Imagine you are at a cocktail party. The room is crowded, people are coming and going, and you can barely hear your friend as they tell you some juicy gossip about the date they went on last week.

The fact you can still follow what their saying is down to your brain performing some very complex operations amid all the noise. Out of all the sound waves reaching your ears, it is successfully isolating the one of interest while filtering out the rest.

Trying to understand how the brain does this has kept auditory neuroscientists occupied since the 1950s, when British cognitive scientist Colin Cherry first coined the term “the cocktail party problem”.

This was initially studied in experiments that asked volunteers to listen to two speeches simultaneously – but only repeat one of them aloud afterwards. Cherry found that listeners could follow and repeat the pre-selected message remarkably well, despite both speeches being played simultaneously, one in each ear. In contrast, they recalled very little of the other message.

These experiments laid the foundation for decades of selective attention research. But it is only in the past 15 years that scientists have studied this phenomenon in experiments that more closely resemble the complicated, multi-layered way we listen in the real world – using technology that accurately tracks the brain’s activity as speech unfolds.

The most common non-invasive option, electroencephalography (EEG), uses what looks like a swimming cap fitted with small sensors. These measure very fast changes in the electrical activity of populations of neurons (the brain’s nerve cells) with millisecond precision.

In a 2014 study, neuroscientists found that, within 200 milliseconds of hearing someone speak, the brain favours the conversation someone is focusing on over all other noise. This prioritised attention shows up most markedly in secondary brain areas such as the superior temporal gyrus, which are responsible for piecing together the sounds we hear into meaningful speech.

This suggests that our attentive brain is not just enhancing the voice of who we are listening to, but helping us make sense of their words while filtering out all other conversations and background noise.

Attention switching

The original cocktail party problem did not investigate the full range of people’s listening experiences, which are often much less static. In everyday life, we repeatedly switch and reorient our auditory attention – for example, when hearing our name called across a crowded room, or when a door slams.

But what happens in that brief moment when we stop listening to one person and turn our attention to another? Can the brain switch from one voice to another instantly, or does it briefly have to process both? These were questions we investigated in our latest study with colleagues from the Eriksholm Research Centre in Denmark, which is funded by Danish hearing aid manufacturer Oticon.

Clarifying how the brain manages these rapid shifts in attention can help explain why some conversations are easy to follow while others become difficult, especially in noisy environments.

Coming back to the cocktail party: here you are, focused on your friend’s voice as they reveal the identity of their recent date. But then another familiar voice suddenly reaches your awareness. Your partner is (secretly) telling a friend about the surprise birthday gift they are planning for you. Your attention immediately shifts to your partner’s voice, while still giving the appearance of listening to your friend.

When we tested such a scenario in our laboratory, we found something striking. During this attention reorienting, the brain does not simply drop one voice and turn to the other. Rather, for a short period of between one and two seconds, the neural signals associated with the two voices overlap. In other words, the brain starts tuning into the new speaker before it has completely let go of the old one.

This mechanism may help explain how we navigate the constantly changing soundscape around us, moving our attention from one voice or sound to another while maintaining enough information about the previous speaker to make that transition seamless. This efficient processing strategy could be described as the brain maintaining a smooth “attention continuum”.

Improved hearing aid design?

These insights have some important real-world applications. For example, traditional hearing aids are often designed to favour sounds coming from in front of the listener, which is obviously limiting in many situations.

But using enhanced these attention decoding techniques, hearing aids could be neurally steered not only to enhance the speaker that is currently attended to, but to switch between different speakers, almost in real time, as the listener’s attention is dynamically reoriented.

More generally, understanding how the brain shifts, maintains and combines information from different speakers can give us a clearer picture of how attention shapes what we ultimately hear, understand and remember.

The approach introduced in our study could be particularly useful for studying how individuals vary in their attentional strategies, particularly in noisy environments – and for relating these differences to the mental effort they use to follow and understand speech.

Ultimately, this brings us closer to understanding how the brain makes successful communication possible – at cocktail parties and everywhere else.

Sara Carta received funding from the William Demant Fonden and Taighde Éireann – Research Ireland.

