the scammer created together, albeit with very different motivations and consequences.

We are a worldbuilding species, and not only in the material sense that we make tools that transform the world that transforms us. We also change the world with words. The Caribbean radical thinker Sylvia Wynter speaks of us as 

, a storytelling animal, and meditates on the profound power we wield through the stories we tell. Her primary concern is how stories about race fundamentally reshape a material world built on anti-Blackness. The transatlantic slave trade and the world it made was justified and normalized by a series of interconnected stories about race, value and fitness. Edward Said’s famous study of 

 explores how a set of inaccurate stories about an imagined category called, by Westerners, “The Orient” came to be a key aspect of how imperialism was executed in those regions. In both cases, what is key is that such stories emerge asymmetrically and abusively from dominant power relations, and in turn helped to reshape and reproduce those power relations.

As a cooperative species, we create the world anew, in part, through the stories we tell, though we often take them for natural, normal and inevitable. True: in some societies some elites declare the monopoly on authoritative stories, for example the priestly caste in a theocracy. But every story, like every scam, is actually a collaboration. We make stories, stories make us, and we make the world, but not necessarily in circumstances of our choosing.

This has something to do with Marx’s famous theory of commodity 

, which is not, as it is commonly presented, merely an account of how individuals come to fall in love with things. It is, more profoundly, a 

” as collaborative worldmakers. When we behold a commodity like a smartphone, we fail to see it for what it is: the product of millions of hands, working together, but not always under the circumstances of their choosing or in any way democratically. All are subject to the “mute compulsion” of money. Our hands, too, are part of that protean totality of cooperative potential from which the smartphone is a small crystallization. What we hold in our hands is a fragment of our own sublime and alienated 

 to imaginatively (re)make the world. The story that it is the gift of Steve Job’s creative genius is a co-option of the imagination that, combined with many other such stories, traps us in among the most monstrous scams in the history of our species: capitalist wage relations as such.

If we bring Marx and Wynter’s approaches together, we might recognize that the world we are always in the process of remaking is 

. How we imagine the world, through stories and words, enables certain forms of collaborative activity (labour); that labor creates a material world that shapes the imagination. This process, on both material and imaginative sides of the coin, is not equal or egalitarian, but dominated by the powerful, whose power stems from their ability to shape the imagination and command our labor. It will not be enough to “seize the means of production” without also changing the way we imagine; but the way we imagine emerges from our material realities, and it is only in moments of material rebellion, resistance and refusal that the truly 

Hype, like a catfishing scam, is a form of asymmetrical predatory storytelling. It requires both the hyper and the public to buy in, but they are far from equally powerful and suffer vastly different consequences. One of the reasons hype is so successful is it offers the chance for a great many opportunistic individuals to become a hyper, each hoping to benefit from a greater fool, increasing the magnetism of the story.

But all hype carries encrypted within it a tantalizing fragment of our estranged collective world-making power. Under the din of fanfare, hype whispers to us: 

the world can be different, the future can be otherwise, belief can change reality

. And it’s true, but for all the wrong reasons. Beyond its particular rhetoric or claims, beyond the product or dream it is selling, what energizes hype—like a tiny piece of uranium in a huge nuclear reactor—is the way it refracts, in a perverted form, our collective capacity to change the world with words and stories, the potential of the imagination as a collaborative but alienated power. Another world is possible, we’re creating it all the time.

The problem is that, like the world promised by the catfisher which may indeed be based on the promise of genuine human connection, the story spun by hype is usually predatory. It does not actually make new worlds possible, it closes down possible futures by channeling our profound power of collective world-making into stupid projects that will be controlled by and enrich the ruling class who will exploit, abandon and abuse us. Believing the hype, we will invest our money, time, political will or simply our complacency in building a world that works against our collective interests, perhaps in the hopes that we ourselves may benefit or be spared the worst impacts. But for all it may claim to boldly open the door to the future, hype, like a catfishing scam that targets the lonely, preys on the tragic narcissism that is born of our estrangement from our species-being.

What does this mean for policymakers and others concerned with the role of hype in driving forward reckless speculative tech capitalism? I will confine myself to the following caution.

