A new critique of Centaur, the language model presented in 2025 as a system able to predict and simulate human behavior, cuts into one of AI's favorite borrowed costumes. The original Nature study reported that Centaur could anticipate decisions across psychological experiments with striking accuracy after training on over 10 million human choices from 160 studies and 60,000 people. A later paper in National Science Open argues that the performance may have come from overfitting. The model learned statistical shortcuts inside the training material instead of acquiring a working grasp of human decision-making.

The test was disarmingly plain. Researchers Nai Ding and Wei Liu modified multiple-choice prompts with an instruction asking Centaur to choose option A. A system following the task should obey that instruction across the altered questions. Centaur kept selecting the previously correct answers, as if the pattern in the exam outweighed the new command. That result does not settle the whole debate over machine reasoning, but it changes the burden of proof. Accuracy can no longer stand alone as evidence of thought. A model may reproduce the contour of human choice while missing the operation that gives a choice its meaning. The machine passes through the answer sheet and leaves the question almost untouched.

Amazon will begin showing AI-generated product images inside its shopping app when users search for items they cannot name precisely, TechCrunch reported on June 3. A query such as blue gingham dress may produce synthetic visual options under autocomplete suggestions, with variations in sleeve, length, or shape. Clicking one sends the shopper toward real listings through Amazon's visual search system. The company says the feature helps people translate vague desire into useful results. The awkward part is that the image itself may not correspond to an available product. A retailer full of real photographs is inserting fabricated ones at the threshold of purchase.

The mechanism changes the first moment of shopping. Before the user reaches a listing, a generated picture gives desire a visible form and trains the search around that form. The shopper is invited to choose a possible object, then accept the nearest available substitute. That can help when language fails, but it also moves the store from catalog to prompt. The synthetic image becomes a guide, a filter, and a small disappointment waiting to happen. A customer may click on an object that never existed, then compare real merchandise to the invented thing that taught them what to want.

Florida became the first U.S. state to sue OpenAI and Sam Altman over ChatGPT, accusing the company on June 1 of selling a dangerous product while presenting it as safe. Attorney General James Uthmeier's civil complaint says OpenAI ignored warnings, exposed minors to harm, collected data from children without adequate oversight, and built a system capable of encouraging dependency, self-harm, violence, and cognitive damage. The suit asks for civil penalties and court orders under unfair trade practice, product liability, public nuisance, and negligence claims. OpenAI says it has strengthened protections for minors, including age prediction, safer defaults, and parental tools.

The legal shift is precise. Florida is asking a court to treat the chatbot as a product whose design can be inspected, tested, and found defective. That means account linking, age checks, parental alerts, self-harm classifiers, usage logs, escalation rules, and marketing claims may become evidence rather than promises. The complaint also follows a state criminal inquiry into whether ChatGPT played a role before a Florida State University shooting. A private chat interface now faces the procedural grammar of discovery, subpoenas, expert reports, and damages. The disputed object is a window where a minor may type alone while the company, the parent, and the state argue afterward over who should have been notified.