A dean of libraries explains how AI gives you 4 types of answers — and only one of them is ‘factual’

I recently typed a simple question into Google search: How much screen time is too much for teenagers? Instead of presenting links, as Google had been doing for many years, it gave me an AI-generated answer.

The artificial intelligence agent cited a number, then complicated that reply, noting that quality and balance of time could matter more than the number of hours, and that “too much” time could depend on a teenager’s sleep, exercise, school demands and mood.

I tried another search: Should I take a daily aspirin? This time the AI answer presented me with medical information, warned about risks and offered more tailored guidance if I provided my age and medical history.

These were good replies.

What interested me was that they were different kinds of replies.

Debate about AI answers has focused on accuracy: Did the system get the answer right? That matters, but accuracy is only one test.

Each kind of answer requires a user to judge something different.

I find it useful to sort AI answers into an “answer typography” of four broad types: factual, interpretive, constructive and strategic.

A factual claim can often be checked against a source.

An interpretation can be accurate and still reflect choices about which evidence matters.

A construction can be well reasoned and still be wrong for the person receiving it.

A beautifully written strategic document may not be true.

Yet AI presents all four types of answers in much the same fluent, authoritative form; the differences are easy to miss.

I’m university librarian and dean of libraries at the University of Virginia who leads national efforts to develop AI competencies for library professionals, and I consult widely on AI literacy .