Case studies on AI and climate change - suggestions for Global Partnership on AI report

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Climate Change AI (CCAI) and the Centre for AI & Climate (CAIC) are soliciting suggestions for case studies on AI and climate change to include in a forthcoming report on this topic to be issued by the Global Partnership on AI (GPAI).

GPAI was launched in June 2020 as a government-recognized multi-stakeholder initiative bringing together leading experts from science, industry, civil society, international organizations, and government. To date, 19 countries have joined. GPAI is looking to prioritize work on AI-for-climate and so is supporting the development of a roadmap for how governments can accelerate responsible adoption of AI applications that help address climate change. More information on the project is available at: https://www.gpai.ai/projects/responsible-ai/environment/

Examples of what case studies might look like:
- A company using AI to increase the energy efficiency of factories.
- An NGO tracking deforestation using AI.
- A research team incorporating AI in climate modeling.
- A governmental agency using AI for disaster response.
Further example topics are provided at https://www.climatechange.ai/summaries

We are interested here in projects that have either been deployed or are aimed towards deployment. In certain cases, this may include research on topics in AI and climate change that has not yet been deployed, as long as there is a clear pathway to climate impact. Projects that have failed or encountered significant barriers to deployment may be submitted as well.

If you have several case studies you would like to suggest, please fill out this form once for each. If your case study is selected, you may be contacted for further input on the write-up of this case study within the GPAI report. This may include asking you to provide an overview of the project in writing.

This call will be open until August 19, 2021.

Your name *

Your email *

Are you proposing a case study on a project that you yourself have worked on? *

Yes

If yes, in what capacity have you been involved in it?

Project title / subject (up to 20 words) *

People or organizations involved in the project *

Brief description (100-200 words) *

Describe the problem that needs to be solved and how the approach helps to address it.

Relevance of this project to AI / machine learning *

Relevance of this project to climate change (please be specific) *

What challenges or bottlenecks have been encountered in the project (if known and able to be shared publicly)? *

Technological readiness level (select whichever best applies) *

Note that we here use the EU Horizon TRLs, slightly paraphrased.

TRL 1 – Basic principles observed

TRL 2 – Technology concept formulated

TRL 3 – Experimental proof of concept

TRL 4 – Technology validated in lab / experiments

TRL 5 – Technology validated in environment relevant to ultimate use

TRL 6 – Technology demonstrated in environment relevant to ultimate use

TRL 7 – System prototype demonstration in operational environment

TRL 8 – System complete and qualified

TRL 9 – Actual system proven in operational environment

Funding source (if able to disclose)

Are there plans for developing this project further (if known and able to be shared publicly)? *

Links or other sources of further information about the project, such as media, publications, websites *

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