Meaning

In May 2026, just hours before President Donald Trump met President Xi Jinping, OpenAI’s Vice President of Global Affairs Chris Lehane floated the idea of a US-led global governance body for artificial intelligence that would include China as a member. The model, according to media reports, was compared to the International Atomic Energy Agency (IAEA), a familiar reference for managing strategic technologies with global consequences.

One month later, at the G7 summit in Évian-les-Bains, a different tone emerged. Several influential AI executives joined leaders from advanced economies to discuss AI governance, online safety, and global security. According to Axios, Anthropic’s Dario Amodei and Google DeepMind’s Demis Hassabis leaned towards a more selective framework among democratic countries, while OpenAI’s Sam Altman used broader language, calling for an international forum to develop shared testing standards and risk assessments.

These two moments reveal something important: the meaning of “global AI governance” remains unsettled. In one setting, global means including China for legitimacy. In another, it can mean a trusted coalition designed to manage access, capability, and strategic risk. AI governance is becoming part of the architecture of global power.

Three Voices, Different Emphases

Their presence at the G7 showed how quickly AI firms have moved from building systems to helping shape the politics around them. The leaders of OpenAI, Anthropic, Google DeepMind, Mistral, Cohere, and other firms were not simply observers of geopolitics. They were part of the conversation about how technological power should be governed.

Their positions were not identical. Amodei reportedly urged democratic countries to coordinate more closely so that AI governance would not fragment. Hassabis stressed the strategic importance of frontier capability. Altman, by contrast, used more institutionally neutral language, suggesting that advanced AI should not be shaped only by the companies building the most capable systems.

Even among frontier AI developers, there is no settled imagination of global governance. Should it include all major AI powers, including strategic rivals? Should it be built around trusted coalitions? Should it prioritize safety, democratic values, geopolitical advantage, or public legitimacy?

The question became more complicated because the G7 discussions came shortly after the US government imposed export controls that forced Anthropic to suspend foreign access to its Fable 5 and Mythos 5 models. Reuters reported that the order required Anthropic to block access to the models for foreign nationals, leading the company to disable them more broadly to ensure compliance. The episode showed how frontier AI governance can move from abstract principles to abrupt restrictions. Even among democratic allies, technological solidarity has limits. When AI becomes strategic infrastructure, every country begins to think about its own room for maneuver.

The Asymmetry of “Global”

The deeper issue lies in who has the power to define the word “global” in the first place. In May, global governance could mean a US-led institution that includes China. In June, it could mean coordination among democracies to manage frontier capability and strategic access. The definition changed because the political room changed.

This reveals a double asymmetry. The first is technical: only a small number of firms can define what counts as a frontier model, how its capabilities should be tested, and who should be allowed to access it. The second is narrative: the same ecosystem also helps frame the language through which the world discusses governance.

For countries outside the frontier AI circle, they may be invited to conversations but not always to the stage where categories, thresholds, and governance priorities are first shaped. They may be asked to adopt best practices whose assumptions were formed elsewhere. They may be told that risks are global, even when preparedness remains highly unequal.

G7 outreach to partner countries such as India, Brazil, Kenya, South Korea, and Egypt is important. It recognizes that AI governance cannot remain a conversation among advanced economies alone. Yet there remains a difference between being present in a forum and helping design the architecture of the forum itself. The question is who defines the table, the agenda, the risk categories, and the meaning of global governance itself.

When the AI Frontier Moves Towards the Market

There is another reason why a broader governance imagination is necessary. Frontier AI innovation is no longer centered primarily in universities or public research institutions. It is increasingly shaped by private firms with the capital, compute, talent, data access, and infrastructure required to train and deploy the most capable models.

Stanford’s AI Index 2025 noted that nearly 90 per cent of notable AI models in 2024 came from industry, up from 60 per cent in 2023. A report prepared for the European Economic and Social Committee on generative AI and foundation models also described significant US dominance across the value chain. These findings point to a structural shift: the frontier is becoming more concentrated, more expensive, and more closely tied to corporate and geopolitical capacity.

