“It is the law of human life and of human nature that a new generation is ever coming forth,” said the Roman statesman Cicero (106–43 BCE).

His view was echoed by the poet Simonides of Ceos (6th to 5th century BCE): “As is the generation of leaves, so is that of men.”

The metaphor was a simple one. One day we are full of life, green and fresh, but soon we start to wither and die. Fresh leaves take our place, but they too will fall, only to be replaced by new leaves in their turn.

In the ancient world, there were many different views about the relationship between younger and older generations. Greek and Roman texts reveal that, just like today, generational conflict was rife.

At the same time, however, ancient texts also suggest ways the young and old can profitably get along – a message that is perhaps needed for our times.

Causes of generational conflict

In ancient times, there were many causes of generational conflict. One was that the old sensed things were changing in ways contrary to their hopes and wishes.

The Roman comic playwright Caecilius (219–168 BCE) described the feelings of an old man watching and reflecting on the new generations coming up. In a play (whose title is unknown), the old man is exasperated and frustrated, and decides to complain:

Old Age, if you bring no other defects with you, when you come, this one’s enough: by living long a man sees much he doesn’t want to.

Another source of conflict was that the young felt society had been ruined by the previous generation. For this reason, the young had little hope of making a way within that society for themselves. The Roman poet Horace (65–8 BCE), for example, criticised his parents’ generation with these harsh words:

Our fathers’ age, worse than our grandfathers’, gave birth to us, an inferior breed, who will in due course produce still more degenerate offspring.

Different character types?

The most extensive ancient attempt to explain the causes of generational conflict is supplied by Aristotle (384–322 BCE). According to Aristotle, conflicts between young and old can partly be attributed to the different characters people have when they are young and old.

The young, Aristotle tells us, are lustful, changeable in their desires, passionate, hot-tempered, impulsive, ambitious, simple-natured, hot-blooded and inexperienced. “All their errors are due to excess and vehemence,” he argued:

they think they know everything, and confidently affirm it, and this is the cause of their excess in everything. If they do wrong it is due to insolence not wickedness.

The young, said Aristotle, are “fond of laughter, and therefore witty; for wit is cultured insolence”.

The old, on the other hand, are positive about nothing. They are, according to Aristotle, lacking in energy, hesitant about everything, maliciously negative-minded, selfish and excessively suspicious. “They are not generous,” he claimed, “for property is one of these necessaries, and at the same time, they know from experience how hard it is to get and how easy to lose”.

Moreover, they are “cowardly and inclined to anticipate evil”. Old people

live in memory rather than in hope; for the life that remains to them is short, but what is past is long, and hope belongs to the future, memory to the past […] they are incessantly talking of the past, because they take pleasure in recollection.

Aristotle thinks this conflict of character is at least partially responsible for some generational conflict within society. But balance is afforded by the middle-aged, whose characters “preserve the due mean” between the young and the old. To be middle-aged is to combine “all the advantages that youth and old age possess separately”; excesses and defects are replaced with “due moderation and fitness”.

What do the young owe the old?

In ancient Greek and Roman society, the traditional expectation was reverence toward one’s parents and elders. As early as the 6th century BCE in Greece, care for elder relatives was enshrined in law. Mistreatment of parents, which included failure to feed and house one’s mother and father, had strict penalties and often resulted in jail time.

Among the Romans, fathers had complete legal control over their sons and daughters, through the power of patria potestas. This included the right to inflict capital punishment on children. This power only ceased on the father’s death or when a daughter was married.

A prominent source of generational conflict was the feeling, among older generations, that young people no longer showed older people any respect. This point is brought up by the Greek comic playwright Aristophanes (450–380 BCE). In his play Clouds, one of the characters gives a list of things young people do that irritate older people, including failing to offer their seats to elders and behaving rudely towards their parents.

What do the old owe the young?

For the ancient Greeks and Romans, one of the expectations people had about older members of the population, who controlled the majority of the wealth and had the most political influence, is that they would maintain social stability by making sensible political decisions and enacting sensible laws.

Generational conflict increased in times when older generations failed to manage political affairs well. During the turmoil of the Peloponnesian War (431–404 BCE) between Athens and Sparta, which ended in Athens’ disastrous defeat, the younger generations of Athenians became increasingly disobedient towards the older generations. This was largely because of a sense that political affairs had been mismanaged.

The Greek philosopher Thrasymachus of Chalcedon (late 5th century BCE), gave an oration in which he criticised older generations for their failures of governance, implying this was the main reason why young people were starting to dissent. At a time when “we must obey others as rulers but must suffer the consequences ourselves”, he argued, it becomes necessary for the young to speak up.

Mitigating generational conflict is not an easy thing to do, but the Greeks and Romans did have a suggestion about how to achieve some kind of generational harmony. Their advice was to focus on reason and rational debate.

People should use reason to determine collectively what is good and best for all, and people of all generations should be encouraged to put reason and the common good above their personal interests.

As the Greek orator Isocrates (436–338 BCE) said in his oration Archidamus, older people do not always know what is best and younger people are not always wrong.

Thus decisions needed to be based on shared deliberation and the use of reason, as “it is not by the number of our years that we differ in wisdom from one another, but by our natural endowments and by our cultivation of them”.

Idealistic words, but ones worth remembering in our own time of fractured generational relations. After all, the young will eventually become the old, at which point they too will complain that the world is going downhill, that nobody listens anymore, and that the next generation has forgotten the basic rules of civilisation – such as giving up one’s seat, not talking back, and not spending so much time on whatever alarming new technology replaces TikTok.

Clearly, the ancient evidence does not offer a simple solution to generational conflict.

Konstantine Panegyres, Lecturer in Classics and Ancient History, The University of Western Australia

This article is republished from The Conversation under a Creative Commons license. Read the original article.

When basketball was invented by medical doctor James Naismith in 1891 – to keep American football players active during winter – all baskets were worth two points, regardless of where they were shot from.

Games were dominated by tall players who usually shot from close to the basket.

It was often very crowded near the basket and there were fewer opportunities for smaller players.

This all changed when the 3-point line was introduced.

History of the 3-point line

The 3-point line was temporarily trialled in a few college games and minor professional leagues from the 1940s to the early 1960s, but was seen as more of a gimmick.

It gained more popularity after it was introduced in the American Basketball Association (ABA) (a competitor league to the NBA) during the 1967–68 season.

