Call for Proposals:
Climate Change AI Innovation Grants

Quick facts

The purpose of this grant

Artificial Intelligence (AI) and machine learning (ML) can help support climate change mitigation and adaptation, as well as climate science, across many different areas, for example energy, agriculture, forestry, climate modeling, and disaster response (for a broader overview of the space, please refer to Climate Change AI’s interactive topic summaries and materials from previous events). However, impactful research and deployment have often been held back by a lack of data and other essential infrastructure, as well as insufficient knowledge transfer between relevant fields and sectors.

The relationship between AI and climate change is also nuanced, and can manifest in various ways that either contribute to or counteract climate action. Thus, the use of AI for climate action must be performed responsibly, and ideally with quantifiable impacts.

With the support of the Quadrature Climate Foundation and Schmidt Futures, a philanthropic initiative founded by Eric and Wendy Schmidt, we are excited to announce funding of USD 1.8M for projects at the intersection of AI and climate change. We are also grateful to Future Earth International for serving as the fiscal sponsor for this program.

Grant information

This program will allocate grants of up to USD 150K for conducting research projects of 1 year in duration. Research projects shall leverage AI or machine learning to address problems in climate change mitigation, adaptation, or climate science, or shall consider problems related to impact assessment and governance at the intersection of climate change and machine learning.

Along with the project, the grantees must publish a documented dataset (or simulator), which was created by collating, labeling, and/or annotating existing data, and/or by collecting, simulating, or otherwise making available new data that can enable further research. We require the dataset to comply with the FAIR Data Principles (Findable, Accessible, Interoperable and Reusable).

Grants are expected to result in a deployed project, scientific publications, or other public dissemination of results, and should include a carefully considered pathway to impactful deployment. All grant IP — e.g., the dataset/simulator produced and (if applicable) trained models or detailed descriptions of architectures and training procedures — must be made publicly available under an open license.

Relevant research includes but is not limited to the following topics:

Eligibility

Each application must have a Principal Investigator (PI) who is a faculty member or postdoctoral researcher at an accredited university or academic research institution in an OECD Member country. There are no eligibility restrictions on co-Investigators, and multi-country and multi-sectoral collaborations are encouraged (e.g., including members outside OECD Member countries or from non-research institutions).

Current members of the Climate Change AI Board of Directors cannot apply to this grant as a PI, and they may not receive funds towards their own salary. Members of the Review Committee for this grant may not apply or receive funds in any way (however, reviewers may, and conflicts of interest will be appropriately managed during the review process).

We do not fund research activity that is currently funded by other grant programs. If other grant proposals for the same project have been submitted and/or are under consideration, the relation of the present proposal to those other proposals needs to be clearly explained. If the proposal is selected for funding, no aspect of a project should be double funded by other funding bodies.

Timeline

Activity Date
Call release date Aug 23, 2021
Informational webinars (slides) Sept 23 & 27, 2021
Proposal submission deadline Oct 15, 2021
Notification of results Dec 10, 2021
Award start date Jan 10, 2022
Award end date Jan 10, 2023

Selection criteria

Proposals will be reviewed through a single-blind process by independent reviewers.

Projects will be evaluated on the following criteria:

In addition, the following aspects will be considered favorably during the review process:

Across the full cohort of grantees, we will additionally seek to allocate grants to represent multiple sectors of climate change mitigation and adaptation, as well as coverage across many geographic regions.

Application instructions

All applications must be received by October 15, 2021 at 23:59 (Anywhere on Earth time, UTC-12). Applications should be made via the CMT website, which will require the following information.

Basic information. The CMT submission portal will require the title and abstract of the proposal; the name, affiliation, and country of affiliation of the Principal Investigator; the names, affiliations, and countries of affiliation of any co-Investigators; and additional short declarations about the project. The first name in the CMT author list will be treated as the Principal Investigator. Only one Principal Investigator may be named, but there is no limit on the number of co-Investigators. Please note that the institution of the Principal Investigator will be used to determine eligibility, and will be responsible for receipt and any further distribution of the funds if a grant is awarded.

Project Description. A detailed description of the project (maximum 12 pages including figures/tables, using no smaller than 12pt font size, single line spacing, and 1 inch margins), with unlimited additional pages allowed for references. The Project Description should be submitted as one PDF attachment via CMT, and include the following subsections (please use the same order and headers to separate the subsections):

Budget and Budget Justification. An itemized Budget (1 page) indicating the total amount requested and how these funds will be used if a grant is awarded, and a brief Budget Justification (1 page) of these amounts, submitted as one PDF file through CMT. Eligible expenses include salaries for Investigators, students, and other research staff; materials, equipment, software, and compute; and expenses associated with conferences and other project-related travel. The Budget should also indicate any institutional overhead, at a maximum rate of 10% of the total amount requested. If this project has other sources of funding, the Budget should make clear which research activities are proposed to be funded by the present grant, and which research activities are funded by other sources. Please note that funds will be contracted solely to the accredited university or academic research institution with which the Principal Investigator is affiliated; any further dissemination of funds to partner institutions must be managed by the lead institution.

