The 'poison AI' movement wants to corrupt ChatGPT and Gemini to make them useless — but it comes with a huge risk of collateral damage
A growing AI data poisoning online movement wants to attack the models themselves. Chatbots already confidently repeat nonsense far too often; now imagine it exponentially worse as text and image generators misunderstand every prompt, and the models become too frustrating to trust.It's not just theory. Data poisoning is an actual area of AI security research.
- ▪A growing AI data poisoning online movement wants to attack the models themselves.
- ▪Chatbots already confidently repeat nonsense far too often; now imagine it exponentially worse as text and image generators misunderstand every prompt, and the models become too frustrating to trust.It's not just theory.
- ▪Data poisoning is an actual area of AI security research.
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| Original publisher | TechRadar |
| Canonical URL | https://www.techradar.com/ai-platforms-assistants/the-poison-ai-movement-wants-to-corrupt-chatgpt-and-gemini-to-make-them-useless-but-it-comes-with-a-huge-risk-of-collateral-damage |
| Publication time | Thu, 06 Aug 2026 16:00:00 +0000 |
| Retrieval time | 2026-08-06T16:05:47.548Z |
| Last seen | 2026-08-06T16:05:47.548Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | E97BJgS_B0tr · 1 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
AI Platforms & Assistants The 'poison AI' movement wants to corrupt ChatGPT and Gemini to make them useless — but it comes with a huge risk of collateral damage Features By Eric Hal Schwartz Published 6 August 2026 Training data poisoning has become both an act of protest and a genuine security concern When you purchase through links on our site, we may earn an affiliate commission. Here’s how it works. (Image credit: Shutterstock) Copy link Facebook X Whatsapp Reddit Pinterest Flipboard Threads Email Share this article 0 Join the conversation Follow us Add us as a preferred source on Google Newsletter Subscribe to our newsletter AI has acquired an unusual new enemy. A growing AI data poisoning online movement wants to attack the models themselves.
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