InBrief - using AI to summarize environmental impact statements

In affiliation with the University of Michigan, Taubman College of Architecture and Urban Planning

As part of Taubman College’s urban technology prototype grant program, I’m building a system that uses new large language modeling (LLM) technology to summarize the lengthy environmental impact analyses (EIAs) required of most urban development projects. In the half century since the National Environmental Protection Act (NEPA), these documents have stretched from an average length of 10 pages to over 1,600 pages.

My current prototype of the system can be found on my Github.