CVs of key personnel. CVs for the Principal Investigator and all co-Investigators, as a single PDF file (no page limit).

About Climate Change AI

Climate Change AI is a volunteer-driven organization that facilitates impactful work at the intersection of climate change and machine learning by providing education and infrastructure, building a global community, and advancing discourse. Since it was founded in June 2019, Climate Change AI has written the foundational (100-page) report “Tackling Climate Change with Machine Learning” on where AI and machine learning can have high leverage in addressing climate change; organized regular conferences and events at venues such as NeurIPS, ICML, and the COP; and led the creation of a global network of researchers, engineers, entrepreneurs, investors, policymakers, companies, and NGOs. See our website for further details.

FAQ

Eligibility

Q: Does my institution qualify as an “accredited university or academic research institution” under the eligibility criteria of this grant?
A: For the purposes of this grant, we consider any officially-recognized non-profit academic institution with faculty to be an “accredited university or academic research institution,” and therefore eligible to be a lead institution on a proposal. If you’re unsure as to whether your institution qualifies under these criteria, feel free to email us at grants@climatechange.ai.

Q: I am from a US national lab. Does this count as an eligible “academic research institution”?
A: US national labs and federally funded research and development centers (FFRDCs) are unfortunately not eligible to be the lead institution on a proposal.

Q: I am from an eligible “accredited university or academic research institution” as defined above and hold a post-PhD research position at that institution, but am not technically considered either a postdoc or faculty member. Am I eligible to be a PI?
A: Yes. Anyone at an eligible lead institution as defined above who holds a post-PhD research position of postdoctoral level or above, and is allowed by their institution to hold grants, is eligible to apply as a PI.

Q: What counts as an OECD country under the eligibility criteria of this grant?
A: For the purposes of this grant, we consider any of the 38 OECD Member countries (as listed on the OECD website) to be an “OECD country.”

Q: I am not an AI or ML expert; can I apply?
A: Yes, as long as your project includes an aspect of AI/ML which addresses one of the areas described in “Purpose of this grant”. You may want to consider finding an AI or ML expert to collaborate with; our workshops, online discussion platform, happy hours, and community directory could be helpful for this.

Q: I am not a climate expert; can I apply?
A: Yes, as long as your project addresses a problem of climate change, with a pathway to impact clearly described. You may want to consider finding an expert in the relevant climate-related domain to collaborate with; our workshops, online discussion platform, happy hours, and community directory could be helpful for this.

Q: I’m a student; can I be the primary grantholder?
A: No, the principal investigator must be at the level of postdoctoral researcher or above.

Q: I’m from a non-OECD country but currently at an institution in an OECD country; can I apply?
A: Yes, as the funds will be disbursed through your institution, not to you directly.

Q: I’m from an OECD country but currently at an institution in a non-OECD country; can I apply?
A: At this time, you unfortunately cannot apply as a Principal Investigator; for logistical reasons, we are currently only able to disburse funds to institutions in OECD countries. However, you may participate as a co-Investigator in a grant proposal, provided the Principal Investigator meets the eligibility requirements. Our workshops, online discussion platform, happy hours, and community directory could be helpful in finding collaborators.

Q: I’ve been affiliated with Climate Change AI in the past, been a co-author with members of Climate Change AI, or otherwise involved with Climate Change AI. Can I apply?
A: Yes, except under specific circumstances. Specifically, members of the Review Committee for this grant may not apply or receive funds in any way (however, reviewers may). Current members of the Climate Change AI Board of Directors cannot apply to this grant as a PI, and they may not receive funds towards their own salary. Other Climate Change AI affiliates are welcome to apply in any capacity.

Q: Am I eligible to apply for these funds if I have applied to other sources for the same research activity?
A: The exact same research activity cannot be double funded. However, this grant may be used to fund a component of a project whose other components are under consideration or have received funding from other sources. This structure should be clearly described in your budget.

Q: Can I apply multiple times with different projects?
A: Yes, you are welcome to apply multiple times. However, as mentioned above, we will seek to select a cohort of grantees “to represent multiple sectors of climate change mitigation and adaptation, as well as coverage across many geographic regions.” This may in turn reduce the probability of multiple proposals from the same team being funded.

