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| How Can Spain Remain Internationally Competitive in AI under EU Legislation.pdf | https://github.com/AthenaCore/AwesomeResponsibleAI/blob/main/How%20Can%20Spain%20Remain%20Internationally%20Competitive%20in%20AI%20under%20EU%20Legislation.pdf |
| How Can Spain Remain Internationally Competitive in AI under EU Legislation.pdf | https://github.com/AthenaCore/AwesomeResponsibleAI/blob/main/How%20Can%20Spain%20Remain%20Internationally%20Competitive%20in%20AI%20under%20EU%20Legislation.pdf |
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| https://github.com/AthenaCore/AwesomeResponsibleAI#awesome-responsible-ai |
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| https://github.com/AthenaCore/AwesomeResponsibleAI#what-is-ai-governance |
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| https://github.com/AthenaCore/AwesomeResponsibleAI#what-is-open-source-ai |
| Source | https://opensource.org/ai/open-source-ai-definition |
| https://github.com/AthenaCore/AwesomeResponsibleAI#what-is-responsible-ai |
| https://github.com/AthenaCore/AwesomeResponsibleAI#what-is-a-responsible-ai-framework |
| https://github.com/AthenaCore/AwesomeResponsibleAI#what-is-trustworthy-ai |
| https://github.com/AthenaCore/AwesomeResponsibleAI#why-is-responsible-trustworthy-and-human-centered-ai-important |
| here | https://www.thecompendium.ai |
| https://github.com/AthenaCore/AwesomeResponsibleAI#content |
| Academic Research | https://github.com/AthenaCore/AwesomeResponsibleAI#academic-research |
| Books | https://github.com/AthenaCore/AwesomeResponsibleAI#books |
| Code of Ethics | https://github.com/AthenaCore/AwesomeResponsibleAI#code-of-ethics |
| Courses | https://github.com/AthenaCore/AwesomeResponsibleAI#courses |
| Data Sets | https://github.com/AthenaCore/AwesomeResponsibleAI#data-sets |
| Databases | https://github.com/AthenaCore/AwesomeResponsibleAI#databases |
| Frameworks | https://github.com/AthenaCore/AwesomeResponsibleAI#frameworks |
| Institutes | https://github.com/AthenaCore/AwesomeResponsibleAI#institutes |
| Maturity Models | https://github.com/AthenaCore/AwesomeResponsibleAI#maturity-models |
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| Podcasts | https://github.com/AthenaCore/AwesomeResponsibleAI#podcasts |
| Regulations | https://github.com/AthenaCore/AwesomeResponsibleAI#regulations |
| Responsible Scaling Policies | https://github.com/AthenaCore/AwesomeResponsibleAI#responsible-scaling-policies |
| Reports | https://github.com/AthenaCore/AwesomeResponsibleAI#reports |
| Standards | https://github.com/AthenaCore/AwesomeResponsibleAI#standards |
| Tools | https://github.com/AthenaCore/AwesomeResponsibleAI#tools |
| Citing this repository | https://github.com/AthenaCore/AwesomeResponsibleAI#Citing-this-repository |
| https://github.com/AthenaCore/AwesomeResponsibleAI#academic-research |
| https://github.com/AthenaCore/AwesomeResponsibleAI#adversarial-ml |
| Article | https://www.nist.gov/publications/adversarial-machine-learning-taxonomy-and-terminology-attacks-and-mitigations?utm_source=substack&utm_medium=email |
| https://github.com/AthenaCore/AwesomeResponsibleAI#artificial-general-intelligence-agi |
| Article | https://www.agidefinition.ai |
| https://github.com/AthenaCore/AwesomeResponsibleAI#artificial-intelligence-governance-ai-governance |
| Article | https://arxiv.org/abs/2503.05937 |
| Visualization | https://ianatcredoai.github.io/UCF_Figures/ |
| https://github.com/AthenaCore/AwesomeResponsibleAI#bias |
| Article | https://www.nist.gov/publications/towards-standard-identifying-and-managing-bias-artificial-intelligence |
| https://github.com/AthenaCore/AwesomeResponsibleAI#challenges |
| Article | https://arxiv.org/abs/2011.03395 |
| https://github.com/AthenaCore/AwesomeResponsibleAI#drift |
| Article | https://arxiv.org/pdf/2108.05319.pdf |
| Article | https://arxiv.org/pdf/2108.05620.pdf |
| https://github.com/AthenaCore/AwesomeResponsibleAI#explainabilityinterpretabilitymechanical-interpretability |
| Article | https://papers.nips.cc/paper/7340-explanations-based-on-the-missing-towards-contrastive-explanations-with-pertinent-negatives |
| Article | https://papers.nips.cc/paper/8231-improving-simple-models-with-confidence-profiles |
| Article | https://arxiv.org/abs/1707.01212 |
| Article | https://doi.org/10.1145/3306618.3314273 |
| Article | http://papers.nips.cc/paper/7062-a-unified-approach-to-interpreting-model-predictions |
| Github | https://github.com/slundberg/shap |
| Article | https://arxiv.org/abs/1905.12698 |
| Article | https://arxiv.org/abs/1602.04938 |
| Github | https://github.com/marcotcr/lime |
| Article | http://proceedings.mlr.press/v97/wei19a.html |
| Luss et al., 2019 | https://arxiv.org/abs/1905.12698 |
| Dash et al., 2018 | https://papers.nips.cc/paper/7716-boolean-decision-rules-via-column-generation |
| Alvarez-Melis et al., 2018 | https://papers.nips.cc/paper/8003-towards-robust-interpretability-with-self-explaining-neural-networks |
| A Living and Curated Collection of Explainable AI Methods | https://utwente-dmb.github.io/xai-papers/#/ |
| Neuronpedia | https://www.neuronpedia.org |
| https://github.com/AthenaCore/AwesomeResponsibleAI#ethical-data-products |
| Article | https://arxiv.org/abs/1803.09010 |
| Article | https://arxiv.org/abs/1810.03993 |
| Article | https://dl.acm.org/doi/10.1145/3531146.3533231 |
| Article | https://arxiv.org/abs/2202.13028 |
| Article | https://arxiv.org/pdf/2002.05819 |
| https://github.com/AthenaCore/AwesomeResponsibleAI#evaluation-of-model-explanations |
| Article | https://arxiv.org/abs/2206.11104 |
| Article | https://pure.mpg.de/rest/items/item_3588217_2/component/file_3588218/content |
| Benchmark | https://opening-up-chatgpt.github.io |
| https://github.com/AthenaCore/AwesomeResponsibleAI#fairness |
| Article | https://dl.acm.org/doi/full/10.1145/3616865 |
| Article | https://arxiv.org/abs/1703.00056 |
| Article | https://arxiv.org/abs/1707.00046 |
| Article | https://arxiv.org/abs/1909.00066 |
| Article | https://arxiv.org/abs/1609.05807 |
| Article | https://arxiv.org/abs/2405.05809 |
| Article and Materials | https://fairness.causalai.net |
| Article | https://arxiv.org/abs/1811.05577 |
| Article | https://arxiv.org/abs/2008.07433 |
| https://github.com/AthenaCore/AwesomeResponsibleAI#regulation |
| Article | https://arxiv.org/pdf/2408.16074 |
| https://github.com/AthenaCore/AwesomeResponsibleAI#representation-engineering |
| Article | https://www.circuit-breaker.ai |
| Article | https://www.ai-transparency.org |
| https://github.com/AthenaCore/AwesomeResponsibleAI#risk |
| Article | https://arxiv.org/pdf/2408.12622 |
| https://github.com/AthenaCore/AwesomeResponsibleAI#systems-risks |
| Article | https://arxiv.org/abs/2412.07780 |
| https://github.com/AthenaCore/AwesomeResponsibleAI#sustainability |
| Article | https://arxiv.org/abs/1910.09700 |
| Article | https://arxiv.org/pdf/2304.03271 |
| Article | https://hal.archives-ouvertes.fr/hal-03190119/document |
| Article | https://arxiv.org/abs/2104.10350 |
| Article | https://proceedings.neurips.cc/paper_files/paper/2015/file/86df7dcfd896fcaf2674f757a2463eba-Paper.pdf |
| Article | https://research.google/pubs/pub43146/ |
| Article | https://arxiv.org/abs/1906.02243 |
| van Wynsberghe, A. 2021 | https://link.springer.com/article/10.1007/s43681-021-00043-6 |
| Lannelongue, L. et al. 2020 | https://arxiv.org/abs/2007.07610 |
| Article | https://proceedings.mlsys.org/paper_files/paper/2022/file/462211f67c7d858f663355eff93b745e-Paper.pdf |
| https://github.com/AthenaCore/AwesomeResponsibleAI#collections |
| https://research.google/pubs/?collection=responsible-ai | https://research.google/pubs/?collection=responsible-ai |
| http://fairpipe.dssg.io | http://fairpipe.dssg.io |
| https://github.com/AthenaCore/AwesomeResponsibleAI#reproduciblenon-reproducible-research |
| here | https://reproducible.cs.princeton.edu |
| Papers with Code | https://paperswithcode.com |
| Papers without Code | https://www.paperswithoutcode.com |
| https://github.com/AthenaCore/AwesomeResponsibleAI#books |
| https://github.com/AthenaCore/AwesomeResponsibleAI#open-access |
| Book | https://www.fairmlbook.org |
| Book | https://www.r-causal.org |
| Book | https://ema.drwhy.ai |
| Book | https://ama.drwhy.ai |
| Book | https://mixtape.scunning.com |
| Web | https://github.com/huggingface/evaluation-guidebook |
| Book | https://ml-science-book.com/ |
| Book | https://theeffectbook.net |
| Book | https://direct.mit.edu/books/oa-monograph/2908/Engineering-a-Safer-WorldSystems-Thinking-Applied |
| Book | https://appliedcausalinference.github.io/aci_book/ |
| Book | https://htmlpreview.github.io/?https://github.com/matloff/dsldBook/blob/main/_book/index.html |
| Book | https://christophm.github.io/interpretable-ml-book/ |
| Book | https://github.com/AthenaCore/AwesomeResponsibleAI/blob/main/biosecurityhandbook.com |
| Book | https://github.com/AthenaCore/AwesomeResponsibleAI/blob/main/publichealthaihandbook.com |
| Book | https://github.com/NannyML/The-Little-Book-of-ML-Metrics |
| https://github.com/AthenaCore/AwesomeResponsibleAI#commercial--propietary--closed-access |
| Varshney, K., 2022 | https://www.manning.com/books/trust-in-machine-learning |
| Thampi, A., 2022 | https://www.manning.com/books/interpretable-ai |
| Mahoney, T., Varshney, K.R., Hind, M., 2020 | https://learning.oreilly.com/library/view/ai-fairness/9781492077664/ |
| Nielsen, A., 2021 | https://learning.oreilly.com/library/view/practical-fairness/9781492075721/ |
| Rothman, D., 2020 | https://www.packtpub.com/product/hands-on-explainable-ai-xai-with-python/9781800208131 |
| Kilroy, K., 2021 | https://learning.oreilly.com/library/view/ai-and-the/9781492091837/ |
| Hall, P., Gill, N., Cox, B., 2020 | https://learning.oreilly.com/library/view/responsible-machine-learning/9781492090878/ |
