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Today’s piece was originally published in Oligarch Watch, Popular Information’s sister publication. We are living in an age of unprecedented wealth concentration. Oligarch Watch produces accountability journalism on the world’s wealthiest people.
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— Judd
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A Peter Thiel-funded startup launched this month will use an “AI jury” to “subject the media’s claims to systematic investigation and judgment.” That same system of AI adjudication assigns a numerical value — the so-called “Honor Index” score — grading the trustworthiness of individual reporters. And for a starting price of $2,000, anyone can pay for the company to review and adjudicate complaints they may have about a news outlet or reporter.
Objection AI was founded by Aron D’Souza, a lawyer best known for leading the Thiel-funded lawsuit that bankrupted the digital news outlet Gawker in 2016. D’Souza has described Objection as a private arbitration court, which individuals can turn to when they feel they have been unfairly maligned by reporters or pundits. “Your reputation takes years to build and seconds to destroy online,” the company wrote in a recent post on X. “Objection makes adjudication fair, fast, and affordable.”
The company is funded with millions of dollars in funding from Thiel, former Coinbase CTO Balaji Srinivasan, and other investors.
Although it carries no legal or formal weight, Objection has put significant effort into making its judgments appear authoritative.
Its AI jurors are fed information and evidence gathered by human investigators whose collective work history the company frequently cites as a source of legitimacy. We have “a team of FBI, CIA, former agents, who will investigate the story that’s been written… line by line, sentence by sentence,” D’Souza told a British news show earlier this month.
For those unmoved by spycraft, Objection hypes the purported capabilities and impartiality of its AI jury, which is comprised of models from xAI, Anthrophic, OpenAI, Google, and Mistral.
“Artificial intelligence adjudicates through a scalable, auditable, incentive-free process,” the company states on its website. “Diverse foundational models debate adversarially - advocates build cases, cross-examiners expose flaws, a neutral ensemble verifies with explicit standards and Bayesian reasoning… AI can be trained to exclude emotion, bias, and ideology. Model diversity cancels blind spots. And it never gets tired.”
Objection also leans heavily on judicial trappings to dress up its reviews, including case numbers and official-sounding case names. “Public v The Wall Street Journal,” reads a label that Objection assigned to its pending investigation of a story the paper published on Donald Trump’s relationship with Jeffrey Epstein.
To promote Objection, D’Souza has claimed that leading AI models apply “law consistently 100% of the time,” adding, “It’s become obvious that lawyers are probably the most displaceable profession, but judges are, too.” However, large language models used by lawyers frequently produce factual errors and hallucinations filed in court. Last week, Sullivan & Cromwell, a top Wall Street law firm, had to apologize after it submitted a key filing that contained erroneous case citations generated by AI.