Giovanni Di Liberto receives funding from William Demant Fonden and Taighde Éireann – Research Ireland. He is also supported by Research Ireland at ADAPT, the Research Ireland Centre for AI-Driven Digital Content Technology at Trinity College Dublin.

Every ancient language that has ever been deciphered needed an anchor. Usually that’s a bilingual text, like the Rosetta Stone, or a known relative to compare it to. Linear A, the writing system of the Bronze Age Minoan civilisation on the Greek island of Crete, has neither.

Linear A is described as a “language isolate” because it has no confirmed link to any known language, living or dead. As such, it has posed a significant challenge for linguists over the past century.

Etruscan, a language of Italy that was used before the rise of the Roman Empire, has fared only slightly better. A partial vocabulary has been collected from short funerary inscriptions, but its grammar and deeper meaning still elude linguists.

Both languages are exactly the kind of puzzle that AI has recently been pulled into – not by replacing the linguists, but by supercharging their hunches. So does AI actually stand a chance of finishing what a century of human effort hasn’t?

A recent case shows both the appeal and the catch. In June 2026, a self-taught AI engineer and amateur linguist claimed a breakthrough on Linear A. It started from a single guess that one unknown word in a prayer inscription derived from a Semitic root meaning “to dwell” or “to inhabit”.

He then used AI-built programming scripts to test that sound-pattern against the rest of a collected Linear A corpus. He was reportedly able to assign values to 40 signs and compiled a 408-word lexicon, showing – in his view – that Linear A is an extinct member of the Semitic language group, which encompasses languages such as Hebrew and Aramaic.

The need for creativity

It’s worth being precise about what AI did and didn’t do here. It didn’t have the idea. The engineer did.

The AI was the research assistant. It rapidly cross-checked a human hypothesis against thousands of characters, work that would have taken a human months by hand. That division of labour is the pattern currently worth paying attention to, far more than any single claim that is still under review.

So where does AI actually help, and where does it hit a wall? It’s genuinely strong at large-scale pattern testing. It can check whether a hunch about one sign or word holds up across an entire archive in minutes instead of years. It can spot repeated sequences a human eye would miss, and restore damaged or fragmentary inscriptions by predicting likely missing characters.

AI also does something distinct called “cross-lingual transfer”, where a model trained on a known language can sometimes infer patterns in a closely related unknown one. This is similar to how knowing Spanish helps you guess at Portuguese.

Researchers have already used this kind of approach successfully on scripts such as Ugaritic, where the language family is known. Ugaritic is an extinct Semitic language, spoken during the late Bronze Age (about 1300-1190BC) in the ancient coastal city of Ugarit (in what is now Syria).

But there’s a hard ceiling: statistical pattern matching can’t manufacture meaning out of nothing. It needs an anchor – a known language family, or a bilingual text – to tell it which patterns are meaningful and which are coincidence.

Linear A and Etruscan are hard precisely because that anchor is missing or incomplete, and no amount of computing power invents one from scratch.

Scant evidence

With a large enough corpus, an AI model could hypothetically get fluent enough to converse with a Minoan or Etruscan speaker on the model’s own statistical terms. This means that it could recognise repeating patterns of words and other structural units of a language that would allow the AI model to repurpose the terms in a different context. One that might approximate a limited conversation, at least on the surface.

But the AI system still wouldn’t be able to hand a human a translation, because fluency and meaning aren’t the same thing here. The model can learn which signs follow which, and which words cluster together, without ever knowing what any of them actually refer to.

This is also why verifying any AI-assisted claim about these languages is so difficult, and it’s a problem bigger than any one case. Normally, you’d check a proposed translation or interpretation against native speakers, other texts or expert consensus built up over decades. None of that exists for a genuinely undeciphered language. Short of a time machine, there’s no way to check.

Small surviving corpora make this worse: Linear A’s entire surviving corpus is about 7,500 characters, short enough to fit on a single screen and with that little data, almost any hypothesis can find scattered matches to support it.

That is why claims in this space lean so heavily on independent expert scrutiny and peer-review rather than statistical confidence scores. It is also why “AI found a pattern” and “AI found the correct meaning” are very different claims that are easy to blur together.

None of this means that AI is a dead end for these languages. Quite the opposite: it’s a real accelerant, able to compress years of manual cross-referencing into mere minutes and let more people attempt these problems than institutional resources ever allowed.

