John Thornhill

The writer is founder of Sifted, an FT-backed site about European start-ups

Ever since the ancient Greeks dreamt up the myth of Prometheus, humanity has been arguing about the dual nature of technology. The fire that Prometheus stole from the gods could warm humans, but also burn us. So it is with the widespread deployment of artificial intelligence systems today. The champions of AI have long argued that this general purpose technology will produce an unprecedented surge in productivity and creativity; its critics fear it carries alarming present-day risks and may even pose an existential threat to humanity in future.

The release last year of powerful generative AI models, such as ChatGPT and Dall-E 2 developed by OpenAI, has reignited that smouldering debate. More than 100mn users have already experienced the weird and wondrous things these types of generative models can do: achieve near-human levels of recognition and replication of text and images, co-create computer code and produce fake viral photos of the Pope in a white puffer jacket.

In a recent post, Bill Gates, the co-founder of Microsoft turned philanthropist, said he watched in “awe” last September as OpenAI’s model aced an advanced biology exam, predicting the technology could bring enormous benefits to the fields of healthcare and education. A research report from Goldman Sachs, published this week, forecast that the widespread adoption of AI could significantly boost labour productivity and increase global annual gross domestic product by 7 per cent.

But the rapid development and increasingly pervasive use of generative AI systems has also alarmed many. Some of Google’s own researchers, such as Timnit Gebru and Margaret Mitchell, were among the first to flag the dangers of the company’s generative AI models baking in existing societal biases, but they were later fired. This week, in an open letter posted by the Future of Life Institute, more than 1,100 signatories, including several prominent AI researchers, amplified the alarm. They called for a six-month moratorium on the development of leading-edge models until better governance regimes could be put in place. Uncontrolled, these machines might flood the internet with untruths, automate meaningful jobs and even threaten civilisation. “Such decisions should not be delegated to unelected tech leaders,” the letter writers said.

At least three threads need to be unpicked amid the controversy. The first, and easiest to dismiss, is the moral panic that accompanies almost every new technology, whether it is steam trains, electricity, motor cars or computers. Even Benjamin Franklin’s invention of the seemingly innocuous lightning rod was initially opposed by Church elders fearing it was interfering with the “artillery of heaven”. As a rule, it is better to debate how to use commercially valuable technologies appropriately than to curse their arrival.

The second is how commercial interests tend to coincide with moral stances. OpenAI started out in 2015 as a non-profit research lab, promising to collaborate with outside partners to ensure the safe development of AI. But in 2019 OpenAI switched to a capped for-profit model, enabling it to raise venture capital funding and issue stock options to attract top AI researchers. Since then, it has attracted big investments from Microsoft and become more of a closed, commercial entity. That said, at least some of the criticisms come from rivals with an interest in slowing OpenAI’s development.

But the third and most important thread is that many serious AI experts, well-acquainted with the latest breakthroughs, are genuinely concerned about the speed and direction of travel. Their concerns are magnified by the trend among some big tech companies, such as Microsoft, Meta, Google and Amazon, to shrink their ethics teams.

As Gates wrote in his post, market forces alone will not tackle societal inequities. Civil society organisations are mobilising fast and some governments are aiming to set clearer regulation. This week, the UK published pro-innovation draft rules on AI, while the EU is drawing up a stiffer directive on controlling the technology’s use in high-risk domains. But for the moment these efforts seem little more than waving a small red flag at an accelerating train.

Unless the companies leading the AI revolution can credibly prove their models are designed to align with humanity’s best interests, they can expect a far fiercer public backlash. Expert independent institutions with the power to audit AI companies’ algorithms, and restrict their use, should be next on the agenda.

The writer is founder of Sifted, an FT-backed site about European start-ups

This year, I have heard several visiting Americans berate Europe for its lack of innovation and entrepreneurial success, with some justification.

Since the beginning of the century, Europe’s share of the top 100 most valuable companies in the world has fallen from 38 to 18, while that of the US has risen from 54 to 61, boosted by the giant west coast tech firms. Part of the reason is that US-style “permissionless innovation” is far more adaptable to disruptive technological change than Europe’s regulation-heavy “upstream governance”, says Andrew McAfee, the Massachusetts Institute of Technology scientist and author.

To defend its technological sovereignty, Europe must “get serious” about building globally relevant tech companies and accept the “radically inegalitarian” outcomes that result, says Alex Karp, the American co-founder of the US data company Palantir. Describing himself as a “classic European progressive” who wants poor people to have “healthcare and teeth”, he argues that the whole European experiment will be in question “if everyone with a high-value revenue is sitting in America”.

