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The unstructured nature of data used in foundation model development is achallenge to systematic analyses for making data use and documentationdecisions. From a Responsible AI perspective, these decisions often rely uponunderstanding how people are represented in data. We propose a frameworkdesigned to guide analysis of human representation in unstructured data andidentify downstream risks. We apply the framework in two toy examples using theCommon Crawl web text corpus (C4) and LAION-400M. We also propose a set ofhypothetical action steps in service of dataset use, development, anddocumentation.

SoUnD Framework: Analyzing (So)cial Representation in (Un)structured (D)ata