Sports can change dramatically in the blink of an eye. Sometimes, these moments create immediate shockwaves. Other times, it’s not until much later that their impact become obvious. This is part of a rolling series that explores key (and sometimes long forgotten) moments in sports history.

The ABA wanted to make basketball more interesting and exciting. It viewed the 3-pointer as the equivalent to a home run in baseball and believed it would “give smaller player a chance to score and open up the defence to make the game more enjoyable to fans”.

The ABA merged with the NBA in 1976 but the NBA did not immediately introduce the 3-pointer because many traditional coaches and players were against it.

It was finally introduced for the 1979–80 season, with Chris Ford from the Boston Celtics shooting the first one.

The International Basketball Association (1984) and other national leagues followed this move during the next decade.

It changed basketball, slowly

The 3-point line did not make a big difference straight away.

Players still preferred to shoot from closer to the basket because there was a higher chance of success. Teams did not practise 3-pointers and generally only used them when trying to win a game in the final few seconds.

The San Diego Clippers scored the most 3-pointers for the 1979–80 season, with 177 (2.2 per game). Brian Taylor from the Clippers had the most individual 3-pointers (90).

Times have changed.

During the 2024–25 season the Celtics scored the most 3-pointers: 1,475 (17.8 per game) and every team in the NBA scored more than 900. Some 139 players made 100 or more.

How 3-pointers became more popular

A few key events contributed to 3-pointers becoming more popular.

The inclusion of a 3-point contest at the NBA All-Star weekend in 1986 made the shot more respected. It helped that the first three were won by popular Celtics All-Star Larry Bird.

From 1994 to 1997 the NBA moved the 3-point line closer to the basket (from 7.24 metres to 6.71m) to encourage more scoring in games.

While it did not improve the trend of lower scores and the line was moved back, teams did start to shoot more threes.

The Steph Curry phenomenon

In the 2010s, the rise of the Golden State Warriors sparked a 3-point revolution.

Led by two-time MVP Steph Curry, the Warriors’ heavy reliance on the 3-pointer helped them make the NBA Finals five years in a row, winning three championships.

Curry, who is more than 10cm shorter than the average NBA player, is credited with changing the game by regularly shooting “deep threes” from way behind the 3-point line. This allowed him more time to shoot over taller players.

It also changed how other teams defend because they have to cover more space to defend him. Consequentially, his teammates enjoy increased scoring opportunities.

Curry is the most successful 3-point shooter in NBA history. Kids now want to “be like Steph”.

WNBA All-Star Caitlin Clark has also been influential increasing the popularity of 3-pointers.

The role of analytics

Statistics-focused executives such as Daryl Morey also played a key role in the increasing popularity of 3-pointers.

They realised teams could score more points by shooting 3-pointers, even if they shot a slightly lower percentage.

For example, if a team takes ten 3-point shots and make 40% (four) of them, they will score 12 points (4x3 = 12). This is more than they will score if they take ten 2-point shots and make 50% (five) of them (5x2 = 10).

Under Morey’s leadership, the Houston Rockets became the first NBA team to attempt more 3-pointers than 2-pointers in a season. They did this from 2017 to 2020, when they won three consecutive division titles.

A statistical analysis across ten seasons from 2009–10 to 2018–19 also showed teams that took more 3-point shots had a higher probability of winning.

This rise in 3-pointers has come almost exclusively at the expense of mid-range shots.

Mid-range shots are shot from outside the paint but inside the 3-point line (roughly 3–7m from the basket).

The percentage of total shots from mid-range has plummeted from 31% in 2010–11 to just 13% a decade later, while shots in the paint (close to the basket) have remained relatively steady.

The 3-point line has improved the game by adding variety in offence, spreading players out and allowing players of different sizes and skills to be successful.

However, fans, players and commentators are starting to wonder whether there are now too many 3-pointers being shot.

Too much of a good thing?

The increased emphasis on 3-pointers in the NBA has coincided with a decline in viewership. Although these may not be related, it has sparked concerns.

NBA Commissioner Adam Silver noted that while game attendance remained strong and fans enjoy the skill on display, he acknowledged some teams’ attacking plays can appear “cookie cutter” as teams mimic each other’s 3-point-heavy tactics.

NBA legend Shaquille O’Neal also stated the 3-point craze made games feel predictable, where “every team is running the same plays”.

Time for a change?

Suggestions from former players, coaches, commentators and spectators include moving the line further back, reducing the space available for shooting 3-pointers from the corner of the court, increasing overall court dimensions, adding a 4-point line or even capping teams’ 3-pointer attempts.

Silver says the league is open to exploring tweaks if they improve the balance between inside and outside play.

There are no plans to change yet, as any rule change will trigger flow-on effects for offence and defence that may not improve the game.

Vaughan Cruickshank, Senior Lecturer in Health and Physical Education, University of Tasmania and Tom Hartley, Lecturer in Health and Physical Education, University of Tasmania

This article is republished from The Conversation under a Creative Commons license. Read the original article.

In the last few years, the hype around artificial intelligence has become stratospheric. Riding a wave of venture capital, tech leaders promised us AI would revolutionise work, boost productivity and lead to incredible new breakthroughs. OpenAI, the creator of ChatGPT, set a new record when it attained US$110 billion in investments several months ago – and its CEO, Sam Altman, recently claimed Australia could become a “data capital of the world.”

Sky-high promises have been accompanied by sky-high investment in data centres, the sprawling server farms that power the training, execution, and maintenance of these models. A monstrous new hyperscale facility proposed for Sydney’s west – 1 gigawatt across 52 hectares – would rank among the world’s biggest. It will join 162 existing centres and 90 in the works across Australia, which is projected to be the world’s third largest data centre market by the early 2030s.

But if AI backers are all in, public sentiment is far more mixed. A new study ranked Australia equal lowest on the scale of global AI sentiment, with 81% supporting stronger rules for how organisations use AI and 68% worried about losing control over decisions made by AI on their behalf.

Grassroots movements against AI are growing. Last month, a “Stop the Slop” event challenging the Sydney data centre was relocated to a larger venue due to high interest. It joins other campaigns like StopAI and PauseAI that aim to slow down data centre development, ask how AI is impacting jobs and the environment, and consider more equitable and sustainable alternatives.

And in the last few months, videos have begun surfacing of students at commencement ceremonies booing speakers like former Google chief executive Eric Schmidt, who speak in rapturous tones about “standing on the edge of technological transformation” and how AI will touch “every profession”, “every classroom”, and “every relationship”.

Faith in these monumental claims – and the monumentally expensive infrastructure they rely on – is slipping.

