AI and data modeling offer opportunities to address climate change by enhancing our ability to compute and predict climate data, track emissions, and provide behavioral nudges. However, these models are not free from biases seen in other areas, such as predictive policing and search engine bias. Further, many corporate communications about climate emissions and impacts can be seen as greenwashing, and the absence of accessible climate impact data creates a data void for people trying to understand the impacts of climate change on their lives. This project investigates how people find and understand information about climate data modeling and its effects on their lives and finances, using a content analysis of corporate ESG reports, interviews, and search tasks assigned to interviewees. A proposed framework aims to help audiences evaluate the effects of a company’s climate actions and reporting, enhancing stakeholder understanding and decision-making processes.
Publisher
iSchools
Series/Report Name or Number
iConference 2025 Proceedings
Type of Resource
Other
Genre of Resource
Conference Poster
Language
eng
Handle URL
https://hdl.handle.net/2142/126219
Copyright and License Information
Copyright 2025 is held by Aashka Dave. Copyright permissions, when appropriate, must be obtained directly from the author.
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212_poster.pdf
212_abstract.docx
