TY - JOUR
T1 - Artificial intelligence possibilities to improve analytical policy capacity
T2 - the case of environmental policy innovation labs and sustainable development goals
AU - Wellstead, Adam M.
AU - Mechling, Sidney M.
AU - Carter, Angie
AU - Gofen, Anat
N1 - Publisher Copyright:
© 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
PY - 2024
Y1 - 2024
N2 - Policy analysts dedicate a great deal of their time performing routine tasks including collecting information, identifying policy issues and options, and appraising policy options. The amount of information available online has become increasingly overwhelming. This “experience” paper examines how readily available AI tools can assist policy workers and researchers. To do so, we examine environmental policy innovation lab (EPIL) websites using three widely used generative AI programs (ChatGPT, Claude AI, and Perplexity) to assess how well they collect information about PILs and how they utilize the UN Sustainable Development Goals (SDGs). To do so, five questions are asked, including defining a PIL, whether the PILs in our database are indeed policy labs and the extent to which PILs explicitly or implicitly contribute to and/or address SDGs. Our results suggest that rapidly emerging AI tools can significantly supplement routine policy analysis and improve the routine tasks associated with analytical policy capacity. However, we conclude that despite the rapid developments, augmented intelligence is not a substitute for human analysis but rather a complementary tool.
AB - Policy analysts dedicate a great deal of their time performing routine tasks including collecting information, identifying policy issues and options, and appraising policy options. The amount of information available online has become increasingly overwhelming. This “experience” paper examines how readily available AI tools can assist policy workers and researchers. To do so, we examine environmental policy innovation lab (EPIL) websites using three widely used generative AI programs (ChatGPT, Claude AI, and Perplexity) to assess how well they collect information about PILs and how they utilize the UN Sustainable Development Goals (SDGs). To do so, five questions are asked, including defining a PIL, whether the PILs in our database are indeed policy labs and the extent to which PILs explicitly or implicitly contribute to and/or address SDGs. Our results suggest that rapidly emerging AI tools can significantly supplement routine policy analysis and improve the routine tasks associated with analytical policy capacity. However, we conclude that despite the rapid developments, augmented intelligence is not a substitute for human analysis but rather a complementary tool.
KW - artificial intelligence
KW - Policy analysis
KW - policy capacity
KW - policy innovation labs
KW - sustainable development goals
UR - http://www.scopus.com/inward/record.url?scp=85200270436&partnerID=8YFLogxK
U2 - 10.1080/25741292.2024.2385118
DO - 10.1080/25741292.2024.2385118
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AN - SCOPUS:85200270436
SN - 2574-1292
JO - Policy Design and Practice
JF - Policy Design and Practice
ER -