Oct 27, 2024
Policy Analysis: AI and Sustainability: Climate Impact Monitoring
Parikirt Oggu & Shawn Reginauld
Organizations are responsible for reporting two emission metrics: direct and indirect
emissions. Reporting direct emissions is fairly standard given activity related to the
generation of such emissions typically being performed within a controlled environment
and on-site, thus making it easier to account for all of the activities that contribute to
such emissions. However, indirect emissions stem from activities such as energy usage
(relying on national grid estimates) and operations within a value chain that make
quantifying such values difficult. Thus, the subjectivity involved with reporting indirect
emissions and often relying on industry estimates to report such values, can
unintentionally report erroneous estimates that misguide our perception and subsequent
action in combating climate change. Leveraging an artificial intelligence (AI) platform
within climate monitoring is critical towards evaluating the specific contributions of
operations within enterprise resource planning (ERP) and supply chain operations,
which can provide an accurate pulse on the total emissions while increasing
transparency amongst all organizations with regards to reporting behavior, to help
shape sustainable practices to combat climate change.
Seokhyun (Nathan) Baek Review
Relevance is clearly stated, but lacks elaboration on specifics, discourse on impact is shallow, innovation and creativity is bland, feasibility (economics, energy, politics)
Monica Lopez
On layout: template not followed, no in-text citations; On content: impact is very general and not uniquely clear to proposal; feasibility narrative is very general not clear on economic policy impacts
Angela Tracy
You've identified an important area that could use the sensitivity of AI and evaluated it well. You also identify legal barriers to implementation, but no strategy to tackle this. I would love to see where this idea goes!
Cite this work
@misc {
title={
@misc {
},
author={
Parikirt Oggu & Shawn Reginauld
},
date={
10/27/24
},
organization={Apart Research},
note={Research submission to the research sprint hosted by Apart.},
howpublished={https://apartresearch.com}
}
