Science Jam¶
Date: Thursday, April 30, 1-3 PM MT
The goal of the Science Jam is to match people together with a topic they are interested in and a product that is exciting to them. Teams might shuffle a little, but our hope is that the Science Jam helps you start to find your team ahead of the Summit.
After the Jam, you will have access to all of the materials so you can revisit them and expand on ideas leading up to the Summit.
At the Summit, you will pick your product, topic, and team.
Science Jam Resources - Brainstorming Sheets - Note the "instructions tab" - You may add ideas until May 3. Please do not delete or type over anyone else’s idea. - VIEW RECORDING HERE
AI for Sustainability Topics and Example Questions¶
As a starting point, we've taken the input from your confirmation forms to create these topics and example questions.
Ecosystem Dynamics & Conservation¶
How can AI support conservation planning by balancing ecosystem services tradeoffs (e.g., biodiversity vs carbon storage vs water quality)?
How can we unify genetic, species, and ecosystem-level biodiversity data to detect ecosystem thresholds and inform decision-making?
Aquatic Systems¶
How can AI-enabled data harmonization improve flood forecasting and sustainable allocation under climate change?
In what ways can AI support sustainable management of fisheries, freshwater, and marine ecosystems?
Food Systems & Agriculture¶
How can AI enable real-time monitoring of crop health and food security risks using remote sensing and field data?
How can AI and data integration support sustainable management of rangelands and grazing systems under changing climate conditions?
How can AI improve prediction of soil carbon sequestration and agricultural emissions?
Climate Hazards & Resilience¶
How can AI tools, such as Digital Twins, improve resilience planning for wildfires, floods, and extreme climate events?
In what ways can AI support nature-based solutions (e.g., ecosystem restoration, disaster risk reduction) for climate resilience?
Energy Systems & Climate Mitigation¶
How might AI methods be used to evaluate and optimize tradeoffs between energy infrastructure development and environmental impact?
How can AI support decarbonization pathways across sectors while balancing economic and social factors?
AI Methods and Modeling¶
How can AI support and advance causal understanding – including through counterfactual analysis and quasi-experimental designs – in sustainability research and policy?
How might we use advanced methods (e.g., multi-agent systems, graph neural networks) to model complex socio-ecological systems?
Earth Observations & Digital Twins¶
How can AI integrate remote sensing, in situ, and socio-environmental data into unified analytical frameworks (e.g., digital twins) to accelerate environmental discoveries and decisions?
What are the data opportunities to advance Earth embeddings and improve predictions and decisions across regions and over time?
Community & Knowledge Co-Production¶
How can AI systems be co-designed with stakeholders to support place-based, culturally relevant environmental solutions?
How can community-generated data be incorporated into scientifically robust and fair AI models?
Sustainable & Ethical AI¶
How can we design frameworks to ensure fairness, transparency, and accountability (including ethical data use) in environmental AI applications?
How can AI be designed and used to address environmental issues, while minimizing its energy and water footprint (such as data centers)?
Policy & Decision Making¶
How can AI enhance science communication and public engagement around environmental science and sustainability?
How can uncertainty and bias in AI models be communicated to build trust among stakeholders?
How can AI inform sustainable planning for cities, land use, and infrastructure development?
AI Education for Sustainability¶
How can we prepare the students of today to use emerging AI technology for a more sustainable future, and how can we support educators in these efforts?
What role could AI play in environmental data science education?
What are some ways that AI could be used to teach sustainability in STEM classrooms?