But it doesn’t remove the two ingredients that decipherment has always required. One is a genuine comparative anchor. The other is rigorous human review, to tell a real breakthrough from an appealing coincidence.

Until one of those shows up for Linear A or Etruscan, AI’s role in deciphering languages will stay what it is today: a very fast assistant to a very old, very human puzzle.

Jane Adkins receives funding from Údarás na Gaeltachta and the Department of Culture, Communications and Sport through the eSTÓR project at the Science Foundation Ireland funded ADAPT Centre.

To people, salt is a kitchen staple. But to crops, too much of it can be devastating.

Across coastal regions and irrigated agricultural land, salt is accumulating in soils, making it harder for plants to absorb water and reducing harvests. Scientists estimate that around half of the world’s irrigated farmland is now affected by salinity to some degree.

The problem is only expected to grow. Rising sea levels can push saltwater into coastal farmland, while changing rainfall patterns and more frequent droughts are increasing reliance on irrigation. Poor-quality irrigation water and the overuse of fertilisers can worsen the problem, leaving salts behind in the soil year after year.

This is an issue because the global population is expected to approach 10 billion by the middle of the century, while demand for food continues to rise. Finding ways to grow crops in increasingly difficult conditions is becoming one of agriculture’s biggest challenges.

But plants are not passive victims. Beneath the surface, their roots are engaged in a constant battle with their environment. They sense danger, adapt their growth and deploy sophisticated strategies to survive.

Underground intelligence network

Roots do far more than anchor plants in the ground. They are the plant’s frontline, constantly gathering information about the soil around them. Every day, roots assess water availability, nutrient levels and environmental threats. When salt levels begin to rise, they are the first part of the plant to detect the change.

For plants, excess salt creates a double challenge. First, it makes it harder to draw water from the soil, almost as if the plant is trying to drink through a blocked straw. Second, sodium can build up inside tissues, damaging cells and interfering with essential biological processes.

Roots can detect these changes remarkably quickly. As salt concentrations increase, cells in the root begin sending warning signals through the plant. These signals trigger a cascade of responses, including shifts in hormone levels and the activation of emergency survival mechanisms designed to protect growth.

One of the most remarkable things about roots is their flexibility. Unlike the branches above ground, roots can continually reshape themselves in response to changing conditions. Faced with salty soil, they may alter how deeply they grow, how many side branches they produce and even the direction they travel.

In effect, roots can steer themselves away from trouble. Research has shown that plants can bend roots away from highly saline patches of soil while continuing to search for water and nutrients elsewhere. Growth may slow in certain areas, helping the plant avoid pushing vulnerable new tissues into harmful conditions.

This hidden reshaping of the root system can make a difference to the chances of survival. By avoiding the saltiest parts of the soil, plants can reduce the amount of sodium they absorb while continuing to access the resources they need.

At the same time, roots are working to control any salt that does enter the plant. Excess sodium is dangerous because it can damage proteins and cell membranes. To prevent this, root cells actively move sodium into storage compartments where it can do less harm, or pump it back into the surrounding soil.

The result is a carefully managed balancing act that helps protect the more sensitive tissues above ground.

Can plants ‘remember’ stress?

Perhaps the most surprising area of research is the idea that plants may be able to learn from experience. Scientists are increasingly finding evidence that previous exposure to environmental stress can influence how plants respond in the future. In crops such as rice, for example, plants that have encountered salt before can sometimes cope better when exposed to it again.

Rather than involving memory in the human sense, these experiences appear to leave lasting chemical marks on DNA and associated structures within cells. These marks can influence which genes are switched on or off when stress returns, allowing plants to respond more quickly or effectively.

---

Read more: How plants are able to remember stress without a brain

---

Similar effects have been observed in responses to heat and drought stress. It suggests that plants may possess a surprisingly sophisticated ability to prepare for future challenges.

Some studies even suggest that aspects of these stress responses could be passed to the next generation, potentially helping offspring cope better with harsh environments. While many questions remain unanswered, the possibility that plants can retain and pass on information about past stresses is opening up an exciting new area of research.

