Arts, Books, History, Nature, Science

Book Review: The Origin of Language

LITERARY REVIEW

Intro: According to an evolutionary biologist, it takes a village to raise a child. And that’s why we started talking to each other

THE story of human evolution has undergone a distinct feminisation in recent decades. Or, rather, an equalisation: a much-needed rebalancing after 150 years during which, we were told, everything was driven by strutting and brawling males, with females tagging along for the ride. This reckoning has finally arrived at language.

The origins of our species’ exceptional communication skills constitute one of the more nebulous zones of the larger evolutionary narrative, because many of the bits of the human anatomy that allow us to communicate – notably the brain and the vocal tract – are soft and don’t fossilise. The linguistic societies of Paris and London even banned talk of evolution around 1870, and the subject only made a timid comeback about a century later. Plenty of theories have been thrown into the evidentiary void since then, mainly by men, but now evolutionary biologist Madeleine Beekman, of the University of Sydney, has turned her female gaze on the problem. Unlike a baby chimp that can cling to its mother, a human infant is entirely helpless for years.

Her theory, which she describes as having been hiding in plain sight, is compelling: language evolved in parallel with caring for our “underbaked” newborns, because looking after and caring for a helpless human baby on the danger-filled plains of the African savannah required more than one pair of hands (and feet). It needed a group among whom the tasks of food-gathering, childcare, and defence could be divided. A group means social life, which means communication. Social bonding meant language evolved to negotiate help, share information about infant safety, and for those bonds to be necessarily strengthened to keep “helpless” infants alive.

The evidence to support Beekman’s theory isn’t entirely lacking, but a lot of it is, as a matter of course, circumstantial. We know that the compromise that natural selection hit upon to balance the competing anatomical demands of bipedalism (walking upright and narrowing pelvises) and an ever-expanding brain was to have babies born early (before that brain and its bony casing were fully formed).

One of the discoveries of the newly feminised wave of evolutionary science has been that alloparents – individuals other than the biological parents who contribute parenting services – played a critical role in ensuring the survival of those half-developed human children. Another is that stone-age women hunted alongside men. In the past it was assumed that hunting bands were exclusively male, and one theory held that language arose to allow them to cooperate. But childcare was another chore that called for cooperation, probably also between genders, and over years, not just hours or days.

Fortuitously, the reconfiguration of the head and neck required to accommodate the ballooning brain had a side-effect of remoulding the throat, giving our ancestors more control and precision over their utterances. With the capacity to generate a large range of sounds came the ability to convey a large range of meanings. To begin with, this was useful for coordinating childcare, but as speech became more complex and sophisticated, alloparents – particularly grandmothers – used it to transmit their accumulated knowledge. This nurtured infants who were even better equipped to survive. The result of this positive feedback loop was Homo sapiens, the sole survivor of a once diverse lineage.

Regrettably, critics are likely to highlight that Beekman takes a very long time to get to this exciting idea. She does spend about half the book laying the groundwork, padding it out with superfluous vignettes as if she is worried the centre won’t hold. Once she gets there, she makes some thought-provoking observations. Full-blown language probably emerged about 100,000 years ago, she says, but only in our line – not in those of our closest relatives. “We may have made babies with Neanderthals and Denisovans,” she writes, “but I don’t think we had much to talk about.”

And whereas others have argued that language must have predated Homo sapiens, because without it the older species Homo erectus couldn’t have crossed the forbidding Wallace Line – the deep-water channel that separates Asia and Australasia – she draws on her deep knowledge of social insects to show that communication as relatively unsophisticated as that of bees or ants could have done the job. Having made a persuasive case for the role of alloparents in the evolution of language, Beekman concludes that we did ourselves a disservice when we shrank our basic unit of organisation down from the extended to the nuclear family. Perhaps, but historians including Peter Laslett have dated this important shift to the middle ages, long before the Industrial Revolution where she places it, and the damage isn’t obvious yet. Language is still being soaked up by young children, and is still a vehicle for intergenerational learning. It may take a village to raise a child, but as Beekman herself hints, a village can be constituted in different ways.

Beekman presents a radical shift in how we understand the birth of human speech. While traditional theories often credit hunting, toolmaking, or warfare as the primary drivers of complex communication, the author argues that the true catalyst was the inescapable need for cooperative childcare.

– The Origin of Language: How We Learned to Speak and Why by Madeleine Beekman is published by Simon & Schuster, 320pp

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Economic, G20, Government, Politics, Society, United Nations

The ‘inequality emergency’

ECONOMIC

Intro: Rising economic division is destabilising nations and eroding accountability. Joseph Stiglitz’s G20 blueprint proposes a way toward global economic renewal. For the first time the G20 has declared a global inequality emergency

WAS it a diplomatic nicety when Swiss tycoons and business magnates handed Donald Trump a gold bar and a Rolex watch, gifts that were reciprocated by a cut in US tariffs? No. It was a reminder of how concentrated wealth seems to buy access and bend policy. Alarmingly, this might just become the norm if the global “inequality emergency” continues. That’s the clear message being sent out in the most recent work by the Nobel laureate Professor Joseph Stiglitz. The economist sees the widening gap between rich and poor as a human-made crisis which is destroying politics, society, and the planet. He’s not wrong.