Much of AI’s progress has come from companies willing to take risks, scale products, and build technical capability at extraordinary speed. But the center of gravity has shifted. When frontier AI is largely financed, defined, and deployed by market actors, the default imagination of AI development can tilt towards commercial viability, platform advantage, user growth, and strategic positioning.

Public interest does not disappear in such a system. It risks becoming secondary unless other actors are strong enough to bring it back into the room.

Open Future, a European digital policy organization, has warned that concentrations of power in AI can make public activities dependent on “a narrow group of monopolists.” The phrase matters because infrastructure-level dependency can weaken society’s ability to negotiate the terms of the technologies it relies on.

A Wider Public-Interest Layer

In a multiplex digital world, power does not flow only through states or markets. It also moves through universities, civil society organizations, professional associations, media, labor groups, open-source communities, public-interest technologists, and moral institutions. Together, these actors form the society layer often missing from discussions dominated by states and markets.

States define security priorities. Companies define technical possibility. Society must help test legitimacy. Who bears the risk? Who benefits from deployment? Who is excluded from design? What harms are being normalized because they are commercially convenient or geopolitically useful?

This is why Pope Leo XIV’s recent intervention on AI is politically relevant beyond its religious context. In his encyclical Magnifica Humanitas, he argues that protecting the human person in the age of AI requires renewed reflection on the common good, solidarity, social justice, and human dignity. Such interventions will not replace regulation or technical standards. They help recover a truth easily lost in frontier AI politics: governance is also about preserving the human meaning of technological progress.

The same question of authorship is beginning to appear in empirical research. Ongoing fieldwork-based research at the University of Oxford has started to examine whether countries in the Global South are developing approaches to AI governance that are neither simple copies of Western regulatory templates nor rejections of international cooperation but pragmatic syntheses shaped by local institutional capacity, regulatory sequencing, and historical experience with technology transfer. Indonesia has appeared as one of the country cases in this line of inquiry.

Governance models worth studying are not only those negotiated in Évian, Brussels, Washington, or New York. They are also being improvised, often informally, by mid-sized digital economies navigating dependency and ambition at the same time.

The United Nations’ Global Digital Compact (GDC), adopted in September 2024, offers a useful multilateral reference point. It frames digital cooperation and AI governance around inclusion, human rights, open standards, interoperability, digital public goods, and multi-stakeholder cooperation. The Compact does not resolve the power asymmetries of frontier AI by itself, but it gives societies, alongside states and firms, a language for claiming a legitimate role in digital governance.

The practical task is to strengthen public-interest evaluation: the ability to test social impact, language bias, local risks, institutional misuse, and deployment consequences in different societies. The aim is to preserve enough room for public reasoning so that the future of AI is not defined only by those with the largest models, the biggest markets, or the strongest strategic leverage.

Imagining a More Inclusive AI Governance

The lesson from the IAEA analogy and the G7 discussions is not that one model is right and the other is wrong. Both reflect real concerns. A broadly inclusive governance arrangement may be necessary for legitimacy, especially when AI risks cross borders. A trusted coalition may also be necessary when capability access raises genuine security concerns. The problem begins when either model claims to be global while leaving too many societies downstream of decisions made elsewhere.

For emerging economies, the strategic challenge is not simply to wait for a better invitation to the next summit. Participation matters, but it is not enough. Countries and societies need stronger capacity to evaluate AI systems, understand their dependencies, articulate local risks, and negotiate governance terms with greater confidence.

This is a call for a more plural architecture of governance, where states, markets, and society all have meaningful roles. The uncomfortable question is not whether AI requires international coordination. It clearly does. The harder question is whether that coordination can remain open enough for societies, not only states and companies, to shape the terms of technological power.

In the age of frontier AI, the future will not be determined only by who builds the largest models. It will also be shaped by who gets to define risk, test systems, question assumptions, and decide what counts as progress.