But what does this mean for future food supplies? As salt levels in soil increase, crops face mounting pressure. Salinity can stunt growth, reduce yields and leave plants less able to cope with other challenges such as drought and extreme heat. In reality, these stresses often arrive together. That’s why understanding roots has become such an important scientific priority.

The better researchers understand how roots detect, avoid and tolerate salt, the better equipped breeders will be to develop crops that can thrive in difficult conditions. By identifying the root traits that help plants survive saline environments, scientists may be able to breed or engineer varieties capable of maintaining yields on land that would otherwise become less productive.

Much of this battle is invisible, unfolding centimetres below our feet. But the decisions that roots make underground could have profound consequences above ground. In a future where climate change is making agriculture increasingly unpredictable, the key to protecting food supplies may lie in understanding how plants wage their quiet war against salt.

Amber Williams receives funding from UKRI.

Seventy years ago, Britain confronted a dilemma. It wanted to remain a leading military power but no longer had the economic resources to sustain all the conventional capabilities it had inherited from the second world war.

The solution proposed in the 1957 Sandys defence white paper was technological. Guided missiles, Duncan Sandys argued, were transforming warfare so fundamentally that many traditional capabilities, including some crewed combat aircraft, would become obsolete.

In other words, by embracing this technological revolution, Britain could achieve defence on the cheap. Britain’s new Defence Investment Plan (DIP) reflects a similar strategic instinct. The technologies may have changed but the underlying dilemma has not.

Announcing the DIP in the House of Commons, Dan Jarvis, the defence secretary, said the UK would be making its “largest ever investment in drone warfare: £5 billion for strike, protector and surveillance drones across the Royal Navy, the Army and the Royal Air Force.”

Here are some of the key technologies discussed in the Dip.

Drone ships

At least a quarter of the £5 billion announced for drone warfare is going towards a “hybrid fleet,” a fundamental re-imagining of the Royal Navy. The UK’s sole ballistic missile defence capability – the Type 45 destroyers – will no longer be replaced by a like-for-like. Instead, a network of Crewed Combat Vessels (CCVs) will act as control hubs for specialised, uncrewed boats.

These would include Type 91 missile barges, Type 92 and Type 93 anti-submarine and underwater surveillance platforms, and Type 94 radar vessels. In principle, distributing the sense, decide and strike functions across the navy offers several advantages.

It could ease chronic personnel shortages by reducing crew requirements, extend radar and sonar coverage over a wider area, and make the fleet more resilient by dispersing combat power rather than concentrating it in a handful of expensive warships.

Uncrewed vessels could also be rearmed or maintained independently and without the design constraints of supporting sailors at sea. However, the challenges are significant.

The DIP envisages this concept becoming proven and operational before the Type 45 retires in the mid-2030s, despite the fact that resilient communications and electronic warfare protection for autonomous warships remain immature.

Nor is Ukraine’s use of naval drones a straightforward template. The Royal Navy’s principal tasks – particularly anti-submarine warfare in the High North and North Atlantic – are far more demanding than Ukraine’s use of maritime drones in the Black Sea.

While experiments such as using RFA Lyme Bay as a mothership for autonomous mine countermeasures (including drone minesweepers) are encouraging, retiring Britain’s only ballistic missile defence destroyers before the wider architecture has been proven would entail significant operational risk.

AI targeting network

The army’s Project Asgard illustrates the same technological philosophy in a different domain. Asgard aims to transform how – and how quickly – the army identifies and strikes targets, by linking sensors, armoured vehicles, drones and long-range weapons into a single, AI-enabled targeting network.

First trialled in 2025, Asgard is now receiving £370 million to develop an operational capability, reflecting the Army’s ambition to achieve a tenfold increase in combat power primarily through automation rather than expanded forces.

This idea has an important intellectual history. During the 1990s, the United States championed the concept of network-centric warfare: the proposition that superior information sharing would enable smaller, more agile forces to defeat numerically superior opponents. But Britain was soon concerned about the affordability and technological challenge of creating such highly connected forces, adopting in its place a lighter version: network-enabled capabilities.

The DIP suggests that the government now believes the technology is catching up with the theory. But old weaknesses remain. Networks only work if they survive. Communications can be jammed, satellites disrupted and software attacked, and Russia has the electronic warfare capabilities that could, without adequate safeguards, do all three.

