AI

Killer robots are rapidly moving from the realm of science fiction into a real debate over the future of warfare. As militaries develop weapons capable of identifying, selecting, and engaging targets with diminishing human intervention, a fundamental question emerges: how much authority over life and death can states safely delegate to machines? The answer will shape not only the conduct of future conflicts, but also the risks of escalation, the protection of civilians, and the ability to hold decision-makers accountable when autonomous systems cause harm.   The military incentives are difficult to ignore. Autonomous capabilities can accelerate responses, process battlefield information at a scale beyond human capacity, and operate in environments where communications are disrupted or reaction times are critical. For states competing to maintain a technological advantage, limiting these capabilities may appear to carry its own strategic costs. Yet the pursuit of speed can undermine the deliberation and oversight that help prevent military errors from becoming wider confrontations.   This creates a strategic dilemma: the same capabilities that promise greater military effectiveness could make the use of force harder to control. As states respond to one another’s advances, autonomous systems may become more deeply embedded in military operations before international rules and command structures can adequately address their risks. The central challenge is therefore not simply whether machines can make lethal decisions, but whether meaningful human control can be preserved when military competition rewards ever-greater autonomy.

In early June, 28 officers and experts from 11 countries gathered in Tunis to extract more than 108,000 facial images from jihadist propaganda and sort them with AI tools. When INTERPOL, the international police cooperation organisation, announced the results on 18 September, the tools had narrowed the pile to 6,362 usable images, and 126 foreign terrorist fighters had been identified. Operation Shams II was billed as the first operation of its kind.   Terrorist groups have rarely been technological pioneers, yet they have repeatedly proved to be capable adopters of tools built by others. AI, which now writes, translates, speaks, and generates images on demand, is the latest example, and governments are working to turn the same technology against the people using it. This is not a story of one side pulling ahead. Because AI is dual-use, meaning the same capability serves attackers and defenders, every advance by one side reshapes the options of the other.   The common assumption is that the winner will be whoever deploys the best tools first. However, that assumption overlooks how differently the two sides adapt. Terrorists move cheaply and largely in the information space, where failure costs them little. States move slowly, at high expense, and under legal and public scrutiny. Adapting faster therefore depends less on who adopts a tool first than on who can sustain its use where violence actually happens, without losing the trust that gives state action its authority. That is where the contest will be won or lost.

The rapid expansion of artificial intelligence is driving a parallel expansion of the infrastructure on which it depends. Data centres consumed around 415 terawatt-hours (TWh) of electricity in 2024, roughly 1.5% of global demand, and the International Energy Agency's base case projects about 945 TWh by 2030. Governments in the Gulf and Europe have responded by treating data centres as strategic assets while remaining committed to decarbonising their energy systems. Yet a commitment to clean energy does not necessarily amount to clean data centres.   This distinction is becoming increasingly important because the timelines differ so sharply. A data centre can be built in one to two years, whereas transmission takes far longer and new clean generation, nuclear in particular, longer still. When demand arrives before supply, the gap tends to be filled by gas. Ireland illustrates the dilemma: data centres accounted for 23% of its metered electricity in 2025, up from 5% in 2015, and the regulator now requires new large facilities to bring their own generation or storage. The central question, therefore, is whether AI infrastructure and the green transition can advance together.

Longevity is moving beyond the domain of medical research to become a potential source of economic and strategic power. Advances in genomics, regenerative medicine, cellular reprogramming, and AI-enabled drug discovery are attracting growing private investment and government attention, even as evidence for dramatic extensions of healthy human lifespan remains limited. Against a backdrop of population ageing and declining fertility, even incremental improvements in healthspan could reshape labour markets, pension systems, healthcare demand, and national productivity.   However, longer healthy lives present a fundamental paradox. While they could expand individual freedom, preserve human capital, and create opportunities for education, creativity, and multiple careers, they could also extend working lives at the expense of personal choice, delay inheritance, compound wealth, and allow political, corporate, and scientific elites to retain influence for longer. If access to longevity interventions remains concentrated among wealthier individuals, existing inequalities could deepen across both generations and societies.   The geopolitical implications are equally significant. The United States, China, Saudi Arabia, the United Arab Emirates, and Singapore represent different approaches to building longevity research, investment, regulatory, and biotechnology capabilities. Countries that develop and deploy effective interventions could strengthen their human capital and technological competitiveness, while those lacking research infrastructure or access to advanced therapies risk greater dependence on external suppliers. The convergence of AI and biotechnology adds further concerns surrounding biological data, dual-use capabilities, cybersecurity, and the concentration of technological power.   This Special Edition identifies the signals that could indicate a transition from scientific promise to systemic change, outlines plausible future scenarios, and examines how governments can prepare. Its central argument is that the strategic consequences of longevity will depend not only on scientific progress, but also on how societies distribute additional healthy years, regulate emerging technologies, and adapt the institutions governing work, wealth, retirement, and political authority.  

