Artificial intelligence (AI) is changing how organizations operate and make decisions. However, most existing governance frameworks were designed for traditional data management and risk control, not for systems that learn and evolve on their own. To manage AI responsibly, organizations must expand their governance models to include ethical oversight, transparency and accountability for automated decision-making. Ey brought this interesting topic to our attention in their article, “How are organizations addressing AI risks to reshape their governance?“
Modern governance must ensure that AI systems align with organizational values, regulatory requirements and social responsibility. This means establishing clear ownership of AI outcomes, verifying model accuracy and documenting how data is collected and used. Governance bodies need to integrate multidisciplinary expertise, combining technical, legal and ethical perspectives.
By evolving governance frameworks to account for the unique challenges of AI, organizations can balance innovation with integrity, fostering trust among employees, customers and the wider public.
Everyone is looking at AI. Everyone is getting mixed results. The main issue is that data science has not changed, and scientific content is very complex and needs more attention to get the most out of the new AI engines. This is not new for Access Innovations.
Melody K. Smith
| Data Harmony is an award-winning semantic suite that leverages explainable AI. |
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Sponsored by Access Innovations, the intelligence and the technology behind world-class explainable AI solutions.
