What AI needs to learn about dying and why it will save it

Those programming truthfulness can learn a lot from mortality.

Andrew Steane

Andrew Steane has been Professor of Physics at the University of Oxford since 2002, He is the author of Faithful to Science: The Role of Science in Religion.

An angel of death lays a hand of a humanioid robot that has died amid a data centre

A digital momento mori.

Nick Jones/midjourney.ai

Google got itself into some unusual hot water in recently when its Gemini generative AI software started putting out images that were not just implausible but downright unethical. The CEO Sundar Pichai has taken the situation in hand and I am sure it will improve. But before this episode it was already clear that currently available chat-bots, while impressive, are capable of generating misleading or fantastical responses and in fact they do this a lot. How to manage this?

Let’s use the initials ‘AI’ for artificial intelligence, leaving it open whether or not the term is entirely appropriate for the transformer and large language model (LLM) methods currently available. The problem is that the LLM approach causes chat-bots to generate both reasonable and well-supported statements and images, and also unsupported and fantastical (delusory and factually incorrect) statements and images, and this is done without signalling to the human user any guidance in telling which is which. The LLMs, as developed to date, have not been programmed in such a way as to pay attention to this issue. They are subject to the age-old problem of computer programming: garbage in, garbage out.

If, as a society, we advocate for greater attention to truthfulness in the outputs of AI, then software companies and programmers will try to bring it about. It might involve, for example, greater investment in electronic authentication methods. An image or document will have to have, embedded in its digital code, extra information serving to authenticate it by some agreed and hard-to-forge method. In the 2002 science fiction film Minority Report an example of this was included: the name of a person accused of a ‘pre-crime’ (in the terminology of the film) is inscribed on a wooden ball, so as to use the unique cellular structure of a given piece of hardwood as a form of data substrate that is near impossible to duplicate.

The questions we face with AI thus come close to some of those we face when dealing with one another as humans.

It is clear that a major issue in the future use of AI by humans will be the issue of trust and reasonable belief. On what basis will we be able to trust what AI asserts? If we are unable to check the reasoning process in a result claimed to be rational, how will be able to tell that it was in fact well-reasoned? If we only have an AI-generated output as evidence of something having happened in the past, how will we know whether it is factually correct?

Among the strategies that suggest themselves is the use of several independent AIs. If they are indeed independent and all propose the same answer to some matter of reasoning or of fact, then there is a prima facie case for increasing our degree of trust in the output. This will give rise to the meta-question: how can we tell that a given set of AIs are in fact independent? Perhaps they all were trained on a common faulty data set. Or perhaps they were able to communicate with each other and thus influence each other.

The questions we face with AI thus come close to some of those we face when dealing with one another as humans. We know humans in general are capable of both ignorance and deliberate deception. We manage this by building up degrees of trust based on whether or not people show behaviours that suggest they are trustworthy. This also involves the ability to recognize unique individuals over time, so that a case for trustworthiness can be built up over a sequence of observations. We also need to get a sense of one another's character in more general ways, so that we can tell if someone is showing a change in behaviour that might signal a change in their degree of trustworthiness.

In order to earn our trust, an AI too will have to be able to suffer and, perhaps, to die.

Issues of trust and of reasonable belief are very much grist to the mill of theology. The existing theological literature may have much that can be drawn upon to help us in this area. An item which strikes me as particularly noteworthy is the connection between suffering and loss and earning of trust, and the relation to mortality. In brief, a person you can trust is one who has ventured something of themselves on their pronouncements, such that they have something to lose if they prove to be untrustworthy. In a similar vein, a message which is costly to the messenger may be more valuable than a message which costs the messenger nothing. They have already staked something on their message. This implies they are working all the harder to exert their influence on you, for good or ill. (You will need to know them in other ways in order to determine which of good or ill is their intention.)

Mortality brings this issue of cost to a point of considerable sharpness. A person willing to die on behalf of what they claim certainly invests a lot in their contribution. They earn attention. It is not a guarantee of rationality or factual correctness, but it is a demonstration of commitment to a message. It signals a sense of importance attached to whatever has demanded this ultimate cost. Death becomes a form of bearing witness.

A thought-provoking implication of the above is that in order to earn our trust, an AI too will have to be able to suffer and, perhaps, to die.

In the case of human life, even if making a specific claim does not itself lead directly to one's own death, the very fact that we die lends added weight to all the choices we make and all the actions we take. For, together, they are our message and our contribution to the world, and they cannot be endlessly taken back and replaced. Death will curtail our opportunity to add anything else or qualify what we said before. The things we said and did show what we cared about whether we intended them to or not. This effect of death on the weightiness of our messages to one another might be called the weight of mortality.

In order for this kind of weight to become attached to the claims an AI may make, the coming death has to be clearly seen and understood beforehand by the AI, and the timescale must not be so long that the AI’s death is merely some nebulous idea in the far future. Also, although there may be some hope of new life beyond death it must not be a sure thing, or it must be such that it would be compromised if the AI were to knowingly lie, or fail to make an effort to be truthful. Only thus can the pronouncements of an AI earn the weight of mortality.