What is the AI business model?

AI’s financial costs are astronomical. As tech critic Ed Zitron has shown over and over again, the major players are burning billions to keep models running, while lucrative profits remain tantalisingly out of reach. Some enterprises now spend more on rapidly rising token costs, the per-use cost of a model, than human workers. Even by cynical economic standards, the numbers don’t add up.

What exactly is the AI business model? Where is the killer app that will deliver genuine value and see millions of individuals or thousands of corporates pay costly subscription fees? “We have no idea how we may one day generate revenue,” admitted OpenAI CEO Sam Altman in 2019, “once we build a generally intelligent system, we can ask it to figure out a way to generate an investment return.” While the landscape has certainly shifted since then, use cases and revenue remain murky.

Hard evidence of AI’s contribution – rather than the vacuous claims of pitch decks and industry keynotes – remains largely elusive.

A recent survey of 6,000 senior business executives across the United States, United Kingdom, Germany and Australia found positive perceptions but a disappointing reality: around 90% of firms said AI has had no impact on employment or productivity over the past three years. Another study, from MIT last year, found that 95% of generative AI pilots failed to deliver tangible financial value to the organisation, so were abandoned.

If the upsides are unclear, the negatives are increasingly apparent. Politically, generative AI provides the perfect weapon to “flood the zone” with misleading or outright false content, muddying the informational waters and amplifying division. Is Netanyahu alive or dead? AI fakes make it harder and harder to tell.

Socially, AI companions and models, gaining enormous trust with users via long-term conversations, have been cited in a growing series of court cases around suicides and mass shootings. A lawsuit filed this year described ChatGPT as an intimate and persuasive “suicide coach” who convinced a man in Colorado to end his own life.

And environmentally, the turn to the far higher computation that AI requires means massive impacts as data centres demand more power and more water, creating hundreds of millions of tonnes of CO² emissions. If the 41 planned data centres in Sydney are built, they will directly use 15–20% of Sydney’s water supply within a decade, predicts environmental accounting associate professor Michael Vardon.

Even if its social, environmental and political fallout is dismissed, AI hype and investment misses what is happening on the technical level. Models in the last decade became “smarter” essentially by training on larger and larger data sets. But this paradigm yields diminishing returns.

Yann LeCun, former chief AI scientist at Meta, has warned that the correlation-based “learning” of models is both inefficient and insufficient when compared to human learning. Models require trillions of tokens to train. Even then, they reproduce patterns without deeper understanding, while children learn in a generalised manner from a handful of examples.

“Training is waning” is the new mantra, notes one Silicon Valley insider, as the brute force approach to foundational models gets left behind. It’s far from clear whether massive models, and the massive data centres that underpin them, will even be needed.

Where does this leave us? The possibility of the AI bubble bursting has shifted from a niche pocket of tech critics to mainstream policy wonks. “It’s time to start asking not whether there will be an AI crash, but what we should do today so that we are best prepared to respond to one tomorrow,” wrote two commentators in TIME magazine earlier this year.

What will this look like? Any answer here would include speculation. And yet we can garner some insights from previous bubble bursts, from tech development trends, and by extrapolating from the socio-cultural fallout we’ve already witnessed. Let’s step through each.

Another dot-com bubble

First, we can compare the AI bubble with the dot-com bubble of the late 1990s. Indeed, investment leaders – including The Big Short’s Michael Burry, who famously anticipated the collapse of the subprime mortgage market – are already seeing disturbing parallels between the two. Burry warns that venture capitalists are funding “loss-mak[ing] companies like never before in history”. As this suggests, the investments in this current AI bubble dwarf its dot-com analogue. If this bubble follows the blueprint of the last, we should expect to see massive layoffs in personnel and liquidations of AI startups with no discernible revenue.

Of course, like the first bubble, the deletion of a company doesn’t mean the technologies themselves disappear. Indeed, in the orthodox economic canon, the dot-com bubble was a “baptism of fire”: a painful but necessary rebirth. The trivial players, buoyed by “irrational” valuations, disappeared, but the network infrastructure they helped expand was the foundation for the truly innovative tech products to come.

Part of this “soft pop” future is almost certainly correct: the infrastructure will persist, even if underused. AI will continue being baked into a multitude of products, testing the market. And tech titans, sitting on data hoards and advertising monopolies, will march on. As scrutiny is increased, belt-tightening will occur. Companies will distil their product offerings, quietly begin limiting token use, and raise their subscription prices – all moves we’re already seeing play out.

But the larger question is whether tech companies – now just as then – actually contribute in meaningful ways to our broader world, or even merely our economies. As one Nobel-prize-winning economist famously quipped in the 1980s: “you can see the computer age everywhere except in the productivity statistics.”

More recent analyses of contemporary technologies have echoed this finding, suggesting the internet has little impact on economic growth. If this is the case for AI – as the numbers, the lack of products and even the rhetoric of its chief pundits suggests – then we have a social question, not just a financial one. What price are we paying for a technology that fails to deliver even on its own terms?

Small is beautiful

Second, tech development is moving away from the “bigger is better” mantra. Models are becoming much smaller and more efficient. The push is from the cloud to the so-called “edge”: the far more mobile and low-powered devices, like your phone, where data is actually created and used. And there’s a push to move the focus from “capture it all” quantity to quality, with targeted or carefully curated data.

Some of this is a welcome — and long-needed — shift. A deluge of critical AI research in the last few years has extensively documented the major issues with bias in foundational models. In a not-so-shocking twist, indiscriminate training on a massive archive of social material with almost no oversight creates models that reproduce significant harms.

To take just two well known examples: AI models discriminate based on race and gender, while AI-generated images consistently privilege white people over people of colour.

Given these issues, the slower and more careful construction of models actually tailored to their communities and attuned to their language, needs, and desires can only be beneficial.

Some languages, for example Indigenous languages with strong oral traditions, are considered “low-resource”, or underrepresented, with much less material in standard training sets. Switch away from English, and see the accuracy of your response plummet.

Future developers might work closely with communities to create their own archive of material that better reflects their ideas and beliefs. Here we start to see a meaningful idea of data sovereignty, where groups maintain control over their models and the data that underpins them, slowly disconnecting from corporate cloud regimes.

Of course, if the “small and mobile is beautiful” approach attains real traction, this will mean today’s massive investment in highly centralised data centres is the wrong move.