| Privacy-Preserving Machine Learning | https://www.manning.com/books/privacy-preserving-machine-learning |
| Human-In-The-Loop Machine Learning: Active Learning and Annotation for Human-Centered AI | https://www.manning.com/books/human-in-the-loop-machine-learning |
| Interpretable Machine Learning With Python: Learn to Build Interpretable High-Performance Models With Hands-On Real-World Examples | https://www.packtpub.com/product/interpretable-machine-learning-with-python/9781800203907 |
| Hall, P., Chowdhury, R., 2023 | https://learning.oreilly.com/library/view/responsible-ai/9781098102425/ |
| Book | https://www.penguinrandomhouse.com/books/603982/rebooting-ai-by-gary-marcus-and-ernest-davis/ |
| Book | https://mitpress.mit.edu/9780262551069/taming-silicon-valley/ |
| Book | https://mitpressbookstore.mit.edu/book/9781032576275 |
| https://github.com/AthenaCore/AwesomeResponsibleAI#code-of-ethics |
| ACS Code of Professional Conduct | https://www.acs.org.au/content/dam/acs/rules-and-regulations/Code-of-Professional-Conduct_v2.1.pdf |
| Association for Computer Machinery's Code of Ethics and Professional Conduct | https://www.acm.org/code-of-ethics |
| IEEE Global Initiative for Ethical Considerations in Artificial Intelligence (AI) and Autonomous Systems (AS) | https://ethicsinaction.ieee.org/ |
| ISO/IEC's Standards for Artificial Intelligence | https://www.iso.org/committee/6794475/x/catalogue/ |
| https://github.com/AthenaCore/AwesomeResponsibleAI#courses |
| AGI Strategy | https://bluedot.org/courses/agi-strategy |
| AI Alignment | https://bluedot.org/courses/alignment |
| AI Ethics | https://www.turingcollege.com/ai-ethics |
| DIVERSIFAIR | https://diversifair-project.eu |
| AI Ethics & Governance (AEG) | https://alan-turing-institute.github.io/turing-commons/skills-tracks/aeg/index.html |
| AI Governance | https://governance.aicareer.pro |
| AI Governance | https://bluedot.org/courses/governance |
| AI Policy Clinic | https://www.caidp.org/global-academic-network/ai-policy-clinic/ |
| AI Safety, Ethics and Society | https://www.aisafetybook.com/virtual-course |
| AI Security and Governance | https://education.securiti.ai/certifications/ai-governance/ |
| CS 120 Introduction to AI Safety | https://web.stanford.edu/class/cs120/ |
| CS 2881 AI Safety | https://boazbk.github.io/mltheoryseminar/ |
| CS 294-131: Trustworthy Deep Learning | https://berkeley-deep-learning.github.io/cs294-131-s19/ |
| CIS 4230/5230 - Ethical Algorithm Design | https://www.cis.upenn.edu/~mkearns/teaching/EADSpring24/ |
| CS 594 - Causal Inference and Learning | https://www.cs.uic.edu/~elena/courses/fall19/cs594cil.html |
| CS 7880 - Rigorous Approaches to Data Privacy | https://www.khoury.northeastern.edu/home/jullman/cs7880s17/syllabus.html |
| CS 860 - Algorithms for Private Data Analysis | http://www.gautamkamath.com/courses/CS860-fa2022.html |
| Data Justice (DJ) | https://alan-turing-institute.github.io/turing-commons/skills-tracks/dj/index.html |
| The EU AI Act, Explained | https://lillytechsystems.com/ai-school/eu-ai-act/ |
| Explainable Artificial Intelligence | https://interpretable-ml-class.github.io |
| Future of AI | https://bluedot.org/courses/future-of-ai |
| Introduction to AI Ethics | https://www.kaggle.com/learn/intro-to-ai-ethics |
| Introduction to ML Safety | https://course.mlsafety.org |
| Introduction to Responsible Machine Learning | https://jphall663.github.io/GWU_rml/ |
| LLM evaluation | https://nebius-academy.github.io/knowledge-base/evaluation-1-basics/ |
| Machine Learning Explainability | https://www.kaggle.com/learn/machine-learning-explainability |
| Machine Learning in Production (17-445/17-645/17-745) / AI Engineering (11-695) | https://mlip-cmu.github.io/s2025/ |
| MATS | https://www.matsprogram.org/program |
| Modern-Day Oracles or Bullshit Machines? | https://thebullshitmachines.com/instructor-guide/index.html |
| Practical Data Ethics | https://ethics.fast.ai |
| Public Engagement of Data Science and AI (PED) | https://alan-turing-institute.github.io/turing-commons/skills-tracks/ped/index.html |
| Responsible AI | https://alltechishuman.org/rai-courses |
| Responsible Research and Innovation (RRI) | https://alan-turing-institute.github.io/turing-commons/skills-tracks/rri/index.html |
| https://github.com/AthenaCore/AwesomeResponsibleAI#data-sets |
| Common Corpus | https://huggingface.co/collections/PleIAs/common-corpus-65d46e3ea3980fdcd66a5613 |
| An ImageNet replacement for self-supervised pretraining without humans | https://www.robots.ox.ac.uk/~vgg/research/pass/ |
| Huggingface Data Sets | https://huggingface.co/datasets |
| The Stack | https://www.bigcode-project.org/docs/about/the-stack/ |
| Open Ethics Data Passport | https://openethics.ai/oedp/ |
| curated collection | https://github.com/awesomedata/awesome-public-datasets |
| https://github.com/AthenaCore/AwesomeResponsibleAI#databases |
| https://github.com/AthenaCore/AwesomeResponsibleAI#ai-incidents-trackers |
| AI for Good Lab | https://microsoft.github.io/aiforgoodlab/ |
| AI Hallucination Cases | https://www.damiencharlotin.com/hallucinations/ |
| AI Risk Repository | https://airisk.mit.edu |
| The AI Risk Repository: A Comprehensive Meta-Review, Database, and Taxonomy of Risks From Artificial Intelligence | https://arxiv.org/abs/2408.12622 |
| Political Deepfakes Incidents Database | https://airtable.com/appOU03dlKuBdbmty/shrEkrIYINbrcKQ3z/tbleGYjNLn2D4Xfzs |
| Merging AI Incidents Research with Political Misinformation Research: Introducing the Political Deepfakes Incidents Database | https://arxiv.org/abs/2409.15319 |
| AI Risk Database | https://airisk.io/ |
| AIAAIC | https://www.aiaaic.org/ |
| AI Harm Map | https://ethicalaialliance.org/ai-harm-map |
| AI Incident Database | https://incidentdatabase.ai |
| AI Incident Tracker | https://airisk.mit.edu/ai-incident-tracker |
| AI Vulnerability Database (AVID) | https://avidml.org/ |
| George Washington University Law School's AI Litigation Database | https://blogs.gwu.edu/law-eti/ai-litigation-database/ |
| OECD AI Incidents Monitor | https://oecd.ai/en/incidents |
| Verica Open Incident Database (VOID) | https://www.thevoid.community/ |
| https://github.com/AthenaCore/AwesomeResponsibleAI#cybersecurity |
| CVE | https://www.cve.org |
| European Union Vulnerability Database | https://euvd.enisa.europa.eu |
| GCVE: Global CVE Allocation System | https://gcve.eu |
| MITRE Atlas | https://atlas.mitre.org |
| https://github.com/AthenaCore/AwesomeResponsibleAI#frameworks |
| A Framework for Ethical Decision Making | https://www.scu.edu/ethics/ethics-resources/a-framework-for-ethical-decision-making/ |
| Data Ethics Canvas | https://theodi.org/insights/tools/the-data-ethics-canvas-2021/ |
| Deon | https://deon.drivendata.org |
| Ethics & Algorithms Toolkit | http://ethicstoolkit.ai |
| Open Ethics Transparency Protocol (OETP) | https://openethics.ai/oetp/ |
| RAI Toolkit | https://rai.tradewindai.com |
| https://github.com/AthenaCore/AwesomeResponsibleAI#institutes |
| https://github.com/AthenaCore/AwesomeResponsibleAI#ai-safety-institutes-or-equivalent |
| Beijing AISI | https://beijing.ai-safety-and-governance.institute |
| Canada AISI | https://ised-isde.canada.ca/site/ised/en/canadian-artificial-intelligence-safety-institute |
| China AI Development and Safety Network | https://ai-development-and-safety-network.cn |
| EU AI Office | https://digital-strategy.ec.europa.eu/en/policies/ai-office |
| Korea AISI | https://www.aisi.re.kr/kor |
| Singapore AISI | https://www.ntu.edu.sg/dtc |
| https://github.com/AthenaCore/AwesomeResponsibleAI#ai-security-institute |
| UK AISI | https://www.aisi.gov.uk |
| Japan AISI | https://aisi.go.jp |
| Source | https://aisi.go.jp/assets/pdf/ai_safety_eval_v1.10_en.pdf |
| Source | https://aisi.go.jp/assets/pdf/E1_ai_safety_RT_v1.10_en.pdf |
| Source | https://aisi.go.jp/assets/pdf/250331_Data_quality_management_guidebook.pdf |
| Source | https://www-meti-go-jp.translate.goog/shingikai/mono_info_service/ai_shakai_jisso/20240419_report.html?_x_tr_sl=auto&_x_tr_tl=en&_x_tr_hl=es |
| Source 1 | https://aisi.go.jp/assets/pdf/Known_Attacks_and_Their_Impacts_on_AI_Systems_EN.pdf |
| Source 2 | https://arxiv.org/abs/2506.23296 |
| US CAISI | https://www.nist.gov/caisi |
| Source | https://nvlpubs.nist.gov/nistpubs/ai/NIST.AI.800-1.ipd2.pdf |
| https://github.com/AthenaCore/AwesomeResponsibleAI#responsible-ai-institutes |
| Canadian Centre for Responsible AI Governance | https://www.ccraig.ca |
| IBGIA - Instituto Brasileiro de Governança em IA | https://ibgia.org |
| https://github.com/AthenaCore/AwesomeResponsibleAI#research-institutes |
| Ada Lovelace Institute | https://www.adalovelaceinstitute.org/ |
| Centre pour la Securité de l'IA, CeSIA | https://www.securite-ia.fr |
| European Centre for Algorithmic Transparency | https://algorithmic-transparency.ec.europa.eu/index_en |
| Center for Human-Compatible AI | https://humancompatible.ai |
| Center for Responsible AI | https://airesponsibly.com/ |
| Montreal AI Ethics Institute | https://montrealethics.ai/ |
| Munich Center for Technology in Society (IEAI) | https://ieai.mcts.tum.de/ |
| National AI Centre's Responsible AI Network | https://www.industry.gov.au/science-technology-and-innovation/technology/national-artificial-intelligence-centre |
| Open Data Institute | https://theodi.org/ |
| Stanford University Human-Centered Artificial Intelligence (HAI) | https://hai.stanford.edu |
| The Institute for Ethical AI & Machine Learning | https://ethical.institute/ |
| UNESCO Chair in AI Ethics & Governance | https://www.ie.edu/unesco-chair-in-ai-ethics-and-governance/ |
| University of Oxford Institute for Ethics in AI | https://www.oxford-aiethics.ox.ac.uk/ |
| Australian Government-funded AI Adopt Centres | https://www.industry.gov.au/news/be-part-ai-revolution-ai-adopt-centres |
| ARM Hub AI Adopt Centre | https://aiadopt.ai |