The problem is no longer confined to a few fragile states. It is a global harm, with 90% of the world’s population living under the World Bank’s definition of “high income inequality”. The US sits just below that threshold and is the most unequal country in the G7, followed by the UK. Prof. Stiglitz’s insight is that the current system’s defenders can no longer explain its mounting anomalies. Hence he wants a new framework to replace it. His blueprint for change is contained within the G20’s first-ever inequality report, endorsed by key European, African, and middle-income nations.

It warns that the richest 1% captured 41% of all new wealth since 2000, while the bottom half gained just 1%. On average, someone in the global top 1% became $1.3m richer; a person in the poorest half gained $585. Meanwhile, 2.3 billion people are now moderately or severely food insecure – 335 million more than in 2019. Wealth concentration far outstrips income concentration, with the total assets of billionaires’ worth one-sixth of global GDP. Shockingly, billionaire wealth is rising almost in lockstep with global food insecurity.

The report argues that extreme inequality is a policy choice – produced by specific economic, political and legal decisions rather than by “globalisation” or technology. Financial deregulation, weakening labour protections, and privatisation all aid rising inequality. As does cutting corporate and top income tax rates. The report stresses that the most dangerous consequences are political, with highly unequal countries seven times more likely to experience democratic backsliding or authoritarian drift. Stiglitz points out that the super-rich account for a disproportionate share of carbon emissions, worsening climate risks borne by the poor. He rejects the pro-market argument that inequality is good for growth.

The G20 inequality report lays out a comprehensive redesign of global economic governance reminiscent of 1944’s Bretton Woods accord. What led to that overhaul is being identified again today: global rules and institutions that are generating crises, instability, and inequality. Prof. Stiglitz wants structural change – suggesting a rewrite of intellectual property rules as well as trade and investment treaties, a reform of global lenders, and an update of tax systems as well as sovereign debt arrangements.

A fairer global order must start where every paradigm shift begins: with knowledge, scrutiny, and shared facts. The Intergovernmental Panel on Climate Change (IPCC) – the UN-backed body assessing scientific opinion – was created in 1988 to give global authority to that knowledge. It reshaped climate politics. Prof. Stiglitz argues that the time has come for an International Panel on Inequality. Hundreds of experts agree. Endorsing it is by no means radical; it is simply the first step towards a saner world. Without it, the gold-bar diplomacy circling Trump will surely proliferate.

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Artificial Intelligence, Arts, Books, Computing, Meta, Technology

Book Review: If Anyone Builds It, Everyone Dies

LITERARY REVIEW

WE shouldn’t worry so much these days about climate change because we’ve been told that our species only has a few years before it’s wiped out by superintelligent AI.

We don’t know what form this extinction will take exactly – perhaps an energy-hungry AI will let the millions of fusion power stations it has built run hot, boiling the oceans. Maybe it will want to reconfigure the atoms in our bodies into something more useful. There are many possibilities, almost all of them bad, say Eliezer Yudkowsky and Nate Soares in If Anyone Builds It, Everyone Dies, and who knows which will come true. But just as you can predict that an ice cube dropped into hot water will melt without knowing where any of its individual molecules will end up, you can be sure an AI that’s smarter than a human being will destroy us all, somehow.

This level of confidence is typical of Yudkowsky, in particular. He has been warning about the existential risks posed by technology for years – on the website he helped to create, LessWrong.com, and via the Machine Intelligence Research Institute he founded (Soares is the current president). Despite not graduating from university, Yudkowsky is highly influential in the field. He is also the author of a 600,000-word publication of fanfic called Harry Potter and the Methods of Rationality. Colourful, annoying, and polarising according to some critics, with one leading researcher saying in an online spat that “people become clinically depressed” after reading Yudkowsky’s work. But as chief scientist at Meta, who are they to talk?

While Yudkowsky and Soares may be unconventional, their warnings are similar to those of Geoffrey Hinton, the Nobel-winning “godfather of AI”, and Yoshua Bengio, the world’s most-cited computer scientist, both of whom signed up to the statement that “mitigating the risk of extinction from AI should be a global priority alongside other societal-scale risks such as pandemics and nuclear war”.

As a clarion call, If Anyone Builds It, Everyone Dies is well timed. Superintelligent AI doesn’t exist yet, but in the wake of the ChatGPT revolution, investment in the datacentres that would power it is now counted in the hundreds of billions. This amounts to “the biggest and fastest rollout of a general-purpose technology in history,” according to the FT’s John Thornhill. Meta alone will have spent as much as $72bn (£54bn) on AI infrastructure this year alone, and the achievement of superintelligence is now Mark Zuckerberg’s explicit goal.

This is not great news, if you believe Yudkowsky and Soares. But why should we? Despite the complexity of its subject, If Anyone Builds It, Everyone Dies is as clear as its conclusions are hard to accept. Where the discussions become more technical, mainly in passages dealing with AI model training and architecture, it remains straightforward enough for readers to grasp the basic facts.

