TL;DR: Salesforce Research and Mila announce AI for Global Climate Cooperation, a working group collaboration and competition to design negotiation protocols and climate agreements. We plan to coauthor a peer-reviewed scientific paper with top-performing teams; insights will be distilled into a policy brief shared with leading policymakers, informing future climate negotiations and contributing to collaborative solutions to mitigate climate change globally. Learn more at www.ai4climatecoop.org and join us!
AI for Global Climate Cooperation: New Collab & Competition
We are excited to announce AI for Global Climate Cooperation, a working group collaboration and competition on designing negotiation protocols and climate agreements. This initiative is co-organized by Mila and Salesforce Research.
Modeling how to achieve and maintain climate cooperation is an interdisciplinary challenge, intersecting a diverse range of fields – from AI to economics to law, and many more. This is an underexplored area of research that is highly relevant to real-world climate policymaking. Join our working group and competition to contribute your expertise!
Motivation
Make an Impact: Design a Climate Negotiation Protocol for a Sustainable Future
Climate change is happening fast. The latest IPCC report warns that it is ‘now or never’ if the world is to stave off climate disaster. However, it is still a race we can win. Propose and test your own climate agreement and negotiation protocols and see if they lead to a better future.
Many Reasons to Participate
- Develop new scientific insights for social good.
- Collaborate with other like-minded innovators working to promote a sustainable future.
- Expand your circle: Meet and work with researchers from other disciplines.
- Get feedback from domain experts.
- We plan to coauthor a peer-reviewed scientific paper with top-performing teams.
- The insights of this project will then be distilled into a policy brief that will be shared with leading policymakers, informing future climate negotiations and contributing to collaborative solutions that mitigate climate change globally.
- Publicity: Standout teams and innovative solutions will be featured in a blog, press release, and social media.
- Publication: Teams submit workshop-style papers, which will be peer-reviewed and published in the competition proceedings.
- Excellent learning opportunity.
- Join, contribute to, and help shape a new, thriving research community.
- Motivate others to write more research papers based on this scientific area.
- Help change the world!
Cross-Discipline Participation Encouraged
AI for Global Climate Cooperation invites and embraces all researchers from relevant disciplines, including machine learning, economics, agent-based modeling, game theory, behavioral science, mathematics, computer science, climate modeling, ethics, (international) law, political science, international relations, and more. We do not expect a single participant to know all of the above subjects. Instead, we hope people across disciplines will work together. You can find teammates in our Slack channel; we will also help you find teammates.
Who should participate, how you can contribute
We believe this working group collaboration and competition opens the way for beneficial contributions to several different areas in research and policy, so we encourage a wide variety of innovative thinkers to register and join us on this journey, including:
AI researchers, economists, climate scientists: Good policy recommendations require rigorous and grounded technical work. Here are just a few examples on how you can contribute:
- Implement negotiation protocols and climate agreements.
- Extend the RICE-N climate-economic simulation to include more economic or climate features that may be necessary.
- Model real-world agents using AI and domain knowledge.
- Develop machine learning algorithms to enable rigorous experiments and analysis.
- Visualize and analyze the outcomes under your proposed solution.
- Work together with domain experts to understand what real-world requirements are important for your analysis and proposal.
Ethics, legal, policy experts: Good science needs to be translated into good policy. Domain expertise (outside of AI, economics, or climate science) is crucial to help shape the analysis and communication of the results.
- AI-driven policy analysis is an open research challenge. For example, what does “good” mean from a non-technical perspective?
- What requirements are there on AI-driven policy analysis? For instance, regarding transparency, explainability, robustness, ethics, fairness, legality, precedence, and other dimensions?
- Communicating outcomes to governments is just as important as the research itself. You could contribute to clear communications as well as defining actionable insights and targeted recommendations.
Impact on Research and Society
Design Climate Negotiations and Agreements, Evaluate Impact
We call on and strongly encourage researchers from all disciplines to collaborate, evaluating their climate impact using RICE-N, an open-source climate-economic simulation that supports modeling AI agents. RICE-N models how economic activity impacts temperatures, and how temperatures in turn affect productivity. Moreover, RICE-N models multiple regions, each trading, negotiating, investing, and mitigating climate change (or not). Each region’s behavior can be modeled using AI, and RICE-N provides a convenient interface and example code to do so. More details can be found in the open-source repository https://github.com/mila-iqia/climate-cooperation-competition.
