Tech
If AI takes most of our jobs, money as we know it will be over. What then?
It’s the defining technology of an era. But just how artificial intelligence (AI) will end up shaping our future remains a controversial question.
For techno-optimists, who see the technology improving our lives, it heralds a future of material abundance.
That outcome is far from guaranteed. But even if AI’s technical promise is realized—and with it, once intractable problems are solved—how will that abundance be used?
We can already see this tension on a smaller scale in Australia’s food economy. According to the Australian government, we collectively waste around 7.6 million tons of food a year. That’s about 312 kilograms per person.
At the same time, as many as one in eight Australians are food-insecure, mostly because they do not have enough money to pay for the food they need.
What does that say about our ability to fairly distribute the promised abundance from the AI revolution?
AI could break our economic model
As economist Lionel Robbins articulated when he was establishing the foundations of modern market economics, economics is the study of a relationship between ends (what we want) and scarce means (what we have) which have alternative uses.
Markets are understood to work by rationing scarce resources toward endless wants. Scarcity affects prices—what people are willing to pay for goods and services. And the need to pay for life’s necessities requires (most of) us to work to earn money and produce more goods and services.
The promise of AI bringing abundance and solving complex medical, engineering and social problems sits uncomfortably against this market logic.
It is also directly connected to concerns that technology will make millions of workers redundant. And without paid work, how do people earn money or markets function?
Meeting our wants and needs
It is not only technology, though, that causes unemployment. A relatively unique feature of market economies is their ability to produce mass want, through unemployment or low wages, amid apparent plenty.
As economist John Maynard Keynes revealed, recessions and depressions can be the result of the market system itself, leaving many in poverty even as raw materials, factories and workers lay idle.
In Australia, our most recent experience of the economic downturn wasn’t caused by a market failure. It stemmed from the public health crisis of the pandemic. Yet it still revealed a potential solution to the economic challenge of technology-fueled abundance.
Changes to government benefits—to increase payments, remove activity tests and ease means-testing—radically reduced poverty and food insecurity, even as the productive capacity of the economy declined.
Similar policies were enacted globally, with cash payments introduced in more than 200 countries. This experience of the pandemic reinforced growing calls to combine technological advances with a “universal basic income.”
This is a research focus of the Australian Basic Income Lab, a collaboration between Macquarie University, the University of Sydney and the Australian National University.
If everyone had a guaranteed income high enough to cover necessities, then market economies might be able to manage the transition, and the promises of technology might be broadly shared.
Welfare, or rightful share?
When we talk about universal basic income, we have to be clear about what we mean. Some versions of the idea would still leave huge wealth inequalities.
My Australian Basic Income Lab colleague, Elise Klein, along with Stanford Professor James Ferguson, have called instead for a universal basic income designed not as welfare, but as a “rightful share.”
They argue the wealth created through technological advances and social cooperation is the collective work of humanity and should be enjoyed equally by all, as a basic human right. Just as we think of a country’s natural resources as the collective property of its people.
These debates over universal basic income are much older than the current questions raised by AI. A similar upsurge of interest in the concept occurred in early 20th-century Britain, when industrialization and automation boosted growth without abolishing poverty, instead threatening jobs.
Even earlier, Luddites sought to smash new machines used to drive down wages. Market competition might produce incentives to innovate, but it also spreads the risks and rewards of technological change very unevenly.
Universal basic services
Rather than resisting AI, another solution is to change the social and economic system that distributes its gains. UK author Aaron Bastani offers a radical vision of “fully automated luxury communism.”
He welcomes technological advances, believing this should allow more leisure alongside rising living standards. It is a radical version of the more modest ambitions outlined by the Labor government’s new favorite book—Abundance.
Bastani’s preferred solution is not a universal basic income. Rather, he favors universal basic services.
Instead of giving people money to buy what they need, why not provide necessities directly—as free health, care, transport, education, energy and so on?
Of course, this would mean changing how AI and other technologies are applied—effectively socializing their use to ensure they meet collective needs.
No guarantee of utopia
Proposals for universal basic income or services highlight that, even on optimistic readings, by itself AI is unlikely to bring about utopia.