On 23 September 2026, the United Nations Security Council confronted an unusual development in international security. The people warning governments about the dangers of AI were not only diplomats or military officials, but the executives building the technology itself. OpenAI CEO Sam Altman, Anthropic CEO Dario Amodei, and Hugging Face co-founder Clément Delangue briefed the 15-member Council as governments grapple with increasingly capable AI systems that can write code, operate autonomously, interact with external systems, and potentially improve their own capabilities. Amodei warned that, if poorly managed, “AI could be a risk to humanity as a whole”, while Altman argued that decisions about AI could not be left to technology companies alone.   The meeting was significant because AI is rapidly moving from a technology-policy issue into the domain of international security. Yet the deeper question is not simply how dangerous AI may become. It is who will establish the rules governing a technology increasingly concentrated in the hands of a small number of states and companies. The UN is attempting to become the forum where those rules are debated, but it is entering a contest in which technological capabilities, economic power, national security interests, and competing visions of governance are already shaping the outcome.

Congress now has a lobbyist that never registers, never discloses a client, and never leaves a paper trail, and it sits open in a browser tab on nearly every staffer's desk. The House Office of Legislative Counsel, the institution responsible for turning policy ideas into legally binding text, has reportedly been inundated with AI-generated bill proposals so riddled with incorrect statutory references and sloppy drafting that its lawyers now spend more time fixing them than they would spend writing the bills from scratch. Around the same time, it became clear how far this had spread. Members of Congress and their staff are increasingly using systems such as ChatGPT, Claude, Copilot, and Gemini for policy research, legislative drafting, speeches, and constituent replies.   On the surface, this looks like any workplace chasing efficiency. But Congress is not any workplace. The information lawmakers receive, the way problems get framed, and the exact language that ends up in statute can affect millions of people. So the real question is not whether chatbots make congressional offices faster. It is what happens once the systems helping policymakers research, frame, and write legislation become an active participant in the political process itself.

The latest AI boom is creating an unusual paradox. The more AI companies need high-quality information, the more aggressively they are buying the physical books that contain it, and in some cases destroying those books once their contents have been absorbed. In recent months, independent booksellers in the United States, Britain, Europe, and elsewhere have reported sudden surges in unexplained bulk purchases, sometimes involving hundreds of unrelated and obscure titles. Some of these books are subsequently being sent to facilities where their bindings are removed, their pages rapidly scanned, and the remains discarded or recycled.   The scale could become far larger than the cases already exposed. ISBNdb, a major book database, now facilitates purchases ranging from 1,000 to one million books per order, while booksellers have described previously unsold titles suddenly becoming highly sought after. At the same time, an Amazon facility in Las Vegas has been identified as a site where employees described cutting book spines, scanning loose pages, and disposing of the resulting paper. The controversy raises a question that extends well beyond publishing. What happens if the race to build better AI systematically removes the physical sources from which that intelligence was created?

Smart glasses are no longer an experimental technology waiting to prove whether consumers will adopt them. They are already spreading rapidly, with Meta having sold more than 7 million pairs of its Ray-Ban smart glasses and daily use reportedly tripling year over year in early 2026. At the same time, the technology is becoming more capable, combining cameras, microphones, AI, translation, navigation, audio, and visual recognition in an object designed to remain on the user's face throughout the day. As manufacturers expand the technology and the market continues to grow, restaurants, theatres, workplaces, conferences, and other venues are increasingly questioning whether existing rules governing photography and recording are adequate.   The question, therefore, is no longer whether smart glasses will become part of everyday life, but what their expanding adoption will do to privacy and public space. Unlike smartphones, which normally require a visible gesture to record, smart glasses can capture and interpret their surroundings while their wearer continues to behave normally. As adoption expands, surveillance power is consequently shifting beyond governments, companies, and security systems towards ordinary individuals. This raises broader questions about who controls the information collected, who owns it, how it can be used after capture, and whether privately generated recordings could become another source of institutional surveillance.