‘Loyal wingmen’

It is also the case that what has worked at smaller levels now needs to be scaled across Nato. If it works, Project Asgard would provide Nato land forces with the ability to control long-range weapons of their own, reducing their reliance on air forces which will need to focus on supressing and destroying enemy air defences.

That task is motivating the DIP’s investment in Collaborative Combat Aircraft (CCAs) – uncrewed platforms that will fly alongside the RAF’s Typhoons and F-35s.

These “loyal wingmen” drones would support crewed aircraft by acting as scouts, decoys, absorbing enemy fire or jamming enemy radars. They could be controlled by the pilot of the combat jet, or work autonomously.

Systems such as the MQ-28 Ghost Bat are at an early stage of development. To be militarily useful CCAs must combine long range, high speed, low observability, resilient data links and meaningful payloads, requirements that quickly approach the complexity, and potentially the cost, of the crewed aircraft they are intended to complement.

Will it be cheaper?

Against these challenges, the government’s headline commitment of £5 billion on these systems therefore seems more like a down payment than the full mortgage. Spread across four years, three armed services and an exceptionally diverse range of programmes, it is less transformative than some may believe, and certainly not on the timelines some think are necessary as tensions continue with Russia.

The unit costs of what will be specialist equipment may remain prohibitively expensive. Take the hybrid Navy as an example. The autonomous systems in question require resilient communications, sophisticated sensors, electronic warfare protection and high engineering reliability, meaning the combined cost of CCVs and their uncrewed flotillas could approach that of the destroyers they replace.

Even if the funding can be found – and there are good reasons to question whether it can – Britain must still demonstrate that its defence industry can deliver this technology-intensive force. Expanding military output requires far more than larger budgets: it demands additional factory capacity, skilled workers, shipbuilding infrastructure and resilient supply chains. This is particularly true for autonomous systems whose military value depends on being produced, sustained and replaced at scale.

The DIP rests on three assumptions: that autonomous systems mature quickly, prove affordable and can be produced at scale. The Sandys Review rightly foresaw the missile age but underestimated the staying power of conventional forces; new technologies reshape warfare but they rarely replace its enduring fundamentals.

If Britain is to bet on autonomy, therefore, it also needs the spending profile to make that bet credible. After all, the most important judgement on the DIP will not be that of future historians, but of the occupant of the Kremlin today.

Arun Dawson is affiliated with the Royal United Services Institute.

Thousands of volunteers across England now regularly take out their own testing kits to study the levels of pollution in rivers and the sea.

With sewage spills rarely out of the news, citizen water testing has become one of the most visible responses to England’s pollution scandals.

A crisis of trust in the water companies appears to be driving the public to take water quality testing into their own hands. Thousands of people take part in the twice yearly water testing events, organised by charity Earthwatch. Spring 2025 saw the highest number of participants at more than 7,000. Other organisations also report rising numbers of people getting involved in water testing.

These people, often referred to as citizen scientists, are doing tasks as varied as surveying aquatic insects to sampling water for chemicals.

Much public attention has centred on sewage pollution in UK rivers in the past few years. Waste is regularly and legally discharged into lakes, rivers and along beaches by water companies during periods of heavy rainfall. But incidents of sewage discharges on days with no to low rainfall have also been identified, and in some cases legal action has followed. In some cases water companies have been fined millions of pounds.

The Environment Agency (EA), the main environmental regulator for the water industry, reported nearly 300,000 sewage spills across England in 2025 alone.

The consequences have affected both wildlife and people. Campaign group Surfers Against Sewage documented more than 7,000 cases of illness linked to swimming at official bathing sites over just five years. In 2025, 12 of England’s 14 inland bathing sites were rated “poor”, meaning swimmers were recommended to avoid the water because of potentially harmful bacteria. In April, the UK’s largest pollution claim began to be heard in the High Court, over allegations of chicken waste pouring into rivers along the Welsh-English border.

Public campaigning is believed to have helped trigger recent government action, with reforms expected in a planned Water Reform Bill.

Citizen sceptics

Some water companies now fund freshwater citizen science initiatives. These run across locations including the Thames Valley, south-east England and Wales. The programmes claim to enhance community awareness, empowerment and improve transparency of water companies’ management efforts.