Instead, as Peter Frase outlines, the combination of technological advance and ecological collapse can create very different futures, not only in how much we collectively can produce, but in how we politically determine who gets what and on what terms.
The enormous power of tech companies run by billionaires may suggest something closer to what former Greek finance minister Yanis Varoufakis calls “technofeudalism,” where control of technology and online platforms replaces markets and democracy with a new authoritarianism.
Waiting for a technological “nirvana” misses the real possibilities of today. We already have enough food for everyone. We already know how to end poverty. We don’t need AI to tell us.
This article is republished from The Conversation under a Creative Commons license. Read the original article.
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Tech
Framework Has a Better, More Take-Apart-Able Laptop
Framework, the company that makes laptops designed for optimal repairability, announced a new version of its main product, a 13-inch screen laptop. It’s called the Framework Laptop 13 Pro, and it has far better battery life, a touchscreen, a haptic touchpad, and is fitted with Intel processors.
At an event in San Francisco today, Framework CEO Nirav Patel showed off the company’s new tech, opening with a joke about making Framework AI—something the company is very much not doing. Framework’s whole thing, after all, is aiming to give users control over the physical tech they use.
“That industry is fighting for you to own nothing, and they own everything,” Patel said about the AI industry. “We’re fighting for a future where you can own everything and be free.”
Framework used the event to detail other updates coming to its 16-inch laptop. It also showed off previews of an official developer kit and a wireless keyboard for controlling your rig from the couch.
Framework 13 Pro
As the name implies, the 13 Pro is a step up from the company’s last version, the Framework 13. It’s also pricier, starting at $1,199 for a DIY Edition that requires assembling the computer yourself. Pre-built units start at $1,499 but can be upgraded with more features. Framework says it will start shipping the 13 Pro in June.
Framework’s signature move for its products is the ability to take the thing apart. The 13 Pro is made with that ethos in mind, so its parts can be easily swapped out, upgraded, or replaced. Four Thunderbolt 4 interfaces let you pick which ports (USB-C, HDMI, etc.) you want and then choose where to place them. Framework says it planned the laptop with cross-generation compatibility in mind, so current Framebook 13 laptop owners will be able to use new 13 Pro parts like the mainboard, display, and battery, and put them into their existing machine.
The big changes in the guts of the 13 Pro come from Framework’s shift away from using an AMD processor to Intel’s Core Ultra Series 3 processors, which Framework described in its press release as “just insanely efficient.” That efficiency, along with a bigger battery, translates to more than 20 hours of battery life while streaming 4K Netflix videos, at least that’s the claim. That’s almost 12 hours longer than the Framework 13.
Courtesy of Framework
Courtesy of Framework
Tech
OpenAI Beefs Up ChatGPT’s Image Generation Model
OpenAI launched a new image generation AI model on Tuesday, dubbed ChatGPT Images 2.0. This model can generate more than one image from a single prompt, like an entire study booklet, as well as output text, including in non-English languages, like Chinese and Hindi. This release is available globally for ChatGPT and Codex users, with a more powerful version available for paying subscribers.
When any major AI company releases a new image model, it can revive interest and boost usage, especially if social media users adopt a meme-able trend, transforming images of themselves. Last year, Google’s launch of the Nano Banana model was a major moment for the company, especially when users started posting hyperrealistic figurines of themselves online. Earlier this year, ChatGPT Images made waves on social media as users shared AI-generated caricatures.
What’s Different?
Since the new model can tap into ChatGPT’s “reasoning” capabilities, Images 2.0 can search the internet for recent information and generate more than one image at a time. In essence, the bot can use additional steps to output more thorough generations from a single prompt. Images 2.0 also has a more recent knowledge cutoff date: December 2025.
This also means that outputs from the new model are more granular. For example, I generated an infographic with San Francisco’s weather forecast for the next day, as well as activities worth doing. The image ChatGPT generated included accurate weather details for the rainy day, along with accurate-looking drawings of the Ferry Building, Castro Theater, Painted Ladies houses, and Transamerica Pyramid.
Additionally, Images 2.0 is more customizable for users who want unique aspect ratios for image outputs. The new model can generate images, ranging from 3:1 wide to 1:3 tall, and users can adjust the image’s size as part of their prompt to the AI tool.