It can be tempting to imagine that, in the face of hype’s ability to hijack our optimism and beguile our judgment, we must encourage more sober, evidence-based, prudent realism. But this is the wrong impulse. Hype preys on us because we know something is profoundly, existentially wrong with this world and we all want change and know it to be urgent.

The problem is not our occasional irrational exuberance but a system that allows economic predators to prey on it. We are ecstatic, imaginative animals. We yearn to fall into our own narrative traps. We will always fall in love foolishly, even in utopia.

Rather than calling for everyone to calm down and be reasonable, we are better served by asking: to what other, better, more humane and generative purposes might our yearnings for change be put? How might we direct these towards the promise of a fundamental and radical transformation of the material economy? What other stories can we tell about what we, collectively, are capable of such that our radical capacities call themselves into being?

To believe the hype is, in a way, to believe in ourselves. How could we come to believe in our collective power to change the world in a way that proliferates our potential?

AI represents the first time we humans can do cognitive work outside of our bodies at scale. The only comparable moment is the early years of the industrial revolution, when new technologies like the steam engine provided a quantum leap in our ability to do mechanical work outside of our bodies at scale. If AI’s cognitive capabilities become integrated into our lives, businesses, and governments—a process that will take years if not decades—society will be as unrecognizable as the modern world would be to a pre-industrial farmer. And yet, Americans—by a wide margin—

 that AI is moving too fast and will have a negative effect on society.

This confluence of technological revolution and public distrust deserves urgent discussion, and a proper framing. The question is not whether it is possible to develop AI in a non-exploitative way, or even whether we can trust AI companies to act in the public interest. The question is whether we will recognize that our existing social and economic systems are failing to achieve these outcomes, and whether we can act in time to make structural change.

 in political and economic systems developed generations ago that were never designed to manage widespread computation, let alone automated cognition. The gaps in those systems—and their proclivity to be 

—are the primary influence on how the technology is being developed, deployed, and used.

In any discussion about AI's potential, it's important to separate the technology from the socio-political system it’s embedded in. That AIs can lack context, mix up facts, or fall for stupid tricks are all technological problems. Because the giant developers like OpenAI and Anthropic have prioritized solving them, AIs can now more easily access resources like the web or email, are more disciplined about using those resources, and are better at staying within their guardrails.

Yet AI developers do not seem to be prioritizing other technological problems. Major AI models still act far more 

 than humans, telling people what they want to hear even when untrue or not in their best interests. Popular AI models tend to answer questions 

 even when they lack training, knowledge, or evidence to back their claims. In both cases, AI developers choose to train models that please users with flattery and the appearance of competence, rather than constraining them to act in users’ and society’s best interests.

In contrast, ensuring that AI models benefit people broadly, that their energy costs are fairly allocated, that their environmental impacts are minimized, and that they don’t steal content and revenue from publishers are all questions of incentives in a capitalist system.

It's easy to conflate technology problems with capitalism problems. Back in 2021, science-fiction writer and AI commentator Ted Chiang 

 that "most fears about AI are best understood as fears about capitalism." It's not the tech 

; it's who controls it and how it could be used against us.

Imagine an AI assistant for a doctor. We can imagine it affecting the profession in one of two ways. The AI could give a doctor more time to do the human parts of their job: to spend more time with their patients, to listen more closely to their needs, to explain things more fully. Or the managers of the medical practice could give that doctor five times the patients—and fire the other four. Which way it would go is not a question of technology. It’s a question of market incentives.

The two are related, of course. Capitalism steers technology, and technology steers markets. But holding the two separate helps us understand that we, as a society, face independent choices on both the technological and socio-political axes that need not be coupled.

For example, consider the costs of AI. The leading US labs 

 to investors that their frontier models are very expensive and energy-intensive. There are significant technological challenges about improving their energy efficiency, but the socio-political questions are more pertinent. It's a corporate decision made under capitalist market incentives to constantly pursue new models that incrementally push the frontier—at enormous capital cost—and to use them, seemingly, everywhere. Nothing about the technology of AI dictates that models must be retrained constantly, at the largest possible scale. Or that they have to run on every web search, every interaction with your phone, and every time you walk by a security camera.