Europe has spent the last few years watching its tech anxiety go from background hum to full orchestra. It's not hard to see why. In June 2026, France's intelligence services announced they were dropping Palantir, the American data analytics firm long embedded in European defence and policing work, in favour of a domestic provider, explicitly citing the need for "strategic autonomy." Germany's military reportedly will not touch Palantir at all, and the UK is now fielding parliamentary debates over a quarter-billion-pound contract with the company, partly because, as one legal analysis bluntly put it, even European data sitting in European data centres can still be pulled by U.S. authorities under American law, contracts or no contracts. It's the kind of detail that makes "data sovereignty" sound less like a policy buzzword and more like a genuine catch.   Then, just days before this was written, the U.S. government ordered Anthropic to cut off access to its most advanced AI model, Mythos, for anyone who wasn't a U.S. citizen, citing national security concerns. Anthropic's response was to switch the model off for everyone, Americans included, rather than build a citizenship checkpoint overnight. The episode lasted only days, but it landed exactly where Europe's anxieties already live: the frontier of AI doesn't just sit outside Europe's control, it sits inside one government's control, and that government can flip a switch.   None of this means Europe should panic, or try to build its own version of everything from scratch by Thursday. As the cost estimates make clear, chasing full autonomy across the entire AI stack would run into the trillions of euros, well past the point of being realistic. The more sensible response, is for Europe to get serious about which parts of the stack actually need to be sovereign, where partnership is a perfectly good substitute for ownership, and where its real strength, regulatory leadership, can be used deliberately rather than as a consolation prize. Sovereignty, in other words, isn't about owning everything. It's about knowing exactly what you can't afford to depend on.

By 2101, the concept of democracy and the architecture of governance will undergo a profound transformation that moves far beyond traditional mechanisms such as ballot boxes and political rhetoric. In their place will emerge a system built around transparent digital interfaces that display the outputs of exceptionally powerful algorithms entrusted with making consequential decisions on behalf of societies. The central dilemma in political philosophy will no longer concern who holds the right to vote. Instead, the debate will shift toward a far deeper and more consequential question: who will possess the authority to design the code that governs human destinies and shapes control over the world’s resources?   Meanwhile, Nada sat in a soaring glass chamber overlooking the heart of the city, where vast digital walls shimmered with data visualisations and undulating lines. The space was known as the Pulse of the People Hall, the neural hub through which algorithms monitored public sentiment in real time. The main display contained no reference to parties or candidates; instead, it presented dense layers of complex code and finely calibrated colour indicators that measured levels of fear, anger, satisfaction, and trust, using the same precision as that used to measure temperature and humidity.   Nada released a heated exhale and murmured to herself, “All of this happened because democracy eroded from within.” She had studied at university what historians came to describe as the Age of Political Chaos in the late twenty-first century, a period in which elections degenerated into open arenas of cyber warfare, driven by legions of automated bots and engulfed by unending torrents of fabricated news. During that era, borderless capital asserted dominance over every dimension of political life, purchasing electoral campaigns, opinion polls, and platforms for public debate. Confronted with successive climate, pandemic, and financial crises, elected governments stood paralysed, absorbed by internal rivalries far more than by the act of governing.   At that pivotal moment, fatigued governments and weary societies alike came to regard a single path as the only rational recourse: “Let the machine decide.” What first emerged was the Comprehensive Algorithmic Governance System, an advanced suite of frameworks designed to support decision-makers in interpreting data and reaching swifter, more objective judgements. These systems were introduced to the public as neutral entities: unconcerned with transient popularity, untroubled by ballot boxes, and untouched by private interests. Yet what began as an auxiliary tool soon transformed into the primary centre of authority and, ultimately, the sole arbiter of decision-making.

Many analysts fall into a recurring methodological error when assessing the United Arab Emirates’ (UAE) position amid regional turbulence. They measure the country’s resilience by its geographical distance from centres of risk, overlooking its exceptional capacity for strategic reinvention in the face of crises. This misreading, in particular, lends early credibility to pessimistic narratives of a “decline of the Gulf”, narratives that quickly unravel under the weight of empirical evidence and the firmness of facts. The UAE has not navigated successive regional crises by relying on geographic insulation or external protection. Rather, it has done so through deeper, more enduring foundations: a demonstrated ability to convert shocks into substantive reform, and to elevate those reforms into sustained competitive advantage.   Accordingly, this analysis does not seek to downplay the scale of the challenges posed by a regional war that is casting a heavy shadow over the security of the Strait of Hormuz, maritime insurance markets, and investment flows. Rather, it offers a structured attempt to address three interrelated core questions: how has the UAE historically navigated major crises; how did it anticipate the current crisis by fortifying its infrastructure and economic systems to sustain resilience; and, finally, how should the present moment be understood, not as signalling the end of a development model, but as marking the transition to a more mature and deeply embedded position within the global economy.

This Pulse survey, conducted in November 2025, explores public attitudes toward AI in Arab societies, with a particular focus on reliance on foreign AI models and their impact on Arab values and identity. The findings highlight growing concerns about how AI systems may influence cultural norms, shape collective identity, and redefine societal priorities. By examining perceptions of the need for Arab-developed AI and views on who should lead its development, the survey offers insight into how technological dependence is increasingly understood as a strategic, cultural, and identity-related issue across the Arab world.