Every era that has tried to govern a transformative technology eventually learns the same lesson: legitimacy borrowed from power is not the same as legitimacy earned through participation. The IAEA’s own history shows that global trust is rarely built at the moment institutions are created; it is earned over time, through broader representation, credible restraint, and shared accountability. The real question for AI governance is whether it can shorten that distance by design, rather than waiting for legitimacy to arrive only after contestation.

The past five years has seen Chwalinska work hard on the lower levels of the WTA Tour, diligently trying to improve her game.

Working on being able to mentally compartmentalise her career – which she associated with “pressure, stress and crying” – from the rest of her life has proved crucial.

A year ago, Chwalinska was playing tiny tournaments in Italian cities Brescia and Bari after going out of the French Open in the second round of qualifying.

Now she has won nine matches in a row at Roland Garros. One more will see her become the first qualifier in the Open era to lift the trophy here.

Maybe the tattoo represents how she has played over the past three weeks – with a freedom and joy that has captivated the Parisian crowds.

Chwalinska has earned notable wins over former French Open semi-finalist Maria Sakkari and Olympic champion Zheng Qinwen, as well as beating three seeded players in Shnaider, Anna Kalinskaya and Elise Mertens.

Playing with variety and spin, Chwalinska can lob, drop shot and moonball her opponents to distraction, but she can also hit with pace to finish off points quickly.

“I feel like I’m in the bubble. I don’t know what’s going on. I’m just very happy to be here,” said Chwalinska, who has almost tripled her career prize money with the guarantee of winning at least £1.2m by reaching the final.

“After the tournament there will be time to process it and breathe in, breathe out.”

SOAP couple Nikki Sanderson and Anthony Quinlan have finally revealed their baby son’s name, and the sweet meaning behind it.

The couple welcomed their first child, a baby boy, in April – just four months after they revealed they were expecting.

At the time, they revealed the news with a monochrome snap and simply dubbed him their ‘little man’.

But now, Hollyoaks actress Nikki and fellow soap star Anthony have revealed their baby boy is named Anthony James Quinlan.

Anthony Jr not only shares the same name as his dad, but Nikki told OK! Magazine that his middle name, James, is an ode to her brother.

“Two very special men,” she explained.

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With two Anthonys at home, things are bound to get confusing, as new dad Anthony says the family are already working ways around it.

He told the publication: “Different members of our family and friends have all started calling him different things. 

“A couple of people call him AJ, some Tony. I used to get called Toe, so he’s little Toe as well. I love the fact that he’s got my name.”

Nikki and Anthony first announced they were expecting a baby with a sweet post at Christmas time.

Sharing a video on Instagram, the caption read: “Merry Christmas from the 3 of us. Baby Quinlan due Spring 2026.”

In the clip, the couple were seen decorating their Christmas tree together, adding baubles, before opening a box and unveiling the most important decoration of all.

The tree ornament included a photo of the baby scan and read: “Baby Quinlan: Arriving 2026.”

Nikki and Anthony got together in 2022, going public with their romance in April of that year.

Last year, Nikki stepped away from her role of Maxine Minniver in Hollyoaks, one she had held since 2012.

But before that, she began her soaps career on Coronation Street, where she played feisty hairdresser Candice Stowe.

Just like the mother of his child, Anthony is also a soap star and is known for playing Gilly Roache in Hollyoaks, and Pete Barton in Emmerdale.

There are moments in history when civilizations continue to advance materially while progressively losing confidence in the values  and structures that once gave direction and coherence to collective life. Institutions continue to function, markets continue to expand, and technological progress accelerates uninterruptedly, yet beneath this movement emerges a quieter uncertainty.

As Simone Weil observed, “to be rooted is perhaps the most important and least recognized

need of the human soul.”[1] Yet contemporary societies often struggle to sustain those forms of

belonging and shared meaning that once anchored human communities. The crisis is

therefore not simply political or economic. It concerns meaning itself.

