AI Ethics & Responsible AI
Discover a clear, standards‑aligned path to Responsible AI. Learn how CognitiveView’s 3‑step Governance, Risk, and Compliance (GRC) journey helps you assess, monitor, and comply with frameworks such as NIST, the EU AI Act, and ISO 42001—while growing at your own pace.
Use Deepeval to build a continuous quality gate for LLMs that blocks hallucinations, bias, and drift. This guide shows how to integrate it with GitHub Actions and your risk framework—aligning AI deployments with NIST and ISO standards using open-source tools.
AI isn’t replacing your workforce—it’s becoming part of it. In this recap of my conversation with Dr. Ranjan Data, we break down how to move from AI fear to fluency with practical steps for reskilling, governance, and designing a truly hybrid workforce.
In regulated industries, AI governance isn’t optional—it’s foundational. Discover how launching a TrustCenter can accelerate your sales by proactively addressing buyer concerns around risk, compliance, and governance.
AI startups struggle when missing AI documentation stalls deals and slows procurement. In this guide, learn how to self-assess, leverage our AI Policy Assistant, and publish a shareable Trust Center—in under two hours—so you can build trust and move forward without a legal team.
Procurement teams are raising the bar for AI startups. This guide helps you prepare with rapid self-assessments, policy automation, and transparency that builds trust and accelerates deals.
Understand how OMB M-25-21 is reshaping AI use in government. From CAIO roles to high-impact AI rules, we break down what agencies and vendors need to know—plus provide a compliance checklist.
The Double-Edged Sword of AI AI is transforming industries, enhancing productivity, and revolutionizing decision-making. But with great power comes great responsibility—and significant risks. From algorithmic bias in hiring systems to deepfake videos manipulating public perception, AI’s dark side is becoming harder to ignore. A recent study found that
Striking the Right Balance Between Automation & Human Oversight AI is revolutionizing industries—from automating customer service to making high-stakes financial decisions. But as AI systems grow more powerful, the question remains: how much human oversight is needed to ensure fairness, compliance, and accountability? The concept of Human-in-the-Loop (HITL) AI
Introduction Why Explainable AI is Critical for Compliance As artificial intelligence adoption grows regulators are demanding greater AI transparency and accountability AI systems make critical decisions in finance healthcare hiring and legal sectors yet many operate as black boxes without clear explanations Regulations such as the EU AI Act GDPR
Can AI be both high-performing and transparent? As black-box AI models dominate decision-making, concerns over bias, accountability, and regulatory compliance grow. Explore the ethical dilemma of AI explainability, its impact on industries, and best practices for responsible AI governance.
AI-generated disinformation is a rising threat, from deepfakes to AI-created fake news. Learn how AI governance frameworks can help prevent misinformation by enforcing transparency, compliance, and ethical AI practices, ensuring trust and accountability in AI-driven content.