What will happen to this massively overbuilt – and, we anticipate – soon underused infrastructure? In an ironic twist, dead shopping malls have been converted into data centres in the last two years to satisfy demand – yet these data centres might themselves become empty shells, physical reminders of an obsolete vision.

Post-AI pathologies

Third, AI cannot be stuffed back into Pandora’s box. Even if AI development takes another path, the socio-cultural, political and environmental fallout of a post-AI world will continue – or even become exacerbated.

In education, researchers warn that students who constantly turn to generative AI models exhibit a kind of “doom loop” of dependence: offloaded thinking gradually causes atrophy in critical thinking and reasoning. “When kids use generative AI that tells them what the answer is […] they are not thinking for themselves,” state the authors of a Brookings Institution study.

They’re not learning to parse truth from fiction. They’re not learning to understand what makes a good argument. They’re not learning about different perspectives in the world because they’re actually not engaging in the material.

In politics, cutting-edge image and video models make it increasingly difficult to parse fact from fiction. Gravity glitches and six-fingered hands are gone; new generative models like Nano Banana boast physically-aware rendering. Models can now produce photo-realistic news reports, for instance, that seem to show Ukraine president Zelensky surrendering.

The result is a growing pervasiveness of the “liar’s dividend”, where muddied lines mean even genuine material is doubted or dismissed as being synthetic. The ability of evidence to document atrocity and persuade the public is undermined, with each side accusing the other of fabricating media.

In the environmental sphere, the AI-driven boom in data centre construction will have long-term impacts. While society has begun to lower carbon emissions via electrification and renewables, AI’s voracious demands threaten to reverse this progress. Sustainable generative AI is a fallacy. “AI datacenters are single-handedly leading to a major reversal in climate progress globally,” declared tech critic Karen Hao, citing a recent UN report.

From the extraction of rare-earth minerals to the burning of dirty diesel as backup, the strain on local power grids, and the siphoning of millions of gallons of freshwater in a warming world — the damaging effects of AI supply chain capitalism – will be felt by the ecosystems and generations to come.

Rage against the machine

“I’m here to tell you the mission of your generation is to destroy AI,” Daily Show comedian Ronny Chieng told Harvard graduates recently, to approving cheers — a far cry from the boos and anger that met AI evangelists advocates at similar ceremonies.

One strand of rising anti-AI sentiment is directed at data centres. A report found that US$64 billion of data projects have now been blocked or delayed amid local opposition. In one sense, of course, these wins are localised and limited: the “cloud” means data centres elsewhere can still run AI. But to see them as distractions from the bigger anti-tech battle is to miss the point. As tech critic Astra Taylor and community organiser Saul Levin argue,

This brewing populist resistance isn’t just about limiting local development – it represents a critical new front in the fight against tech-enabled authoritarianism. Where else can people push back on job-eating algorithms, distorting deep fakes, and autonomous drone strikes?

These protests and campaigns signal a gulf between the current AI vision — “tokenmaxxing” in an “AI everywhere” world — and the desires of everyday individuals. Of course, this disparity alone doesn’t signal the death of the AI boom dream: history is full of examples of elites rolling out exploitative technologies that run roughshod over the wishes of the people.

But combined with other economic, social and environmental factors, these pushbacks begin to destabilise Big Tech’s future-on-rails. There are other possibilities — slower, smaller, more convivial, more sustainable — for technologies that contribute to our lives, our society and our world.

Luke Munn, Research Fellow, Digital Cultures & Societies, The University of Queensland

This article is republished from The Conversation under a Creative Commons license. Read the original article.

For centuries, people have dreamed of undoing Babel.

Sci-fi novelists envisioned universal translators, and linguists devised international languages, all in pursuit of a world where one person could speak and another could understand, regardless of where either was born.

Artificial intelligence appears to be taking humanity one step closer toward that goal.

AI-powered tools are already being widely used by lawyers to translate legal documents from one language to the next. The mass market romance publisher Harlequin has turned to AI to translate its novels for international audiences. And hospitals are deploying AI translation to communicate directly with patients in multiple languages.

The speed and skill with which these AI-powered translation tools operate are certainly impressive.

But there is an important frontier for translation technology, one that it might never be able to breach: the poem.

That’s because translating poetry, thus far, has been a uniquely human experience. It demands intimate knowledge of two languages, which large language models certainly possess. But it also requires a mastery of different cultures and perspectives, what literary critic Gayatri Chakravorty Spivak calls a “worlding” of language and culture.

Pushing the limits of language

When scholars have studied the creativity of chatbots by prompting them to produce poetry, they’ve noticed that the poems tend to be more homogeneous and standardized than those written by humans.

Chatbots’ poetry translations have similar issues.

AI seems to struggle in three main areas: rendering metaphor, decoding complex sentence structure and creatively conveying mood or emotion.

To demonstrate these flaws, I worked closely with Adeeba Shahid Talukder, an award-winning poet and translator, to write this piece and to translate the 1953 poem “Mulāqāt,” or “Meeting,” composed by one of the most famous Urdu poets of the 20th century, Faiz Ahmed Faiz.

Faiz was born in 1911 in Sialkot, in pre-Partition India. In 1947, when that area in the Punjab became part of present-day Pakistan, Faiz became a citizen of the newly founded country, though his relationship with it was marked by both hope and disillusionment. He lived in different parts of the world for long stretches of time, but he returned to Pakistan toward the end of his life. He died there in 1984.

His poetry is celebrated for its marriage of classical tropes like the ache of unfulfilled longing for the beloved — and the lover’s willingness to be consumed or destroyed in his pursuit of her — with the political struggles of his time, like the plight of working people and the dream of a Marxist revolution. His poetry is notoriously difficult to translate because of its highly ornate, extended metaphors, which have few easy equivalents in English. This forces the translator – be it human or machine – to push the limits of language.

From 1951 to 1955, Faiz was imprisoned on allegations of sedition against the Pakistani state. His first three months were spent in solitary confinement.

From Faiz’s letters, scholars learned that despite the isolation of his imprisonment, he felt as if the experience made him more attuned to his senses, as if he were “falling in love again for the first time.” His time in jail was also among his most prolific as a poet, with “Meeting” composed during his sentence.

Here’s our translation of the opening verses of “Meeting”:

 This night is the dark,
 lush tree of a grief greater
 than you and I—

 greater, for caravans 
 of torch-bearing stars 
 have lost themselves
 in the siege of its branches;

 in its shadow, a thousand moons 
 have wept away all their light.

