Coding the Climate: AI Algorithms as the New Environmental Policy

Bùi Đức Anh (), Subhra R. Mondal () and Subhankar Das ()
Additional contact information
Bùi Đức Anh: Duy Tan University
Subhra R. Mondal: Duy Tan University
Subhankar Das: Duy Tan University

A chapter in Generative AI for a Net-Zero Economy, 2025, pp 217-232 from Springer

Abstract: Abstract The climate crisis is ratcheting up, and the political frameworks of environmental policy, which tend to be reactive, fragmented, and costly, are increasingly unable to keep up with the scale and urgency of ecological collapse. This chapter examines the transformative possibilities for climate governance of artificial intelligence (AI), situating algorithms as active agents of a net carbon economy. Based on policy analysis, interviews with policymakers, and cases from around the world, the study spotlighted three AI-based innovations: AI-enabled impact assessments that make real-time emissions and deflection tracking possible; predictive modeling of policy realized in scenario-based simulations of decarbonization strategies; and automated systems of regulatory compliance that facilitate the enforcement of climate treaties. These technologies offer unprecedented accuracy and efficiency, but often at the price of serious ethical and equity concerns—algorithmic bias, data inequity, and concentration of decision-making power, among others. Both are discussed through examples (from the EU’s controversial carbon auditing algorithm to Kenya’s AI-driven anti-poaching networks), and the chapter concludes with a practical implementation framework for connecting the ethics of AI governance with data: adopt a participatory design process; organ transparency in our data practices; and accountability mechanisms. It argues that technical efficiency should not eclipse the importance of diversity and climate justice in environmental policymaking, enabling algorithmic tools to benefit the communities most affected by climate change. In the end, the chapter contends, the road to a sustainable future will rest on “coding equity into the algorithm”—on channeling AI’s disruptive promise by bending it toward fairness, adaptability, and planetary caretaking.

Keywords: AI governance; Climate policy; Algorithmic equity; Predictive modeling; Environmental justice; Net-zero transition (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-96-8015-3_13

Ordering information: This item can be ordered from
http://www.springer.com/9789819680153

DOI: 10.1007/978-981-96-8015-3_13

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().