# AI Virtue: What is "Good" Knowledge in the Age of Artificial Intelligence?

arXiv: https://arxiv.org/abs/2607.01776 · HTML: https://mlsanity.com/paper/2607.01776/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 6 of its 78 references that are in the map.
- First posted on arXiv 2 Jul 2026.

## Builds on (most cited first, 6 of 6)

- [Homogenization Effects of Large Language Models on Human Creative Ideation](https://mlsanity.com/paper/2402.01536/) (2024)
- [Algorithmic Monoculture and Social Welfare](https://mlsanity.com/paper/2101.05853/) (2021)
- [On the Creativity of Large Language Models](https://mlsanity.com/paper/2304.00008/) (2023)
- [Confabulation: The Surprising Value of Large Language Model Hallucinations](https://mlsanity.com/paper/2406.04175/) (2024)
- [Why Slop Matters](https://mlsanity.com/paper/2601.06060/) (2025)
- [Critical Confabulation: Can LLMs Hallucinate for Social Good?](https://mlsanity.com/paper/2511.07722/) (2025)

## Abstract (arXiv)

In the age of AI, what will be good knowledge? This article, which is accepted and forthcoming in a special issue of Modern Fiction Studies on "Cultural AI" in 2027, applies digital humanities methods to map epistemic virtues (like "true," "accurate," "creative") used in a corpus of 553 journal articles on AI published in 2024. "Creativity" comes in for special attention as an example. Exploring this discourse of value, the article considers how a framework might be developed for evaluating the knowledge-worth of AI -- one less locked into values formed around pre-AI "knowledge work" agents or structures, and more open to the future values of "generativity." The essay is supported by an online digital kit for exploring data models of the corpus of articles on AI it studies.