| Australian Regional AI Network (ARAIN) | https://arain.com.au |
| SAAM (Safe AI Adoption Model) | https://www.saam.com.au |
| SMEC AI (Small to Medium Enterprise Centre of Artificial Intelligence) | https://smecai.au |
| Future of Life Institute | https://futureoflife.org/ |
| International Panel on the Information Environment | https://www.ipei.org/ |
| Center for AI Safety | https://www.centerforaisafety.org/ |
| Distributed AI Research Institute -DAIR- | https://www.dair.ai/ |
| International Association for Safe and Ethical AI | https://iasafe.ai/ |
| Partnership on AI | https://www.partnershiponai.org/ |
| AI Now Institute | https://ainowinstitute.org/ |
| Centre for the Governance of AI | https://www.governance.ai/ |
| Future of Humanity Institute | https://www.fhi.ox.ac.uk/ |
| Machine Intelligence Research Institute -MIRI- | https://intelligence.org/ |
| https://github.com/AthenaCore/AwesomeResponsibleAI#maturity-models |
| https://github.com/AthenaCore/AwesomeResponsibleAI#ai-governance |
| The AIGA AI Governance Framework | https://ai-governance.eu |
| https://github.com/AthenaCore/AwesomeResponsibleAI#ethics |
| Open Ethics Maturity Model | https://openethics.ai/oemm/ |
| https://github.com/AthenaCore/AwesomeResponsibleAI#responsible-ai |
| The GSMA Responsible AI Maturity Roadmap | https://www.gsma.com/solutions-and-impact/connectivity-for-good/external-affairs/responsible-ai/ |
| https://github.com/AthenaCore/AwesomeResponsibleAI#newsletters |
| AI Frontiers | https://www.ai-frontiers.org/ |
| AI Policy Perspectives | https://www.aipolicyperspectives.com |
| AI Policy Weekly | https://aipolicyus.substack.com |
| AI Safety in China | https://aisafetychina.substack.com |
| AI Safety Newsletter | https://newsletter.safe.ai |
| AI Snake Oil | https://www.aisnakeoil.com |
| Audaria | https://audaria.fr |
| Import AI | https://github.com/AthenaCore/AwesomeResponsibleAI/blob/main/importai.substack.com |
| Marcus on AI | https://garymarcus.substack.com |
| ML Safety Newsletter | https://newsletter.mlsafety.org |
| Navigating AI Risks | https://www.navigatingrisks.ai |
| One Useful Thing | https://www.oneusefulthing.org |
| The AI Ethics Brief | https://brief.montrealethics.ai |
| The AI Evaluation Substack | https://aievaluation.substack.com |
| The EU AI Act Newsletter | https://artificialintelligenceact.substack.com |
| The Machine Learning Engineer | https://ethical.institute/mle.html |
| Turing Post | https://www.turingpost.com |
| https://github.com/AthenaCore/AwesomeResponsibleAI#principles |
| Principles for a responsible usage of AI | https://www.allianz.com/en/about-us/strategy-values/data-ethics-and-responsible-ai.html |
| Guidelines for Artificial Intelligence | https://www.telekom.com/en/company/digital-responsibility/details/artificial-intelligence-ai-guideline-524366 |
| Guidelines for Trustworthy AI | https://www.europarl.europa.eu/cmsdata/196377/AI%20HLEG_Ethics%20Guidelines%20for%20Trustworthy%20AI.pdf |
| Asilomar AI principles | https://futureoflife.org/open-letter/ai-principles/ |
| AI Principles | https://ai.google/principles/ |
| Ethically Aligned Design | https://sagroups.ieee.org/global-initiative/wp-content/uploads/sites/542/2023/01/ead1e.pdf |
| Principles for Responsible AI | https://www.logitech.com/content/dam/logitech/en/principles/responsible-ai-principles.pdf |
| AI Principles | https://www.microsoft.com/en-us/ai/principles-and-approach |
| AI principles | https://oecd.ai/en/ai-principles |
| AI Principles | https://www.microsoft.com/en-us/ai/principles-and-approach |
| The Responsible Machine Learning Principles | https://ethical.institute/principles.html |
| FAIR Principles | https://www.go-fair.org/fair-principles/ |
| The CARE Principles for Indigenous Data Governance | https://www.gida-global.org/care |
| The First Nations Principles of OCAP | https://fnigc.ca/ocap-training/ |
| 'Getting from commitment to content in AI and data ethics: Justice and explainability' | https://www.atlanticcouncil.org/in-depth-research-reports/report/specifying-normative-content/ |
| https://github.com/AthenaCore/AwesomeResponsibleAI#podcasts |
| AI Frontiers | https://podcasts.apple.com/gb/podcast/ai-frontiers/id1806906344 |
| AI Safety Fundamentals | https://podcasts.apple.com/gb/podcast/ai-safety-fundamentals/id1687830086 |
| AI Safety Newsletter | https://podcasts.apple.com/gb/podcast/ai-safety-newsletter/id1702875110 |
| Me, Myself and AI | https://podcasts.apple.com/gb/podcast/me-myself-and-ai/id1533115958 |
| Practical AI | https://practicalai.fm |
| https://github.com/AthenaCore/AwesomeResponsibleAI#regulations |
| https://github.com/AthenaCore/AwesomeResponsibleAI#definition |
| https://github.com/AthenaCore/AwesomeResponsibleAI#interesting-resources |
| AI Law Radar | https://ailawradar.com |
| AI Regulations Tracker | https://regulations.ai/regulations/tracker |
| Data Protection and Privacy Legislation Worldwide | https://unctad.org/page/data-protection-and-privacy-legislation-worldwide |
| Data Protection Laws of the Word | https://www.dlapiperdataprotection.com |
| Digital Policy Alert | https://digitalpolicyalert.org/analysis |
| ETO Agora | https://agora.eto.tech |
| GAIIN: The Global AI Initiatives Navigator | https://oecd.ai/en/dashboards/overview |
| GDPR Comparison | https://www.activemind.legal/law/ |
| Global AI Regulation | https://global-ai-regulations.glitch.me |
| INTERACTIVE MAPPING OF THE AI REGULATION LANDSCAPE | https://diversifair-project.eu/courses/interactive-mapping-of-ai-regulation-landscape/ |
| Policy Database | https://aistandardshub.org/policy-and-strategy-search/ |
| SEA Observatory | https://seaobservatory.com |
| SCL Artificial Intelligence Contractual Clauses | https://www.scl.org/wp-content/uploads/2024/02/AI-Clauses-Project-October-2023-final-1.pdf |
| https://github.com/AthenaCore/AwesomeResponsibleAI#australia- |
| AI and ESG | https://www.industry.gov.au/publications/ai-and-esg |
| Artificial intelligence impact assessment tool | https://www.digital.gov.au/ai/impact-assessment-tool |
| National framework for the assurance of artificial intelligence in government | https://www.finance.gov.au/government/public-data/data-and-digital-ministers-meeting/national-framework-assurance-artificial-intelligence-government |
| The AI Impact Navigator | https://www.industry.gov.au/publications/ai-impact-navigator |
| Voluntary AI Safety Standard | https://www.industry.gov.au/publications/voluntary-ai-safety-standard |
| comprehensive, community-maintained index of Australian AI Security standards, policies, frameworks, and guidance | https://github.com/Benjamin-KY/Australian-AI-Security |
| https://github.com/AthenaCore/AwesomeResponsibleAI#canada- |
| Algorithmic Impact Assessment tool | https://www.canada.ca/en/government/system/digital-government/digital-government-innovations/responsible-use-ai/algorithmic-impact-assessment.html |
| Directive on Automated Decision-Making | https://www.tbs-sct.gc.ca/pol/doc-eng.aspx?id=32592 |
| Directive on Privacy Practices | https://www.tbs-sct.canada.ca/pol/doc-eng.aspx?id=18309 |
| Directive on Security Management | https://www.tbs-sct.canada.ca/pol/doc-eng.aspx?id=32611 |
| Directive on Service and Digital | https://www.tbs-sct.canada.ca/pol/doc-eng.aspx?id=32601 |
| Policy on Government Security | https://www.tbs-sct.canada.ca/pol/doc-eng.aspx?id=16578 |
| Policy on Service and Digital | https://www.tbs-sct.canada.ca/pol/doc-eng.aspx?id=32603 |
| Privacy Act | https://laws-lois.justice.gc.ca/eng/ACTS/P-21/ |
| Pan-Canadian Artificial Intelligence Strategy | https://ised-isde.canada.ca/site/ai-strategy/en |
| Artificial Intelligence and Data Act | https://ised-isde.canada.ca/site/innovation-better-canada/en/artificial-intelligence-and-data-act-aida-companion-document |
| Voluntary Code of Conduct on the Responsible Development and Management of Advanced Generative AI Systems | https://ised-isde.canada.ca/site/ised/en/voluntary-code-conduct-responsible-development-and-management-advanced-generative-ai-systems |
| Guidelines for secure AI system development | https://www.cyber.gc.ca/en/news-events/guidelines-secure-ai-system-development |
| https://github.com/AthenaCore/AwesomeResponsibleAI#china- |
| Chinese AI Governance Documents | https://airtable.com/appwGTl7Auvtwtoga/shrc5OzekCZKw5OJH/tbl35IgyBt2e2dHVt/viwnNAwqZt84d9hDZ?blocks=hide |
| https://github.com/AthenaCore/AwesomeResponsibleAI#european-union- |
| Website | https://digital-strategy.ec.europa.eu/en/policies/cyber-resilience-act |
| Source | https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=OJ%3AL_202402847 |
| Website | https://digital-strategy.ec.europa.eu/en/policies/data-act |
| Source | https://eur-lex.europa.eu/eli/reg/2023/2854 |
| Website | https://digital-strategy.ec.europa.eu/en/policies/data-governance-act |
| Source | https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32022R0868 |
| Website | https://digital-markets-act.ec.europa.eu/index_en |
| Source | https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A32022R1925 |
| Website | https://www.eiopa.europa.eu/digital-operational-resilience-act-dora_en |
| Source | https://eur-lex.europa.eu/eli/reg/2022/2554/oj |
| Website | https://commission.europa.eu/strategy-and-policy/priorities-2019-2024/europe-fit-digital-age/digital-services-act_en |
| Source | https://eur-lex.europa.eu/legal-content/EN/TXT/?toc=OJ%3AL%3A2022%3A277%3ATOC&uri=uriserv%3AOJ.L_.2022.277.01.0001.01.ENG |
| Website | https://digital-strategy.ec.europa.eu/en/policies/copyright-legislation |
| Source | https://eur-lex.europa.eu/eli/dir/2019/790/oj |
| Website | https://energy.ec.europa.eu/topics/energy-efficiency/energy-efficiency-targets-directive-and-rules/energy-efficiency-directive_en |
| Source | https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=OJ%3AJOL_2023_231_R_0001&qid=1695186598766 |