First Impressions
After a few hours of generating images with the new model, I was generally impressed with the text rendering capabilities, in English at least. Not that long ago, image outputs featuring text, from any of the major models, often included numerous malformed characters or words with errant extra letters. ChatGPT struggled to label images accurately two years prior, so the cleaner, more complex outputs from Images 2.0 are a sign of continued improvement. Google has also focused on improving image outputs featuring text in its recent iterations of Nano Banana.
Tech
Nation states responsible for ‘nationally significant’ cyber attacks against UK, says NCSC chief | Computer Weekly
The UK is facing a “perfect storm” in cyber security as attacks driven by hostile states, combined with advances in artificial intelligence (AI), create new risks to UK infrastructure, the head of the UK’s National Cyber Security Centre (NCSC) will warn on Tuesday.
Hostile nation states are now directly or indirectly responsible for the majority of “nationally significant” cyber security attacks against the UK, running at an average of four per week, Richard Horne, CEO of the NCSC, is expected to say.
A combination of technological change and rising geopolitical tension is creating “tumultuous uncertainty”, as well as opportunities in cyber security, he is expected to say at the NCSC’s CyberUK conference in Glasgow.
Lessons from the battlefield
Russia is taking cyber lessons learned during the war in Ukraine and is deploying “tactics and techniques honed in conflict” against western states, including the UK, Horne will tell conference attendees.
That has led to sustained “hybrid” attacks, which incorporate physical and cyber disruption, targeting the UK and Europe.
“Russia is taking the cyber lessons it has learnt in a theatre of war and is moving them beyond the battlefield,” he will say.
China’s intelligence and military agencies are capable of an “eye-watering level of sophistication” in offensive cyber operations.
The Chinese hacking group Volt Typhoon has targeted multiple operators of critical national infrastructure (CNI) in Asia and across the US, as it pre-positions for future attacks, which could rank among the most severe experienced to date, Computer Weekly has previously reported.
And Iran is “almost certainly” using cyber activity to support the repression of people in Britain who are seen as threats to the Iranian regime.
Iranian state-linked hackers were also identified as being behind the cyber attack on the US medical technology firm, Stryker, in March.
Cyber is an integral part of conflict
Horne is expected to warn that cyber attacks are now an integral part of conflict, and as much a part of modern warfare as drones and missiles.
Groups linked to Russian military and intelligence services were behind a series of cyber attacks on Poland’s energy infrastructure in December 2025, for example.
They targeted two combined heat and power plants and an energy management system for renewable energy.
Cyber security has become “integral to conflict” and will become a new “home front”, Horne is expected to say.
Ransomware without the ransom
In the event of conflict, or near conflict, the UK would likely face cyber attacks “at scale” that would cause similar disruption to ransomware attacks, but without the possibility of recovering data by paying a ransom.
Ransomware attacks on Jaguar Land Rover cost the UK an estimated £1.9bn, while attacks on Marks & Spencer and the Co-op had estimated costs of between £270m and £440m, according to the UK Cyber Monitoring Centre.
Horne will say that defending against such attacks will require every organisation to make cyber security part of their corporate mission and to “build defence in-depth” so that they can remain operational following a successful attack.
Risks from Mythos and frontier AI
Anthropic’s AI model, Mythos, has exposed widespread security vulnerabilities in legacy software that could be exploited by malicious attackers if they became known.
Horne will warn that such “frontier AI” will quickly show where the fundamentals of cyber security need to be addressed.
It will expose poor quality code shipped by software suppliers with significant vulnerabilities, organisations that are not patching their IT systems quickly or widely enough, and those that fail to replace outdated legacy computer systems.
But Horne is expected to argue that there is an opportunity for AI to be a net positive for cyber defence.
Cyber security in space
In the near future, organisations will need to expand cyber security to protect energy systems, production lines, robotics, space-based communications and autonomous AI agents.
Technology that is physically integrated into the human body, including medical devices, will also need to be protected.
Defending against cyber attacks requires a “cultural shift”, and for cyber security and resilience to be seen as a strategic investment, rather than a cost.
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