2025-11-05 05:39:47
Could a ‘grey swan’ event bring down the AI revolution? Here are 3 risks we should be preparing for
The term "black swan" denotes unforeseen events with significant impacts, while "grey swans" refer to rare but more foreseeable risks that are often inadequately prepared for. Examples of grey swans in the AI industry include security threats from malicious use of AI, legal challenges over intellectual property rights, and technological breakthroughs that could disrupt market stability. These risks highlight the need for greater resilience in应对AI领域的灰天鹅事件,包括来自恶意使用AI的安全威胁、知识产权问题的法律挑战以及可能破坏市场稳定的技术突破。这些风险强调了建立更强韧性的必要性,
为了符合摘要的要求并保持英文表述,以下是精简后的版本:
The term "grey swan" describes rare but foreseeable risks often neglected. In AI, these include security threats from malicious use, legal challenges over IP rights, and disruptive technological breakthroughs. These risks underscore the need for greater resilience in应对AI领域的灰天鹅事件,包括恶意使用带来的安全威胁、知识产权问题的法律挑战以及可能破坏市场稳定的技术突破。这些风险强调了建立更强韧性的必要性,
更简洁版本:
Grey swans represent foreseeable but neglected risks, including security threats from malicious AI use, legal challenges over IP rights, and disruptive technological advancements. These highlight the need for greater resilience in应对AI领域的灰天鹅事件,包括恶意使用带来的安全威胁、知识产权问题的法律挑战以及可能破坏市场稳定的技术突破。这些风险强调了建立更强韧性的必要性,
最终精简:
Grey swans represent foreseeable risks like security threats from malicious AI use, legal challenges over IP rights, and disruptive technological advancements. These highlight the need for greater resilience in应对AI领域的灰天鹅事件,包括恶意使用带来的安全威胁、知识产权问题的法律挑战以及可能破坏市场稳定的技术突破。这些风险强调了建立更强韧性的必要性,
最终版本:
Grey swans represent foreseeable risks like security threats from malicious AI use, legal challenges over IP rights, and disruptive technological advancements. These highlight the need for greater resilience in dealing with AI's unpredictable future.
The term âblack swanâ refers to a shocking event on nobodyâs 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 â
grey swans
â. Derived from
Talebâs work
, grey swans are rare but more foreseeable events. That is, things we know could have a massive impact, but we donât (or wonât) 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 doesnât appear to be a big fan of grey swans. Heâs previously
expressed frustration
that his concepts are often misused, which can lead to
sloppy thinking
about the deeper issues of truly unforeseeable risks.
But itâs hard to deny there is a spectrum of predictability, and itâs 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 âMagnificent Sevenâ US tech stocks â Amazon, Alphabet (Google), Apple, Meta, Microsoft, Nvidia and Tesla â now make up
about 40% of the S&P 500 stock index
.
The impact of a collapse for these companies â and a stock market bust â would be devastating at a global level, not just financially but also in terms of dashed
hopes for progress
.
Jensen Huang, chief executive of Nvidia, which has become the worldâs most valuable company.
Lee Jin-man/AP
AIâs grey swans
There are three broad categories of risk â beyond the economic realm â that could bring the AI euphoria to an abrupt halt. Theyâre grey swans because we can see them coming but arguably donât (or wonât) prepare for them.
1. Security and terror shocks
AIâs 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 âwhite swanâ â a foreseeable risk with relatively predictable consequences â stems from
Chinaâs aggression toward Taiwan
.
The worldâs biggest AI firms depend heavily on
Taiwanâs 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 â 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 vaporise the profits of todayâs industry leaders. We got a glimpse of this possibility in Januaryâs
DeepSeek dip
, when details about a relatively cheaper, more efficient AI model developed in China caused US tech stocks to plummet.
Artificial intelligence investment has driven remarkable growth on stock markets.
Seth Wenig/AP
Why we struggle to prepare for grey 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 doesnât always behave like the past.
The wise among us
apply reason to carefully confirmed facts
and are sceptical 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 â as weâve seen with the worldâs
slow response to climate change
.
How can we deal with grey swans?
Staying aware of risks is important. But what matters most isnât prediction. We need to design for a deeper sort of resilience that Taleb calls â
antifragility
â.
Taleb argues systems should be built to withstand â or even benefit from â 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 grey swans. Some may collide and cause
spectacular destruction
before we can react.