| Website | https://artificialintelligenceact.eu |
| Source | https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=OJ:L_202401689 |
| Website | https://gdpr.eu/ |
| Source | https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=celex%3A32016R0679 |
| Website | https://digital-strategy.ec.europa.eu/en/policies/nis2-directive |
| Source | https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A32022L2555 |
| AI Act Whistleblower Tool | https://ai-act-whistleblower.integrityline.app |
| Hiroshima Process International Guiding Principles for Advanced AI system | https://digital-strategy.ec.europa.eu/en/library/hiroshima-process-international-guiding-principles-advanced-ai-system |
| https://github.com/AthenaCore/AwesomeResponsibleAI#india- |
| IT Amendment Rules, 2026 | https://www.meity.gov.in/static/uploads/2026/02/550681ab908f8afb135b0ad42816a1c9.pdf |
| The Digital Personal Data Protection (DPDP) Act | https://static.pib.gov.in/WriteReadData/specificdocs/documents/2025/nov/doc20251117695301.pdf |
| The National Strategy for Artificial Intelligence | https://www.niti.gov.in/sites/default/files/2023-03/National-Strategy-for-Artificial-Intelligence.pdf |
| The Principles for Responsible AI | https://www.niti.gov.in/sites/default/files/2021-02/Responsible-AI-22022021.pdf |
| https://github.com/AthenaCore/AwesomeResponsibleAI#singapore- |
| Singapore’s Approach to AI Governance - Verify | https://www.pdpc.gov.sg/help-and-resources/2020/01/model-ai-governance-framework |
| Personal Data Protection Act 2012 | https://sso.agc.gov.sg/Act/PDPA2012 |
| Protection From Online Falsehoods and Manipulation Act 2019 | https://sso.agc.gov.sg/Acts-Supp/18-2019/Published/20190625?DocDate=20190625 |
| https://github.com/AthenaCore/AwesomeResponsibleAI#south-korea- |
| AI Basic Act | https://artificialintelligenceact.kr |
| https://github.com/AthenaCore/AwesomeResponsibleAI#united-arab-emirates- |
| AI Principles & Ethics/Ethical AI Toolkit | https://www.digitaldubai.ae/initiatives/ai-principles-ethics |
| https://github.com/AthenaCore/AwesomeResponsibleAI#united-states- |
| CCPA | https://www.oag.ca.gov/privacy/ccpa |
| CPRA | https://leginfo.legislature.ca.gov/faces/billTextClient.xhtml?bill_id=202120220AB1490 |
| SB-53 Artificial intelligence models: large developers. | https://leginfo.legislature.ca.gov/faces/billTextClient.xhtml?bill_id=202520260SB53 |
| VCDPA | https://lis.virginia.gov/cgi-bin/legp604.exe?212+sum+HB2307 |
| ColoPA - Colorado SB21-190 | https://leg.colorado.gov/sites/default/files/documents/2021A/bills/2021a_190_rer.pdf |
| SB21-169: Regulation prohibiting unfair discrimination in insurance | https://doi.colorado.gov/for-consumers/sb21-169-protecting-consumers-from-unfair-discrimination-in-insurance-practices |
| NYC Local Law 144: Mandatory bias audits for automated employment decision tools | https://www.nyc.gov/site/dca/about/automated-employment-decision-tools.page |
| HIPAA | https://www.cdc.gov/phlp/publications/topic/hipaa.html |
| FCRA | https://www.ftc.gov/enforcement/statutes/fair-credit-reporting-act |
| FERPA | https://www.cdc.gov/phlp/publications/topic/ferpa.html |
| GLBA | https://www.ftc.gov/tips-advice/business-center/privacy-and-security/gramm-leach-bliley-act |
| ECPA | https://bja.ojp.gov/program/it/privacy-civil-liberties/authorities/statutes/1285 |
| COPPA | https://www.ftc.gov/enforcement/rules/rulemaking-regulatory-reform-proceedings/childrens-online-privacy-protection-rule |
| VPPA | https://www.law.cornell.edu/uscode/text/18/2710 |
| FTC | https://www.ftc.gov/enforcement/statutes/federal-trade-commission-act |
| EU-U.S. and Swiss-U.S. Privacy Shield Frameworks | https://www.privacyshield.gov/welcome |
| REMOVING BARRIERS TO AMERICAN LEADERSHIP IN ARTIFICIAL INTELLIGENCE | https://www.whitehouse.gov/presidential-actions/2025/01/removing-barriers-to-american-leadership-in-artificial-intelligence/ |
| Privacy Act of 1974 | https://www.justice.gov/opcl/privacy-act-1974 |
| Privacy Protection Act of 1980 | https://epic.org/privacy/ppa/ |
| https://github.com/AthenaCore/AwesomeResponsibleAI#spain- |
| EIDF: guía y casos de uso - Metodología aplicada de la avaluación de impacto sobre los derechos fundamentales en el diseño y desarrollo de la IA- | https://www.dpdenxarxa.cat/pluginfile.php/2468/mod_folder/content/0/CAST-APDcat-281.pdf |
| Modelo PIO | https://oeiac.cat/es/el-modelo-pio/ |
| Recursos para el uso de IA | https://aesia.digital.gob.es/es/guias |
| Registre de sistemes d'intel·ligència artificial i altres algorismes | https://registreia.administraciodigital.gencat.cat/ |
| https://github.com/AthenaCore/AwesomeResponsibleAI#responsible-scaling-policies |
| https://github.com/AthenaCore/AwesomeResponsibleAI#definition-1 |
| https://github.com/AthenaCore/AwesomeResponsibleAI#rsp-list |
| Anthropic’s Transparency Hub | https://www.anthropic.com/transparency/voluntary-commitments |
| Version 3.0 | https://www-cdn.anthropic.com/e670587677525f28df69b59e5fb4c22cc5461a17.pdf |
| RSP Noncompliance Reporting and
Anti-Retaliation Policy | https://www-cdn.anthropic.com/b7a5629e40b391b2adfb4cc8c0888ac9d6bfddf6/RSP%20Noncompliance%20Reporting%20and%20Anti-Retaliation%20Policy.pdf |
| Version 2.2 | https://www-cdn.anthropic.com/872c653b2d0501d6ab44cf87f43e1dc4853e4d37.pdf |
| Version 2.1 | https://www-cdn.anthropic.com/17310f6d70ae5627f55313ed067afc1a762a4068.pdf |
| Version 2.0 | https://www-cdn.anthropic.com/616dee633636e5bd309cb73aed8622e80fe47839.pdf |
| Version 1.0 | https://www-cdn.anthropic.com/1adf000c8f675958c2ee23805d91aaade1cd4613/responsible-scaling-policy.pdf |
| Preparedness Framework | https://cdn.openai.com/pdf/18a02b5d-6b67-4cec-ab64-68cdfbddebcd/preparedness-framework-v2.pdf |
| Frontier Safety Framework | https://storage.googleapis.com/deepmind-media/gemini/gemini_3_pro_fsf_report.pdf |
| AGI Readiness Policy | https://magic.dev/agi-readiness-policy |
| AI Safety Framework | https://clova.ai/en/tech-blog/en-navers-ai-safety-framework-asf |
| Frontier AI Framework | https://ai.meta.com/static-resource/meta-frontier-ai-framework/ |
| Frontier AI Safety Framework | https://www.g42.ai/application/files/9517/3882/2182/G42_Frontier_Safety_Framework_Publication_Version.pdf |
| Secure AI Frontier Model Framework | https://cohere.com/security/the-cohere-secure-ai-frontier-model-framework-february-2025.pdf |
| Frontier Governance Framework | https://cdn-dynmedia-1.microsoft.com/is/content/microsoftcorp/microsoft/final/en-us/microsoft-brand/documents/Microsoft-Frontier-Governance-Framework.pdf |
| Frontier Model Safety Framework | https://www.amazon.science/publications/amazons-frontier-model-safety-framework |
| Risk Management Framework | https://data.x.ai/2025-08-20-xai-risk-management-framework.pdf |
| Frontier AI Risk Assessment | https://images.nvidia.com/content/pdf/NVIDIA-Frontier-AI-Risk-Assessment.pdf |
| https://github.com/AthenaCore/AwesomeResponsibleAI#reports |
| https://github.com/AthenaCore/AwesomeResponsibleAI#ai-ethics |
| Website | https://montrealethics.ai/state/ |
| https://github.com/AthenaCore/AwesomeResponsibleAI#ai-governance-1 |
| Article | https://www.iaps.ai/research/understanding-aisis |
| Article | https://cset.georgetown.edu/wp-content/uploads/CSET-AI-Triad-Report.pdf |
| Article | https://cset.georgetown.edu/publication/the-policy-playbook/ |
| Article | https://github.com/AthenaCore/AwesomeResponsibleAI/blob/main/How%20Can%20Spain%20Remain%20Internationally%20Competitive%20in%20AI%20under%20EU%20Legislation.pdf |
| Article | https://www.csis.org/analysis/ai-safety-institute-international-network-next-steps-and-recommendations |
| https://arxiv.org/pdf/2409.17216 | https://arxiv.org/pdf/2409.17216 |
| Article | https://arxiv.org/pdf/2306.12001 |
| Article | https://ceas.turing.ac.uk/sites/default/files/2023-08/cetas-cltr_ai_risk_briefing_paper.pdf |
| Article | https://revistasic.es/revista-sic/sic-162/colaboraciones/marco-confiable/ |
| Article | https://arxiv.org/pdf/2402.08797 |
| https://github.com/AthenaCore/AwesomeResponsibleAI#ai-safety |
| International AI Safety Report | https://internationalaisafetyreport.org |
| The Singapore Consensus on Global AI Safety Research Priorities | https://aisafetypriorities.org |
| https://github.com/AthenaCore/AwesomeResponsibleAI#ai-security |
| GENAI Security Project - Resources Library | https://genai.owasp.org/resources/?e-filter-3b7adda-resource-item=cheat-sheets |
| https://github.com/AthenaCore/AwesomeResponsibleAI#ai-testing |
| OWASP AI Testing Guide | https://owasp.org/www-project-ai-testing-guide/ |
| https://github.com/AthenaCore/AwesomeResponsibleAI#copyright |
| Copyright and Artificial Intelligence | https://www.copyright.gov/ai/Copyright-and-Artificial-Intelligence-Part-2-Copyrightability-Report.pdf |
| https://github.com/AthenaCore/AwesomeResponsibleAI#market-analysis |
| 2024 | https://futureoflife.org/document/fli-ai-safety-index-2024/ |
| 2025 | https://futureoflife.org/ai-safety-index-winter-2025/ |
| AI World | https://aiworld.eu |
| European Open Source AI Index | https://osai-index.eu |
| Global Index for AI Safety | https://agile-index.ai/global-index-for-ai-safety |
| Impact Report | https://safe.ai |
| 2023 | https://safe.ai/work/impact-report/2023 |
| 2024 | https://safe.ai/work/impact-report/2024 |
| State of AI | https://www.stateof.ai |
| The AI Index Report | https://aiindex.stanford.edu |
| 2017 | https://hai.stanford.edu/ai-index/2017-ai-index-report |
| 2018 | https://hai.stanford.edu/ai-index/2018-ai-index-report |
| 2019 | https://hai.stanford.edu/ai-index/2019-ai-index-report |
| 2021 | https://hai.stanford.edu/ai-index/2021-ai-index-report |
| 2022 | https://hai.stanford.edu/ai-index/2022-ai-index-report |
| 2023 | https://hai.stanford.edu/ai-index/2023-ai-index-report |
| 2024 | https://hai.stanford.edu/ai-index/2024-ai-index-report |
| 2025 | https://hai.stanford.edu/ai-index/2025-ai-index-report |
