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Minimizing Climate Risks with AI

Step into the world of Climate AI with Nathan Shuler, an expert who has spent years working in the climate space. Discover how organizations and companies are leveraging AI-driven forecasts to optimize their practices, mitigate risks, and seize new opportunities. From seasonal predictions to long-term forecasts, explore the tangible business value that Climate AI brings to the table.

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Interview with Nathan Shuler

Dunja Jovanovic: Hi, Nathan, thank you for joining us on the Green New Perspective Podcast. Let’s talk about the work being done by Climate AI and why it is significant in the context of sustainability.

Nathan Shuler: Climate AI is a company specializing in weather forecasting and climate projection. Our primary focus is to provide organizations, including companies, with insights into how climate change will affect their supply chains and operations. We offer forecasts ranging from a few days to several years into the future. The importance of our work lies in addressing several key aspects.

DJ: How did the company start?

NS: We have two co-founders, Max Evans, and Himanshu Gupta. Max, who grew up in Ecuador and had a family-run pineapple farm, witnessed firsthand the impact of climate change on agriculture. This experience drove his interest in the subject. While pursuing his studies at Stanford's business school, he met Himanshu Gupta, our CEO and co-founder. Himanshu Gupta, hailing from a small village in India, personally experienced the effects of monsoons and climate change, as India is highly vulnerable to rapid climate change. Combining Max's expertise in artificial intelligence with Himanshu's background in climate work, they identified a gap in the market.

Initially, we noticed that many organizations relied on outdated weather forecasting methods that only looked at historical averages or had limited future projections. However, climate change introduces new complexities. Therefore, our first aim was to bridge this gap by developing technology that provides accurate short-term weather forecasts and predictions. Additionally, we recognized the challenge of making long-term climate projections accessible and actionable for everyday businesses. This led us to focus on creating tools that enable users to interpret and visualize climate information effectively. While it may sound intricate, this backstory explains how we arrived at these two core aspects of our work.

DJ: Does Climate AI's application extend beyond the agricultural sector?

NS: Absolutely. Climate change will impact every sector of the economy, albeit to varying degrees. While we do serve a significant number of clients in agriculture, our services are expanding to other industries as well. We work with companies in building materials, traditional private equity, and the financial sector, among others. However, agriculture and its related sectors offer unique advantages for us. Firstly, our short-term weather forecasts, which cover up to six months in advance, are particularly valuable for farmers.

They appreciate having advanced knowledge of potential heatwaves or drought conditions to plan their operations effectively. This information helps them make decisions such as adjusting sourcing regions or accelerating harvests in specific locations to mitigate risks. Secondly, agriculture is already experiencing the direct impacts of climate change. It's evident in reduced crop yields and the unfortunate instances of livestock fatalities due to extreme heat. This sector has a sense of urgency in finding solutions, which align with our goals. Although agriculture remains our primary focus, we are also exploring opportunities in other domains.

DJ: Can you share the details of Climate AI's first successful project, the one that gained recognition for the company?

NS: We collaborated with a Canadian group interested in real estate in Toronto. Our task was to model energy demand expectations for key buildings, taking into account extreme temperatures throughout the year. This analysis helped determine the appropriate sizing of HVAC systems, electrical systems, and air conditioning units, considering capital costs and operational expenses. It was a progressive project for the real estate market at that time. Although we explored various verticals initially, we eventually found our niche in agriculture.

DJ: Could you provide an example of an organization or farmers who have benefited from Climate AI's technology?

NS: One notable organization is Pacific Seeds, a seed company based in Australia. They leverage two parts of our technology: the seasonal model, providing a forecast for 0 to 6 months, and our long-term forecast. Pacific Seeds is an excellent example of how our application can be used effectively and demonstrate tangible business value. As a seed company, they operate as both a grower-producer and a supplier to other growers and producers.