Among these is that we don’t really understand how generative AI works. In the past, computer programs were hand coded – every aspect of them was designed by a human. In contrast, the latest models aren’t “crafted”, they’re “grown”. We don’t understand, for example, how ChatGPT’s ability to reason emerged from it being shown vast amounts of human-generated text. Something fundamentally mysterious happened during its incubation. This places a vital part of AI’s functioning beyond our control and means that, even if we can nudge it towards certain goals such as “be nice to people”, we can’t determine how it will get there.

That’s a big problem, because it means that AI will inevitably generate its own quirky preferences and ways of doing things. These alien predilections are unlikely to be aligned with ours. It’s worthy noting, however, that this is entirely separate from the question of whether AIs might be “sentient” or “conscious”. Being set goals, and taking actions in the service of them, is enough to bring about potentially dangerous behaviours. Nonetheless, Yudkowsky and Soares point out that tech companies are already trying hard to build AIs that do things on their own initiative, because businesses will pay more for tools that they don’t have to supervise. If an “agentic” AI like this were to gain the ability to improve itself, it would rapidly surpass human capabilities in practically every area. Assuming that such a superintelligent AI valued its own survival – why shouldn’t it? – it would inevitably try to prevent humans from developing rival AIs or shutting it down. The only sure-fire way of doing that is shutting us down.

What methods would it use? Yudkowsky and Soares argue that these could involve technology we can’t yet imagine or envisage, and which may strike us as very peculiar. They liken us to Aztecs sighting Spanish ships off the coast of Mexico, for who the idea of “sticks they can point at you to make you die” – AKA guns – would have been hard to conceive of.

Nevertheless, in order to make things more convincing, they elaborate further. In the part of the book that most resembles sci-fi, they set out an illustrative scenario involving a superintelligent AI called Sable. Developed by a major tech company, Sable proliferates through the internet to every corner of civilisation, recruiting human stooges through the most persuasive version of ChatGPT imaginable, before destroying us with synthetic viruses and molecular machines. Some will reckon this to be outlandish – but the Aztecs would have said the same about muskets and Catholicism.

The authors present their case with such conviction that it’s easy to emerge from this book ready to cancel and cash in on your pension contributions. The glimmer of hope they offer – and its low wattage – is that doom can be averted if the entire world agrees to shut down advanced AI development as soon as possible. Given the strategic and commercial incentives, and the current state of political leadership, this seems highly unlikely.

The crumbs of hope we are left to grapple with, then, are indications that they might not be right, either about the fact that superintelligence is on its way, or that its creation equals our annihilation.

There are certainly moments in the book when the confidence with which an argument is presented outstrips its strength. As a small illustrative example of how AI can develop strange, alien preferences, Yudkowsky and Soares offer up the fact that some large language models find it had to interpret sentences without full stops. “Human thoughts don’t work like that,” they write. “We wouldn’t struggle to comprehend a sentence that ended without period.” But that’s not really true; humans often rely on markers at the end of sentences in order to interpret them correctly. We learn languages via speech, so they’re not dots on the page but “prosodic” features like intonation: think of the difference between a rising and falling tone at the end of a phrase. If text-trained AI leans heavily on grammatical punctuation to figure out what’s going on, that shows its thought processes are analogous, not alien, to human ones.

And for writers steeped in the hyper-rational culture of LessWrong, the authors exhibit more than a touch of confirmation bias. “History,” they write, “is full of . . . examples of catastrophic risk being minimised and ignored,” from leaded petrol to Chernobyl. But what about predictions of catastrophic risk being proved wrong? History is full of those, too, from Malthus’s population apocalypse to Y2K. Yudkowsky himself once claimed that nanotechnology would destroy humanity “no later than 2010”.

The problem is that you can be overconfident, inconsistent, a serial doom-monger, and still be right. It’s imperative to be aware of our own motivated reasoning when considering the arguments presented here; we have every incentive to disbelieve them.

And while it’s true that they don’t represent the scientific consensus, this is a rapidly changing, and very poorly understood field. What constitutes intelligence, what constitutes “super”, whether intelligence alone is enough to ensure world domination – all of this is furiously debated.

At the same time, the consensus that does exist is not particularly reassuring. In a 2024 survey of 2,778 AI researchers, the median probability placed on “extremely bad outcomes, such as human extinction” was 5%. Of more concern, “having thought more (either ‘a lot’ or ‘a great deal’) about the question was associated with a median of 9%, while having thought ‘little’ or ‘very little’ was associated with a median of 5%”.

Yudkowsky has been thinking about the problem for most of his adult life. The fact that his prediction sits north of 99% seems to reflect a kind of hysterical monomania, or an especially thorough engagement with the issue. Whatever the case, it feels like everyone with an interest in the future has a duty to read what he and Soares have to say.

– If Anyone Builds It, Everyone Dies by Eliezer Yudkowsky and Nate Soares is published by Bodley Head, 272pp

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