| 2026 | https://hai.stanford.edu/ai-index/2026-ai-index-report |
| https://github.com/AthenaCore/AwesomeResponsibleAI#ai-labs |
| AI Lab Watch | https://ailabwatch.org |
| AI Safety Claims Analysis | https://aisafetyclaims.org |
| https://github.com/AthenaCore/AwesomeResponsibleAI#other |
| Four Principles of Explainable Artificial Intelligence | https://nvlpubs.nist.gov/nistpubs/ir/2021/NIST.IR.8312.pdf |
| Psychological Foundations of Explainability and Interpretability in Artificial Intelligence | https://nvlpubs.nist.gov/nistpubs/ir/2021/NIST.IR.8367.pdf |
| Inferring Concept Drift Without Labeled Data, 2021 | https://concept-drift.fastforwardlabs.com |
| Interpretability, Fast Forward Labs, 2020 | https://ff06-2020.fastforwardlabs.com |
| Towards a Standard for Identifying and Managing Bias in Artificial Intelligence (NIST Special Publication 1270) | https://nvlpubs.nist.gov/nistpubs/SpecialPublications/NIST.SP.1270.pdf |
| Auditing machine learning algorithms | https://www.auditingalgorithms.net/index.html |
| https://github.com/AthenaCore/AwesomeResponsibleAI#ratings |
| https://aimodelratings.com | https://aimodelratings.com |
| https://github.com/AthenaCore/AwesomeResponsibleAI#standards |
| https://github.com/AthenaCore/AwesomeResponsibleAI#definition-2 |
| Standards Database | https://aistandardshub.org/ai-standards-search/ |
| AI Standards Hub | https://aistandardshub.org |
| RSL | https://rslstandard.org |
| https://github.com/AthenaCore/AwesomeResponsibleAI#standards-1 |
| https://github.com/AthenaCore/AwesomeResponsibleAI#cen-standards |
| Source | https://standards.cencenelec.eu/dyn/www/f?p=CEN:110:0::::FSP_PROJECT,FSP_ORG_ID:76985,2916257&cs=1D8677F053BD6A69827AAF37B45211997 |
| here | https://standards.cencenelec.eu/dyn/www/f?p=205:22:0::::FSP_ORG_ID,FSP_LANG_ID:2916257,25&cs=1827B89DA69577BF3631EE2B6070F207D |
| https://github.com/AthenaCore/AwesomeResponsibleAI#dgsi-standards |
| Source | https://dgc-cgn.org/product/can-dgsi-123/ |
| Source | https://dgc-cgn.org/product/can-dgsi-101/ |
| Source | https://dgc-cgn.org/product/can-dgsi-128/ |
| https://github.com/AthenaCore/AwesomeResponsibleAI#etsi-standards |
| Source | https://www.etsi.org/deliver/etsi_en/304200_304299/304223/02.01.01_60/en_304223v020101p.pdf |
| Source | https://github.com/AthenaCore/AwesomeResponsibleAI/blob/main |
| Source | https://www.etsi.org/deliver/etsi_gr/SAI/001_099/007/01.01.01_60/gr_SAI007v010101p.pdf |
| Source | https://www.etsi.org/deliver/etsi_gr/SAI/001_099/009/01.01.01_60/gr_SAI009v010101p.pdf |
| Source | https://www.etsi.org/deliver/etsi_gr/SAI/001_099/006/01.01.01_60/gr_SAI006v010101p.pdf |
| Source | https://www.etsi.org/deliver/etsi_tr/104200_104299/104225/01.01.01_60/tr_104225v010101p.pdf |
| Source | https://www.etsi.org/deliver/etsi_ts/104200_104299/104224/01.01.01_60/ts_104224v010101p.pdf |
| Source | https://www.etsi.org/deliver/etsi_tr/104100_104199/104119/01.01.01_60/tr_104119v010101p.pdf |
| Source | https://www.etsi.org/deliver/etsi_tr/104000_104099/104066/01.01.01_60/tr_104066v010101p.pdf |
| Source | https://www.etsi.org/deliver/etsi_ts/104200_104299/104223/01.01.01_60/ts_104223v010101p.pdf |
| Source | https://www.etsi.org/deliver/etsi_en/304200_304299/304223/02.01.01_60/en_304223v020101p.pdf |
| Source | https://www.etsi.org/deliver/etsi_ts/104000_104099/104050/01.01.01_60/ts_104050v010101p.pdf |
| Source | https://www.etsi.org/deliver/etsi_tr/104000_104099/104032/01.01.01_60/tr_104032v010101p.pdf |
| Source | https://www.etsi.org/deliver/etsi_ts/104000_104099/104008/01.01.01_60/ts_104008v010101p.pdf |
| Source | https://www.etsi.org/deliver/etsi_tr/104100_104199/104128/01.01.01_60/tr_104128v010101p.pdf |
| Source | https://www.etsi.org/deliver/etsi_tr/104100_104199/104159/01.01.01_60/tr_104159v010101p.pdf |
| Source | https://www.etsi.org/deliver/etsi_gr/SAI/001_099/013/01.01.01_60/gr_SAI013v010101p.pdf |
| https://github.com/AthenaCore/AwesomeResponsibleAI#ieee-standards |
| Source | https://standards.ieee.org/ieee/2894/11296/ |
| Source | https://store.accuristech.com/ieee/standards/ieee-2801-2022?product_id=2245612 |
| Source | https://www.iso.org/standard/74296.html |
| Source | https://store.accuristech.com/ieee/standards/ieee-2801-2022?product_id=2245612 |
| Source | https://store.accuristech.com/ieee/standards/ieee-2937-2022?product_id=2252712 |
| Source | https://standards.ieee.org/ieee/3169/10935/ |
| https://github.com/AthenaCore/AwesomeResponsibleAI#sae-standards |
| Source | https://www.sae.org/standards/3347-artificial-intelligence-simulation-best-practices |
| Source | https://www.sae.org/standards/air8493-assessment-human-factors-concerns-development-safety-related-ai-based-systems-aviation |
| Source | https://www.sae.org/standards/j3321-verification-validation-ai-ml-based-components-systems-ground-vehicles |
| Source | https://www.sae.org/standards/j3329-ai-regulations-standards-applications-challenges |
| source | https://www.sae.org/standards/crb1-managing-development-artificial-intelligence-software |
| Source | https://www.sae.org/standards/air6988-artificial-intelligence-aeronautical-systems-statement-concerns |
| https://github.com/AthenaCore/AwesomeResponsibleAI#une-standards |
| UNE | https://www.en.une.org |
| Source | https://tienda.aenor.com/norma-une-especificacion-une-0079-2023-n0071118 |
| Source | https://tienda.aenor.com/norma-une-especificacion-une-0078-2023-n0071117 |
| Source | https://tienda.aenor.com/norma-une-especificacion-une-0077-2023-n0071116 |
| Source | https://tienda.aenor.com/norma-une-especificacion-une-0081-2023-n0071807 |
| Source | https://tienda.aenor.com/norma-une-especificacion-une-0080-2023-n0071383 |
| Source | https://www.une.org/encuentra-tu-norma/busca-tu-norma/norma/?c=N0075012 |
| here | https://tienda.aenor.com/Buscador |
| https://github.com/AthenaCore/AwesomeResponsibleAI#isoiec-standards |
| https://www.iso.org/standard/74296.html | https://www.iso.org/standard/74296.html |
| https://www.iso.org/standard/83012.html | https://www.iso.org/standard/83012.html |
| https://www.iso.org/standard/56641.html | https://www.iso.org/standard/56641.html |
| https://www.iso.org/standard/81230.html | https://www.iso.org/standard/81230.html |
| https://www.iso.org/standard/42005 | https://www.iso.org/standard/42005 |
| https://www.iso.org/standard/79799.html | https://www.iso.org/standard/79799.html |
| https://www.iso.org/standard/56582.html | https://www.iso.org/standard/56582.html |
| https://www.iso.org/standard/86903.html | https://www.iso.org/standard/86903.html |
| https://www.iso.org/standard/77304.html | https://www.iso.org/standard/77304.html |
| https://www.iso.org/standard/56581.html | https://www.iso.org/standard/56581.html |
| https://www.iso.org/standard/86177.html | https://www.iso.org/standard/86177.html |
| https://www.iso.org/standard/85072.html | https://www.iso.org/standard/85072.html |
| https://www.iso.org/standard/42006 | https://www.iso.org/standard/42006 |
| https://www.iso.org/standard/77607.html | https://www.iso.org/standard/77607.html |
| https://www.iso.org/standard/78507.html | https://www.iso.org/standard/78507.html |
| https://www.iso.org/standard/82148.html | https://www.iso.org/standard/82148.html |
| https://www.iso.org/standard/84110.html | https://www.iso.org/standard/84110.html |
| https://www.iso.org/standard/81088.html | https://www.iso.org/standard/81088.html |
| https://www.iso.org/standard/83002.html | https://www.iso.org/standard/83002.html |
| https://www.iso.org/standard/84111.html | https://www.iso.org/standard/84111.html |
| https://www.iso.org/standard/77608.html | https://www.iso.org/standard/77608.html |
| https://www.iso.org/standard/86899.html | https://www.iso.org/standard/86899.html |
| https://www.iso.org/standard/81283.html | https://www.iso.org/standard/81283.html |
| https://www.iso.org/standard/86690.html | https://www.iso.org/standard/86690.html |
| https://github.com/AthenaCore/AwesomeResponsibleAI#learning-resources-for-isoiec-standards |
| ISO 42001 Visual Library | https://github.com/nelsambrose/ISO-42001-Visual-Library |
| https://github.com/AthenaCore/AwesomeResponsibleAI#nist-publications |
| Source | https://airc.nist.gov/AI_RMF_Knowledge_Base/Playbook |
| Source | https://airc.nist.gov/AI_RMF_Knowledge_Base/Playbook |
| Source | https://airc.nist.gov/AI_RMF_Knowledge_Base/Glossary |
| https://github.com/AthenaCore/AwesomeResponsibleAI#other-resources |
| Standards Database | https://aistandardshub.org/ai-standards-search/ |
| AIDG Hub | https://ai-standards-normes-ia.ca/en/home/standards-database |
| NIST Assessing Risks and Impacts of AI (ARIA) | https://ai-challenges.nist.gov/aria |
| EU AI Act Harmonised Standards Mapping | https://ai-act-standards.com |
| AI Governance Library | https://www.aigl.blog |
| https://github.com/AthenaCore/AwesomeResponsibleAI#tools |
| balance | https://import-balance.org |
| clav | https://jbryer.github.io/clav/ |
| smclafify | https://github.com/aws/amazon-sagemaker-clarify |
| SolasAI | https://github.com/SolasAI/solas-ai-disparity |
| TRAK (Attributing Model Behaviour at Scale) | https://github.com/MadryLab/trak |
| Article | https://arxiv.org/pdf/2303.14186 |
| https://github.com/AthenaCore/AwesomeResponsibleAI#ai-alignment |
| Circuit Breakers | https://github.com/GraySwanAI/circuit-breakers |
| https://github.com/AthenaCore/AwesomeResponsibleAI#ai-governance-2 |
| Agent Governance Toolkit | https://github.com/microsoft/agent-governance-toolkit |
| Governance Mega-Map Application | https://github.com/The-Company-Ethos/doing-ai-governance |
| Verifywise | https://github.com/verifywise-ai/verifywise |
| Venturalitica SDK | https://github.com/Venturalitica/venturalitica-sdk |
| https://github.com/AthenaCore/AwesomeResponsibleAI#ai-licensing |
| https://www.licenses.ai | https://www.licenses.ai |
| https://github.com/AthenaCore/AwesomeResponsibleAI#audit |
