CosAI Releases "AI Shared Responsibility Framework"
The Coalition for Secure AI has introduced the AI Shared Responsibility Framework to clarify accountability in AI systems. This framework addresses the complexities of AI governance that traditional models fail to cover. It establishes clear responsibilities across five layers of AI operations to prevent confusion and liability issues when AI systems cause harm or fail compliance audits.
- ▪The AI Shared Responsibility Framework is designed to clarify accountability across the AI stack.
- ▪It consists of five layers: AI Business and Usage, AI Information, AI Application, AI Platform, and AI Model Provider.
- ▪The framework aims to address accountability gaps that have led to legal challenges for organizations using AI.
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Story provenance
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Record
| Original publisher | Coalition for Secure AI |
| Canonical URL | https://www.coalitionforsecureai.org/whos-responsible-when-ai-goes-wrong-a-new-framework-aims-to-answer-that-question/ |
| Publication time | Fri, 29 May 2026 00:42:52 +0000 |
| Retrieval time | 2026-05-29T00:49:38.880Z |
| Last seen | 2026-05-29T00:49:38.880Z |
| 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 | JFQ2NS5uHE4N |
| 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
Coalition for Secure AI Unveils New Agentic Identity and Security Research Following High-Profile Sessions at RSAC 2026May 6, 2026 May 28, 2026 When an AI system causes harm or fails a compliance audit, the finger-pointing starts almost immediately. The model provider blames the configuration. The cloud provider points to the tenant. The application team cites model limitations. Our new AI Shared Responsibility Framework is designed to end that cycle before it starts. Most organizations have spent years building clear lines of ownership around their technology stacks. They know who owns the network, who owns the application layer, who calls the vendor when something breaks at 2 a.m. AI has complicated all of that. The problem is not that AI systems are inherently ungovernable.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Coalition for Secure AI.
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