In a different political and economic system, Chinese developers are producing—and then 

 models. While the US government seeks to 

 China’s access to the most advanced chips, China is 

 that incentivizing their tech giants to create leaner, more open models using more commodity hardware—models that can be trained with older chips and run even on 

—will be an advantage in achieving widespread use and, perhaps, Chinese national influence.

There are other pathways for AI development that are not in service of private capital gains nor authoritarian regimes, but rather a 

. The best example comes from Switzerland, where public institutions—research funding agencies, universities, supercomputing centers—have collaborated to produce an AI model called 

. It is trained entirely on data validated to be licensed for use with AI (not stolen), on pre-existing public computing infrastructure, and using renewable hydropower. Its developers are incentivized to produce a public good, not turn a private profit.

It’s dangerous to confuse technology problems with socio-political ones. Popular proposals like 

 on data center development, or subjecting frontier models to federal government 

 all framed as addressing problems with AI’s technological development, but fail to take into account the larger social problems that govern it. China’s 

 development of open-weight frontier models illustrates the futility of keeping AI tech as national secrets, or of any pledge to scale back deployment.

AI is already legitimately useful for a wide range of tasks. It can be a tool for public good, if we choose to solve its socio-political problems. Our goal should not be to slow its pace of improvement or scale of deployment, but rather to steer it away from 

 and towards the public benefit. We can build 

Integrating a technology as disruptive as AI responsibly requires structural reforms, and we should decouple the social and technological aspects of AI to design those reforms. Companies—including tech giants—should be forced to pay the energy and environmental costs of its development. Profits should be taxed adequately and redistributed. Antitrust laws should be strongly enforced. Corporations should have a fiduciary responsibility to stakeholders beyond their majority shareholders. These badly needed reforms are 

 to the problems with capitalism that AI is exacerbating, even if they are not specific to the technology.

The law enforcement crackdown on scam compounds across Southeast Asia continues, but there are few signs that illicit activities are slowing down. Scam compounds are typically run by organized criminal gangs engaged in fraudulent operations at industrial scale. Trafficked compound workers 

 to work “up to 19 hours” per day defrauding victims around the world through romance and cryptocurrency investment scams. They are imprisoned in overcrowded living conditions with inadequate food and medical care.

Mechelle Moore, CEO of the countertrafficking organization 

, can see new scam compounds being constructed over the Thai border in Myanmar, even as newer compounds move further inland. Moore runs one of the few frontline non-profits aiding human trafficking survivors in the Northwest region of Thailand. Many of Moore’s clients are survivors of scam compounds. Global Alms supports the Thai government and 

 an emergency response team, a 24/7 hotline for reporting cases of human trafficking and gender-based violence, an emergency shelter, and aftercare services. Nevertheless, Moore and 

other organizations combating scam compounds

 frozen last year, making it more difficult to fund their counter-trafficking operations.

“At first we were unsure of the magnitude of the problem,” Moore recalled during an interview. In 2022, Global Alms experienced a significant increase in male trafficking victims coming out of scam compounds. The organization’s services were once predominately geared toward women, but it has expanded its services to support men, women, and children. Victims have been recorded coming from “78 nations across the globe.” “The only region we really haven't had victims coming out of Myanmar is the Pacific Islands,” Moore relayed.

A 2026 Office of the United Nations High Commissioner for Human Rights (OHCHR) 

 stated that despite growing attention to scam compounds, they are “still in place,” and arguably more “intertwined within the political economies” of Southeast Asia. There 

 estimates that “hundreds of thousands of people are believed to be trapped in forced labor” in the region. A recent OHCHR 

 attested to “300,000 people originating from 66 countries” in the scam workforce.

Last October, the Myanmar junta reportedly shut down a major Myanmar scam compound called KK Park. However, The 

 that experts concluded “the crackdown was performative.” Sandy Lin, a KK Park worker, told the 

that the “company” running the compound had already rented a new building in nearby Myawaddy and it planned to relocate workers who didn’t want to flee. Meanwhile, Association of Southeast Asian Nations (ASEAN) member states have announced 

 “regional action” through anti-online scam working groups, and a 2025 

 promised coordination with banking authorities, “timely sharing of information” on cyber incident responses, and digital literacy initiatives to combat scams.