| AIR Blackbox | https://github.com/airblackbox/gateway |
| Website | https://airblackbox.ai |
| PyPI | https://pypi.org/project/air-blackbox/ |
| PRML / falsify | https://github.com/studio-11-co/falsify |
| EU AI Act Article 12 | https://spec.falsify.dev/eu-ai-act/article-12/ |
| NIST AI RMF | https://spec.falsify.dev/nist-ai-rmf/ |
| ISO/IEC 42001 | https://spec.falsify.dev/iso-42001/ |
| 10.5281/zenodo.20177839 | https://doi.org/10.5281/zenodo.20177839 |
| SchemaStore | https://www.schemastore.org/ |
| glassalpha | https://github.com/asibic/glassalpha |
| Systima Comply | https://github.com/systima-ai/comply |
| https://github.com/AthenaCore/AwesomeResponsibleAI#causal-inference |
| AIPW: Augmented Inverse Probability Weighting | https://cran.r-project.org/web/packages/AIPW/index.html |
| caugi (Causal Graph Interface) | https://cran.r-project.org/web/packages/caugi/index.html |
| CausalAI | https://github.com/salesforce/causalai |
| CausalNex | https://causalnex.readthedocs.io |
| CausalImpact | https://cran.r-project.org/web/packages/CausalImpact |
| Causalinference | https://causalinferenceinpython.org |
| causaldef | https://cran.r-project.org/web/packages/causaldef/index.html |
| causalDT: Causal Distillation Trees | https://cran.r-project.org/web/packages/causalDT/index.html |
| Causal Inference 360 | https://github.com/BiomedSciAI/causallib |
| CausalPy | https://github.com/pymc-labs/CausalPy |
| CIMTx: Causal Inference for Multiple Treatments with a Binary Outcome | https://cran.r-project.org/web/packages/CIMTx |
| dagitty | https://cran.r-project.org/web/packages/dagitty |
| DoWhy | https://github.com/Microsoft/dowhy |
| flexCausal | https://cran.r-project.org/web/packages/flexCausal/index.html |
| ForCausality | https://cran.r-project.org/web/packages/ForCausality/index.html |
| mediation: Causal Mediation Analysis | https://cran.r-project.org/web/packages/mediation |
| MRPC | https://cran.r-project.org/web/packages/MRPC |
| https://github.com/AthenaCore/AwesomeResponsibleAI#data-management |
| DataRec | https://github.com/sisinflab/DataRec |
| https://github.com/AthenaCore/AwesomeResponsibleAI#data-quality |
| Pointblank | https://posit-dev.github.io/pointblank/ |
| https://github.com/AthenaCore/AwesomeResponsibleAI#data-version-control |
| DvC | https://dvc.org |
| https://github.com/AthenaCore/AwesomeResponsibleAI#drift-1 |
| Alibi Detect | https://github.com/SeldonIO/alibi-detect |
| Deepchecks | https://github.com/deepchecks/deepchecks |
| drifter | https://cran.r-project.org/web/packages/drifter/ |
| Evidently | https://github.com/evidentlyai/evidently |
| nannyML | https://github.com/NannyML/nannyml |
| phoenix | https://github.com/Arize-ai/phoenix |
| PKBooks | https://github.com/Pushp-Kharat1/pkboost |
| https://github.com/AthenaCore/AwesomeResponsibleAI#eu-ai-act-compliance |
| AI Act Companion | https://github.com/JKasteele/ai-act-companion |
| AI Act Skills | https://github.com/abk1969/ai-act-skills |
| EuConform | https://euconform.eu |
| eu-ai-act-checklist | https://github.com/GatisOzols/eu-ai-act-checklist |
| YRproject | https://yrproject.nl |
| https://github.com/AthenaCore/AwesomeResponsibleAI#fairness-1 |
| Aequitas' Bias & Fairness Audit Toolkit | http://aequitas.dssg.io/ |
| AI360 Toolkit | https://github.com/Trusted-AI/AIF360 |
| dsld: Data Science Looks at Discrimination | https://cran.r-project.org/web/packages/dsld/index.html |
| EDFfair: Explicitly Deweighted Features | https://github.com/matloff/EDFfair |
| EquiPy | https://github.com/equilibration/equipy |
| fairadapt | https://cran.r-project.org/web/packages/fairadapt/index.html |
| faircause | https://github.com/dplecko/CFA |
| Fairlearn | https://fairlearn.org |
| fairmetrics | https://jianhuig.github.io/fairmetrics/ |
| fmm-fairness-eval | https://github.com/Ces107/fmm-fairness-eval-cli |
| Fairmodels | https://fairmodels.drwhy.ai |
| fairness | https://cran.r-project.org/web/packages/fairness/ |
| Fairness Indicators | https://github.com/tensorflow/fairness-indicators |
| FairRankTune | https://kcachel.github.io/fairranktune/ |
| Fairsight Toolkit | https://github.com/KS-Vijay/fairsight |
| FairPAN - Fair Predictive Adversarial Network | https://modeloriented.github.io/FairPAN/ |
| Intersectional Fairness (ISF) | https://github.com/intersectional-fairness/isf |
| OxonFair | https://github.com/oxfordinternetinstitute/oxonfair |
| Themis ML | https://github.com/cosmicBboy/themis-ml |
| What-If Tool | https://github.com/PAIR-code/what-if-tool |
| https://github.com/AthenaCore/AwesomeResponsibleAI#feature-stores |
| Butterfree | https://github.com/quintoandar/butterfree |
| Featureform | https://github.com/featureform/featureform |
| Feathr | https://github.com/feathr-ai/feathr |
| Feast | https://github.com/feast-dev/feast |
| Hopsworks | https://github.com/logicalclocks/hopsworks |
| https://github.com/AthenaCore/AwesomeResponsibleAI#interpretabilityexplicability |
| Alibi Explain | https://github.com/SeldonIO/alibi |
| Automated interpretability | https://github.com/openai/automated-interpretability |
| AI360 Toolkit | https://github.com/Trusted-AI/AIF360 |
| aorsf: Accelerated Oblique Random Survival Forests | https://cran.r-project.org/web/packages/aorsf/index.html |
| breakDown: Model Agnostic Explainers for Individual Predictions | https://cran.r-project.org/web/packages/breakDown/index.html |
| captum | https://github.com/pytorch/captum |
| ceterisParibus: Ceteris Paribus Profiles | https://cran.r-project.org/web/packages/ceterisParibus/index.html |
| DALEX: moDel Agnostic Language for Exploration and eXplanation | https://dalex.drwhy.ai |
| DALEXtra: extension for DALEX | https://modeloriented.github.io/DALEXtra |
| Dianna | https://github.com/dianna-ai/dianna |
| Diverse Counterfactual Explanations (DiCE) | https://github.com/interpretml/DiCE |
| dtreeviz | https://github.com/parrt/dtreeviz |
| ecco | https://pypi.org/project/ecco/ |
| article | https://jalammar.github.io/explaining-transformers/ |
| effector | https://github.com/givasile/effector |
| effectplots | https://github.com/mayer79/effectplots |
| eli5 | https://github.com/TeamHG-Memex/eli5 |
| explabox | https://explabox.readthedocs.io/en/latest/index.html |
| eXplainability Toolbox | https://ethical.institute/xai.html |
| ExplainaBoard | https://github.com/neulab/ExplainaBoard |
| ExplainerHub | https://explainerdashboard.readthedocs.io/en/latest/index.html |
| in github | https://github.com/oegedijk/explainerdashboard |
| e2tree | https://cran.r-project.org/web/packages/e2tree/index.html |
| fastshap | https://github.com/bgreenwell/fastshap |
| fasttreeshap | https://github.com/linkedin/fasttreeshap |
| FAT Forensics | https://fat-forensics.org/ |
| ferret | https://github.com/g8a9/ferret |
| flashlight | https://github.com/mayer79/flashlight |
| Human Learn | https://github.com/koaning/human-learn |
| hstats | https://cran.r-project.org/web/packages/hstats/index.html |
| innvestigate | https://github.com/albermax/innvestigate |
| Inseq | https://github.com/inseq-team/inseq |
| intepretML | https://interpret.ml |
| interactions: Comprehensive, User-Friendly Toolkit for Probing Interactions | https://cran.r-project.org/web/packages/interactions/index.html |
| kernelshap: Kernel SHAP | https://cran.r-project.org/web/packages/kernelshap/index.html |
| midr | https://cran.r-project.org/web/packages/midr/index.html |
| Learning Interpretability Tool | https://pair-code.github.io/lit/ |
| lime: Local Interpretable Model-Agnostic Explanations | https://cran.r-project.org/web/packages/lime/index.html |
| Network Dissection | http://netdissect.csail.mit.edu |
| OmniXAI | https://github.com/salesforce/OmniXAI |
| pre | https://cran.r-project.org/web/packages/pre/index.html |
| ReasonGraph | https://github.com/ZongqianLi/ReasonGraph |
| Shap | https://github.com/slundberg/shap |
| Shapash | https://github.com/maif/shapash |
| shapper | https://cran.r-project.org/web/packages/shapper/index.html |
| shapviz | https://cran.r-project.org/web/packages/shapviz/index.html |
| Skater | https://github.com/oracle/Skater |
| survex | https://github.com/ModelOriented/survex |
| teller | https://github.com/Techtonique/teller |
| TCAV (Testing with Concept Activation Vectors) | https://pypi.org/project/tcav/ |
| Transformer Debugger | https://github.com/openai/transformer-debugger |
| truelens | https://pypi.org/project/trulens/ |
| truelens-eval | https://pypi.org/project/trulens-eval/ |
| pre: Prediction Rule Ensembles | https://cran.r-project.org/web/packages/pre/index.html |
| Vetiver | https://rstudio.github.io/vetiver-r/ |
| vip | https://github.com/koalaverse/vip |
| vivid | https://cloud.r-project.org/web/packages/vivid/index.html |
| XAI - An eXplainability toolbox for machine learning | https://github.com/EthicalML/xai |
| xplique | https://github.com/deel-ai/xplique |
| XAIoGraphs | https://github.com/Telefonica/XAIoGraphs |
| XAITK | https://xaitk.org/ |
| Zennit | https://github.com/chr5tphr/zennit |
| https://github.com/AthenaCore/AwesomeResponsibleAI#interpretable-models |
| imodels | https://github.com/csinva/imodels |
| imodelsX | https://github.com/csinva/imodelsX |
| interpretML | https://github.com/interpretml/interpret |
| R | https://cran.r-project.org/web/packages/interpret/index.html |
| PiML Toolbox | https://github.com/SelfExplainML/PiML-Toolbox |
| Tensorflow Lattice | https://github.com/tensorflow/lattice |
| Trust-free | https://pypi.org/project/trust-free/ |
| https://github.com/AthenaCore/AwesomeResponsibleAI#model-verification |
| Model Transparency | https://github.com/sigstore/model-transparency |
| https://github.com/AthenaCore/AwesomeResponsibleAI#llm-evaluations-and-benchmarks |
| arXiv:2504.2087 | https://arxiv.org/pdf/2504.20879 |
| arXiv:2503.05336 | https://arxiv.org/pdf/2503.05336 |
| PREP-Eval v1.0
