Page 21 - AI Governance Day - From Principles to Implementation

AI Governance Day - From Principles to Implementation

doing what, and where we are heading, how we can implement AI governance frameworks,
and how we can ensure inclusion and trust are at the heart of all of our efforts.

These are the three topics that we're going to be discussing in the breakouts this morning, and
I would like to briefly say a few words about each.

The AI regulatory landscape

First, from the AI regulatory landscape. We have seen quite a fast response, in particular, over
the past year, with governments activating regional groups on the global level as well, starting
to discuss this issue. But I think many are still contemplating what to do. The ITU actually
conducted a landscaping survey among our 193 Member States, and we found that about 85%
of our responding Member States hadn't yet put in place regulations or policies. Some are just
beginning to think about these issues. But I think one important result of the survey was that it
demonstrated that all countries are eager to learn. And so that's also part of the objective of
the discussions this morning. Through dialogue, we can help to avoid fragmentation when it
comes to AI governance.

Collaboration around areas of common interest and priorities comes next. A good example
is standards, and we're joined this morning by many of our standards friends. Standards
are definitely central to this debate and, of course, to the entire summit. It's critical for all AI
governance initiatives.

How to implement AI governance frameworks?

That brings me to my second point, which is how to implement AI governance frameworks.
From algorithm transparency to safety and security of systems, standards really serve as a
prerequisite for the effective implementation of guardrails. Simply put – and I look to Gabriela
[Ramos] from UNESCO – the best ethical or human rights guidelines would be incomplete
without being translated into actionable, enforceable technical standards. ITU already has
more than 200 AI-related standards, either published or currently under development. Our
standardization process ensures that all voices are heard, including those from the developing
world. But more standards are needed to address the pressing challenges around artificial
intelligence. And, more importantly, we need to be developing them in a coordinated way,
using established mechanisms like the World Standards Cooperation. I recognize the leaders
of ISO and IEC who are with us this morning.

Inclusion and trust

That's a natural segue to the third topic this morning, which is inclusion and trust. These two
elements are deeply interconnected. Without trust, people will hesitate to engage with AI,
potentially creating yet another digital divide in an already unequal digital world. I think this
risk is real. For the first time this year, adverse outcomes of AI actually entered into the top 10
rankings of the World Economic Forum Global Risks Perception Survey. It's important to note
that not everyone feels the same way about AI. A recent survey carried out by BCG revealed
that consumers in low and middle-income countries were actually much more excited than
consumers in mature markets. Many see this as an opportunity, an opportunity to leapfrog
technological gaps and accelerate innovation in vital areas such as education and healthcare,
and I would say all the SDGs.

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