Shopping is where AI confidence goes to embarrass itself. Ask a frontier model for a gift, a replacement part, a budget-friendly product, or a game recommendation, and the answer often looks excellent. It is neatly formatted. It gives reasons. It may even include links and prices, because apparently nothing says “trust me” like a fabricated discount on a product page that no longer exists. ...
A customer asks your AI assistant to “find me a better phone contract.” The agent browses comparison sites, selects a cheaper plan, authorizes the switch, cancels the old plan, and arranges payment of the cancellation fee from the user’s bank account. Lovely, in the way a self-driving forklift is lovely: impressive until it nudges the wrong shelf. ...
TL;DR for operators Dinner plans are where elegant recommender theory goes to be quietly embarrassed. Five people do not usually open a dedicated app, rate every restaurant, agree on a utility function, and wait for a ranked list to descend from the heavens. They argue in a chat. They change their minds. Someone forgets the budget. Someone says “anything is fine” while absolutely not meaning it. Someone else proposes a venue that is closed on Mondays. Humanity, as usual, remains a hostile runtime environment. ...
TL;DR for operators Most AI product debates still treat “control” as a single slider: more automation on the right, more human control on the left. Convenient, tidy, and wrong in exactly the way tidy models usually are. The MOSAAIC paper argues that control in human-AI co-creation has at least three separable dimensions: autonomy, or who can choose creative actions; initiative, or who can proactively contribute; and authority, or who can decide and direct the process.1 This matters because a system can be highly autonomous but still reactive, proactive but not authoritative, or authoritative in small tactical ways while leaving the human responsible for the final artifact. ...