People are increasingly turning to AI for advice, and the numbers come first.
A 2026 Pew report found that 10% of Americans are using chatbots for emotional support or companionship. The same report said some users even find a charismatic leader in AI. Separately, a large-scale study of 1.1 million ChatGPT conversations found that 49% of the messages involved users seeking 'information or advice' to help them be 'better informed or make better decisions.'
The pattern is not limited to ordinary questions. In 2021, Ask Delphi, an AI-based website where people could pose ethical or moral questions, received 3 million queries in a few weeks. The system's designers, researchers at the Allen Institute for AI and the University of Washington, said they did not intend it to be a moral authority, but worried that users might see it that way.
The piece draws a line between modern chatbots and older forms of divination. It says the ancient idea of an oracle has resurfaced in discussions about conversational AI, and argues that modern AI is increasingly consulted about difficult questions that exceed the judgment or knowledge of any individual.
The authors say the resemblance goes deeper than the questions people ask. They argue that the processes through which AI arrives at an answer are inscrutable not just to users but also to the designers of these systems, and that this opacity is part of the reason people perceive these systems as having authority.
The article also points to historical examples. It cites the Delphic oracle in Ancient Greece, the I Ching in China, the Ram Shalaka oracle based on the Ramcharitmanas, and Christian bibliomancy, in which a person opens the Bible at random and interprets the passage as an answer.
The market has already voted on convenience, but not yet on trust. When a system starts to function like a private oracle, the question is no longer only what it can answer. It is who gets to decide how much authority an opaque machine should have over human judgment.
Capital rewards clear rules, and that principle is not optional in the age of AI. If users cannot understand how a system reaches its conclusions, then confidence becomes fragile, and the burden falls on developers to prove that 'black box' power is not becoming a substitute for accountability.
