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NewsMaterial4 min readDisconfirmAI Editorial

Diginomica Editor Chris Middleton: The AI Chaos Cannot Be Blamed Solely on Vendors; Users Are Also to Blame

In a commentary published on October 26, 2026, Diginomica editor Chris Middleton argues that the discussion of AI risks should not focus solely on vendors' data scraping; unverified professional use by users also constitutes a systemic risk.

2026-10-26 19:20 GMT+8

People are accustomed to blaming AI chaos on vendors' unrestrained data scraping, but Diginomica editor Chris Middleton believes there is also a "Wild West" on the user side: lawyers, consulting firms, publishers, and news organizations angrily condemn vendors while simultaneously embedding AI into their professional workflows without verification.

Middleton cites a large-scale audit published in The Lancet in July 2026 to quantify the severity of the problem. The Lancet conducted a reference integrity check on 2.5 million biomedical papers and found that 4,046 fabricated references were contained within 2,810 papers. More critically, the rate of degradation has accelerated: in 2023, approximately one in every 2,828 papers contained at least one fabricated reference; by 2025, this had risen to one in 458; and in the first seven weeks of 2026, it reached one in 277. The fabrication rate increased from approximately four per 10,000 papers in 2023 to 51.3 per 10,000 papers in the fourth quarter of 2025, reaching 56.9 per 10,000 papers in early 2026—an increase of more than 12 times over three years.

The Lancet explains in its paper that fabricated references may stem from paper mills, intentional misconduct, or the uncritical use of AI writing tools. Large language models generate references that sound plausible but do not actually exist; this is a well-documented failure mode. Previous studies estimate that 30% to 69% of LLM-generated references in the biomedical field are fabricated. These references are often correctly formatted, attributed to real researchers, and bear plausible publication dates, making them difficult to detect through conventional peer review.

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Middleton argues that this degradation has self-reinforcing characteristics.

He further lists cross-industry failure cases: researcher Damien Charlotin’s real-time database has recorded over 2,200 instances of lawyers submitting fake AI case law in court, with more than 100 new cases added monthly and no sign of slowing down; all four Big Four accounting firms—KPMG, Deloitte, EY (Ernst & Young), and PwC (PricewaterhouseCoopers)—have been exposed or accused of publishing research reports containing hallucinated citations. Industry publication Consultancy stated that they have "all been caught passing off generative content as thought leadership." Specific cases include: in May 2026, EY Canada retracted a report on loyalty scheme fraud due to numerous AI-generated references; in October 2025, 40 out of 45 citations in a PwC report were determined to be fake by GPTZero; later that same year, Deloitte partially refunded the Australian government for a report filled with AI hallucinations.

What alarmed Middleton most was an account relayed by a structural engineer in London. This senior engineer, who works on major construction and restoration projects, told him that he now receives building specification documents written by ChatGPT every week, which contain incorrect load calculations and dangerous material combinations. He described the situation as "terrifying," especially given that roles like his are themselves on the front lines of automation and cost-cutting pressures. Middleton then asked: What would happen if such an engineer were no longer part of the review process for a major project?

Middleton’s conclusion is that responsible AI use can only come from a strategic decision—to use technology to solve quantifiable problems within the scope of an organization’s mission, otherwise do not use it at all. It will never come from tactical impulses to follow suit hastily because everyone else is doing so, nor from the myths of immediate financial, time, and productivity gains painted by marketing departments.

It should be noted that Middleton’s argument relies on secondary sources he compiled: The Lancet data was cited via Forbes, the Charlotin database and GPTZero reports are third-party tools, and the story of the structural engineer is an anonymous relay that cannot be independently verified. His core claim—that the lack of professional responsibility on the user side constitutes a systemic risk—is an attribution argument supported by evidence, rather than an empirical study with identified causality. Furthermore, in some professional scenarios, the process of AI-assisted drafting followed by item-by-item expert review does not necessarily constitute the unverified "Wild West" usage criticized by Middleton.

Middleton’s final sentence is: In the face of AI, we all need to be much smarter, much smarter.

Sources

  • diginomica.comdiginomica↗
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