Climate change is one of the most pressing challenges of our time, requiring rapid action across society. As artificial intelligence tools (AI) are rapidly deployed, it is therefore crucial to understand how they will impact climate action. On the one hand, AI can support applications in climate change mitigation (reducing or preventing greenhouse gas emissions), adaptation (preparing for the effects of a changing climate), and climate science. These applications have implications in areas ranging as widely as energy, agriculture, and finance. At the same time, AI is used in many ways that hinder climate action (e.g., by accelerating the use of greenhouse gas-emitting fossil fuels). In addition, AI technologies have a carbon and energy footprint themselves. This symposium brought together participants from across academia, industry, government, and civil society to explore these intersections of AI with climate change, as well as how each of these sectors can contribute to solutions.

Modern civilian and military systems have created a demand for sophisticated intelligent autonomous machines capable of operating in uncertain dynamic environments. Such systems are realizable thanks in large part to major advances in perception and decision-making techniques, which in turn have been propelled forward by modern machine learning tools. However, these newer forms of intelligent autonomy raise questions about when/how communication of the operational intent and assessments of actual vs. supposed capabilities of autonomous agents impact overall performance. This symposium examines the possibilities for enabling intelligent autonomous systems to self-assess and communicate their ability to effectively execute assigned tasks, as well as reason about the overall limits of their competencies and maintain operability within those limits. The symposium brings together researchers working in this burgeoning area of research to share lessons learned, identify major theoretical and practical challenges encountered so far, and potential avenues for future research and real-world applications.

The use of AI to analyze, synthesize, and evaluate pathways to achieve carbon neutrality (e.g., energy sector transition plans from fossil fuels to low-carbon technologies) and for applications in climate change mitigation-related policy more broadly. The use of AI to understand and/or alleviate the effect of climate change on economies, society, production, conflict, and international trade, and for applications in climate change adaptation-related policy more broadly. Methodologies and frameworks for assessing the climate impacts of AI technologies in general (e.g., increased computational energy demand, the effects of applications, and broader systemic effects), including strategies for measurement and reporting. Governance and policies required to align the use of AI with societal climate change goals, the UN Sustainable Development Goals, and associated ESG frameworks. The use of AI to analyze, synthesize, and evaluate pathways to achieve carbon neutrality (e.g., energy sector transition plans from fossil fuels to low-carbon technologies) and for applications in climate change mitigation-related policy more broadly.

In October 2021, Cynthia Rudin was announced as the winner of the AAAI Squirrel AI award, which was formally presented during an award ceremony at AAAI 2022. Following the presentation, Cynthia delivered an invited talk about her research on interpretable machine learning.

Welcome to our February 2022 monthly digest, where you can catch up with any AIhub stories you may have missed, get the low-down on recent events, and much more. This month, we cover our latest New voices in AI interview, hear from a NeurIPS award winner, and get stuck into AAAI 2022. You may have seen the launch of our new series last month. In the latest episode, Isabel Cachola talks about how she got into AI and her work on interpretability of NLP models. In this interview, Bernard Koch tells us about research that won him, and co-authors Emily Denton, Alex Hanna and Jacob Foster, a best paper prize at NeurIPS 2021.

The 36th AAAI Conference on Artificial Intelligence (AAAI2022) started on Tuesday 22 February and runs until Tuesday 1 March. Although we haven't yet had the official opening ceremony, the talks and posters are available to view, and the LatinX in AI event has taken place. Here, we round-up some thoughts from participants, and we look ahead to some of the other events planned for this week. If you are attending AAAI 2022, please come by to our tutorial (Feb 23, 2022, 10 pm – 11:30 pm IST) MQ3: Hate Speech: Detection, Mitigation and Beyondhttps://t.co/Uw1jIRyGmn A particularly relevant topic since healthcare raises unique problems & challenges that require new methodologies & ways of thinking.

The 36th AAAI Conference on Artificial Intelligence (AAAI 2022) is being hosted virtually from February 22th - March 1st. We're excited to share all the work from SAIL that's being presented, and you'll find links to papers, videos and blogs below. Feel free to reach out to the contact authors directly to learn more about the work that's happening at Stanford. We look forward to seeing you at AAAI 2022.