The term “black swan” refers to a shocking event on nobody’s radar until it actually happens. This has become a byword in risk analysis since a book called “The Black Swan” by Nassim Nicholas Taleb was published in 2007. A frequently cited example is the 9/11 attacks.

Fewer people have heard of “gray swans“. Derived from Taleb’s work, gray swans are rare but more foreseeable events. That is, things we know could have a massive impact, but we don’t (or won’t) adequately prepare for.

COVID was a good example: precedents for a global pandemic existed, but the world was caught off guard anyway.

Although he sometimes uses the term, Taleb doesn’t appear to be a big fan of gray swans. He’s previously expressed frustration that his concepts are often misused, which can lead to sloppy thinking about the deeper issues of truly unforeseeable risks.

But it’s hard to deny there is a spectrum of predictability, and it’s easier to see some major shocks coming. Perhaps nowhere is this more obvious than in the world of artificial intelligence (AI).

Putting our eggs in one basket

Increasingly, the future of the global economy and human thriving has become tied to a single technological story: the AI revolution. It has turned philosophical questions about risk into a multitrillion-dollar dilemma about how we align ourselves with possible futures.

US tech company Nvidia, which dominates the market for AI chips, recently surpassed US$5 trillion (about A$7.7 trillion) in market value. The “Magnificent Seven” US tech stocks—Amazon, Alphabet (Google), Apple, Meta, Microsoft, Nvidia and Tesla—now make up about 40% of the S&P 500 stock index.

The impact of a collapse for these companies—and a stock market bust—would be devastating at a global level, not just financially but also in terms of dashed hopes for progress.

AI’s gray swans

There are three broad categories of risk—beyond the economic realm—that could bring the AI euphoria to an abrupt halt. They’re gray swans because we can see them coming but arguably don’t (or won’t) prepare for them.

1. Security and terror shocks

AI’s ability to generate code, malicious plans and convincing fake media makes it a force multiplier for bad actors. Cheap, open models could help design drone swarms, toxins or cyber attacks. Deepfakes could spoof military commands or spread panic through fake broadcasts.

Arguably, the closest of these risks to a “white swan“—a foreseeable risk with relatively predictable consequences—stems from China’s aggression toward Taiwan.

The world’s biggest AI firms depend heavily on Taiwan’s semiconductor industry for the manufacture of advanced chips. Any conflict or blockade would freeze global progress overnight.

2. Legal shocks

Some AI firms have already been sued for allegedly using text and images scraped from the internet to train their models.

One of the best-known examples is the ongoing case of The New York Times versus OpenAI, but there are many similar disputes around the world.

If a major court were to rule that such use counts as commercial exploitation, it could unleash enormous damages claims from publishers, artists and brands.

A few landmark legal rulings could force major AI companies to press pause on developing their models further—effectively halting the AI build-out.

3. One breakthrough too many: innovation shocks

Innovation is usually celebrated, but for companies investing in AI, it could be fatal. New AI technology that autonomously manipulates markets (or even news that one is already doing so) would make current financial security systems obsolete.

And an advanced, open-source, free AI model could easily vaporize the profits of today’s industry leaders. We got a glimpse of this possibility in January’s DeepSeek dip, when details about a relatively cheaper, more efficient AI model developed in China caused US tech stocks to plummet.

Why we struggle to prepare for gray swans

Risk analysts, particularly in finance, often talk in terms of historical data. Statistics can give a reassuring illusion of consistency and control. But the future doesn’t always behave like the past.

The wise among us apply reason to carefully confirmed facts and are skeptical of market narratives.

Deeper causes are psychological: our minds encode things efficiently, often relying on one symbol to represent very complex phenomena.

It takes us a long time to remodel our representations of the world into believing a looming big risk is worth taking action over—as we’ve seen with the world’s slow response to climate change.

How can we deal with gray swans?

Staying aware of risks is important. But what matters most isn’t prediction. We need to design for a deeper sort of resilience that Taleb calls “antifragility“.

Taleb argues systems should be built to withstand—or even benefit from—shocks, rather than rely on perfect foresight.

For policymakers, this means ensuring regulation, supply chains and institutions are built to survive a range of major shocks. For individuals, it means diversifying our bets, keeping options open and resisting the illusion that history can tell us everything.

Above all, the biggest problem with the AI boom is its speed. It is reshaping the global risk landscape faster than we can chart its gray swans. Some may collide and cause spectacular destruction before we can react.

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

Germany’s Volkswagen said on Wednesday it would develop an in-house assisted driving chip for its business in China as it seeks to recover from sagging sales in the world’s largest auto market.

Volkswagen is still the leading foreign group operating in China but the auto giant’s sales have drooped as local brands rise. It is also seeking to insulate itself from global tensions over semiconductors.

The group announced a series of new electric and hybrid vehicles in April and an assisted driving system designed specifically for the Chinese market in an effort to counter that slide.

