WEBVTT

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- Let me round out this course by walking you

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through the five key enabling conditions that are needed

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to unlock AI's full potential for sustainability.

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These were identified in collaboration

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with sustainability researchers

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and practitioners with many years

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of experience in the field.

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First, we need increased investment in AI

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for sustainability.

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This must include providing financial incentives,

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creating opportunities

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for AI research-focused on sustainability

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and fostering partnerships between AI

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and sustainability experts.

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Second, we need more development of inclusive digital

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and data infrastructure.

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For AI's promise in sustainability to be successful,

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it must be representative and inclusive.

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This requires investing in filling critical data gaps,

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particularly in underrepresented regions of the world.

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Data gaps are widespread across many sustainability issues.

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The UN Environment program estimates that 58%

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of the environment related indicators

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for the world's sustainable development goals

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lack sufficient data to monitor progress.

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In addition, AI-ready-data standards need to be established

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and adopted to enable effective use

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of available environmental data.

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Third, we need to minimize resource use

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and prioritize renewable resources.

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As AI demand increases, minimizing the resource footprint

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of AI operations becomes essential.

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This requires sustained investments in data center

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efficiency and following best practices

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for resource utilization.

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Prioritizing zero carbon energy sources in AI infrastructure

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and operations is essential

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for reducing environmental impact of building

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and running AI models.

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Fourth, we need

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to advance AI policy principles and governance.

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Establishing robust policy principles

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and governance structures for AI in sustainability is vital.

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Policies are needed to support the transition

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to carbon-free electricity grids,

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and the integration

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of AI into existing sustainability frameworks.

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Effective governance must ensure that the use

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of AI in sustainability is safe, secure, and trustworthy.

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Fifth, we'll need to build capacity in the workforce

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to use AI for sustainability.

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Unlocking AI's potential

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for sustainability will rely on a workforce able

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to use AI tools.

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This means creating pathways for education

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and training that equip the sustainability workforce

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with the skills and knowledge to use AI effectively.

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Cultivating AI fluency within the sustainability context

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is crucial for leveraging AI in meaningful ways.

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With these five enabling conditions in place,

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AI can be the game changer we need to deploy

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sustainability solutions faster, cheaper, and better.

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As you move forward on your sustainability journey,

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I encourage you to learn more about how you can use AI

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to accelerate your sustainability efforts.

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How you could build AI skills for sustainability

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and ask yourself, what can you

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or your organization do

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to help establish the broader enabling conditions

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that are needed for AI

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to help the world accelerate to sustainability?

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The window for transitioning the world

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to sustainability is narrowing.

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Fortunately, the growing AI toolbox presents

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an incredible opportunity to drive change at the scale

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and pace needed to achieve our global sustainability goals.

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But only if as a society we collectively focus

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on establishing the enabling conditions for success.

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Together, we can do this.