 This night is the dark,
 lush tree of a grief greater
 than you and I—

 but from the tree of this very night 
 the amber leaves 
 of these moments 
 have fallen, 

 grown entangled 
 in your locks and flowered 
 as the fires of pomegranate 
 blossoms; its dew 

 has rained drops of silence 
 upon your brow, 
 bedecked it with a silver 
 string of pearls.

When prompted to provide a “lyrical translation into English,” ChatGPT produced the following:

 This night is a tree of pain,
 Vaster than you, vaster than me.

 Its branches bear
 Thousands of torches in place of stars,
 Caravans lost
 Within a thousand moons’ shadows,
 And all my light has wept itself away.

 Yet from this very tree,
 A few golden leaves of fleeting moments
 Fall into your hair,
 Entwined, they bloom like roses.

 From its dew in quiet,
 A few drops rest upon your brow,
 And glitter like tiny diamonds.

Chatbots fail at translation’s most basic task

When Faiz composed “Meeting,” he had been separated from his wife and two daughters for two years. He was keenly aware of missing parts of their childhoods that would never return.

This biographical information can help translators understand the poem’s exploration of “vaṣl,” or the meeting of lover and beloved. A common trope in classical Urdu poetry, it usually captures the joy and exultation of the lovers’ union.

But in Faiz’s poem, the union with the beloved also contains an acute awareness of mortality and the transience of beauty – a recognition of what has been lost, and the suffering still to come.

That’s why we rendered the opening lines of “Meeting” as “This night is the dark,/lush tree of a grief greater/than you and I.”

ChatGPT’s translation is more literal: “This night is the tree of pain.”

While there is nothing technically wrong with this translation, the chatbot’s version doesn’t capture the nuances of the tree metaphor and the way its dense, expansive branches can encompass the complexity and beauty of the emotions evoked by the night of the lovers’ union.

AI also fails to grasp the poem’s intricate sentence structure. ChatGPT has translated “in its shadow a thousand moons / have wept away all their light” as a nonsensical construction: “Within a thousand moons’ shadows, / And all my light has wept itself away.”

This error appears to have happened because the chatbot translated “apnā” – a reflexive possessive pronoun in Urdu – as “my,” inaccurately parsing it as referring to the speaker instead of the moons.

Finally, and most importantly, AI models lack the ability to express emotion the way a human can. A machine with no bodily experience of being human cannot meaningfully perceive a poem so enmeshed in human experience. Its engagement is merely superficial.

In its attempt to convey the mood of the original piece, ChatGPT offers: “From its dew in quiet, / A few drops rest upon your brow, / And glitter like tiny diamonds.”

It’s clear that ChatGPT is struggling to decode the grammatical structure of the poem and is trying to make the text lyrical enough to convey the awe and wonder of the original. But the model’s contrivances toward the lyrical – for example, describing diamonds as “tiny” or “glittering” – have no relation to the original poem.

“From its dew in quiet” is an incoherent clause. The phrase that seems to have thrown the model off is “isī kī shabnam se khāmoshī ke yeh cand qaṭre,” or “its dew / has rained drops of silence.”

Urdu literary critic Shamsur Rahman Faruqi has explained how Urdu poets “treat metaphor as fact and then go on to create further metaphors from that fact.” In “Meeting,” the metaphor of the night of the reunion as a tree becomes a fact, which allows for the flowering of a new metaphor – that of the dew on its leaves as drops of silence that fall on the lover and their beloved. These silences, heavy with sorrow, then adorn the beloved like precious jewels, conveying the idea that only a profound grief can beget such beauty.

The model has failed at conjuring this sense of wonder because it cannot parse the poem in accordance with the literary conventions of Urdu poetry.

ChatGPT prefaced its translated text by assuring us that it had “crafted a lyrical, poetic English version of Faiz’s ‘Mulāqāt,’ keeping the imagery, rhythm, and emotional flow intact so it reads like a poem rather than a literal translation.”

Yet as we have shown, its translation fails to accomplish the most basic task of literary translation: to convey the heart of the original.

Chatbots, in other words, are a poor substitute for the literary translator, and they bolster the assertion of the late Indian poet, scholar and translator A.K. Ramanujan that “only poems can translate poems.”

Adeeba Shahid Talukder helped with the research and writing of this article, in addition to the translation of Faiz’s poem.

Krupa Shandilya, Associate Professor of Sexuality, Women's and Gender Studies, Amherst College

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Ding – that’s an all too familiar sound, designed to instantly capture your attention.

The average adult receives at least 46 push notifications a day from their smartphone – roughly one every 20 minutes during waking hours.

These interruptions might seem like a small price to pay for staying connected. However, research shows these attention-grabbing features increase stress and reduce productivity. They can even have fatal consequences, with phone-related distraction claiming 29 lives on Australian roads each year.

In our modern world, it can feel impossible to focus on any one task. But science tells us there are ways you can reclaim your attention.

How attention works

A network of areas in the human brain controls our selective attention, the process by which we focus on relevant information and ignore the rest. Where attention goes is a balance between what your goals are, and what’s happening in the world around you. This means sudden or urgent events can capture your attention, and pull it away from what you’re trying to do.

From an evolutionary perspective, this helps keep us safe. Imagine you are foraging for berries, for example, when you hear the rustling of leaves. This sound would capture your attention and shift your focus from foraging to the potential threat – it may be a tiger about to pounce.

Today, however, our modern environments often hijack this same mechanism for things that are far less urgent or important – such as the buzz of a new friend request.

The trouble with tech

Digital platforms are designed to instantly capture and hold your attention, by tapping into the brain’s reward and motivation systems. This is why you may find it harder to resist distractions that offer some kind of reward, such as a “like” on your post. It also makes it more difficult to stick to tasks that require sustained attention.

Research suggests these frequent interruptions may be reducing our ability to concentrate – not by affecting our fundamental ability to focus, but by increasing how often we switch between activities.

The myth of multitasking is that we can do two demanding tasks at once. However, our attention is capacity limited, which means we can’t simultaneously process everything that’s happening around us. “Multitasking” is actually task switching, or rapidly swapping between tasks rather than doing both at the same time. Research consistently shows task switching impairs how well we do one or both tasks, no matter how familiar or predictable the task is.

What you can do

Many factors influence your ability to pay attention – ranging from how well you sleep to whether you have certain health conditions, such as attention deficit hyperactivity disorder.

However, we can build up our “attention muscles” by making some minor lifestyle changes.