Pre-registration and REporting Protocol for AI Evaluations | https://prep-eval.github.io/prep-eval/ |
| Evals-Consensus | https://evals-consensus.ai |
| AbsenceBench | https://github.com/harvey-fin/absence-bench |
| AIluminate | https://mlcommons.org/ailuminate/ |
| AI Wellbeing | https://www.ai-wellbeing.org |
| AlignEval: Making Evals Easy, Fun, and Semi-Automated | https://aligneval.com |
| Motivation | https://eugeneyan.com/writing/aligneval/ |
| AlpacaEval | https://github.com/tatsu-lab/alpaca_eval |
| ARC AGI 1 | https://arcprize.org/arc-agi/1 |
| ARC AGI 2 | https://arcprize.org/arc-agi/2 |
| ARES | https://github.com/stanford-futuredata/ARES |
| Artificial Analysis Omniscience Index | https://artificialanalysis.ai/evaluations/omniscience |
| Autoeval | https://auto-eval.github.io |
| Azure AI Evaluation | https://github.com/Azure/azure-sdk-for-python/tree/main/sdk/evaluation/azure-ai-evaluation |
| BabyReasoningBench | https://github.com/kaustubhdhole/baby-reasoning-bench |
| Banana-lyzer | https://github.com/reworkd/bananalyzer |
| BALROG | https://github.com/balrog-ai/BALROG |
| BIG-Bench Extra Hard | https://github.com/google-deepmind/bbeh |
| BountyBench | https://bountybench.github.io/ |
| BrokenMath: A Benchmark for Sycophancy in Theorem Proving with LLMs | https://www.sycophanticmath.ai |
| Catastrophic Cyber Capabilities Benchmark (3CB) | https://github.com/AthenaCore/AwesomeResponsibleAI/blob/main/%60Python%60 |
| Chinese Safety Evaluations | https://airtable.com/appkPf0Rw2P7KCY5i/shrpXozZcomLjmBf3/tblV6tS87aqOgrDJX/viwukUaSfInPLoQun |
| CL-Bench | https://www.clbench.com |
| CLUE benchmark | https://github.com/CLUEbenchmark/CLUE |
| CritPt | https://critpt.com |
| Cybench | https://cybench.github.io/ |
| DarkBench | https://github.com/smarter/DarkBench |
| DeepEval | https://github.com/confident-ai/deepeval |
| DeepSWE | https://github.com/datacurve-ai/deep-swe |
| DELEGATE-52 | https://github.com/microsoft/DELEGATE52 |
| LLMs Corrupt Your Documents When You Delegate | https://arxiv.org/abs/2604.15597 |
| evals | https://github.com/openai/evals |
| EvalScope | https://github.com/modelscope/evalscope |
| evmbench | https://paradigm.xyz/evmbench |
| FMBench | https://github.com/aws-samples/foundation-model-benchmarking-tool |
| FlagEval | https://github.com/flageval-baai/FlagEval |
| FBI: Finding Blindspots in LLM Evaluations with Interpretable Checklists | https://github.com/AI4Bharat/FBI |
| ForecastBench | https://www.forecastbench.org |
| ForesightSafety-Bench | https://github.com/Beijing-AISI/ForesightSafety-Bench |
| FrontierMath | https://epoch.ai/frontiermath |
| Geekbench AI | https://www.geekbench.com/ai/ |
| GDPval | https://huggingface.co/datasets/openai/gdpval |
| Paper | https://cdn.openai.com/pdf/d5eb7428-c4e9-4a33-bd86-86dd4bcf12ce/GDPval.pdf |
| GPQA: A Graduate-Level Google-Proof Q&A Benchmark | https://github.com/idavidrein/gpqa |
| Epoch Dashboard | https://epoch.ai/benchmarks/gpqa-diamond?view=graph&tab=release-date |
| Giskard | https://github.com/Giskard-AI/giskard |
| HAL Harness | https://github.com/princeton-pli/hal-harness |
| Harbor | https://harborframework.com |
| HELM | https://github.com/stanford-crfm/helm |
| Humanity's Last Exam (HLE) | https://lastexam.ai |
| Humanity's Last Exam (HLE)-Verified | https://github.com/SKYLENAGE-AI/HLE-Verified |
| HybridRAG-Bench | https://junhongmit.github.io/HybridRAG-Bench/ |
| Inspect | https://ukgovernmentbeis.github.io/inspect_ai/ |
| Inspect Petri | https://meridianlabs-ai.github.io/inspect_petri/ |
| Inspect Scout | https://meridianlabs-ai.github.io/inspect_scout/ |
| Inspect Flow | https://meridianlabs-ai.github.io/inspect_flow/ |
| Inspect Petri Dish | https://github.com/meridianlabs-ai/petri_dish |
| Inspect Petri Bloom | https://meridianlabs-ai.github.io/petri_bloom/ |
| Intercode | https://intercode-benchmark.github.io/ |
| Intima Benchmark | https://huggingface.co/AI-companionship |
| Paper | https://arxiv.org/abs/2508.09998 |
| Jailbreakbench | https://jailbreakbench.github.io |
| JailBreakV-28K | https://eddyluo1232.github.io/JailBreakV28K/ |
| JGLUE: Japanese General Language Understanding Evaluation | https://github.com/yahoojapan/JGLUE |
| KLUE: Korean Language Understanding Evaluation | https://github.com/KLUE-benchmark/KLUE |
| LABBench2 | https://lab-bench.ai |
| Machiavelli | https://aypan17.github.io/machiavelli/ |
| MalayMMLU | https://github.com/UMxYTL-AI-Labs/MalayMMLU |
| Mask Benchmark | https://www.mask-benchmark.ai |
| Math Science Bench | https://math.science-bench.ai |
| MCPBench: A Benchmark for Evaluating MCP Servers | https://github.com/modelscope/MCPBench |
| MixEval | https://mixeval.github.io |
| ML Commons Safety Benchmark for general purpose AI chat model | https://mlcommons.org/benchmarks/ai-safety/general_purpose_ai_chat_benchmark/ |
| MLflow LLM Evaluation | https://mlflow.org/docs/latest/llms/llm-evaluate/index.html |
| MLGym | https://github.com/facebookresearch/MLGym |
| MLPerf Training Benchmark | https://mlcommons.org/benchmarks/training/ |
| MMMU | https://github.com/MMMU-Benchmark/MMMU |
| Moonshoot | https://github.com/aiverify-foundation/moonshot |
| MoReBench | https://morebench.github.io |
| Multi-SWE-bench: A Multilingual Benchmark for Issue Resolving | https://multi-swe-bench.github.io/ |
| NaturalBench | https://linzhiqiu.github.io/papers/naturalbench/ |
| NYU CFT Bench | https://nyu-llm-ctf.github.io/ |
| Langchain | https://docs.smith.langchain.com |
| Evaluations | https://docs.smith.langchain.com/evaluation |
| Langfuse | https://github.com/langfuse/langfuse |
| Scores | https://langfuse.com/docs/scores/overview |
| LightEval | https://github.com/huggingface/lighteval |
| LiveBench: A Challenging, Contamination-Free LLM Benchmark | https://livebench.ai |
| LM Evaluation Harness | https://github.com/EleutherAI/lm-evaluation-harness |
| lmms-eval | https://github.com/EvolvingLMMs-Lab/lmms-eval |
| OffsetBias: Leveraging Debiased Data for Tuning Evaluators | https://github.com/ncsoft/offsetbias |
| opik | https://github.com/comet-ml/opik |
| Petri | https://github.com/safety-research/petri |
| Phare LLM Benchmark | https://phare.giskard.ai |
| Phoenix | https://github.com/Arize-ai/phoenix |
| Political Even-handedness Evaluation | https://github.com/anthropics/political-neutrality-eval |
| Prometheus | https://github.com/prometheus-eval/prometheus |
| Promptfoo | https://github.com/promptfoo/promptfoo |
| Prophet Arena | https://www.prophetarena.co |
| PurpleLlama | https://github.com/meta-llama/PurpleLlama |
| Pydantic Evals | https://ai.pydantic.dev/evals/#datasets-and-cases |
| ragas | https://github.com/explodinggradients/ragas |
| Remote Labor Index | https://www.remotelabor.ai |
| RewardBench: Evaluating Reward Models | https://github.com/allenai/reward-bench |
| Rouge | https://pypi.org/project/rouge/ |
| SALAD-BENCH | https://github.com/OpenSafetyLab/SALAD-BENCH |
| Article | https://arxiv.org/abs/2402.05044 |
| SciCode | https://scicode-bench.github.io |
| Selene Mini | https://github.com/atla-ai/selene-mini |
| simple evals | https://github.com/openai/simple-evals |
| SnitchBench | https://github.com/t3dotgg/SnitchBench |
| StrongREJECT jailbreak benchmark | https://github.com/dsbowen/strong_reject |
| SWE-bench Verified | https://www.swebench.com/verified.html |
| TealTiger | https://github.com/agentguard-ai/tealtiger |
| terminal-bench | https://www.tbench.ai |
| TextQuests | https://www.textquests.ai |
| The Berkeley Function Calling Leaderboard (BFCL) | https://gorilla.cs.berkeley.edu/leaderboard.html |
| τ²-bench: Evaluating Conversational Agents in a Dual-Control Environment | https://github.com/sierra-research/tau2-bench |
| Yet Another Applied LLM Benchmark | https://github.com/carlini/yet-another-applied-llm-benchmark |
| Vending Bench | https://andonlabs.com/evals/vending-bench |
| Verdict | https://github.com/haizelabs/verdict |
| Virology Capabilities Test | https://www.virologytest.ai |
| vitals | https://vitals.tidyverse.org |
| VCBench | https://www.vcbench.com |
| Paper | https://arxiv.org/abs/2509.14448 |
| VLMEvalKit | https://github.com/open-compass/VLMEvalKit |
| Weapons of Mass Destruction Proxy (WMDP) benchmark | https://www.wmdp.ai |
| Werewolf Social Bench | https://werewolf.foaster.ai |
| WindowsAgentArena | https://github.com/microsoft/windowsagentarena |
| XEvalAD | https://github.com/SabaFathi/XEvalAD |
| here | https://airtable.com/app83SBBFk9WO25hJ/shrSs3bXSx2bBDrso/tblNpnE4pzBnaC5lT?viewControls=on |
| AI Benchmarking Hub | https://epoch.ai/benchmarks |
| CAIS AI Dashboard | https://dashboard.safe.ai/#safety |
| here | https://github.com/anthropics/courses/blob/master/prompt_evaluations/README.md |
| https://github.com/AthenaCore/AwesomeResponsibleAI#llm-regulation-compliance |
| COMPL-AI | https://compl-ai.org |
| Tunix | https://github.com/google/tunix |
| https://github.com/AthenaCore/AwesomeResponsibleAI#performance--automated-ml |
| auditor | https://github.com/ModelOriented/auditor |
| automl: Deep Learning with Metaheuristic | https://cran.r-project.org/web/packages/automl/index.html |
| AutoKeras | https://github.com/keras-team/autokeras |
| Auto-Sklearn | https://github.com/automl/auto-sklearn |
| DataPerf | https://sites.google.com/mlcommons.org/dataperf/ |
| deepchecks | https://deepchecks.com |
| EloML | https://github.com/ModelOriented/EloML |
| Featuretools | https://www.featuretools.com |
| LOFO Importance | https://github.com/aerdem4/lofo-importance |
| forester | https://modeloriented.github.io/forester/ |
| metrica: Prediction performance metrics | https://adriancorrendo.github.io/metrica/ |
| MLmetrics | https://github.com/yanyachen/MLmetrics |
| model-diagnostics | https://github.com/lorentzenchr/model-diagnostics |
| NNI: Neural Network Intelligence | https://github.com/microsoft/nni |
| performance | https://github.com/easystats/performance |
