Hope Schroeder

schoolMassachusetts Institute of Technologybar_chart#2886 Global Rank

Total Papers

HCI Rank

#2886

Research Areas

Years Active

Recent Publications

Interpretive Cultures: Resonance, randomness, and negotiated meaning for AI-assisted tarot divination

While generative AI tools are increasingly adopted for creative and analytical tasks, their role in interpretive practices,where meaning is subjective, plural, and non-causal, remains poorly understood. This paper examines AI-assisted tarot reading, a divinatory practice in which users pose a query, draw cards through…

CHI '261st AuthorHuman-LLM Collaboration +2

Forage: Understanding LLM-facilitated sensemaking of conversation data

Large language models (LLMs) are increasingly used to make sense of unstructured data, but their use in contexts like conversation analysis, where sensemaking is often human-driven, iterative, and subjective, is underexplored. We introduce Forage, a retrieval-augmented generation (RAG) tool for making sense of convers…

CHI '252nd AuthorHuman-LLM Collaboration +1

Understanding the LLM-ification of CHI: Unpacking the Impact of LLMs at CHI through a Systematic Literature Review

Large language models (LLMs) have been positioned to revolutionize HCI, by reshaping not only the interfaces, design patterns, and sociotechnical systems that we study, but also the research practices we use. To-date, however, there has been little understanding of LLMs' uptake in HCI. We address this gap via a system…

CHI '251st AuthorHuman-LLM Collaboration +2

Large Language Models in Qualitative Research: Uses, Tensions, and Intentions

Qualitative researchers use tools to collect, sort, and analyze their data. Should qualitative researchers use large language models (LLMs) as part of their practice? LLMs could augment qualitative research, but it is unclear if their use is appropriate, ethical, or aligned with qualitative researchers’ goals and valu…

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