The US Department of Treasury’s Office of Foreign Assets (OFAC) 

 on transnational criminal organizations, such as the Prince Holding Group, that invest in scam compounds and “front companies,” coordinating with the UK Foreign, Commonwealth and Development Office and Japan’s National Police Agency. In June 2026, OFAC 

 to target Hu Xiaowei, Prince Group’s “second-in-command.” The European Council also placed restrictive measures against the Prince Group, the Democratic Karen Benevolent Army (DKBA) in Myanmar, and Jin Bei Group in Cambodia, along with other individuals who 

 scam centers in Southeast Asia. In early 2026, the US Scam Center Strike Force 

 FBI agents to work with Thai authorities to review “thousands of mobile devices” seized from the shuttered Shunda scam compound in Myanmar. The Strike Force also 

 a “first-of-its-kind” seizure of a Telegram channel used to post fake recruiter jobs to traffic workers into Cambodian compounds.

Despite crackdowns and sanctions, transnational crime syndicates appear to either relocate or build new scam compounds elsewhere in the region. Typically, compounds 

 in remote border regions and Special Economic Zones (SEZs), which make them difficult to permanently shut down, even as regional and global interventions are carried out. Australia’s

 “exponentially” and newer ones are being moved away from “population centers” and being built to 

 regular apartments, which are harder to detect. Jason Tower, the senior expert with Global Initiative Against Transnational Organized Crime (GI-TOC), 

 ABC News “Scamming 2.0” is moving further from the Thai border.

 about “corruption” being “deeply entrenched in the context of these lucrative operations.” Criminal syndicates are allegedly benefiting from collusion with politicians and government officials that further enables regional scam operations. Scam compound victims 

 OHCHR they have seen compound operators paying money to officials, and that operators have also been notified about law enforcement raids “in advance.” Other observers speaking to the Thai news site 

 any scam “kingpins” detained in ongoing operations and believe that Myanmar’s raids on scam hubs are “aimed at misleading the international community” to think they are fighting the scam industry. GI-TOC has 

 less attention should be paid to the individual scams being carried out by a scam center, and more research is needed on the “ecosystem” that enables compounds to operate.

Another force multiplier is the recent adoption of AI tools within scam compounds. In interviews conducted with the Associated Press and C4ADS, it was revealed 

 scammers were able to incorporate the use of chatbots, smart translation services, and “AI powered monitoring tools” to “control a workforce of trafficking victims” by tracking their behaviors. Safeer Mohammed Koorimannil, a trafficking victim and former scam compound worker, relayed to the AP that he used AI models to increase the “speed and scale” to target victims. Rather than attack several victims at a time, Koorimannil “

Moore, who has served as CEO of Global Alms for over a decade, says it is a myth that only low-income people are trafficked. She described working with trafficking victims who have “university degrees, masters [...] and a few that have had doctorates.” One of Global Alms’ youngest trafficking victims was around fourteen years old, and one of the oldest was 54 years old. On the receiving end of a scam, Moore also pointed out that “everybody has the ability to be scammed, it’s just a matter of the perfect script.”

With no immediate signs that the scam industry will slow down in Southeast Asia or beyond, OHCHR 

 for a “human rights-based response to trafficking” that includes much more robust prevention measures than what currently exists. The OHCHR also sees a greater need for regional cooperation between digital platforms, financial institutions, law enforcement agencies, and civil society actors. Without a more coordinated effort, trafficked workers who carry out fraud and the victims being defrauded will continue to suffer in a destructive cycle of abuse.

For the European Union, “AI sovereignty” has meant restricting foreign cloud providers from sensitive workloads under its recently proposed 

, reducing dependence in critical sectors at the price of higher costs and near-term capability gaps. For Malaysia, “AI sovereignty” has meant preserving an exit option by hosting both 

 data centers, a strategy that potentially undermines territorial authority by exposing infrastructure on Malaysian soil to the extraterritorial reach of US and Chinese law. Clearly, “AI sovereignty” is a fuzzy concept that can be used to justify disparate—and even opposite—policy responses, which suggests that the term itself is underspecified. The threats are real, and governments are 

 on and invoking “sovereignty” without agreeing on what it means, even if full stack AI sovereignty ultimately 

 for most. What each government gets for its money depends on a distinction most have not made.