Artificial intelligence has appeared precisely within such a historical juncture. Most contemporary discussions approach AI primarily as a technological revolution, or as an element of economic and geopolitical competition between great powers. Governments now frame it as a strategic race, corporations present it as the next engine of productivity, and Silicon Valley often speaks of AI in the language of inevitability and destiny, recalling Aldous Huxley’s fear that technological progress might ultimately weaken rather than deepen human civilization.[2]

 But such interpretations may ignore something deeper still. AI may be less the cause of a civilizational transformation than one of its clearest symptoms. It reflects a broader historical transition in which inherited moral and symbolic frameworks are dissolving faster than new forms of collective meaning can emerge.

Slouching Towards Bethlehem[3]

This condition closely resembles what Antonio Gramsci described as an interregnum: a period in which the old world is dying while the new world struggles to be born. [4] Such periods produce not only political instability, but also moral exhaustion, the erosion of shared narratives, and declining confidence in beliefs once considered self-evident. Civilizations have passed through similar moments before.

The enduring fascination of Edward Gibbon’s monumental The Decline and Fall of the Roman Empire lies not merely in its account of imperial decline, but in its portrayal of the slow weakening of the moral and symbolic foundations that once sustained an entire civilization.[5] Rome did not collapse overnight. Its institutions remained impressive long after few still believed in the civilization they were meant to serve. Administrative power survived even as collective meaning and aspirations deteriorated.

That pattern feels strangely familiar.

Never before have technological capacities appeared so extensive while social distrust, political fragmentation, and loneliness have become so pervasive. Hyperconnectivity was supposed to bring societies closer together. In many cases, it has done the reverse.

AI in the Anthropocene

AI emerges from within this historical condition . It appears perfectly suited to societies organized around abstraction, speed, quantification, and technological mediation. In this sense, AI is profoundly historical. It results from a long civilizational development in which rationalization, efficiency, and technical calculation have come to replace older moral, religious, and symbolic frameworks as primary sources of legitimacy and meaning. What distinguishes AI from previous technologies is that it extends these same principles into domains traditionally considered irreducibly human. Activities once understood as distinctly human, such as reasoning, creativity, interpretation, and even emotional interaction, are now becoming technologically mediated.

The deeper unease therefore concerns anthropology as much as technology. What remains distinctively human when machines become capable of imitating reasoning, generating art, and mediating human relationships?

Such moments of civilizational disorientation are not entirely unprecedented.

The Renaissance confronted a similar rupture. Medieval Europe had long possessed a relatively coherent worldview capable of organizing religion, politics, morality, and human identity within a common order. By the late fifteenth century, however, this equilibrium was beginning to fracture under the pressure of new scientific discoveries, religious wars, and the weakening of older political and spiritual authorities. Thinkers such as Niccolò Machiavelli and Giovanni Pico della Mirandola sought, in radically different ways, to redefine humanity’s place within a rapidly changing world.[6] Pico celebrated human beings as creatures capable of shaping themselves through freedom and intellect, while Machiavelli recognized more soberly that periods of transition dissolve inherited certainties and force societies to confront instability and power directly.

Both understood that historical transformation is ultimately existential before being institutional. Our own transition may prove even more radical because technology no longer transforms only economic or political life, but cognition itself.

AI now mediates everyday experience itself: how people search for information, communicate, work, and make sense of the world around them.

Algorithms no longer merely distribute information. They shape attention, influence perception, and affect how individuals relate emotionally to public life and to one another. Under such conditions, the distinction between human judgment and technological mediation becomes far less clear.

The Price of Nostalgia

One striking feature of the contemporary digital environment is the degree to which individuals now participate voluntarily in their own data extraction. Recent Instagram trends such as the viral “What Were You Like in the ’90s?” challenge encourage users and celebrities alike to upload curated archives of personal photographs spanning decades of their lives. Presented as nostalgia and entertainment, these trends also generate immense quantities of highly valuable visual and behavioural data: faces across time, emotional reactions, aesthetic preferences, social interactions, and patterns of self-presentation. Whether or not such material is directly incorporated into future AI systems, the broader objective remains significant. Human memory, identity, and even nostalgia itself increasingly becomes raw material for computational analysis and commercial platforms.