During my PhD, I researched how one group of volunteers in Oxfordshire collected and interpreted river data. Some told me that they felt that water companies encouraged participation in citizen science, while ignoring the data.

---

Read more: Five warning signs that rivers are polluted – even when they look clean

---

As one citizen scientist explained in my own ongoing preliminary research, “people keep beavering away, and eager beavers are just what the water industry wants”. In his view, citizen science risks becoming a tool for keeping volunteers busy and distracted, rather than driving accountability.

However, recent research shows water companies have historically underreported the number of sewage spills. The Consumer Council for Water, which represents customers, has reported widespread dissatisfaction with water companies. An independent water commission has also highlighted a deterioration of public confidence in the environmental regulators.

A recent Channel 4 docudrama, Dirty Business, echoes these frustrations. It follows two citizens trying to hold water companies and regulators to account.

In line with some recent academic research, the programme explores suggestions that the water industry attempts to deflect blame and distract attention from sewage pollution. In a statement addressing the allegations, the EA said: “Prosecutions are just one tool against water pollution, and we have also levied a record £8.5 million in enforcement undertakings against water companies in the last year alone.”

Public confidence

The Environment Agency also faces questions about public confidence. Research suggests that volunteers believe current regulations allow water companies to act without sufficient oversight. In this study, people felt that the EA was not fulfilling its responsibility to hold the water industry to account.

In 2024, the head of the EA, Philip Duffy, said that the organisation had buried freedom of information requests, with staff worried about revealing the embarrassing truth of water pollution. In a statement reported in the Guardian at the time, the EA said: “Philip is completely committed to the highest standards of transparency.” It added that he wanted to make more EA data readily available.

In January 2026, the Office for Environmental Protection, a public watchdog on environmental protection, also found possible failures by the EA to comply with water quality laws.

My participants felt that the agency shouldn’t ignore their data in monitoring water quality.

Concerns about data bias and reliability are often cited as reasons to limit the use of volunteer data to support regulatory responses to pollution incidents.

These concerns are not unreasonable. Citizen science data can indeed vary in quality, depending on training and sampling practices. Ensuring consistency across the sheer number of volunteer groups is also a challenge.

Using citizen science

Nevertheless, research now suggests volunteers can produce reliable data suitable for official monitoring. The debate is gradually shifting to how regulators can include it in decision-making. For example, a national programme has already developed a shared framework on how to use data collected by citizens.

In the meantime, groups such as environmental charity Earthwatch and Surfers Against Sewage design and publish their own online maps and dashboards. These make thousands of historic data points publicly available.

As summer arrives and 13 new bathing sites open, pressure is again mounting on water companies and regulators to clean up England’s rivers and beaches. The citizen water sample collectors will be on standby.

Hope Steadman receives funding from the Economic and Social Research Council's Grand Union Doctoral Training Partnership; grant number ES/P000649/1.

The effective collapse of the Future Combat Air System (FCAS) fighter jet programme is a major setback for European defence cooperation.

France, Germany and Spain have spent nearly a decade trying to develop what was intended to become Europe’s premier next-generation combat aircraft, only for the programme to succumb to disputes over leadership, the distribution of work and intellectual property.

Yet Europeans shouldn’t be surprised. The history of European combat aviation is littered with programmes that struggled under the weight of competing national ambitions. In this respect, FCAS looks less like an extraordinary failure than the latest chapter in a recurring story.

The more important question is not why FCAS has run into trouble, but rather what its collapse reveals about Europe’s ability to generate and sustain the military capabilities it will need in a more dangerous world.

Adversaries are now investing heavily in integrated and layered air defences encompassing long-range missiles, electronic warfare capabilities and increasingly sophisticated sensors. Maintaining the ability to penetrate defended airspace in future conflicts will require a step change in capability.

FCAS was conceived as a “sixth-generation” combat system – the latest leap in fighter jet technology – to overcome this contested air environment. At its centre would sit a new combat aircraft, supported by autonomous drones, advanced sensors, electronic warfare systems and a digital network linking everything together from the 2040s.

The challenge is that such programmes are becoming extraordinarily expensive to develop. By sharing costs, expertise and industrial capacity, European governments hope to achieve capabilities that would otherwise be beyond their reach.