They use our technology to predict events that may affect their crops' growth and make informed decisions about planting and harvesting timings. For example, they consider factors such as potential weather events to plan their operations. This helps them optimize their processes, such as choosing the right time to harvest when conditions are favorable. On the sales side, they use our technology to understand when to bring certain crops to market. By aligning their planting schedules with optimal conditions, they can deliver their seeds more appropriately, which has led to a 5 to 10 percent increase in the market.

DJ: I'm curious, as a US-based company, how do you tailor your tool to the specific needs of farmers outside the US?

NS: Our modeling approach is global, but we can make certain adjustments to cater to individual geographies. We have extensive global data coverage. However, if farmers have on-site weather stations or other data sources, we can incorporate that information to enhance the accuracy of our models and provide more localized insights. Our tool utilizes a machine learning technique called super ensembling, which selects the most reliable forecasts from various sources. We are open to incorporating additional data sources, such as weather station data, to improve our modeling and provide more precise results for specific locations. While it's not a requirement, some farmers and food companies do opt to integrate their data into our tool.

DJ: Adrian Ferrero, Co-Founder of Biome Makers was one of our podcast guests, and during our conversation, he mentioned that it's challenging for farmers to incorporate new concepts when we talk about technology. How did Climate AI overcome this hurdle?

NS: That's a great question. One of the challenges we face in the market is farmer adoption. It complements what Adrian mentioned about farmers finding it difficult to understand new concepts and ideas. To address this challenge, we often target the level above individual farmers. This could be processors or entities with the financial means and a stronger need for our technology. These higher-level institutions are often more trusted by the farming community, which helps us establish credibility and build trust. It takes time to develop a brand and gain trust in the market. Technological adoption is a significant element in the agricultural industry, but I don't believe the perception that farmers are resistant to technology is entirely accurate.

DJ: Farmers are hardworking individuals with busy schedules, so incorporating new technology into their daily routines can be challenging.

NS: True, so to encourage adoption, we need to ensure that the technology is simple, easy to use, and seamlessly integrates into their existing processes. We simplify access to information through methods like SMS messaging, making tools easily available to farmers. Alongside technological adoption, enhancing society's adaptability and resilience to climate change is crucial. This challenge is shared across the resilience-as-a-service marketplace. When it comes to forecasting, we recognize the importance of respecting farmers' expertise while offering additional insights and perspectives that they may find valuable. Building trust is key to striking the right balance.

DJ: Do you believe that education can help bridge the gap in farmer adoption? Are you creating educational materials like videos or marketing tools to explain to farmers how they can improve their work through your platform?

NS: Regarding the grower and farmer community, we are less focused on direct education because our primary focus is on seed companies, processors, and food and beverage companies. However, even in that space, there is an educational gap, particularly when it comes to climate change information. Our main motivation for creating Climate AI and our long-term climate projection modeling was to make complex information more accessible. Many insights from organizations like the Intergovernmental Panel for Climate Change (IPCC) are challenging for the average person to understand. Raw data downloads may require specialized knowledge in areas like GIS (Geographic Information System). Our goal is to make climate information visible and easy to access. There has been a wave of companies that started around 2015-2017, including ours, focusing on visualizing risk information. Another wave emerged in 2019-2020, including the present time, which aims to translate climate information into actionable insights that drive business value. This shift requires collaboration between us and our customers, leading to mutual education. It's not a one-way street where we have all the answers and simply educate them.

DJ: The relationship is often symbiotic.

NS: Yes. For example, we work closely with individuals in the agricultural community to develop agronomic models. These models depict the phenological lifecycle of different crops, including planting, blooming, and harvesting periods. Weather-related risks can impact crop yield differently throughout the lifecycle. While we have an agronomy team at Climate AI, a significant portion of our insights comes from collaborating with our customers. They provide valuable feedback on risks, variables, and impacts that we may not have initially considered. In essence, we need to extract information from proprietary silos within organizations to understand how businesses operate and how weather affects their operations.