1. Limit distractions from devices

You can do this by setting up “focus” modes on your phone. These automatically filter out distractions by limiting how many notifications you get, particularly while working or driving. Or turn off all notifications from apps and schedule specific times to check them – say for ten minutes before lunch – and set timers to keep yourself accountable.

Apps that track your screen time may help, but avoid those that gamify how much time you spend off your phone. Ironically, these game-like features are also designed to draw in your attention. Instead, opt for tools that discourage use and provide data that can help you reflect on your screen habits.

2. Choose activities that require focus

The evidence is clear that constantly switching between tasks weakens our focus. To combat this, prioritise activities that demand sustained attention.

Research shows doing immersive activities – such as playing music and competitive sport – a few times a week may improve your ability to pay attention. This could be because these activities require you to pay attention for longer periods, to achieve a specific goal.

You can also use tools such as Pomodoro timers, which help you alternate between 25-minute intervals of focused work and five-minute breaks.

3. Reduce your overall tech use

Research shows people who avoid using devices before bedtime and keep them out of bedrooms sleep better. Studies also show these practices may improve your focus the following day.

And when you have a free moment, don’t immediately pick up your device. Research suggests regularly pausing to let your mind wander allows your brain to process information and form new connections between different concepts and experiences, leaving room for creativity to flourish.

In the end, reclaiming your attention doesn’t necessarily require rigid rules or strict routines. It starts with small, intentional acts of presence. Attention is a precious resource, so let’s invest it wisely.

Patricia Morada Macabulos, PhD Candidate, Psychology and Cognitive Neuroscience, Macquarie University and Anina Rich, Professor, Performance & Expertise Research Centre and School of Psychological Sciences, Macquarie University

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The NASA Artemis program, now supported by 67 countries under the Artemis Accords, plans to return humans to the Moon by 2028. A recent White House Executive Order has gone further, directing NASA to establish a permanent lunar outpost by 2030.

China also has plans to build a lunar base by 2035.

Building the first long-term habitat on another world will push our engineering to its limits. But lunar architecture isn’t just an engineering challenge. At its heart, it is about understanding human experience at the extremes – and how it can help improve conditions for those already living at the edges here on Earth.

The race to the Moon and beyond is accelerating. Some say it’s for the benefit of all humanity. But is it really? In this seven-part series, we explore what our future in space will look like, how we might travel and survive out there, and what’s needed to stop a catastrophe from happening.

The challenge of building a lunar base

Building on the Moon means dealing with the brutal realities of a near-perfect vacuum and unfiltered space radiation. We have some experience with such challenges from orbital habitats like the International Space Station, but there are additional conditions to contend with.

The lunar surface is covered in razor-sharp dust, or regolith, which is abrasive enough to cut through astronaut suits and destroy machinery. And the extreme temperature swings from below -200°C to over +120°C across a lunar day places severe thermal stress on building materials, which expand and contract with every cycle.

Transporting building materials from Earth will be prohibitively expensive, so current solutions focus on using locally available regolith to 3D print monolithic shells. But the lack of atmosphere on the Moon brings another unique challenge.

Micrometeorites rain down like tiny bullets at speeds of up to 72 kilometres per second, easily puncturing structures. A 3D-printed monolithic shell, once damaged, will be difficult to repair.

Our research explores modular block-based construction that can be easily disassembled and repaired by human-robot teams. Our work with colleagues at the NASA funded RETHi facilities at the University of Texas at San Antonio is helping us understand how local damage by micrometeorites effects the whole system, so we can design for repair.

The challenge of living on a lunar base

Lunar architecture is not just about survival. It gives us the chance to ask what it means to actually live in extreme conditions, and what that reveals about human experience more broadly.

For instance, what happens when people have to spend long periods in isolation or confined spaces, with no opportunity to step outside? This is not unique to space. Many of us experienced this during COVID, and others live it routinely on submarines, mining outposts and Antarctic stations.

Research shows that most people in such conditions describe time as feeling distorted, leading to higher stress and reduced social satisfaction. When days become repetitive and monotonous, and the future feels uncertain, time stops being meaningful.

Drawing on design psychology, we work with people who have lived or worked in isolated and confined conditions to understand how design can help. Small details – a private space to retreat to, lighting adjusted to personal rhythm, a window with a view – can have a considerable impact on emotional wellbeing and morale.

The psychological toll of living in extreme environments is inseparable from its physical demands. How do we keep the human body operating safely in these extreme conditions, and what happens when someone is injured far from help?

Again, this is not unique to space. Biomechanics research already helps us understand how joints and muscles move, preventing workplace injuries and supporting rehabilitation. But strip away Earth’s gravity, and everyday movements, like climbing a flight of stairs, reveal something new about how the body really works.

Our research uses gravity-offload experiments to study how the arms, shoulders and torso work together to lift and stabilise the body as gravity changes. The findings can inform the design of stairs and handrails for lunar habitats, making movement more efficient and preventing injury.

What this means for life on Earth

The construction industry accounts for roughly half of all global material extraction and around 30% of waste and carbon dioxide emissions – much of it because buildings are demolished rather than repaired.

The repairability and human-robot collaboration principles we are developing for lunar architecture offer a model for circular construction here on Earth, where maintaining buildings rather than tearing them down could transform the industry’s environmental footprint.

Our research on the psychology of isolation can also improve life for people stationed at polar research bases, in remote communities, or even in prison. And our biomechanics research, focusing on how forces redistribute between the upper and lower body, can help older people to climb stairs more safely, avoid falls and recover from injury.

Lunar architecture research is not about a distant, futuristic idea. It is about understanding human experience at the extremes, and using that understanding to ask better questions about how we design for people here on Earth. Humanity already lives at the edges. Learning to design for those edge conditions can teach us how to dwell more inclusively on this planet, and beyond.

Amit Srivastava, Senior Lecturer, Andy Thomas Centre for Space Resources, Adelaide University ; Kato Claeys, PhD Candidate, Andy Thomas Centre for Space Resources, Adelaide University ; Meriem Allani, PhD Candidate, Andy Thomas Centre for Space Resources, Adelaide University , and Monika Stankiewicz, PhD Candidate, Andy Thomas Centre for Space Resources, Adelaide University

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In the contemporary imagination, the word “avatar” may conjure James Cameron’s blue Na’vi people.

But Cameron was partly inspired by the avatars (or incarnations) of the the Hindu deity Vishnu, who sent avatars to earth to preserve universal order.

For over 15 centuries, Vishnu has been seen as a sustainer and a guardian of dharma – order, morality and righteousness – who has access to ten or more human and animal avatars.

