Artificial intelligence and complex sustainability policy problems:: translating promise into practice
Loading...
Date
Authors
Ruby, O'Connor
Bolton, Mitzi
Saeri, Alexander K.
Chan, Tom
Pearson, Ross
Journal Title
Journal ISSN
Volume Title
Publisher
Access Statement
Abstract
Addressing sustainability policy challenges requires tools that can navigate complexity for better policy processes and outcomes. Attention on Artificial Intelligence (AI) tools and expectations for their use by governments have dramatically increased over the past decade. We conducted a narrative review of academic and grey literature to investigate how AI tools are being used and adapted for policy and public sector decision-making. We found that academics, governments, and consultants expressed positive expectations about AI, arguing that AI could or should be used to address a wide range of policy challenges. However, there is much less evidence of how public decision makers are actually using AI tools or detailed insight into the outcomes of use. From our findings we draw four lessons for translating the promise of AI into practice: 1) Document and evaluate AI’s application to sustainability policy problems in the real-world; 2) Focus on existing and mature AI technologies, not speculative promises or external pressures; 3) Start with the problem to be solved, not the technology to be applied; and 4) Anticipate and adapt to the complexity of sustainability policy problems.
Description
Keywords
Citation
Collections
Source
Policy Design and Practice
Type
Book Title
Entity type
Publication