Responsible AI
Ethics, fairness, bias, transparency and accountability in how AI is built and used
Latest stories See all →
- What Did a New Automation Bias Study Find About AI in Mammography?
- Can Your AI Show Its Work? Why Enterprise Data Agents Need an Evidence Layer
- New AI Transparency Cards help answer customer questions in Autodesk Assistant
- The AI Ethics Brief #199: The Capacity to Govern
- Who can you trust in the age of AI agents?
- The trust gap: why AI works for code but not (yet) for the rest of your work
- Can Your AI Show Its Work? Why Enterprise Data Agents Need an Evidence Layer
- Political Bias Grows as the Adoption of Chinese AI Models Accelerates, New Benchmark Reveals
- Latest postThe trust gap: why AI works for code but not (yet) for the rest of your work
- Explainable Deny: Authorization Decision Evidence for SOC 2-Style Access Reviews
- Trust by Design: What Makes Patient-Generated Data Reliable?Patient-generated data from smartphones, wearables, home-monitoring devices, digital therapeutics, and patient-reported outcomes is becoming essential to decentralized care and clinical research. Its value, however, depends not on volume but on confidence in its authenticity, accuracy, provenance, and clinical relevance. In decentralized trials, where sponsors may not directly observe adherence, safety events, or protocol activities, trustworthy data is critical to reliable study results and sound clinical decisions. As AI expands across healthcare, high-quality data supports better predictions and more actionable insights, while poor data can amplify errors. The organizations best positioned to lead will be those that validate patient-generated information at the point of capture and transform it into evidence that clinicians, researchers, regulators, and patients can trust.
- Why enterprise AI needs two modes to be trustworthy
- Agentic Telemetry Is Not an Audit Trail: Why We Built the Sovereign Trust Plane
- Agentic Telemetry Is Not an Audit Trail: Why We Built the Sovereign Trust Plane
- Top 5 AI Code Review Tools 2026
- Who Is Responsible for AI-Generated Code in Production?
- Responsible AI for Higher Education
- InsightsEvaluating Legal AI Providers Across Trust, Privacy, and Security
- Meet Grok Bot: xAI's Answer to the Agent Problem
- {unscripted} SF recap: do you trust your AI agents?
- The morning after: AI’s trust problem and what hospitality leaders should do about it
- Your Claude Code Agent Opened a PR. Now What?
- The AI race: progress, humanity, and trust
- Human or AI? The Clues You Trust May Be Fooling You
Videos
- Can We Predict AI Loss of Control? Trustworthy AI in the Age of Agents | Yinpeng Dong
- Beyond Vector Search: Building Trustworthy AI for Production
- Keynote: Trustworthy AI with Confidential Computing - Dr. Najwa Aaraj, CEO, TII
- Ep. 9 - IAPP transparency, accountability, and Bedoya on AI ethics
- AI+Education Summit 2026: Scaling Human-Centered AI – What It Takes to Transform Learning for All
- [AMA] Kickstart Your AI Fluency: Exec Ops & HR Transformation with Zapier and Zoominfo
- How Ashoka Uses Trustible to Enable Responsible AI Adoption
- Monitor Domain-Specific AI with Custom Evaluators in Your Environment
- Joule: Agility Without Compromise | SAP Business AI
- Responsible AI Evaluation ‘’What’’s, and ‘’How’’s of Evaluation
- The AI Governance Playbook You Need with Tolga Erbay
- How Companies Should Manage Shadow AI (Without Banning AI)
Podcasts
- In Machines We Trust
- The Privacy Insider
- Data Science Ethics Podcast
- Singularity.FM
- Machine Ethics Podcast
- The Good Robot
- Your Undivided Attention
- Ethical Machines
Recent episodes
- Recommender Systems Today and Tomorrow
- Recommender Systems Optimization Goals
- Building Responsible AI for Public Services With AWS
- Bill Gates wants to see a robot tax and ‘Human Reserved’ jobs, Z.ai is the AI lab behind the mysterious Ox Alpha, and US seizes domains of Chinese botnet
- Critical Thinking and Trust in AI Projects: Insights from Cheryl Howard
- 510. The AI-Savvy Leader
- Zuckerberg’s Anti-Doom Fantasy + Finally an A.I. Detector That Works + A.I. Math
- Managing Change Across Modern Financial Operations - with Ajay Swamy of JPMorganChase and Founder of FundLens.ai
- 506. Building Trustworthy AI: Eliminating Hallucinations
- Social Choice for Fair Recommendations
- 502. Moving Beyond AI Buzzwords in the Boardroom
- Inside out