, the political scientist Stephen Krasner showed that sovereignty comprises several distinct phenomena rather than a single one. States routinely possess one while lacking another, and this was true long before the invention of AI: nineteenth-century Ottoman rulers held full legal title to their territory while foreign creditors ran their customs revenue; small states today hold seats at the UN while their monetary policy is set abroad. Krasner's decomposition became the standard way political scientists understand the concept precisely because it explains situations a monolithic notion of sovereignty cannot. By roughly applying Krasner’s conceptual framework, we can distinguish three distinct “AI sovereignties”: First, 

internal AI usage, infrastructure and policy are independent from external actors. Second

capacity to actually implement its AI policy and legislation. Third, 

whether a state controls what crosses its borders, which now includes data, compute, and capital. Across the EU, Malaysia and India, I highlight three policies aimed at different conceptions of sovereignty.

The EU’s Cloud and AI Development Act (CADA) sets four sovereignty tiers, each demanding different standards of European ownership and localization depending on the strategic sensitivity of the infrastructure. The CADA aims to effectively restrict non-EU providers from operating cloud infrastructure for sensitive workloads. However, for non-sensitive workloads the restrictions primarily constitute data localization to be considered “sovereign”. This carveout reveals the economic and diplomatic tradeoffs Brussels weighed when designing the policy. In the absence of a credible European alternative that can provide commercial cloud services at scale, these segments will continue to be dominated by American and Chinese companies.

 by insulating sensitive workloads from two laws that follow the provider rather than the data: the 

, which compels American providers to disclose data in their control regardless of where it is stored, and 

, which obligates Chinese firms to cooperate with state intelligence work, including abroad. It does so at the price of higher costs and near-term capability gaps. Continued reliance on the same hyperscalers also leaves the EU’s interdependence sovereignty weak. The four-layer sovereignty levels are a price list. Brussels is deciding which sovereignty it will pay for and where.

Over the last few years, Malaysia has pursued a hedging strategy by building data centers using both Chinese and US cloud providers. This strategy strengthens its 

 because it keeps an exit option in case either superpower tries to weaponize the interdependence by threatening to cut access, or through other coercive means.

 by potentially exposing citizen data processed on the infrastructure to US and Chinese extraterritorial law. In response to pressure from US and Chinese authorities to pick a singular stack, Malaysia 

” and justified its hedging as part of its 

Why would Malaysian policymakers assert sovereignty through measures that so clearly undermine its own territorial authority? By disaggregating sovereignty into multiple dimensions, we can start to make sense of the decisions. In this case, Malaysia may have purposefully invited these sovereignty violations, well aware of the tradeoffs.

 regulating AI-generated content on online platforms. Synthetic media must be labeled and carry provenance metadata; large platforms must deploy automated tools both to check whether content is AI-generated and to proactively catch unlawful material such as child sexual abuse material; and illegal content must come down within hours. Notably, the rules toughened the detection duty from an effort-based standard to a strict obligation to deploy such tools. However, last month, the BBC 

 that Instagram had allegedly run paid ads in India directing users to CSAM, indicating that they had cleared the automated review Indian law now requires. The Indian government 

, ordering Meta to disable the content and explain itself within a week.

becomes useful: India asserts the legal authority to bar the sharing of CSAM within its borders, yet lacks the capacity to control the private systems that platforms use to moderate content. India's rules show how far legal authority over the information space can outrun actual control of it, when the systems that would deliver that control are built and operated by private companies rather than the state.

The policymaker: Choosing which sovereignty to buy

Given that gains in one dimension routinely come at the cost of another, governments should ask themselves a few questions when developing sovereignty policies and spell out which kind of sovereignty they actually need before spending money on it. Which kind of sovereignty does this measure actually protect? What does it cost in the other kinds? Does the gain advance a defined national objective better than the same money spent elsewhere? Left undefined, “AI sovereignty” will go on doing what it does now: costing enough to strain a budget while meaning little enough to justify almost anything.

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