Ed Zitron on Big Tech, Backlash, and the AI Boom: “AI Has Taught Us That People Are Excited to Replace Human Beings”
In an era dominated by rapid advancements and soaring expectations about artificial intelligence (AI), Ed Zitron has emerged as an outspoken sceptic whose views challenge the prevailing narratives around generative AI and big tech. The British author, podcaster, and critic has carved a niche with his blunt, brash scepticism, positioning himself as a critical voice amid the AI hype. As concerns mount over the promises and realities of large language models (LLMs), Zitron’s insights resonate with a growing segment of industry insiders and the wider public.
A Contrarian Amid the AI Boom
Zitron’s skepticism dates back to 2023, a year after OpenAI launched ChatGPT, which set the tech world alight with excitement about the future potential of generative AI. However, unlike many optimistic voices, Zitron approached the technology with caution and critical scrutiny. “The more I looked, the more confused I became,” he told The Guardian in a recent interview. “Large language models very clearly did not do the things that people were excited about and they didn’t have any path to doing them either.”
Despite the fanfare around AI’s capacity to transform industries and displace workers, Zitron argues that the technology itself remains fundamentally limited. He points out that LLMs “hallucinate and give wrong answers,” lack consistent learning ability, and produce varying outputs, which challenges the label “intelligence” often assigned to these systems. “It’s intelligent in the same way a pair of dice are intelligent,” Zitron said, highlighting that these models operate on large-scale probability rather than genuine understanding or creativity.
The Limits of AI’s Disruptive Claims
Though some tech executives have made dire predictions about AI’s impact on jobs—like Anthropic’s CEO Dario Amodei, who warned of up to a 50% loss in entry-level white-collar jobs within five years—Zitron remains unconvinced these outcomes are imminent or inevitable. While anecdotal evidence suggests AI tools are aiding workplaces to improve efficiency or reduce staff, Zitron cautions against claiming causation too quickly. He references studies such as a June survey showing a 30% drop in UK entry-level jobs since ChatGPT’s release, but notes a lack of definitive proof linking these declines directly to AI.
Supporting his argument, Zitron points to a recent MIT report revealing that 95% of companies integrating AI into their operations had seen “zero return” on their investments, with many generative AI systems failing to effectively retain feedback or adapt to context. This disconnect between perceived AI potential and commercial reality fuels his prediction that the technology will struggle to fulfill its promises on a meaningful scale.
Questioning the AI Investment Frenzy
Beyond technological limitations, Zitron scrutinizes the economics underpinning the AI boom. He highlights the “magnificent seven” tech giants—Alphabet (Google), Amazon, Apple, Meta, Microsoft, Nvidia, and Tesla—which collectively dominate global stock markets and AI hardware supply chains. Nvidia, the chief supplier of GPUs essential for AI computing, is currently enjoying immense growth. Yet, Zitron warns that aside from Nvidia, many companies are burning through capital at unsustainable rates.
Building AI infrastructure entails massive costs. Establishing a one-gigawatt AI data centre can cost up to $35 billion, requiring vast arrays of expensive GPUs (each costing upwards of $50,000), alongside sophisticated software, networking, and enormous power and water resources. This financial model heavily favors "hyperscalers" such as Google, Microsoft, and Amazon, who possess the deep pockets needed to operate at this scale.
However, Zitron expresses skepticism about revenue streams supporting such investments. For example, OpenAI’s promised investment of $1.4 trillion in infrastructure over five years contrasts starkly with projected revenues of around $20 billion in 2025. Moreover, he highlights circular financial arrangements where companies invest in each other: Nvidia invested $100 billion in OpenAI, which in turn spends heavily on Nvidia chips. This ecosystem of intertwined deals, according to Zitron, obscures an unclear market demand beyond the largest players. “When you remove the hyperscalers, there’s less than a billion dollars total in AI compute revenue in 2025,” he said.
The Future of AI and Its Place in Society
With some 800 million estimated ChatGPT users globally, the majority either use free versions or subscribe at modest rates, raising questions about profitability. Zitron’s critical lens on both technology efficacy and financial sustainability prompts broader debates about the real-world impact of AI and its societal implications.
More than a mere sceptic, Zitron’s voice serves as an essential counterbalance against unchecked AI enthusiasm. He warns that AI has revealed something deep about human nature—our eagerness to replace human workers with machines, often without fully understanding the consequences or the feasibility of such transitions.
As the AI conversation evolves, Ed Zitron stands as an influential, if provocative, voice reminding us to interrogate AI’s promises with rigorous analysis and caution. Whether the so-called “AI bubble” will burst remains uncertain, but Zitron’s blend of sharp critique and detailed investigation ensures he will remain a defining figure in the ongoing dialogue about technology’s role in our future.