“We are accelerating and deepening the implementation of our ‘In China, for China’ strategy—moving beyond localized production to mastering the core technologies that shape tomorrow’s mobility,” Ralf Brandstatter, CEO of Volkswagen Group China, said in a news release on Wednesday.

It is the first time the Volkswagen Group has developed its own in-house chip of this sort, a spokesman said.

Responsibility for its design and production will lie with a joint venture between CARIAD, Volkswagen’s software company, and Chinese technology company Horizon Robotics.

Smart driving capabilities have emerged as a key battleground in China’s cut-throat domestic auto market.

Semiconductors have also increasingly become the target of global trade tensions, in particular between the United States and China.

Washington has steadily expanded export controls in recent years, particularly in advanced chips and digital infrastructure.

European automakers have also been rocked by a row between China and the Netherlands over Nexperia chips, which despite being relatively simple in technology terms are nonetheless crucial as vehicles rely more on electronics.

Volkswagen’s aim with the new chip is “taking control of a key technology that will define the future of intelligent driving,” CEO Oliver Blume said in the news release.

“This marks the next logical step in our strategy for outstanding long-term innovation capabilities.”

The chip is expected to be delivered within the next three to five years, the release said.

Asked whether there were plans to eventually use the chip outside the Chinese market, a spokesman said the focus was currently on “localized implementation”.

“Looking ahead, we will align with the Group’s overall strategic roadmap to feed technological achievements from China back into the global business,” he said.

© 2025 AFP

Last month, The US Food and Drug Administration approved a new blood test for assisting the diagnosis of Alzheimer’s disease. Produced by Roche, Elecsys pTau181 measures the concentration of a specific molecule—a phosphorylated form of the tau protein—in the blood. Tau is one of two proteins, the other being amyloid, that become malformed and accumulate in the brains of patients with certain types of dementia. It is believed that the buildup of these proteins interferes with the communication of brain cells, leading to these patients’ symptoms.

The test had already received authorization in July for marketing in Europe and is thus the first early screening system for Alzheimer’s for use in primary care settings approved in the planet’s two major pharmaceutical markets. It is an opener in what should soon become a crowded field, as there are several other tests in advanced stages of testing and approval.

How Do Such Tests Work?

Elecsys pTau181 looks in the blood plasma for a form of the tau protein that has a phosphate group attached, which is often found in elevated amounts in Alzheimer’s patients. This molecule is an indirect marker of the plaques of amyloid and neurofibrillary tangles of tau observed in the brains of patients with the disease.

Some other tests have also been approved, though not for early screening. These assess other biomarkers that relate to these two proteins. One test, called Lumipulse and made by the Japanese company Fujirebio, looks at the ratio between another form of phosphorylated tau (pTau217) and a key protein fragment that forms amyloid plaques (amyloid beta peptide 1-42).

The bottom line is that these tests offer clues to the probable presence of amyloidosis in the brain, which then needs to be diagnosed with greater accuracy using more invasive tests, such as a PET (positron emission tomography) scan and cerebrospinal fluid analysis by lumbar puncture, considered the clinical gold standard for diagnosing amyloid pathology in living patients. Even these, however, come with some degree of uncertainty; true diagnostic certainty can only be had with a post-mortem dissection of the brain.

Why Approve These Tests Now?

In the past, confirmation of an Alzheimer’s diagnosis was not that important, as there were no drugs or therapies that could alter the course of the disease. But with the approval of new Alzheimer’s monoclonal antibody treatments, the landscape has changed in the past few years.

To use these medicines, you need a way to confirm which patients can benefit. And since the drugs ideally yield the best results when used early on in the disease’s progression, a relatively inexpensive and minimally invasive diagnostic test will be extremely useful. Subjecting all elderly people with suspected symptoms of cognitive decline to PET scans and cerebrospinal fluid sampling is impractical, so this is where blood testing for Alzheimer’s comes in.

Just How Useful Are These Tests?

Elecsys pTau181 is the first test to be approved for use as a community-screening tool. The idea is for it to be administered at the primary care level—so, for instance, by a primary care physician or general practitioner. The test has been shown to have a good “negative predictive value”—that is, it is effective at accurately indicating who does not have amyloid disease. In settings where the overall prevalence of amyloid disease is low, a negative result from this test is 97.9 percent reliable. This makes it useful for selecting which patients to put forward for further testing.

The results are similar to those of other tests that have already been approved in recent months, such as Lumipulse from Japan’s Fujirebio, which in trials has shown a negative predictive value of about 97 percent.

However, there is an important limitation to note: for all blood tests for Alzheimer’s, there tends to be a relatively large proportion of patients (15-30 percent is a common estimate) who fall into a gray area of uncertainty, in which the levels of identified biomarkers do not allow for either a positive or a negative answer.