Enviro - A Comprehensive Environmental Solution Using Policy and Technology
Arun Nimmagadda, Sohil Shah, Tushar Gidadhubli, Arnav Patel · Team Enviro
Submitted to AI Policy Hackathon at Johns Hopkins University. Sprint projects are early-stage work by participants, not Apart Research publications.
This policy proposal introduces a data-driven technical program to ensure that the rapid approval of AI-enabled energy infrastructure projects does not overlook the socioeconomic and environmental impacts on marginalized communities. By integrating comprehensive assessments into the decision-making process, the program aims to safeguard vulnerable populations while meeting the growing energy demands driven by AI and national security. The proposal aligns with the objectives of the National Security Memorandum on AI, enhancing project accountability and ensuring equitable development outcomes.
The product (EnviroAI) addresses challenges associated with the rapid development and approval of energy production permits, such as neglecting critical factors about the site location and its potential value. With this program, you can input the longitude, latitude, site radius, and the type of energy to be used. It will evaluate the site, providing a feasibility score out of 100 for the specified energy source. Additionally, it will present insights on four key aspects—Economic, Geological, Demographic, and Environmental—offering detailed information to support informed decision-making about each site.
Combining the two, we have a solution that is based in both policy and technology.
Reviews
Relevance to AI is explored through identifying the problem and impact on marginalized communities, feasibility is outlined (existing workflow integration, concerns for costs). Impact and risk assessment
Well done! I thought you proposed a solid solution to an important problem. The only real thing I would work on is expanding on how the data-driven program would function technically.
Impressive submission of paper and demo. I would've loved to see more detail into how you anticipate the implementation process.
Cite this project
@misc{nimmagadda2024enviro,
title = {{Enviro - A Comprehensive Environmental Solution Using Policy and Technology}},
author = {Arun Nimmagadda and Sohil Shah and Tushar Gidadhubli and Arnav Patel},
year = {2024},
month = oct,
note = {Submitted to AI Policy Hackathon at Johns Hopkins University, an Apart Research Sprint},
howpublished = {\url{https://apartresearch.com/sprints/projects/enviro-a-comprehensive-environmental-solution-using-policy-and-technology}},
url = {https://apartresearch.com/sprints/projects/enviro-a-comprehensive-environmental-solution-using-policy-and-technology}
}More from AI Policy Hackathon at Johns Hopkins University
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