ERSM for ARSTM, An AI search tool for the Rhetoric of Science, Technology, & Medicine

August 01, 2026

ERSM is a conversational AI agent designed to share scholarship in the rhetoric of science, technology, and medicine (RSTM). Built by importing Anthropic’s Large Language Model, Claude, ERSM holds a diverse bibliography of RSTM scholarship and set of key concepts (such as neurorhetoric, risk communication, etc.) and requires Claude to conduct a live web search that combines the user’s inputs with what has been provided with what has been found online and then generates probablistic responses. ERSM also incorporates some community-oriented rules guiding its outputs; it is instructed to mention foundational sources but to also incorporate work on race, cultural rhetorics, or less represented scholars in areas where dominate figures would otherwise structure its responses. Further, ERSM is instructed to always provide a summary for the user and a list of sources, and ERSM is free to mention other related lines of inquiry at the end of its responses. In this way, rather than functioning as a general-purpose chatbot, ERSM is purpose-built to assist graduate students and those unfamiliar with RSTM to learn more about rhetorical scholarship and get a sense of the whole rage of work available. Over time, new theorists can be added through an “Add a Scholar” function, and the database information can continue to evolve as RSTM grows and changes.

ERSM’s primary audience is graduate students and early-career scholars in rhetoric, communication studies, and science and technology studies (STS) who need a well-informed starting point for literature reviews, seminar preparation, or exploratory research. It may also prove useful more broadly to instructors designing courses on a rhetoric of science or on science communication. By pairing domain-specific expertise with real-time search, ERSM aims to lower the barrier to engaging with a specialized and citation-dense field. Importantly, the tool also includes an “Environmental Impact” tracker (under the search bar) to call attention to how AI-as-search requires environmental resources. In this way, the tool aims to use AI for educational purposes, taking a pragmatic perspective on AI, without being blind to its real-world material requirements.

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