From Watts Up With That?

Essay by Eric Worrall

Imagine a world run by ChatGPT

FOURTH INDUSTRIAL REVOLUTION

Post breakthrough: How AI can lift climate research out of the lab and into the real world

May 29, 2024

• Technological innovation is needed if the world is to avert the most dangerous climate change scenarios.
• Innovation begins with research and development (R&D) but does not end there. AI can catalyze innovation by translating R&D into climate action.
• Generative AI’s capabilities for natural language processing, data synthesis and down-scaling and product prototyping can deliver practical tools to climate leaders.

The world is making big bets on technology’s role in the climate crisis. Across the globe, scientists and technologists are pushing for the next wave of breakthroughs in climate adaptation and mitigation. And there is reason for optimism: recent years have seen meaningful progress, from weather forecasting to industrial decarbonization.

…

AI and climate change

The debut of Generative AI (GenAI) expanded the collective imagination of what AI can do. We already know that AI can drive scientific breakthroughsbut can it go further? Leaders should explore how AI can act as a downstream catalyst in the innovation cycle, driving adoption of the latest tools and awareness of the latest science. Here are three places to start:

1. Organizing unstructured Earth data and down-scaling models to local levels

Earth science has been seen as “data messy” due to complex Earth systems and unstructured environmental data from observational methods. Recently, the volume of such data has exploded, with over 100 terabytes of satellite imagery collected daily. Yet, this doesn’t simplify the data’s unstructured nature. AI is key to organizing and down-scaling this vast data for local applications.

…

2. Building a ‘GPT’ interface to translate climate models into simple language 

…

GenAI could simplify this by providing a GPT-like interface enabling users of all backgrounds to interact with climate data relevant to their needs, such as monitoring local sea-level changes. This approach could make climate models more accessible and build trust in climate projections.

3. Accelerating the prototyping phase of technology development

…

Leaders must, therefore, step up to build ecosystems for AI and climate change. The World Economic Forum’s Tech for Climate Adaptation Initiativehelps enable this necessary environment by convening players from big technology, startups, academia, government and other stakeholders.

…Read more: 

https://www.weforum.org/agenda/2024/05/ai-lift-climate-research-out-lab-and-real-world/

Maybe I’m being too harsh about this latest WEF brainstorm.

Generative AI has a known tendency to lie and make things up (technically known as “hallucinations” in the AI industry), but Google recommends one way to combat hallucinations is to limit the range of possible responses.

There is an obvious output limitation would protect the reputation of the proposed climate chatbot.

If climate ChatGPT had a limitation of only discussing climate disasters which would occur at least 50 years in the future, and ignoring or deflecting dangerous questions like “where are today’s climate disasters?”, there would be no chance the climate chatbot’s “hallucinations” would ever be discovered. 50 years from now, who would remember what a chatbot said today?