While accepting the urgent need to raise their technological game, Europeans answer in two ways. First, they say Europe’s social model is not optimised for maximising gross domestic product so much as eudaimonia, the ancient Greek concept of happiness. On that score, several European countries outperform the US. Europe shows up strongly in the latest World Happiness Report, which asks people how satisfied they are with their lives. Eight European countries, led by Finland, Denmark and Iceland, are among the world’s top 10 happiest nations (Israel and New Zealand are the other two). The US ranks 15th.

That makes some of the US criticism of Europe sound like the question posed by the novelist Jeanette Winterson’s adoptive mother on hearing that her daughter had fallen in love with another woman. “Why be happy when you could be normal?” she asked. If economic “normality” results in societal unhappiness, maybe it is better just to stay happy after all.

The second, more defiant, response is that Europe is finally “getting serious” about tech, albeit in its own patchy, culturally diverse way. Over the past decade, tech-enabled start-ups have exploded across Europe, benefiting from some imported Silicon Valley mindset and methodology. Up until the end of October, last year, early stage European start-ups attracted 31 per cent of total global investment in this sector compared with 33 per cent in the US, according to Atomico’s State of European Tech report. Picking up on the trend, storied US venture capital firms, including Sequoia Capital and Bessemer Venture Partners, have set up shop in Europe.

“Europe really is becoming a tech hotspot,” says Roxanne Varza, director of the Paris tech campus Station F, which has worked with 5,000 start-ups since it opened in 2017. Whereas a decade ago the most ambitious European entrepreneurs would automatically head to Silicon Valley, many are now staying at home and recruiting top-tier talent from around the world, including the US, Varza tells me.

In spite of the global tech market downturn that is hitting the industry, Europe’s upbeat entrepreneurs are quick to list the region’s advantages: some great technical universities, many highly skilled, and relatively cheap, software engineers and plenty of ambition to tackle the world’s biggest problems, such as climate change. But they are equally quick to identify the remaining constraints on growth: an incomplete single market, making it hard to expand across borders, overly restrictive regulations and a later-stage funding gap.

One European country that shows how to combine societal happiness and entrepreneurial dynamism is Sweden, which has one of the highest rates of social mobility in the world and has created more tech unicorns (start-ups valued at more than $1bn) per head than almost any other country.

The idea that the US is the land of opportunity is only true until you want to get into school or pay your healthcare bill, according to Sebastian Siemiatkowski, co-founder of the Swedish fintech giant Klarna and son of Polish immigrants. With free education and free healthcare, Sweden is a “fantastic society” where everyone is equally valued. “It is one country where if you want to make it, it is up to yourself,” Siemiatkowski told me at a Sifted event in Stockholm earlier this month.

At least in some parts of Europe, entrepreneurs succeed because of its social model, not in spite of it. The rest of Europe, and some US critics, should take note.

The writer is founder of Sifted, an FT-backed site about European start-ups

Technology, they say, is about turning the magical into the mundane. A decade ago, digital assistants such as Siri, Alexa and Cortana seemed like astonishing inventions. Nowadays, Microsoft’s chief executive, Satya Nadella, dismisses them as “dumb as a rock”. How quickly will today’s much-hyped generative AI models become similarly humdrum?

On Tuesday, the San Francisco-based research company OpenAI released GPT-4, its latest content-generation model, demonstrating nifty new features, such as helping to calculate a tax return. OpenAI’s launch of its uncannily plausible — if unnervingly flawed — ChatGPT chatbot in November caused a sensation. But in several significant ways, GPT-4 is even more impressive.

The new model is more accurate and powerful and has greater reasoning capabilities. ChatGPT struggles to answer the question: what’s the name of the daughter of Laura’s mother? But, as the philosopher Luciano Floridi found when experimenting, the new GPT-4 model gives the correct answer (Laura, in case you’re wondering) when told the question is a logic puzzle.

Moreover, GPT-4 is a multimodal model, combining both text and images. At the launch event, Greg Brockman, OpenAI’s co-founder, quickly turned a photograph of a handwritten note into a functioning website containing some awful dad jokes. “Why don’t scientists trust atoms?” GPT-4 asked. “Because they make up everything.”

The applications of these generative AI models are seemingly limitless, which explains why venture capital investors are pouring money into the sector. These models are also seeping into all kinds of existing digital services. Microsoft, a big investor in OpenAI, has embedded GPT-4 in its Bing search engine. The payments company Stripe is using it to help detect online fraud. Iceland is even employing GPT-4 to improve local language chatbots. That is surely worth it just to preserve the lovely Icelandic word for computer: tölva, meaning number prophetess.

