Whitepaper
One thing is clear as we approach an AI Era.
We require a dramatic shift in our approach to AI Governance and risk management.
This involves integrating the stability and proven practices of traditional governance with the dynamic, often unpredictable nature of AI governance.
This requires not only a deep understanding of both realms but also a visionary approach to anticipate and shape future standards. Balancing these two aspects of governance is not just about compliance and risk management.
It is about steering the Organization in a way that respects ethical boundaries while embracing technological innovation. It’s a delicate tightrope walk between the known and the unknown, the established and the emerging, the safe and the revolutionary.
This whitepaper lays out why we need to rethink our AI Strategy, AI Governance, and the impact of regulations, namely the differences in regulation approach that will heavily impact the approach organizations need to prepare for today.
I also talk about bridging the gap between requirements, planning and actionable strategy.
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Whitepaper
Generative AI Policy: A Comprehensive Analysis and Recommendations for EU and US Local Governments
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Whitepaper
Trust in AI, a KPMG paper link it to The KPMG research provides comprehensive, timely, global insights into the public’s trust and acceptance of AI systems, including who is trusted to develop, use and govern AI, the perceived benefits and risks of AI use, community expectations of the development, regulation and governance of AI, and how organisations can support trust in their AI use. It also sheds light on how people feel about the use of AI at work, current understanding and awareness of AI, and the key drivers of trust in AI systems. We also explore changes in trust and attitudes to AI over time.
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Towards Responsible AI in the era of CHatGPT REference Architecture (.pdf)
Business Pandemic Influenza Planning Checklist (.pdf)
Why you should adopt the NIST Cybersecurity Framework (.pdf)
Health system-scale language models are all-purpose prediction engines (.pdf)
How Health Systems Are Navigating the Complexities of AI (.pdf)