Real-World Contributions
Furthermore, we intend to have real-world impact.
First, we plan to form a diverse working group with interested competition participants – in particular, teams whose findings are of sufficient scientific or policymaking novelty. The working group will write a research paper based on the findings in the competition.. This work will be submitted to a peer-reviewed journal and undergo rigorous scientific and ethical use review.
Following this, given suitable findings, we intend to write a policy brief with actionable insights for policymakers, which will be distributed and promoted through our partners. We also plan to organize a marketing campaign around the findings of the competition.
Ethics
While the intention of this challenge is to stimulate innovative solutions to climate change, there are some potential unintended consequences, including the carbon footprint of running the simulation, the economic disparities that can exist with climate negotiations, and the potential extensibility of this simulation to the real world. Teams should consider these potential consequences; the ethical implications of solutions will be considered in Tracks 2 and 3 of the competition.
Key Details: AI for Global Climate Cooperation
Competition Tracks
The competition has three tracks:
- Track 1: Solutions are ranked according to the empirical trade-offs between climate and economic scores.
- Track 2: Teams submit a justification for why their solution is relevant and implementable in the real world. Solutions will be evaluated in totality and given feedback by an expert jury of AI, economics, climate, behavioral, ethics, and policy researchers. There will be an overall winner and prizes for the best submissions in various categories, e.g., technical, relevancy, legality, innovation, etc.
- Track 3: Teams submit analyses, describe weaknesses of the current simulation and policy analysis tools as well as areas of improvement. We also encourage participants to consider ethics and fairness in their analyses.
Upcoming Workshop and Competition Proceedings
After the submission period has ended, we plan to organize a workshop in March 2023. Top performing teams will be invited to present their work there.
We also invite all teams to submit a workshop-style paper (via OpenReview) to document their findings, which will be peer-reviewed and published in the competition proceedings.
Next Steps
- Individuals: Please register here first. You don’t need a team to register!
- Forming teams: We want to encourage interdisciplinary collaboration and ideally have diverse teams who participate.
- If you don’t have a team, or are looking for more teammates, we will facilitate finding team members. Please join Slack and/or submit your contact and profile info when you register. You can find all such submitted public info on our public Google Spreadsheet, so you can get in touch with other interested researchers!
- Team size: If your team has more than 5 team members, we will ask you to describe the expertise and background of each team member. We will refuse teams with more than 5 people that come from a single discipline only. The overall goal is for every team to include multidisciplinary expertise. We ask teams to consider reasonable interdisciplinary team compositions; the organization reserves the right to evaluate each case independently.
- Watch videos on our website that describe the research challenge, theoretical framework, and a technical tutorial on how to participate.
- Read our white paper with technical background on RICE-N and more details. View the RICE-N code on Github: https://github.com/mila-iqia/climate-cooperation-competition.
- Check out our website for a schedule of key events, important dates, and other essential information.
- We encourage you to register to get updates.
Learn More: Links and Resources
For more information, please check out the following:
- Website: https://www.ai4climatecoop.org
- Social Media: Twitter: @AI4ClimateCoop – WeChat: AI4ClimateCoop
- YouTube: See our video for more info on the AI for Global Climate Cooperation Competition
- Code: https://github.com/mila-iqia/climate-cooperation-competition/tree/main
- Google Group: https://groups.google.com/g/climate-cooperation-competition
- Slack: Discuss, debate, collaborate with other participants on our Slack channel
- OpenReview: Submit a workshop-style paper via OpenReview
- Contact us: send questions or comments to st.t.zheng@gmail.com
We kindly request that you distribute this message to your networks, and we hope you’ll join us in this new initiative!
About the Authors
Stephan Zheng (www.stephanzheng.com) leads the AI Economist team at Salesforce Research, working on deep reinforcement learning and AI simulations to design economic policies.
Anna Bethke is a Principal Data Scientist focused on fair, accountable, transparent, and explainable (FATE) AI in Salesforce’s Ethical AI Practice Team.
Donald Rose is a Technical Writer at Salesforce AI Research, specializing in technical content creation for blog posts, video scripts, newsletters, media/PR material, workshops, and more.