Big companies, such as Microsoft and Google, will be the first to deploy these systems at scale. But some start-ups see opportunities in arming the smaller battalions. Josh Browder, who runs the robolawyer company DoNotPay, which contests parking tickets, says GPT-4 will be a powerful new tool to help users counter automated systems. His company is already working on embedding it into an app to issue one-click lawsuits against nuisance robocallers. The technology could also be used to challenge medical bills or cancel subscriptions. “My goal is to give power back to the people,” Browder tells me.

Alongside the positive uses of generative AI, however, there are many less visible abuses. Humans are susceptible to the so-called Eliza effect, or falsely attributing human thoughts and emotions to a computer system. This can be an effective way to manipulate people, warns Margaret Mitchell, researcher at the Hugging Face AI company.

Machine learning systems, which can synthesise voices and generate false personalised emails, have already contributed to a surge in imposter scams in the US. Last year, the Federal Trade Commission recorded 36,000 reports of people being swindled by criminals pretending to be friends or family. They can also be used for generating disinformation. It is perhaps telling that China’s regulators have instructed their tech companies not to offer ChatGPT services, seemingly for fear of losing control over information flows.

Much remains mysterious about OpenAI’s models. The company accepts that GPT-4 exhibits societal biases and hallucinates facts. But the company says it spent six months stress-testing GPT-4 for safety and has introduced guardrails through a process known as reinforcement learning from human feedback. “It’s not perfect,” Brockman said at the launch. “But neither are you.”

Furious rows over the training of these models seem inevitable. One researcher has been periodically testing ChatGPT’s “bias” by prompting it to answer political-orientation questions. Initially, ChatGPT fell in the left-libertarian quadrant but has since been moving towards the neutral centre as the model has been tweaked. But, in an online post, the AI researcher David Rozado argues it will be hard to eliminate pervasive societal biases and blind spots reflected on the internet. “Political biases in state of the art AI systems are not going away,” he concludes.

Elon Musk, a founder of OpenAI who later quit the company, has repeatedly criticised “woke AI” and is exploring whether to launch a less restrictive model, according to The Information. “What we need is TruthGPT,” he tweeted. Such rows over bias are only a foretaste of far bigger fights to come.

The writer is founder of Sifted, an FT-backed media company covering European start-ups

In the justifiable, if spicy, words of one veteran tech investor in Israel: “It’s a fricking miracle what we’ve built here.” Over the past three decades, the tiny country of 9mn people, located in a hostile neighbourhood, has shrugged off wars, uprisings and financial crises to create one of the world’s most extraordinary technology hotspots. But the recent lurch away from democracy by Israel’s rightwing coalition government is alarming the country’s celebrated tech entrepreneurs with some now threatening to leave. Is the world’s original start-up nation in danger of turning into a shut-down nation?

To listen to the highly charged rhetoric of many liberal Israeli intellectuals, entrepreneurs and investors, you might think so. The rockstar Israeli historian Yuval Noah Harari has likened the government’s move to restrict the powers of the Supreme Court to an “anti-democratic coup”. The political confrontation, which has triggered mass protests on the streets, has shaken local entrepreneurs and international investors alike and led to a plunge in the value of the shekel. “The tech moguls know that without an independent judiciary and a democratic society, their entire industry is in danger,” Harari wrote in the Washington Post.

On Monday, the three-year-old cloud security start-up Wiz, which has just raised $300mn at an eye-popping valuation of $10bn, became the latest of a string of Israeli-founded tech companies to trumpet the alarm. Wiz said it would not transfer any of the money it had raised to Israel while the political uncertainty continued. The government’s judicial moves endangered the core values of respect for the law and tolerance that underpin Israel’s democracy, Assaf Rappaport, Wiz’s chief executive, told me. “This is more of an existential threat than any missiles.” 

Over many years, Israel’s tech sector has shown astonishing resilience in the face of repeated security threats and has been little distracted by the performative psychodrama of national politics. Its singular focus on building vibrant start-ups, particularly in the fields of enterprise software, security and fintech, has made it the engine of the Israeli economy. Last year, the tech sector accounted for 54 per cent of the country’s exports and employed about one-tenth of the workforce.

Like most other countries, Israel has been hit by the latest tech market downturn, with start-up funding falling by almost half to $15.5bn last year. But that annual total remained the second highest on record and early-stage investment continued to grow in 2022, according to the Start-up Nation Policy Institute. Israel also spends more on research and development as a proportion of GDP — 5.4 per cent — than any other OECD country.

But the government’s judicial power grab has mobilised the tech sector like nothing before. “Restraint has been thrown out the window. Tech people are the muscle behind the protest movement,” another entrepreneur told me. “It’s great that we live in a real democracy as we are seeing today. But the situation is scary as shit.” Some entrepreneurs, such as Rappaport, remain optimistic that a compromise can be reached, clinging to the fact that prime minister Benjamin Netanyahu has been an active champion of Israel’s start-up nation. But others are already hedging their bets, chatting away on messaging groups about the relative merits of relocating to Cyprus, Spain or the US. 

