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WHERE AI INNOVATION
AND PURPOSE COLLIDE

Butterflies

Go Fast and Break Things:
Climate Edition

We must address the concerns about environmental impact, ethics, and societal inequities by focusing on the needs of global populations and scarce or threatened resources.

VULNERABLE PEOPLES AND PLANET

Challenging AI and its Consumption of Limited Resources

"Driven partly by the growth in AI, Google’s scope-1 onsite water consumption in 2022 increased by 20% compared to 2021, and Microsoft saw a 34% increase over the same period. Most big tech water consumption for server cooling comes from potable sources. Here, the consumed water is actually evaporated and “lost” into the atmosphere." - OECD.ai

WATER CRISIS IN THAILAND

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"The primary sources for drinking water for many Thai citizens are from surface and ground water sources. Untreated domestic sewage, industrial wastewater and solid hazardous wastes have increased in the surface water bodies. It is reported that one third of the surface water is of poor quality in Thailand... Water scarcity is a global threat that is estimated to hit Thailand hard by 2025. The country must develop a long-term plan to manage these challenges. Effective water management needs to be implemented in Thailand, especially in effectively dealing with flood and drought problems."

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Water Crisis in Thailand >

FREE CLIMATE TRAINING

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A diverse collection of courses is available from the UN through their learning hub. Courses are free and can be brief or require up to 12 hours of learning. Certificates are available.

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But don't simply take the short courses, invest in the longer ones. Hiring managers and those that care deeply about these topics understand the difference between a 30 minute course and one that lasts for weeks or requires hours.

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Invest in you! Explore the course catalog, today!

Top 10 risks for AI and climate:

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  1. Energy Consumption and Carbon Footprint

  2. Reinforcement of Inequitable Systems

  3. Over-reliance on Technological Solutions

  4. Lack of Accountability and Transparency

  5. Vulnerability to Infrastructure

  6. Unintended Consequences and Reinforcement Loops

  7. Dependency on Finite Resources for AI Infrastructure

  8. Displacement of Human Labor in Green Initiatives

  9. Bias in Climate Modeling and Decision Making

  10. Acceleration of Resource Extraction for AI Development

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