Reality check

Despite the perceived commonalities, the FCAS nations – France and Germany in particular – had very different objectives.

For France, the project was never simply about replacing its Rafale fighter jet. Any successor aircraft would eventually have to support the airborne component of France’s nuclear deterrent, operate from its aircraft carrier, and preserve sovereign industrial capabilities – specifically the ability to independently design and build advanced combat aircraft. The insistence by France on design leadership for FCAS therefore reflected concerns about national autonomy, even if portrayed as industrial obstinacy.

Meanwhile Germany, represented by the aerospace giant Airbus, had little interest in financing a programme that was likely to concentrate Europe’s most valuable expertise, intellectual property and design authority in Dassault, the French aerospace company, for decades to come.

These tensions are hardly new. In the 1960s, Britain and France attempted to build the Anglo-French Variable Geometry aircraft. But France’s withdrawal in 1967, for similar reasons to FCAS, led to the project’s collapse.

Other joint European projects have succeeded. For instance, the Panavia Tornado. And in the 1980s, the Eurofighter consortium was developed. This time, despite France withdrawing (to produce the Rafale), the UK, Germany and Italy proceeded (with Spain later joining) with what would become the Eurofighter Typhoon.

Reliance on America

For decades, therefore, European collaborative programmes have been expected to do several things at once: deliver military capability and sustain national industries while strengthening diplomatic relationships or at least not upsetting them.

That may have been a manageable compromise when Europe’s security was underwritten by the United States and the threat from Russian appeared contained. It is far harder to justify when European governments are warning that the continent must rearm.

The challenge is compounded by the changing relationship between governments and industry. Unlike Airbus, which remains partly state-owned, Dassault is controlled by the family that bears its name.

This reflects a broader trend of European governments often exercising less influence over major defence firms than they did during the cold war, when state ownership and greater industrial competition gave them more leverage. This is to say nothing of the tech firms increasingly fundamental to military capability.

That matters because armed forces are built over decades, not electoral cycles. If European governments struggle to mobilise industry to meet their defence requirements, they may find themselves confronting capability gaps at precisely the moment they are trying to deter aggression.

Germany’s defence minister, Boris Pistorious, has already outlined three alternatives to FCAS. The first and simplest is to buy more F-35s from the US. But this would fall short of Germany’s requirements while also deepening dependence on the US – something European nations are keen to avoid.

The second option is to join another collaboration, most likely the UK-Italian-Japanese effort to build a sixth-generation fighter, called the Global Combat Air Programme (GCAP). Germany’s growing defence budget could provide the project with additional funding and a larger order book. But it would also raise questions about influence.

If Berlin rejected a subordinate role within FCAS, it is unlikely to accept one within GCAP. Existing partners may therefore conclude that the benefits of expansion are outweighed by the risks of delay to a programme targeting entry into service by 2035.

The third option is a German-led effort, being discussed through the proposed Team Gen 6 industrial grouping – an Airbus-led alliance of eight defence firms. This would solve industry concerns, preserve German design ambitions and might allow Berlin to build a coalition with other partners, such as Spain and Sweden.

But it could be prohibitively expensive, risky, and by further fragmenting Europe’s already crowded combat aircraft landscape, reduce the viability of all the existing programmes. France faces similarly difficult choices. It can pursue a national successor to Rafale, preserving control over industrial, nuclear and carrier requirements but accepting substantial costs. Or it could seek a revised collaborative framework.

In the meantime, both French president Emmanuel Macron and Germany’s chancellor Friedrich Merz have made clear that other opportunities for collaboration exist, such as the drones intended to support the FCAS fighter jet, or the main aircraft’s engine.

The experience of FCAS is not that Europe cannot cooperate. History shows otherwise, and GCAP may yet again demonstrate that a pragmatic coalition can succeed where a more politically ambitious partnership failed.

What FCAS does reveal, however, is a growing mismatch between Europe’s security environment, the way it continues to procure defence equipment and the costs involved. The recent resignation of Britain’s defence secretary, John Healey, amid disputes over defence funding, points to the same problem.

European governments increasingly agree on the threats they face, but remain “unwilling” to make the financial and political compromises required to address them. That should concern us all.

Arun Dawson does not work for, consult, own shares in or receive funding from any company or organisation that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.