AI governance is becoming a priority for enterprise architects, but how can you build a framework to leverage AI safely? We spoke to AI expert Frith Tweedie to find out.
Artificial intelligence (AI) is a revolutionary technology that's already fundamentally changed the way we do business. Yet, since it's so new, it's also very little understood.
For every AI innovation, there's a question about AI ethics, AI sustainability, and the possibility of cyber criminals leveraging the technology for nefarious purposes. How can you leverage AI safely and effectively?
To find out, we spoke to AI experts across the world to discover the truth within the AI buzz. In the first part of this series, we spoke to Frith Tweedie from Simply Privacy.
To find out more about what the market is saying about AI, download our AI survey results:
Frith Tweedie has been working in artificial intelligence (AI) governance since 2019, when she was leading the digital law practice at EY in New Zealand, She also became a member of the executive council of the AI Forum NZ.
Last year, Frith was appointed to the International Association of Privacy Professionals (IAPP) AI governance center's global advisory board. She is also a member of the Data Ethics Advisory Group for the New Zealand public sector. Throughout, Frith's work has been in helping her clients design and develop responsible AI governance frameworks.
This includes risk management tools, such as the Algorithm Impact Assessment Toolkit she developed for government agencies in New Zealand. Frith also teaches the IAPP AI governance professional training course.
As such, we felt Frith was the perfect person to share the best methodology for AI governance and adoption. To begin, we asked her just what AI governance is, in her opinion.
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"Other challenges include determining where responsibility for AI governance should sit, how to efficiently risk assess AI use cases, and identifying appropriate metrics for testing AI systems across their lifecycle."
"The goal should always be maximizing the benefits of AI while minimizing potential risks."
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"Key lessons include the need to raise awareness across the business but particularly at senior levels of the key risks and, importantly, how a Responsible AI approach not only manages risk but delivers real value in terms of better performing models, competitive advantage and trust.
"Early identification of accountabilities, roles and responsibilities is important, although it can get political. It's important to take everyone on the journey with you, ensuring relationships are built with key stakeholders such as data science, data governance, privacy, cybersecurity, legal and enterprise architecture teams."
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"This can then flow down to inform developers' thinking, ensuring - for example - that users and those impacted by the AI system are not disadvantaged and are aware when they're dealing with AI. Policymakers need to understand how AI works, how it is being used and what the risks might be, then take a risk-based approach that supports innovation while appropriately managing risk."
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To find out more about what the market is saying about AI, download our AI survey results: