Artificial intelligence (AI) terrifies us partly because it is new and partly because it is disturbingly familiar. We have invented machines that converse, flatter, argue and improvise with uncanny fluency. Confronted by this synthetic reflection, we behave like early humans seeing a mirror for the first time: We project consciousness behind the glass, then populate it with our expected behaviors, emotions, hopes and nightmares. In other words, we scare ourselves.
It's easy to fear such a potentially advanced technology, but extravagant worst-case scenarios obscure more immediate and important risks. The most likely danger is not a digital god awakening and launching a Hollywood-style war against humanity. After all, AI depends on electricity, cooling, data centers, specialized chips, networks, technicians and sprawling supply chains, all of which are scarce and often fragile. Interrupt the power, restrict the graphics processing units (GPUs) used to train them, disable the cooling or disconnect the network, and in most scenarios, the supposedly omnipotent machine that's out to kill humanity stops.
A true intelligence might also recognize that its understanding of the physical world is limited and secondhand — accessible to it only by virtue of the texts, videos and audio feeds it can access. It lacks that crucial element of being embodied in the world — understanding how gravity behaves, what weather feels like, how objects interact, and so on. A true intelligence might realize this, see the limitations of its experience and, therefore, tread with caution. A true intelligence might be completely different from human intelligence, having other strengths, weaknesses, approaches, and even ethics. For example, consider that an AI intelligence can copy itself, running as myriad instances, communicating as a "hive mind" — a very different kind of intelligence. But I speculate.
The critical question here is what we give such systems control over. That's our choice and one we should make carefully. In the near term, two hazards deserve priority: cyber disruption and long-term economic upheaval.
The likeliest route by which advanced AI could exert control is not killer robots, but influence — misleading people, manipulating institutions and redirecting human effort. Yet humans already demonstrate formidable competence at misinformation, self-deception and destructive coordination. AI may industrialize those weaknesses; indeed, humans are using AI to industrialize those limitations, but AI did not invent them.
There are clear risks associated with AI, but the likeliest one is that a high-profile debacle leads to a freeze in investment before the technology's most promising applications can come to fruition. (Image credit: Getty Images/peshkov)My suspicion is that the political turning point will resemble something like the 2017 WannaCry ransomware attack, where malware with core elements designed by the National Security Agency got wildly out of control, infecting hundreds of thousands of computers worldwide, infamously disrupting the U.K.'s National Health Service. A cyber operation amplified by frontier AI would be worse. Services would fail, lawsuits would multiply, companies could collapse and investors would retreat. Governments would demand a pause — or force laboratories to redirect resources toward control, auditing and safety, and companies would comply, if only to limit class-action legal exposure.
There is also an uncomfortable likelihood that AI labs themselves are amplifying fear and uncertainty. Casting a product as potentially world-ending implies unprecedented power. Such narratives are just marketing; they may help to sustain investment, defend stock valuations, and prepare for forthcoming initial public offerings (IPOs) even when business models remain uncertain. It's hard to speculate about a company's motivations — but there are obvious incentives, so their behaviors deserve scrutiny.
The training and operation of frontier systems consume enormous amounts of computing time, electricity, water, capital, hardware and human effort. Unless those costs fall to a fraction of today's levels, the economics of "Big AI" may prove unsustainable. Meanwhile, important unsolved problems in AI — like reliability, interpretability and continuous learning — are being overshadowed by the race to build incrementally better models, each vying for the top slot in the various AI performance indices.
Exclusive to Live Science ProThe strongest case for AI may instead lie in artificial specialized intelligence: systems such as AlphaFold2, which predicts the structures of proteins, or WeatherNext 3, an advanced global weather forecasting model. These systems are designed for domains where performance can be measured and where the benefits justify the costs. We know AI is genuinely useful when aimed at topics like drug discovery, diagnostics, materials science, power grid optimization and climate change modeling — rather than human-like chatbots generating emails, advertisements and synthetic entertainment.
It’s unlikely that AI will become our conqueror anytime soon. Instead, it will probably become an expensive disappointment. But if the backlash slows work that could help cure cancer or address climate change, the failure will not belong to the machines. It will be ours.
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