One theory as to why the Israeli tech industry has boomed is because it has perversely benefited from what the historian Mark Zachary Taylor has called “creative insecurity.” Like other small countries facing big security threats, such as South Korea and Taiwan, Israel has made it a strategic imperative to prioritise external security over domestic fights, and technological innovation over wealth redistribution. In his book The Politics of Innovation, Taylor explains how technologically dynamic countries, such as Israel, also rely far more on informal social networks of entrepreneurs and investors than any governmental institutions.

The danger for Israel’s tech sector is that domestic infighting will degrade that creative insecurity and erode the country’s delicate social networks. The veteran investor says it has taken 30 years to build the Start-up Nation but it can be easily damaged. “It has not been built in the ground but in our minds and hearts,” he says. There may be bigger forces at play in Israel than the future of its tech sector. But it would do untold damage to the dynamism of Israel’s economy and its geopolitical security, if the government were to lose those hearts and minds.

The writer is founder of Sifted, an FT-backed media company covering European start-ups

As we now know, generative AI models, such as ChatGPT and DALL-E, are great at making stuff up. Mostly, this is harmless fun, generating faux Beyoncé lyrics or a mock Raphael painting of a Madonna and child eating pizza. Sometimes, however, this ability to “hallucinate” facts generates disinformation and deep fakes.

Ideally, we want machines to make up stuff that is reliable, not just plausible, and to extend the range of human insight. Can we use machine learning models to generate truly novel ideas in hard areas, including mathematics and science, and enrich human creativity? It is beginning to look that way.

First, though, we should define creativity. Margaret Boden, research professor at Sussex university, has three useful classifications: combinational, exploratory and transformational. Creativity can be about mashing together improbable combinations of familiar ideas (think poetic imagery) or exploring new conceptual spaces (think jazz) — the most common forms, she suggests. Machines are pretty good at these pattern recognition and replication tasks, as generative AI models have shown.

But the most elusive, and arguably most valuable, kind of creativity is transformational: generating previously unimagined ideas or concepts. “The ultimate vindication of AI-creativity would be a program that generated novel ideas which initially perplexed or even repelled us, but which was able to persuade us that they were indeed valuable,” Boden wrote in a paper published in 1998.

Since then, machine creativity has failed Boden’s test. But at a recent discussion hosted by the London Institute for Mathematical Sciences, researchers highlighted how machine learning models were beginning to reshape mathematics by generating important new conjectures, subsequently proved to be true, in areas such as knot theory. “The field is at a delicious inflection point: the possibilities have been proven but it has not yet been fully explored,” one participant said.

Mathematics may be a particularly good testing ground for transformational machine creativity. ChatGPT is an impressive linguistic correlation machine, predicting what the next words in any sentence are statistically likely to be. Other types of machine learning models, however, can be trained to generate more substantive, and provable, outputs. “There are no coincidences in pure mathematics. It is either true or not true,” as one participant noted.

According to Alex Davies, the founding lead of the AI for Maths initiative at DeepMind, owned by Google parent Alphabet, machine learning models can help tackle three barriers to creativity: boredom, shame and vision. AI can perform dull, repetitive tasks. They also have no shame in generating apparently dumb, but occasionally inspired, outputs, which humans might be too embarrassed to air.

But the most intriguing aspect is vision. The promise is that machine learning tools can explore mathematical problems in dimensions that humans do not fully grasp. At present, Davies says experts are working with machine learning systems to guide their intuition towards creative results, but he anticipates further progress. “I believe we will eventually see machine learning have a transformational impact in mathematics,” he tells me.

That all sounds highly theoretical. DeepMind has already used machine learning models to predict the 3D structures of more than 200mn proteins. “It’s sort of like unlocking scientific exploration at digital speed,” said Demis Hassabis, co-founder of DeepMind. What does it mean in practice today? Researchers are using these models to help create wholly new proteins and to originate hypotheses for new battery materials. They are also using them to design antiviral drugs.

For the moment, companies in this sector remain mostly “financial optimisation machines”, using machine learning models to streamline processes and maximise earnings, says Martin Reeves, co-author of The Imagination Machine. But he suggests that they will increasingly have to become “imagination machines” that can use machine learning models to boost creativity and develop new products and services. “More than a visionary or a poet, companies imagine things that do not yet exist. We need that imagination more than ever to deal with issues like climate change,” he says.

The artist Pablo Picasso, a prime example of human creativity, is reputed to have said that “computers are useless, they can only give you answers”. Life will become more interesting as they help us formulate original questions.