--- title: "awesome-ai-safety vs sad" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/giskard-ai-awesome-ai-safety-vs-lrudl-sad" tools: ["giskard-ai-awesome-ai-safety", "lrudl-sad"] --- # awesome-ai-safety vs sad *GraphCanon updated Sep 20, 2026* ## Verdict Pick awesome-ai-safety if awesome-ai-safety is a curated list of papers and technical articles focused on ensuring AI quality and safety across various machine learning domains including CV and NLP; pick sad if situational Awareness Dataset is a resource for llm-evaluation and ml topics under CC-BY-4.0 license. [awesome-ai-safety](https://giskard.ai) reports 221 GitHub stars, 41 forks, and 20 open issues, last pushed Apr 14, 2025. [sad](https://situational-awareness-dataset.org/) has 55 stars, 8 forks, and 5 open issues, last pushed Dec 14, 2024. Figures are from public GitHub metadata via [awesome-ai-safety's repository](https://github.com/Giskard-AI/awesome-ai-safety) and [sad's repository](https://github.com/LRudL/sad). | | [awesome-ai-safety](/tools/giskard-ai-awesome-ai-safety.md) | [sad](/tools/lrudl-sad.md) | | --- | --- | --- | | Tagline | A curated list of papers and technical articles on AI Quality & Safety | Situational Awareness Dataset | | Stars | 221 | 55 | | Forks | 41 | 8 | | Open issues | 20 | 5 | | Language | - | HTML | | Adopt for | awesome-ai-safety is a curated list of papers and technical articles focused on ensuring AI quality and safety across various machine learning domains including CV and NLP. | Situational Awareness Dataset is a resource for llm-evaluation and ml topics under CC-BY-4.0 license. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | CC-BY-4.0 | | Categories | Evaluation & Observability | Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [awesome-ai-safety](/tools/giskard-ai-awesome-ai-safety.md) | [sad](/tools/lrudl-sad.md) | | --- | --- | --- | | Days since push | 504d | 634d | | Open issues (now) | 20 | 5 | | Stars delta | +1 (30d) | +2 (30d) | | Open issues delta | +3 (30d) | 0 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/giskard-ai-awesome-ai-safety/trust.md) | [trust report](/tools/lrudl-sad/trust.md) | ## Decision facts: awesome-ai-safety - **Pricing:** freemium - The repository is free to use under the Apache-2.0 license. However, external resources linked might have their own licensing terms or costs. - **Adopt for:** awesome-ai-safety is a curated list of papers and technical articles focused on ensuring AI quality and safety across various machine learning domains including CV and NLP. ## Decision facts: sad - **Adopt for:** Situational Awareness Dataset is a resource for llm-evaluation and ml topics under CC-BY-4.0 license. ## Choose when ### Choose awesome-ai-safety if… - License: awesome-ai-safety is Apache-2.0, sad is CC-BY-4.0. - Pricing: The repository is free to use under the Apache-2.0 license. However, external resources linked might have their own licensing terms or costs.. - Tags unique to awesome-ai-safety: ai, ai-alignment, ai-quality, ai-safety. - When you need an aggregated source to explore topics such as AI alignment, robustness, fairness in ML models. ### Choose sad if… - License: sad is CC-BY-4.0, awesome-ai-safety is Apache-2.0. - Tags unique to sad: dataset, llm-evaluation, ml. - When Python 3.12 or similar recent versions are available ## When NOT to use awesome-ai-safety - Not suitable if your requirement is a repository with hands-on coding examples rather than research papers and articles. - Avoid this resource if you are searching for datasets or tools that are not in the form of academic literature but practical utilities. - This platform may not provide sufficient guidance on hardware-specific testing, where practical constraints diverge from theoretical models. ## When NOT to use sad - If you require a tool with interactive features beyond dataset provision - In environments restricted to languages other than HTML and Python ## Common questions ### What is the difference between awesome-ai-safety and sad? awesome-ai-safety: A curated list of papers and technical articles on AI Quality & Safety. sad: Situational Awareness Dataset. See the comparison table for live GitHub stats and shared categories. ### When should I choose awesome-ai-safety over sad? Choose awesome-ai-safety over sad when License: awesome-ai-safety is Apache-2.0, sad is CC-BY-4.0; Pricing: The repository is free to use under the Apache-2.0 license. However, external resources linked might have their own licensing terms or costs.; Tags unique to awesome-ai-safety: ai, ai-alignment, ai-quality, ai-safety; When you need an aggregated source to explore topics such as AI alignment, robustness, fairness in ML models. ### When should I choose sad over awesome-ai-safety? Choose sad over awesome-ai-safety when License: sad is CC-BY-4.0, awesome-ai-safety is Apache-2.0; Tags unique to sad: dataset, llm-evaluation, ml; When Python 3.12 or similar recent versions are available. ### When should I avoid awesome-ai-safety? Not suitable if your requirement is a repository with hands-on coding examples rather than research papers and articles. Avoid this resource if you are searching for datasets or tools that are not in the form of academic literature but practical utilities. This platform may not provide sufficient guidance on hardware-specific testing, where practical constraints diverge from theoretical models. ### When should I avoid sad? If you require a tool with interactive features beyond dataset provision In environments restricted to languages other than HTML and Python ### Is awesome-ai-safety or sad more popular on GitHub? awesome-ai-safety has more GitHub stars (221 vs 55). Stars measure visibility, not whether either tool fits your constraints. ### Are awesome-ai-safety and sad open source? Yes - both are open-source projects on GitHub (awesome-ai-safety: Apache-2.0, sad: CC-BY-4.0). ### Where can I find alternatives to awesome-ai-safety or sad? GraphCanon lists graph-backed alternatives at [awesome-ai-safety alternatives](/tools/giskard-ai-awesome-ai-safety/alternatives) and [sad alternatives](/tools/lrudl-sad/alternatives) ([awesome-ai-safety markdown twin](/tools/giskard-ai-awesome-ai-safety/alternatives.md), [sad markdown twin](/tools/lrudl-sad/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/giskard-ai-awesome-ai-safety-vs-lrudl-sad.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, awesome-ai-safety or sad? awesome-ai-safety: Dormant. sad: Dormant. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for awesome-ai-safety and sad? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [awesome-ai-safety trust report](/tools/giskard-ai-awesome-ai-safety/trust); [sad trust report](/tools/lrudl-sad/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=giskard-ai-awesome-ai-safety`](/api/graphcanon/graph?tool=giskard-ai-awesome-ai-safety) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_