Reactions to AI therefore oscillate easily between fascination and anxiety. Beneath both lies a deeper uncertainty about whether modern societies still possess a coherent understanding of what human beings are for, beyond economic productivity and consumption.

Friedrich Nietzsche anticipated aspects of this crisis more than a century ago. His declaration that “God is dead” did not merely constitute a theological provocation but signalled the emergence of a civilization in which traditional moral structures would lose authority long before new ones could replace them.[7] Nietzsche feared not nihilism alone, but the possibility that societies might become incapable of generating new forms of transcendence once older ones had collapsed. We saw how his worldview provided an intellectual base for Fascism.

I Read, therefore I Am

In increasingly mediated environments, the act of sustained reading itself begins to take on a countercultural character. To read is, in some sense, to resist. We have access to more information than any previous generation, yet physical books can still provide a sense of orientation. The books people return to, annotate, or simply keep close over time often reveal something enduring about the way they think and who they are.

The central issue, therefore, is not simply whether artificial intelligence will become more powerful. The deeper question is whether societies organized around AI can still sustain stable forms of responsibility and belonging strong enough to preserve coherent collective life. This is ultimately a political and civilizational problem before it is a purely technical one.

Much contemporary discourse still assumes that technological advancement naturally produces historical progress. History offers little evidence for such confidence.

Civilizations do not endure simply because they innovate technologically. They endure because they preserve, or reinvent, systems of meaning capable of holding societies together over time.

The Roman Empire mastered engineering yet gradually lost the moral cohesion that had once sustained it. Renaissance Europe produced extraordinary creativity precisely because it confronted existential instability directly rather than attempting to ignore it.

Contemporary Western societies appear caught between immense technological sophistication and growing uncertainty about their own civilizational narrative.

AI therefore represents more than innovation. It reflects a transformation in how human beings understand themselves, authority, knowledge, and reality itself. The danger is not simply that machines become too powerful. It is that societies now outsource judgment, imagination, and responsibility while slowly losing the cultural and moral resources required to govern these technologies wisely. Yet periods of interregnum are not necessarily periods of decline alone. They are also moments in which civilizations redefine themselves.

AI For Good ?

Historical transitions create possibilities as well as dangers. The Renaissance emerged from the crisis of medieval Europe. Modern democracy emerged from the upheavals of industrial society. Today’s uncertainty may likewise force Western societies to confront questions long obscured by economic growth and technological optimism:

What constitutes a good society? What forms of belonging remain possible in a hyper-mediated world? What aspects of human life should never be reduced to data, prediction, or optimization?

AI cannot answer these questions. But its emergence makes avoiding them increasingly difficult.

[1] Simone Weil, The Need for Roots: Prelude to a Declaration of Duties Towards Mankind (1949/1952).

[2] See Aldous Huxley, Brave New World (1932) and his later essays such as Brave New World Revisited (1958), where he warns that technological efficiency and social conditioning could erode authentic human experience.

[3] The phrase alludes to the final lines of W.B. Yeats’ poem “The Second Coming” (1919): “And what rough beast, its hour come round at last, / Slouches towards Bethlehem to be born?”

[4] Antonio Gramsci, Prison Notebooks (written 1929–1935, published posthumously). The “interregnum” concept appears in Notebook 3: “The crisis consists precisely in the fact that the old is dying and the new cannot be born; in this interregnum a great variety of morbid symptoms appear.”

[5] Edward Gibbon, The History of the Decline and Fall of the Roman Empire (6 volumes, 1776–1789). Gibbon famously attributed part of the decline to the rise of Christianity and the erosion of civic virtue.

[6] Giovanni Pico della Mirandola, Oration on the Dignity of Man (1486) — often called the “Manifesto of the Renaissance”; Niccolò Machiavelli, The Prince (1532) and Discourses on Livy.

[7] Friedrich Nietzsche, The Gay Science (1882, §125 – “The Madman”) and Thus Spoke Zarathustra. The full phrase is usually rendered “God is dead. God remains dead. And we have killed him.”