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Articles by Tag: Responsible AI

Learning from Shadow AI: Delivering the AI Tools Your Employees Actually Need
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Learning from Shadow AI: Delivering the AI Tools Your Employees Actually Need

As AI adoption surges, shadow AI was bound to follow, just like shadow IT before it. This can lead to data leaks and compliance violations, prompting urgent alarms when detected. However, it is also important to understand why shadow AI occurs. By uncovering its root causes, CISOs and IT leaders can close gaps and deploy the AI tools that employees truly need.
Shadow AI: Turning Hidden Risks into Secure Innovation
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Shadow AI: Turning Hidden Risks into Secure Innovation

Shadow AI, the unsanctioned use of generative AI in enterprises, offers productivity benefits but introduces serious risks, from data leaks to regulatory breaches. SMEs can respond by strengthening governance, enabling secure experimentation, and integrating sanctioned AI pathways to balance innovation with compliance. CISOs and IT leaders must address shadow AI risks while enabling safe, innovative adoption.
How ISO/IEC 42001 is Shaping Responsible AI
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How ISO/IEC 42001 is Shaping Responsible AI

ISO/IEC 42001 is the world’s first international standard for managing AI responsibly. It provides a formal AI Management System framework to help AI developers embed governance and transparency into their AI. IT leaders and AI teams can embed this standard into procurement to ensure that their businesses only adopt auditable, trustworthy, and ethical AI.
Bias in the Machine: How to Find Blind Spots in LLMs
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Bias in the Machine: How to Find Blind Spots in LLMs

Auditing bias in large language models (LLMs) is not just a technical requirement; it is mission-critical for fair, trusted AI. Biased models can lead to regulatory penalties, financial loss, reputational damage, and eroded trust. IT leaders and AI teams in SMEs must understand how to detect biases in data and models to create more trustworthy AI systems.
Mitigate AI Risk with the OWASP AI Testing Guide
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Mitigate AI Risk with the OWASP AI Testing Guide

As AI systems scale into production, traditional validation practices may fall short. The OWASP AI Testing Guide (AITG) provides a structured framework for testing AI-specific risks, from adversarial threats to infrastructure vulnerabilities. CISOs should review OWASP’s AI Testing Guide to help ensure secure and responsible AI deployment.
ChatGPT Edu: AI’s Charge Towards Higher Education
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ChatGPT Edu: AI’s Charge Towards Higher Education

ChatGPT Edu aims to bring responsible AI use to educational institutions. Despite its security and privacy features, there are still concerns with ChatGPT Edu and other similar AI products. CIOs and education technologists can read this article to learn about ChatGPT Edu’s strengths and shortcomings.
Mitigating Bias and Fostering Inclusivity in Your LLM Solutions
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Mitigating Bias and Fostering Inclusivity in Your LLM Solutions

As Large Language Models (LLMs) become more integrated into business solutions, more instances of how they perpetuate social bias can be identified. Companies using LLMs must recognize that the model's output may reflect inherent biases, which can have adverse business implications. Developers and users of LLMs should implement bias mitigation strategies to ensure outputs align with organizational values.