Singapore investors are reassessing the risks around artificial intelligence after new warnings about the possibility of AI development contributing to human extinction triggered a sell-off i
Singapore investors are reassessing the risks around artificial intelligence after new warnings about the possibility of AI development contributing to human extinction triggered a sell-off in AI-related stocks. The warnings have renewed debate over whether the industry is moving too quickly without enough safeguards.
Fears about the consequences of AI development are not new, but recent warnings have brought the issue back into focus for investors. Anthropic CEO Dario Amodei has called for the industry to slow the pace of frontier AI development so safety measures can catch up. OpenAI CEO Sam Altman, Elon Musk and other AI figures have backed parts of the push, while Nvidia CEO Jensen Huang has argued that AI has moved into a production phase and pushed back against calls for a broad slowdown.
The warnings initially hit AI-linked stocks, particularly chipmakers and companies tied to data-centre spending. But the reaction has not been limited to equities. Bitcoin rose above $77,000 as AI stocks fell on September 14, while gold dropped almost 1% to about $4,300 an ounce. Ether also gained about 1%, suggesting that some money was moving differently across markets as investors reassessed the AI trade.
Source: StraitTimes
The crypto market has already become closely linked to the same liquidity and risk flows that drive technology stocks. Bitcoin and gold had reached unusually high correlation earlier in September, with their 30-day correlation hitting 0.8, according to The Block. Yet the latest AI-driven sell-off produced as a result of Bitcoin rose while technology stocks and precious metals fell.
That does not necessarily mean investors see Bitcoin as a direct hedge against AI risk. The move happened alongside other forces, including oil prices and changing expectations for interest rates. Coinbase Institutional also reported that Bitcoin had recently outperformed gold as the so-called debasement trade shifted toward crypto.
Crypto’s connection to AI is also becoming more complicated. Bitcoin miners have been expanding into AI and high-performance computing because their power infrastructure can be used for data centres. MARA Holdings, for example, has been moving part of its business toward AI infrastructure while continuing to hold Bitcoin. That means a prolonged slowdown in AI spending could eventually affect parts of the crypto industry through the infrastructure side, even if Bitcoin itself remains relatively independent of AI demand.
The debate is no longer between AI supporters and critics. Some of the industry’s most prominent figures are arguing for tighter controls without abandoning development. Amodei has called for safety testing, cooperation between developers and international coordination, while Altman has said OpenAI will use third-party evaluations and publish regular incident reports. Former DeepMind CEO Demis Hassabis and Andrej Karpathy have also supported parts of the safety push.
Others see a slowdown as potentially damaging. Jensen Huang has argued that AI products are now generating real economic value and that the industry has moved beyond its research phase. Meta CEO Mark Zuckerberg has taken a different approach, saying companies have a responsibility to improve safety but rejecting a coordinated slowdown.
That split matters for markets because the outcome does not have to be either “AI stops” or “AI continues unchanged.” JPMorgan Asset Management said a move from expensive model training toward inference could reduce the pace of hardware capital spending while potentially making AI cheaper and more widely adopted. In that scenario, chip and data-centre spending could slow without ending the AI investment cycle.
For investors, the important question is therefore becoming what part of the AI economy they actually own. A slowdown in frontier-model training would affect Nvidia, memory makers and data-centre operators differently from software companies, cybersecurity firms or businesses using AI to reduce costs. The recent market moves suggest that investors are beginning to make those distinctions rather than treating AI as a single trade.
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