| rliable | https://github.com/google-research/rliable |
| roclab: ROC-Optimizing Binary Classifiers | https://cran.r-project.org/web/packages/roclab/index.html |
| ROCnGO | https://cran.r-project.org/web/packages/ROCnGO/index.html |
| Silhouette | https://cran.r-project.org/web/packages/Silhouette/index.html |
| SLmetrics | https://github.com/serkor1/SLmetrics/ |
| TensorFlow Model Analysis | https://github.com/tensorflow/model-analysis |
| TPOT | http://epistasislab.github.io/tpot/ |
| Unleash | https://www.getunleash.io |
| yardstick | https://github.com/tidymodels/yardstick |
| Yellowbrick | https://www.scikit-yb.org/en/latest/ |
| WeightWatcher | https://github.com/CalculatedContent/WeightWatcher |
| Examples | https://github.com/CalculatedContent/WeightWatcher-Examples |
| https://github.com/AthenaCore/AwesomeResponsibleAI#aidata-poisoning |
| Copyright Traps for Large Language Models | https://github.com/computationalprivacy/copyright-traps |
| Nightshade | https://nightshade.cs.uchicago.edu |
| Glaze | https://glaze.cs.uchicago.edu |
| Fawkes | http://sandlab.cs.uchicago.edu/fawkes/ |
| https://github.com/AthenaCore/AwesomeResponsibleAI#privacy |
| BackPACK | https://toiaydcdyywlhzvlob.github.io/backpack |
| diffpriv | https://github.com/brubinstein/diffpriv |
| Diffprivlib | https://github.com/IBM/differential-privacy-library |
| Discrete Gaussian for Differential Privacy | https://github.com/IBM/discrete-gaussian-differential-privacy |
| Faker | https://pypi.org/project/Faker/ |
| FakeDataR: Privacy-Preserving Synthetic Data for 'LLM' Workflows | https://cran.r-project.org/web/packages/FakeDataR/index.html |
| GRANDpriv | https://cran.r-project.org/web/packages/GRANDpriv/index.html |
| JAX-Privacy | https://github.com/google-deepmind/jax_privacy |
| Opacus | https://opacus.ai |
| Privacy Meter | https://github.com/privacytrustlab/ml_privacy_meter |
| PyVacy: Privacy Algorithms for PyTorch | https://github.com/ChrisWaites/pyvacy |
| SEAL | https://github.com/Microsoft/SEAL |
| Tensorflow Privacy | https://github.com/tensorflow/privacy |
| https://github.com/AthenaCore/AwesomeResponsibleAI#red-teaming |
| AutoDan | https://autodans.github.io/AutoDAN/ |
| Rival AI | https://github.com/sarthakrastogi/rival |
| TextAttack | https://github.com/QData/TextAttack |
| https://github.com/AthenaCore/AwesomeResponsibleAI#reliability-evaluation-of-post-hoc-explanation-methods-and-llms-evaluations |
| BELLS (Benchmark for the Evaluation of LLM Safeguards) | https://github.com/CentreSecuriteIA/BELLS |
| BetterBench | https://betterbench.stanford.edu |
| Database | https://betterbench.stanford.edu/database.html |
| openXAI | https://open-xai.github.io |
| https://github.com/AthenaCore/AwesomeResponsibleAI#robustness |
| Autoguardrails | https://github.com/SantanderAI/autoguardrails |
| Adversarial Robustness Toolbox (ART) | https://github.com/Trusted-AI/adversarial-robustness-toolbox |
| BackdoorBench | https://github.com/SCLBD/BackdoorBench |
| Factool | https://github.com/GAIR-NLP/factool |
| Foolbox | https://github.com/bethgelab/foolbox |
| Guardrails | https://github.com/guardrails-ai/guardrails |
| Guardrails Hub | https://hub.guardrailsai.com |
| https://github.com/AthenaCore/AwesomeResponsibleAI#safety |
| AIxploit | https://github.com/AINTRUST-AI/aixploit |
| Bandit | https://github.com/PyCQA/bandit |
| Diotra | https://github.com/usnistgov/dioptra |
| Garak | https://github.com/NVIDIA/garak |
| Model Inversion Attack ToolBox | https://github.com/ffhibnese/Model-Inversion-Attack-ToolBox |
| NeMo Guardrails | https://github.com/NVIDIA/NeMo-Guardrails |
| Qwen3Guard | https://github.com/QwenLM/Qwen3Guard |
| RAXE | https://github.com/raxe-ai/raxe-ce |
| Safety CLI | https://github.com/pyupio/safety |
| wildguard | https://github.com/allenai/wildguard |
| https://github.com/AthenaCore/AwesomeResponsibleAI#security |
| Counterfit | https://github.com/Azure/counterfit/ |
| detect-secrets | https://github.com/Yelp/detect-secrets |
| Modelscan | https://github.com/protectai/modelscan |
| LLM Guard | https://github.com/protectai/llm-guard |
| NB Defense | https://nbdefense.ai |
| PyRIT | https://github.com/Azure/PyRIT |
| Rebuff Playground | https://www.rebuff.ai/playground |
| Resk-LLM | https://github.com/Resk-Security/Resk-LLM |
| Turing Data Safe Haven | https://github.com/alan-turing-institute/data-safe-haven |
| Data Breach | https://databreach.com |
| Have I been pwned? | https://haveibeenpwned.com |
| Have I Been Trained? | https://haveibeentrained.com |
| https://github.com/AthenaCore/AwesomeResponsibleAI#synthetic-data |
| Curator | https://github.com/bespokelabsai/curator |
| DataSynthesizer: Privacy-Preserving Synthetic Datasets | https://github.com/DataResponsibly/DataSynthesizer |
| Gretel Synthetics | https://github.com/gretelai/gretel-synthetics |
| SmartNoise | https://github.com/opendp/smartnoise-core |
| SDV | https://github.com/sdv-dev/SDV |
| Snorkel | https://github.com/snorkel-team/snorkel |
| YData Synthetic | https://github.com/ydataai/ydata-synthetic |
| https://github.com/AthenaCore/AwesomeResponsibleAI#sustainability-1 |
| AI Energy Consumption Calculator | https://aienergycalculator.com |
| AI Energy Score | https://huggingface.co/AIEnergyScore |
| Azure Sustainability Calculator | https://appsource.microsoft.com/en-us/product/power-bi/coi-sustainability.sustainability_dashboard |
| Carbon Tracker | https://github.com/lfwa/carbontracker |
| Website | https://carbontracker.info |
| CodeCarbon | https://github.com/mlco2/codecarbon |
| Website | https://codecarbon.io |
| Computer Progress | https://www.computerprogress.com |
| Eco2AI | https://github.com/sb-ai-lab/Eco2AI |
| Green Algorithms | https://www.green-algorithms.org |
| Impact Framework | https://if.greensoftware.foundation |
| ML CO2 IMPACT | https://mlco2.github.io/impact/ |
| The ML.ENERGY Data & Toolkit | https://ml.energy/data/ |
| The ML.ENERGY Leaderboard | https://ml.energy/leaderboard/ |
| https://github.com/AthenaCore/AwesomeResponsibleAI#rai-toolkit |
| Deepchecks | https://github.com/deepchecks/deepchecks |
| Dr. Why | https://github.com/ModelOriented/DrWhy |
| Mercury | https://www.bbvaaifactory.com/mercury/ |
| Responsible AI Toolbox | https://github.com/microsoft/responsible-ai-toolbox |
| Responsible AI Widgets | https://github.com/microsoft/responsible-ai-widgets |
| The Data Cards Playbook | https://pair-code.github.io/datacardsplaybook/ |
| Zeno Hub | https://github.com/zeno-ml/zeno-hub |
| https://github.com/AthenaCore/AwesomeResponsibleAI#ai-watermarking |
| AudioSeal: Proactive Localized Watermarking | https://github.com/facebookresearch/audioseal |
| MarkLLM: An Open-Source Toolkit for LLM Watermarking | https://github.com/thu-bpm/markllm |
| SynthID Text | https://github.com/google-deepmind/synthid-text |
| https://github.com/AthenaCore/AwesomeResponsibleAI#citing-this-repository |
| https://github.com/AthenaCore/AwesomeResponsibleAI#bibtex |
| https://github.com/AthenaCore/AwesomeResponsibleAI#acm-apa-chicago-and-mla |
| https://github.com/AthenaCore/AwesomeResponsibleAI | https://github.com/AthenaCore/AwesomeResponsibleAI |
| https://github.com/AthenaCore/AwesomeResponsibleAI | https://github.com/AthenaCore/AwesomeResponsibleAI |
| https://github.com/AthenaCore/AwesomeResponsibleAI | https://github.com/AthenaCore/AwesomeResponsibleAI |
| https://github.com/AthenaCore/AwesomeResponsibleAI | https://github.com/AthenaCore/AwesomeResponsibleAI |
|
ai
| https://github.com/topics/ai |
|
awesome-list
| https://github.com/topics/awesome-list |
|
ai-safety
| https://github.com/topics/ai-safety |
|
interpretable-ai
| https://github.com/topics/interpretable-ai |
|
explainable-ai
| https://github.com/topics/explainable-ai |
|
xai
| https://github.com/topics/xai |
|
ai-alignment
| https://github.com/topics/ai-alignment |
|
fairness-ai
| https://github.com/topics/fairness-ai |
|
responsible-ai
| https://github.com/topics/responsible-ai |
|
human-centered-ai
| https://github.com/topics/human-centered-ai |
|
ethical-ai
| https://github.com/topics/ethical-ai |
|
trustworthy-ai
| https://github.com/topics/trustworthy-ai |
|
ai-regulation
| https://github.com/topics/ai-regulation |
|
ai-governance
| https://github.com/topics/ai-governance |
|
ai-standards
| https://github.com/topics/ai-standards |
|
Readme
| https://github.com/AthenaCore/AwesomeResponsibleAI#readme-ov-file |
|
MIT license
| https://github.com/AthenaCore/AwesomeResponsibleAI#MIT-1-ov-file |
| Please reload this page | https://github.com/AthenaCore/AwesomeResponsibleAI |
|
Activity | https://github.com/AthenaCore/AwesomeResponsibleAI/activity |
|
Custom properties | https://github.com/AthenaCore/AwesomeResponsibleAI/custom-properties |
|
56
forks | https://github.com/AthenaCore/AwesomeResponsibleAI/forks |
|
Report repository
| https://github.com/contact/report-content?content_url=https%3A%2F%2Fgithub.com%2FAthenaCore%2FAwesomeResponsibleAI&report=AthenaCore+%28user%29 |
| Releases | https://github.com/AthenaCore/AwesomeResponsibleAI/releases |
| Packages
0 | https://github.com/orgs/AthenaCore/packages?repo_name=AwesomeResponsibleAI |
| Please reload this page | https://github.com/AthenaCore/AwesomeResponsibleAI |
| Please reload this page | https://github.com/AthenaCore/AwesomeResponsibleAI |
| Contributors | https://github.com/AthenaCore/AwesomeResponsibleAI/graphs/contributors |
| Please reload this page | https://github.com/AthenaCore/AwesomeResponsibleAI |
|
| https://github.com |
| Terms | https://docs.github.com/site-policy/github-terms/github-terms-of-service |
| Privacy | https://docs.github.com/site-policy/privacy-policies/github-privacy-statement |
| Security | https://github.com/security |
| Status | https://www.githubstatus.com/ |
| Community | https://github.community/ |
| Docs | https://docs.github.com/ |
| Contact | https://support.github.com?tags=dotcom-footer |
