Call summary :

This year, the Mozilla Technology Fund seeks to fund open source projects at the intersection of environmental justice and AI which are making a positive impact in ecosystems and human communities.

Some categories of projects we are interested in funding during this round:

-Projects which expose or mitigate the climate impacts of AI systems: We are beginning to see research that reveals the large footprint that AI systems have in terms of carbon emissions, water and electricity use, as well as the environmental impacts of extracting lithium, cobalt, rare earth elements and conflict minerals for use in batteries and hardware. Furthermore, machine learning and remote sensing are now being used by oil and mining companies to accelerate the speed at which natural resources can be extracted. We are excited to consider any projects which help illuminate or take steps to mitigate the environmental impacts of AI technologies, including those mentioned above.

- Projects which utilize AI to conduct environmental impact assessments: Could AI technologies be used to catalog and analyze environmental degradation, land and water use, pollution and other environmental impacts? Could these systems be used to monitor the ways in which specific industries—large agribusinesses, the timber industry, mining and coal—are impacting the environment and climate? Are there insights which could be gleaned that could help affected communities advocate for a safer environment or more responsible use of resources? Are there frameworks that could help evaluate the effectiveness of AI as a tool for environmental assessment and the tradeoffs involved with regards to broader environmental justice concerns? Could these frameworks provide activists with data that could help them resist harmful AI solutions?

- Projects that prototype Grassroots AI systems for ecological management: Are there AI systems which could be built and maintained by or in deep partnership with communities to help them better manage the use of their resources and the safety of their land, water, air and food systems? Could these systems help communities achieve goals like responsible forest and wildfire management, promoting biodiversity, or traceability of agricultural products? Are there new types of intelligent systems—non-human intelligence or “natural intelligence”—which could be leveraged in such systems? Data sources for such projects might include satellite imagery, remote sensing data, socio-biodiversity records, climate data, historical land-use data, and local ecological knowledge contributed by communities and groups impacted.

- Projects which combat climate disinformation: A great deal of climate disinformation (false and misleading content on climate, ecology, land, and territorial rights) flows through social media and other media channels. What AI-based tools might we provide citizens to help identify and combat the spread of climate information which is verifiably untrue? How might we push back against “greenwashing” and disingenuous “climate solutions” by providing data and analysis that shows the true ecological impacts of industry, commerce and other human activities?

What to expect

The Mozilla Technology Fund will provide awards of up to $50,000 each and one year of mentorship and support to open source projects which meet the criteria listed below. Our goal is to provide projects in the MTF: AI and Environmental Justice cohort with the resources needed to unlock their full potential and to make them more sustainable in the long term...

What are we looking for?

We imagine that the MTF: AI and Environmental Justice Awards will support a variety of hardware and software projects (including utilities and frameworks), datasets, tools, and design concepts. We will not consider applications for policy or research projects (though software projects which leverage, support, or amplify policy and research initiatives will be considered—for example, software which is built to support an ecological study that can be leveraged by other researchers).

All applicants should:
- Have a product or working prototype in hand (we will also consider projects at the idea stage if the project team can demonstrate a track record of success in launching and building community around similar projects in the past)
- Already have a core team in place to support the development of the project (this team might include software developers working in close collaboration with ecologists, AI researchers, designers, product/project managers, and subject matter experts)
- Embrace openness, transparency, and community stewardship as methodology
- Make their work available under an open-source license