ACIS 2024 Proceedings

Abstract

Climate change has posed great threats to achieving environmental sustainability in the twenty-first century. Artificial intelligence-based sustainability systems can play a significant role in tackling this grand challenge. One specific problem for mitigating climate change is carbon stock estimation at scale, which is critical for decision-making in carbon stock management and carbon trading. Using the design research science approach, this study proposes the initial set of design principles for designing a sustainability artificial intelligence system that performs carbon stock estimation on a global scale, including mapping, detecting, and strategizing. Through the first round of design and development, we instantiated these design principles into a prototypical system that can be used, evaluated, and further developed. By presenting this design journey, we hope to accumulate design knowledge for information systems that address the pressing challenge of climate change.

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