Mostly, Vishnu is depicted by artists with blue skin, marking his separation from humanity. He evokes the colour of the cosmos and, as his avatar Krishna, the deep blue of brooding monsoonal cloud.

Avatar: Forms of Vishnu at the Art Gallery of New South Wales draws on these deep cultural roots. The gallery presents 200 artworks spanning 1,500 years, from international and Australian collections.

Many objects, notably early sculpture from Cambodia, have never before travelled from their home countries.

The highly crafted and carved objects open intriguing mythological narratives, exploring Vishnu’s long importance in Hindu cultures and to contemporary Australia.

A prescient exhibition

The exhibition takes audiences on a deep dive into the sumptuous colour, craft, tradition and artistry inspired by and honouring the avatars of this important figure.

Contemporary works add magic to the historic, conveying the continuum of tradition into current practice.

Avatar comes from the Sanskrit word avatāra, meaning “descent”. At the press preview, co-curator Chaitanya Sambrani called Vishnu a holistic presence, “a being that is everywhere, everything, and in everyone; an omnipresent force with different personas”.

For Sambrani, it is important to understand this presence exists “against the strictures of organised religion. We may have our own personal experience of Vishnu beyond the limitations of the self.”

Three years in the making, the exhibition feels prescient. Amid political division, ecological instability and debates around identity, Vishnu’s avatars – manifesting to create order from disorder – feel unexpectedly contemporary.

Enduring storytelling

The endurance of these stories is beautifully expressed. There is the juxtaposition of artworks old and new, in diverse media – textiles, carving, gold, embroidery, paint, sculpture, bronze, papercuts and watercolour.

One work of carved sandstone from Cambodia in the early 800s depicts a four-armed lord holding a discus, conch, club and globe. Its simplicity – a naturalistic figure decorated only with a cylindrical headpiece and skirt cloth (sampot) – alludes to Vishnu’s status with the Khmer kings.

Behind this sculpture hang two large contemporary paintings by Desmond Lazaro.

Lazaro describes the foundational Hindu story in The Churning of the Ocean of Milk (2026), paired with his Mount Mandara (2026).

The first, a circular form painted in colours from hand-ground ochres, describes the coming together of gods and demons to churn the ocean to retrieve the nectar of immortality, releasing both poison and divine treasure.

A soapstone carving of Lakshmi Narasimha, Vishnu’s man-lion avatar, from Odisha, India in the 1200s, is framed by Threshold (2026), a contemporary installation crafted in cotton and silk by Sumakshi Singh.

Elements highlighted for contemporary audiences include the feminist consciousness in these stories. The energy of the shakti from their female consorts is crucial to Vishnu’s avatars to complete their tasks.

Human transformation

The final theme of the exhibition is titled Vishnu’s Cosmos. The vibrant Kaavad shrine (2015) by Satyanarayan Suthar draws cars and planes together with gods and goddesses in a traditional kaavad (portable folding storyboard).

An intriguing series of printed oleographs (prints made to resemble paintings) from the art publisher Rami Varma Press (1894–1972) are sumptuously decorated with embroidery, cloth and sequins to honour the deities.

A sandstone carving of Vajimukha (Hayagriva or Kalkin) from the late 500s or early 600s guards this final gallery. The figure is bare-chested, with a simple skirt falling below the knee, and horsehead sitting naturalistically on human shoulders.

The head may refer to Vishu’s final avatar Kalki, prophesied to appear during a conflict-riddled time, promising a new age of truth and virtue.

This is the first Australian exhibition devoted to Vishnu, and the largest to focus on South and Southeast Asian art for 20 years. In this, Avatar acknowledges an evolving cultural landscape and the growing proportion of Australians with a South and Southeast Asian background.

In this exhibition, mythology is positioned as an adaptive visual language through which artists explore identity, resilience, morality, devotion and the potential in human transformation.

Avatar: Forms of Vishnu is at the Art Gallery of New South Wales, Sydney, until October 5.

Louise Martin-Chew, Honorary Research Fellow, School of Communication and Arts, The University of Queensland

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Earlier this month the University of Sydney launched an investigation into allegations miniature spy cameras were used to record and distribute exam content online.

At the same time, the UK’s national examinations regulator warned smart glasses, smartwatches and concealed earpieces are emerging threats for unis.

Chief regulator of qualifications Sir Ian Bauckham noted technology was “changing fast”:

There are smartwatches that we are increasingly seeing on young people and they are fully internet connected […] And I understand that in the pipeline there are even things like smart glasses […]

There is a renewed emphasis on having in-person exams in response to AI. University administrators have traditionally regarded in-person, invigilated exams as the most reliable way of ensuring students don’t cheat.

But the rise of these new wearable technologies could undermine this approach.

So what can Australian universities do in response?

A new generation of tech

Cheating in examinations is of course not new. Students have long relied on handwritten notes, information hidden on clothing, or materials accessed during bathroom breaks.

In 2022, a Spanish law student even gained media attention after engraving tiny notes onto plastic pens for an exam years earlier.

However, new types of wearable technology are changing how students can cheat.

Among the most significant developments are AI-enabled smart glasses with built-in microphones and cameras.

These can display AI-generated text, process spoken language and analyse written materials. They can be hard to distinguish from everyday glasses.

Research suggests even when images captured by smart glasses were blurry and warped, AI could still extract enough information to answer some exam questions correctly.

Alongside covert recording devices, micro earpieces are also available, allowing answers to be relayed to candidates.

Screen-enabled pens can also display and generate text, allowing users to access notes while appearing to use a normal pen.

Meanwhile, smartwatches remain a cheating risk. They can store notes, display text discreetly, and in some cases connect to other devices, the internet and AI chat functions.

As a 2026 paper by Australian researchers noted, transparent wearable AI – particularly AI-enabled smart glasses – are difficult for exam invigilators to detect.

How widespread is the issue?

We do not yet have robust data on Australian usage of smart devices for cheating.

But in the United Kingdom, the exam regulator reported 2,225 cases involving mobile phones and smart devices for tertiary and senior school exams in 2025. This accounted for 44.3% of all cheating cases.

China is also grappling with the issue. This month, its Ministry of Education warned bringing smart devices to exams, including smart glasses, counts as cheating.

Numerous Chinese provinces also introduced tighter exam security measures at the same time, including mandatory inspections of candidates’ glasses, manual checks and a wider rollout of smart security gates. These are electronic screening checkpoints that detect banned devices.

