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.

Reviewer's Comments

Reviewer's Comments

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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}

}

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This work was done during one weekend by research workshop participants and does not represent the work of Apart Research.
This work was done during one weekend by research workshop participants and does not represent the work of Apart Research.