Something has begun to move in the same direction across places that have nothing to do with one another. A company that started by encrypting email now builds an entire parallel infrastructure — calls, files, calendars, even an assistant — on the single premise that none of it should be read, stored, or learned from. A writer leaves the platform that had grown his audience and moves his work to one running on solar-powered servers at the far end of another continent, where t

A pattern has emerged across the 2026 commencement season in the United States. Speakers who have praised artificial intelligence from the podium have been met with boos. At the University of Arizona, the former chief executive of Google was interrupted by the graduates as he turned to the subject. At the University of Central Florida, a real estate executive who described the rise of artificial intelligence as the next industrial revolution drew the same response, audible en

Of the four worlds the Decision-Maker occupies — wealth, art, philanthropy, lineage — the last is the most recorded, and the most full of deliberate gaps. Genealogy, the reading of the lineage, is the discipline in which what is missing matters most. Mass AI and the genealogical platforms handle the surface fluently. They assemble names, dates, places. They suggest records, propose matches, extend a tree backward with apparent confidence. For a documented family, they will pr

The Decision-Maker lives in four worlds — wealth, art, philanthropy, lineage. Art is the most visible of them — and a collection is never a list of works. It is a personal statement, the most visible thing about its owner, and the most easily misread. Mass AI handles the surface fluently. It identifies the artists, places them within movements, locates them in market trajectories, summarises critical reception. A Decision-Maker asking what a particular work is, or what a part

The Decision-Maker lives in four worlds — wealth, art, philanthropy, lineage. Wealth is the most documented, and the most easily misread. Mass AI handles the vocabulary fluently. Discretionary trusts, family limited partnerships, holding structures, jurisdictional layering, generation-skipping vehicles — the terms are explained with confidence, the mechanisms described with precision. A Decision-Maker asking what a particular instrument is, or how it generally functions, will

Mass AI can answer almost any specialist question. That is precisely what makes it so easy to mistake for a specialist. The Decision-Maker asks a particular question — about a collection, a structure, a lineage, a foundation — and a credible-sounding response arrives. The answer is fluent. It uses the right vocabulary. It cites the right references. It satisfies the form of the question. On the strength of that fluency, the instrument is taken to be specialist. It is not. It