Essay by Eric Worrall
According to advocates, AI can generate better flood predictions than physics and geography. But is this just more magic box thinking?
Should AI’s Role To Cut Greenhouse Gas Emissions Be Greater?
22 hours ago Carolyn Fortuna
Scientists warn that heat waves, floods, droughts, and severe storms will get far worse in the decades ahead unless we change course. Looking ahead, could AI’s role in developing new climate models save us many gigatons of carbon emissions?
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AI’s role in the struggle against climate change is already prominent and is also controversial. While it seems evident that AI can serve in the pursuit of a greener future, checks and balances that ensure fairness and equity must be implemented.
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For decades, scientists looked at climate prediction models based largely on the rules of physics and chemistry to forecast weather patterns. Now hybrid-based models consider machine learning and other generative AI tools which help climate scientists create even more accurate and precise systems. For example, doctoral students who are working with officials from the Tennessee Valley Authority to provide a more accurate hybrid-based flood prediction system than the one they are using that is based solely on physics.
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Read more: https://cleantechnica.com/2023/12/31/should-ais-role-to-cut-greenhouse-gas-emissions-be-greater/
The article also provides a link to their ICEF submission;
ARTIFICIAL INTELLIGENCE FOR CLIMATE CHANGE MITIGATION ROADMAP
Innovation for Cool Earth Forum
DRAFT FOR COMMENT
October 2023…
PREFACE
Artificial intelligence (AI) is a hot topic. One business leader recently called it “the defining
technology of our time.” Another said “It is difficult to think of a major industry that AI will not
transform.”Meanwhile countries around the world are struggling to respond to the challenge of climate change. Despite encouraging developments, including steep declines in the price of renewable power, global emissions of greenhouse gases keep rising. Scientists warn that heat waves, floods, droughts and severe storms will get far worse in the decades ahead unless we change course.
Can AI help cut emissions of greenhouse gases? This roadmap explores that question. Our goal is to provide a useful resource for experts and non-experts alike. In Part I of the roadmap, we provide
brief introductions to both AI and climate change. In Part II, we explore six areas in which AI is
helping respond to climate change and could do much more. (These are greenhouse gas emissions monitoring, the power grid, manufacturing, materials innovation, the food system and road transport.) In Part III, we explore cross-cutting barriers, risks and policies. We finish with findings and recommendations.The relationship between AI and climate change is a big topic. Among the questions we do not
explore in this roadmap are (1) how AI could contribute to climate change adaptation (an important
area for work and study) and (2) whether the broad societal forces that AI may unleash are more
likely to help or hinder the response to climate change (a difficult question in light of the many
uncertainties with respect to AI’s impacts in the years ahead). Instead, we aim to provide a resource that will make favorable outcomes more likely, pointing toward ways in which AI can contribute to climate solutions.This roadmap builds on the body of literature produced annually in connection with the ICEF
conference. Previous roadmaps have addressed the following topics:
- Low-Carbon Ammonia (2022)
- Blue Carbon (2022)
- Carbon Mineralization (2021)
- Biomass Carbon Removal and Storage (BiCRS) (2020)
- Industrial Heat Decarbonization (2019)
- Direct Air Capture (2018)
- Carbon Dioxide Utilization (2017 and 2016)
- Energy Storage (2017)
- Zero Energy Buildings (2016)
- Solar and Storage (2015)
Read more: ICF AI Roadmap
The reference to checks and balances is entertaining. From the full report:
… Bias-related risks when using AI for climate mitigation include using AI models that prioritize certain groups due to historic data availability. For example, data for wealthier nations and neighborhoods are often better than data for poorer ones. Privacy-related risks include unauthorized data leaks to third parties, personal identification and even surveillance. Security-related risks are especially acute if AI is used for real-time decision-making (for example in operating factories or the electric grid). …
Read more: ICF AI Roadmap
Chapter 10 Risks explains these bias-related risks in more detail. The risk includes cultural biases, programmer biases and data biases (e.g. putting more solar panels into an area already rich with solar panels, because it is obviously a good place for solar panels – while ignoring other potentially useful locations).
I suspect this point about checks and balances has been added because some of their preliminary AI model runs produced some embarrassing recommendations.
For example if you were to feed an artificial intelligence RCP8.5 climate scenario assumptions, then ask the AI to maximise economic production in a global hothouse scenario, the AI might recommend ignoring renewables and maximising fossil fuel energy production.
If you then program the AI to give more priority to the alleged climate harms to nations like Bangladesh and Arabia, the AI might recommend ignoring renewables, but subsidising air conditioners and building sea walls and flood levees, rather than the politically acceptable recommendation of more climate action.
It would obviously be unacceptable for the AI to produce a product which embarrasses its political backers, so there would likely be a strong temptation for AI researchers to add “checks and balances” to their system until it produces the right answer. A lot like the policymaker review of IPCC reports, or allegedly dubious adjustments of temperature records, except AI scientists who yield to this temptation to prioritise political correctness would be more likely to try to restrain their systems by tweaking the software rather than editing the final product.
Whether this “checks and balances” constrained AI product has any practical value is a different question.