Abstract Description: Artificial intelligence and machine learning have been topping the headlines in the past year, but is it all hype or is there real value in utilizing these technologies for environmental applications? As the availability and quantity of environmental data has rapidly expanded, there are significant insights that artificial intelligence and machine learning can provide that go beyond traditional technology capabilities.
Generative AI, such as large language models, can be effectively leveraged to interact with very large collections of documents and text. This has the capability to change the paradigm of how environmental professionals work with technical documents, permits, and regulations. Predictive AI, used for modeling, classification, and pattern recognition, can work effectively with large data sets to provide insights that go far beyond traditional statistical and visualization methods.
Join us as we examine practical use cases for how artificial intelligence can be used in environmental applications and ways that your organizations can incorporate these technologies to excel in the digital age. We will examine limitations of current AI-based tools, while also looking ahead to what we can expect to come in near future. Use cases surveyed will include customized and curated ways of interacting with regulations via AI chatbots, building teams with AI "agents," forecasting or modeling emissions, and detecting pollution fingerprints through pattern recognition. Participants can expect to gain an overall understanding of what artificial intelligence is, what is unique about it that makes it so powerful, and why it is important for us to understand as environmental professionals.