Our role is to digitize that information, layer our projections and forecasting on top of it, and help them make smarter decisions. We strive to make the data easily accessible and understandable without requiring a Ph.D. in climate science. Sometimes, our approach resembles that of a consulting firm, as we work closely with organizations to unpack their operations and creatively integrate climate information. Additionally, sharing case studies of successful collaborations with customers plays a crucial role. By obtaining permission and documenting these examples, we can inspire others and spark creativity. Often, the challenges in this space stem from a lack of time or imagination rather than a lack of interest or belief in the need for resilient supply chains and operations. Sharing compelling examples can help unlock that creative thinking and encourage stakeholders to explore the potential benefits of our platform.

DJ: How do you feel the climate market has evolved, especially with the recent boom in AI? Are people more receptive to what you're doing?

NS: I've worked in the climate space for almost a decade, starting with an Americorps position at the Center for EcoTechnology in Massachusetts. After consulting for five years, I joined Climate AI. The pivotal transition year of 2019-2020 saw a push for decarbonization strategies and integrating climate risks into financial disclosures. Despite concerns during the COVID-19 pandemic, sustainability and ESG gained recognition as risk management strategies for corporations. Companies realized the importance of avoiding the negative press, preparing for regulatory changes, and appealing to responsible-minded consumers. This period accelerated the focus on ESG and sustainability, leading to intensified efforts in these areas.

DJ: What are your thoughts on climate AI technology and its role in the future of agriculture and beyond?

NS: As someone working in the early stages of this technology, I believe it will have a significant presence in the market. The key factor is the changing landscape and recognizing the black swans on the horizon. Many companies are focusing on decarbonization and being proactive due to the lessons learned from the COVID-19 pandemic. They want to get ahead of potential carbon taxation and government regulations that may mandate certain disclosures. However, there's still a lack of guidance when it comes to addressing physical risks associated with climate change. This uncertainty hinders full-scale adoption.

Nevertheless, as we approach the imminent targets of 2030, anxiety will likely increase, leading to greater adoption of adaptation and resilience efforts. In agriculture and other sectors, the technology's success depends on simplifying the impact translation and providing actionable recommendations for strategic planning, operations, and supply chain management.

Our goal is not only to demonstrate the impact but also to assist in implementing mitigative actions, helping individuals and organizations navigate the potential risks effectively.

DJ: How do you view the future of sustainability?

NS: That's a great question. Working in the climate space has a mix of emotions. I am constantly inspired by the innovation, thoughtfulness, and generosity of the people involved in this field. However, there are also times when it feels quite dismal and sad to grapple with the information and challenges we face. I acknowledge that I am privileged to live in the United States, where we have the resources and capital to respond to climate change more rapidly than many other communities and countries.

So, I try to remain humble and mindful of the fact that others are more severely impacted. The sustainability community is filled with caring, creative, and wonderful individuals. While we have made progress over the past ten years with increased adoption of targets and commitments, there are still significant challenges ahead. The clock is ticking, and companies have a long way to go to achieve their goals by 2030 or even 2025. This realization keeps me focused on the need for realistic and sustained efforts in decarbonization and other necessary changes.

DJ: One of our podcast guests, Dr. Simon Schillebeeckx mentioned being “cautiously optimistic”. Would you say that's an accurate description of your outlook as well?

NS: Yes, I think "cautiously optimistic" is a fitting term. I often contemplate the balance between technological innovation and cultural change. While I'm not confident that cultural change alone can solve our problems, our system seems more inclined toward technological advancements. There are many exciting initiatives and substantial funding going into breakthrough technologies, which is encouraging.

However, it also raises concerns about relying too heavily on technological solutions rather than focusing on changing consumer demand and cultural shifts. We are seeing some progress in areas like meat alternatives, but these changes involve both innovation and shifts in consumer preferences. So, finding the right balance between driving consumer demand and technological innovation can be challenging. It fascinates me, but it also worries me because time is of the essence.

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