# kaal:claim:5095633-011

**Claim.** As AI-generated content proliferates online it dilutes the diversity and originality of the text pool available for later training, producing performance degradation across successive model generations.

**Type.** mechanism  **Support.** evidenced

**Holds when.**

- repeated training generations drawing on an increasingly synthetic web

**Source quote.**

> As AI-generated content proliferates online, it dilutes the overall diversity and originality of text available for subsequent training processes, potentially leading to a degradation in model performance over repeated generations.

**From.** Wulf A. Kaal, *Artificial Intelligence The Final Frontier* (2025), 2.1.2. Volume and Variety of Data, page 4

**Cite as.** Wulf A. Kaal, Artificial Intelligence The Final Frontier (2025). SSRN: https://ssrn.com/abstract=5095633

**Verify.** sha256 of source PDF `cbb484711f89bcefc9fc6a5730a1ed0a3f764d7999ad9b6f7d8ea05634c26c63` at https://raw.githubusercontent.com/wulfkaal/Academic-Papers/main/papers/pdf/Kaal%20-%202025%20-%20Artificial%20Intelligence%20The%20Final%20Frontier.pdf

**Failure mode.** recursive synthetic dilution  (family: ai-model-and-training-failure)

**Topics.** education-and-practice

**Keywords.** model-collapse, synthetic-data, data-diversity, recursive-training

**Canonical form.** This markdown file is the canonical hashed representation of the claim. Its sha256 is the content hash used for attestation.