Application and review process

Q: Can I send my application via email?
A: No, all applications must be via CMT.

Q: Do I need to use a particular software, like LaTeX or Word, to write the proposal?
A: No, you may use any software to write the proposal, as long as it follows the requirements on length, font, line spacing, and margins.

Q: Is review of the proposals double-blind?
A: No, the review process is single-blind (reviewers’ identities are hidden from proposal authors). Proposals are encouraged to be very specific about their pathway to impact, and this is likely to contain de-anonymizing information that reviewers would need in order to evaluate the feasibility of the proposed project.

Timeline

Q: I’m uncertain about the start and end dates for my project, what should I do?
A: Just give your best guess, with an explanation of the reasons for your uncertainty if you believe it would help in evaluating your proposal.

Budget

Q: My project would require a budget greater than the maximum allowed (USD 150K). What should I do?
A: In order to distribute grants equitably and fund a larger number of projects, we will not allocate more than USD 150K to a single project. You should describe and apply to us for a USD 150K portion of your project, and apply for additional funding elsewhere. Make sure to describe this in your budget, including the additional funding sources you have secured or intend to apply to.

Q: My institution takes an overhead greater than 10% of the grant. Am I still eligible to apply?
A: You are still eligible to apply, but you will need to obtain an exemption from your institution regarding overhead, as your institution will not be allowed to take more than 10% overhead.

Scope and relevance

Q: Does this grant call include other environmental or social issues that do not directly pertain to climate change?
A: All proposals should clearly describe the relevance to climate change, as well as the pathway to impact for the climate problem. As problems of climate change intersect with a host of other issues, we welcome grantees to lean into these connections and consider their project holistically.

Q: Does the machine learning proposed in the project need to be ‘novel’?
A: No, in the sense that it is perfectly acceptable to use a previously published ML algorithm or architecture. However, the scientific knowledge generated in this project (e.g. trying the previously published ML technique in a novel setting, combining existing techniques in a novel way, etc.) should be novel, i.e., informative and not previously published.

Q: The pathway to impact for my project is highly speculative. Will this hurt my proposal?
A: We encourage submissions anywhere on the spectrum from guaranteed-but-small impact to high-risk/high-reward. The important part for evaluation is that you thoroughly and accurately describe the pathway to impact, including your level of uncertainty about any aspects, and take steps to reduce or address uncertainty where possible. E.g., it may hurt your proposal if the speculation is due to lack of domain research, but not if it is due to irreducible uncertainty about future outcomes, physical processes, etc.

Q: Does the dataset have to be for supervised learning?
A: Not at all. In order to enable future impactful work, do ensure that you clearly describe the way you intend the dataset or simulator to be used.

Q: My proposed project involves human or animal experimentation that requires explicit ethics approval. Does getting the grant provide this approval?
A: No. You should include in your project description (and budget, if appropriate) any approvals or regulatory oversight necessary for your project, and obtaining those are your responsibility.

Terminology

Q: What is climate change mitigation?
A: Climate change mitigation refers to the reduction of greenhouse gases in order to reduce the extent of climate change. As described by the IPCC Working Group III, this “is achieved by limiting or preventing greenhouse gas emissions and by enhancing activities that remove these gases from the atmosphere.” For examples of where AI and ML can help with climate change mitigation, please see Climate Change AI’s report on “Tackling Climate Change with Machine Learning.”

Q: What is climate change adaptation?
A: Climate change adaptation refers to activities that aim to prepare for or build resilience to the conditions created by climate change. For more information, please see resources from the IPCC Working Group II. For examples of where AI and ML can help with climate change adaptation, please see Climate Change AI’s report on “Tackling Climate Change with Machine Learning.”

Q: What is climate science?
A: Climate science is the study of the environmental processes that determine past, present, and future climate. For more information, please see resources from the IPCC Working Group I. For examples of where AI and ML can help with climate science, please see Climate Change AI’s report on “Tackling Climate Change with Machine Learning” as well as the proceedings of the Conference on Climate Informatics.

Q: What is meant by AI and ML? A: Artificial intelligence (AI) refers to any algorithm that allows a computer to perform a complex task — typically, tasks such as speech, perception, and reasoning that are associated with human intelligence. Machine learning (ML) is a sub-area of AI referring to techniques whose behaviors or outcomes depend on “learning” — corrections or changes made as a result of seeing examples or descriptions — rather than being hard-coded in advance. ML is used to describe a wide variety of techniques that range in their complexity, including, e.g., linear regression, decision trees, and deep neural networks.

Other

Q: I have a question that isn’t answered here. What should I do?
A: Please contact us at grants@climatechange.ai.

Sponsors

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