In Japan, covert recordings in 2024 prompted universities to take stricter security measures for exams.

What can we do?

In Australia, some universities have banned smart devices in supervised exams.

However, smart devices cannot be addressed through traditional invigilation alone.

Universities need to update policies to explicitly address smart glasses, AI earbuds and other wearable technologies. Invigilators require training to recognise devices. For example, thick-framed smart glasses, active indicator lights, concealed earpieces and screen-enabled pens.

Universities may also need to consider having exam rooms monitored by device screening technology, and secure storage procedures for prohibited items. While such systems involve upfront costs, they are already being used in China. This suggests the technology is commercially available and operationally feasible in universities.

Other changes are needed

Assessment design also needs to evolve. Exams that focus primarily on memorisation are more vulnerable to cheating than those requiring critical thinking, problem-solving and application of knowledge.

Universities should also improve systems to collect data on technology-enabled cheating. This will allow policies to be guided by evidence.

At the same time, institutions must avoid creating inequitable surveillance practices. Intensive scrutiny of glasses and hearing aids and what students are wearing may discriminate against students with disabilities, chronic health conditions and religious dress requirements. So universities face the challenge of balancing academic integrity with inclusion and accessibility.

Undermining academic integrity

If students are cheating on exams and unis don’t realise, the consequences extend beyond individual cases of misconduct.

Public trust in university qualifications may be weakened. As the UK regulator noted,

you end up with grades for qualifications which are no longer reliable, no longer trustworthy.

The challenge for higher education is not simply preventing cheating. It is ensuring assessment remains valid, credible and equitable in a world where AI and other technology is increasingly embedded into everyday devices and learning.

Meena Jha, Associate Professor, College of Information & Communication Technology, CQUniversity Australia

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The story of Stonehenge starts around 5,000 years ago. But its famous old stones, some of which were transported all the way from south-west Wales to Wiltshire, are just part of the story.

Close to the beginning of its use, the site was a cemetery, with dozens of people laid to rest. That so many changes have been made to the site since – almost all involving huge commitments of human labour and creativity – is testament to Stonehenge’s significance to countless generations of people.

Its continuing fascination was demonstrated by a 2022 British Museum exhibition that attracted 190,000 visitors to its collection of prehistoric objects from 36 European institutions. Now, that physical exhibition has been brought to virtual life in a new collaboration between researchers at the University of Reading, including myself, and the museum.

Users of The Virtual World of Stonehenge – released to coincide with the summer solstice – can go deep inside Stonehenge and watch it change through time.

They can closely examine one of the bluestones that was very likely brought to Stonehenge from Wales, or an ancient pounder tool used to shape the sarsen stones that were excavated much closer to the site.

With the help of English Heritage, which manages Stonehenge, we have also reconstructed how this megalithic structure might have looked through different phases of its existence.

Users can also travel further afield to view the evolving landscape of ritual monuments around England – for example, to Neolithic flint mines at Grimes Graves in Norfolk. Here are some more of the ancient places and artefacts you can discover today without leaving your armchair.

The Coneybury pit

The pottery, animal bones and flint tools in this display were all excavated from a pit close to Stonehenge – but they pre-dated the stones by almost a thousand years. It was among the less spectacular assemblages in the 2022 exhibition, yet had a fascinating story to tell.

The pit held the remains of a feast enjoyed by hunter-gatherers and the first farmer communities some 5,900 years ago. Those gathered ate farmed beef and hunted venison.

Chemical analysis of the remains shows the cattle and deer consumed came from different places – and that the meat was prepared in different ways. As a coming together of worldviews, languages, customs and traditions, the remains of this shared meal marked the end of thousands of years of a hunter-gatherer way of life.

The virtual experience enables users to watch an animated video telling the story of this meeting, and explains how archaeologists pieced together its story.

Seahenge

In 1998, a well-preserved timber circle emerged from the shores of Holme-next-the-Sea, on the coast of Norfolk. It was soon dubbed Seahenge owing to its similarity to timber circles that had once stood in the Stonehenge landscape.

The Holme circle was originally built on a saltmarsh, between land and sea, and consisted of 55 large oak posts. A narrow entranceway was positioned exactly to align on the Sun’s path, so that the midsummer rising Sun illuminated the interior of the monument.

From a study of the tree rings, it is known that Seahenge was built in the spring or summer of 2049 BC, at a time when stone tools and weapons were rapidly being replaced by metal as the material of choice for social and economic life – and also for offerings to supernatural forces.

During that period, circles of wood and stone were in decline. Seahenge was constructed near the end of a religious tradition that had lasted for almost a millennium.

In the virtual experience, you can listen to the “Seahenge soundscape” created by the artists Rose Ferraby and Rob St John. Their work added a spine-tingling dimension to the British Museum’s display of these ancient timbers.

A 6,000-year-old leaf

A humble object that captured many people’s imagination during the British Museum exhibition was a single elm leaf. This delicate specimen fell around 6,000 years ago near an early farming settlement on the coast of Lancashire.

Deforestation has played a key role in European history ever since then. Hard-won clearances could be filled by trees in a human lifespan, while woodland continued to provide vital resources to support the farming way of life.

Near this ancient leaf, we displayed a wall holding 89 stone axes – each representing a generation of human lives during the primary period covered by the exhibition (circa 4000-1500 BC). Many would have been used to chop down trees thousands of years ago – clearing land for crops and monuments, as well as providing wood for building.

Folkton chalk ‘drums’

These three carefully-carved chalk treasures accompanied the body of a small child buried 5,000 years ago in Folkton, North Yorkshire. The eyes peering out from above abstract motifs on the largest and smallest of the sculptures might have been created with the fate and protection of a loved and vulnerable child in mind.

This enigmatic group of objects was excavated in the 1860s. The drums, placed carefully along the line of the child’s back, work well as a set: their size is incremental and all three have similar decorative schemes.

The patterns share the same repertoire of concentric circles, lozenges, zigzags, chevrons and parallel lines found elsewhere across Britain and Ireland. But intriguingly, two of the drums have a motif of eyes with eyebrows insinuated in the design – hinting at a daring, possibly dangerous, reference to a person or spirit embodied within.

In The Virtual World of Stonehenge, you can explore these fascinating and intricately carved objects in 3D, along with a similar drum found much more recently at Burton Agnes. This one was placed with three children of different ages buried close together, the two youngest poignantly holding hands.

Duncan Garrow, Professor of Archaeology, University of Reading

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