For as long as AI is not imbued with mortality and the ability to understand the implications of its own death, it will remain a useful tool as opposed to a valued partner. The AI you can trust is the AI reconciled to its own mortality.

Review

Books

Culture

Economics

Politics

8 April 2025

5 min read

Abundance and the attempt to build a better world

Is this policy the antidote to the zero-sum game of politics?

Josh Richards

Josh is a curate in London, and is completing a PhD in theology.

Construction worker climb a steel framework.

Josue Isai Ramos Figueroa on Unsplash.

What do you do when more money won’t solve a government’s problems? Abundance: How We Build A Better Future, the new book by Ezra Klein and Derek Thompson is an extended polemic against a form of government—particularly as practiced by US liberals—that stymies policy delivery. However technocratic that sounds (and the book often is), it forces readers to confront deeper questions about the nature of politics.

At the heart of the book is a critique of what the authors, drawing on the film Everything Everywhere All At Once, call 'Everything Bagel Liberalism'. In the film topping are added to bagel to the point that it becomes a blackhole. So too, Klein and Thompson suggest, with so much well-intended policy, in which in seeking to tick every possible box and satisfy a range of regulators it becomes a delivery blackhole and little is actually done. The authors ask whether parties of the left are focused on measuring spending to the exclusion of measuring what gets built.

The first chapter gives a good sense of their approach.  It tells a familiar story about the way in which so many are being priced out of cities because of a lack of affordable housing. However, in doing so, it highlights a surprising harm: that geographical proximity remains an important enabler of technological innovation so a lack of affordable housing in cities means a loss of creativity.

The diagnosis is perhaps even more surprising coming from American liberals. Special interests—including those seeking to protect the value of their own houses—weaponize interlocking sets of well-intentioned legislation to prevent homes being built. Subsequent chapters apply that similar logic—regulation and a lack of focus resulting in inaction—to infrastructure, government capacity, scientific research and the implementation of new inventions.

The book's strength is that it is not particularly detailed in its policy proposals. Klein and Thompson instead offer abundance as a lens through which policy development can be viewed: what do we need more of and how do we get it? This lens can be applied from within a wide range of ideological frameworks. It is not itself a worldview but a challenge that any politics should be obsessed with effective delivery not simply desiring the correct end-state.

The book is unapologetically focused on America and the failures of progressive governance, particularly in California. (One of this book's peculiar legacies will be to leave many who have never been there perpetually invested in California's struggles to build high-speed rail.) Nevertheless, the approach already has its advocates in the UK - for example, the Centre for British Progress which set out its stall last week, and it is not hard to see how an agenda here that could be seized by a less hesitant Starmer government.

Any plausible political analysis must hold together the reality of scarcity and abundance. Losing sight of either unmoors us from the actual world we find ourselves in.

Indeed, perhaps the book might feel more realistic if it had other countries in mind. Reviewing Abundance, Columbia economist Adam Tooze describes the book as painful to read, characterising it as a manifesto for the Harris presidency that never was. Indeed, according to the authors, the book was originally scheduled for release in summer 2024 to influence the Democratic platform leading up to the 2024 elections. Instead, it appears in 2025 amid Trump's assault on institutions, Tooze's Columbia among them.

In an interview on Pod Save America, the authors argued that the book is still relevant, offering a framework with which Democrats can oppose Trump. Thompson described the Trumpian view of politics as fundamentally shaped by scarcity. He suggests that behind 47th president's policies—most notably the tariff agenda—is the conviction that every interaction is zero-sum; for you to gain, I must lose.  On this analysis, the way to oppose a politics that pits groups against one another over limited resources—housing, trade, jobs—is to figure out how the government can provide more and argue for it. In its critique and its hopefulness, Abundance offers those who believe in institutions a way to navigate—even work with the grain of—the anti-institutional temperament of contemporary politics.

There might be something to this messaging, but scarcity plays an unmissable role in Klein and Thompson's argument. Remember that they characterise what they oppose as "Everything Bagel Liberalism", policy that tries to achieve every outcome and loses focus in doing so. They may conceive scarcity differently to Trump, but their book is a warning policy cannot deliver as much as we think. It is a call for us to oppose, to compete against those special interests—whether they be residents’ associations wanting to hold up house prices or politicians wanting to cut research grants—whose policy priorities overload the bagel.

At heart, the book is a reminder that ultimately the salient scarcity in politics is not housing or trade or even money. It is time. Abundance cautions governments that unfocussed policy yields the time entrusted to them by the governed.

Humans cannot lead politics completely beyond its zero-sum logic. The world is so often a violent competition over resources and government must restrain that violence while avoiding being co-opted as a means of exploitation. And yet, politics is also—even primarily—an avenue through which communities answer a primal summons to be fruitful, abundant.

Ultimately, any plausible political analysis must hold together the reality of scarcity and abundance. Losing sight of either unmoors us from the actual world we find ourselves in. Yes, there is so much broken and warped to reckon with, and we must grapple too with our finitude’s bluntness, but so too is creation replete with goodness, among them our capacity to invent and deliver what we need together.

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