{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T21:40:23Z","timestamp":1772228423603,"version":"3.50.1"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643683942","type":"print"},{"value":"9781643683959","type":"electronic"}],"license":[{"start":{"date-parts":[[2023,6,22]],"date-time":"2023-06-22T00:00:00Z","timestamp":1687392000000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,6,22]]},"abstract":"<jats:p>Designing cooperative AI-systems that do not automate tasks but rather aid human cognition is challenging and requires human-centered design approaches. Here, we introduce AI-aided brainstorming for solving guesstimation problems, i.e. estimating quantities from incomplete information, as a testbed for human-AI interaction with large language models (LLMs). In a think-aloud study, we found that humans decompose guesstimation questions into sub-questions and often replace them with semantically related ones. If they fail to brainstorm related questions, they often get stuck and do not find a solution. Therefore, to support this brainstorming process, we prompted a large language model (GPT-3) with successful replacements from our think-aloud data. In follow-up studies, we tested whether the availability of this tool improves participants\u2019 answers. While the tool successfully produced human-like suggestions, participants were reluctant to use it. From our findings, we conclude that for human-AI interaction with LLMs to be successful AI-systems must complement rather than mimic a user\u2019s associations.<\/jats:p>","DOI":"10.3233\/faia230081","type":"book-chapter","created":{"date-parts":[[2023,6,23]],"date-time":"2023-06-23T15:43:42Z","timestamp":1687535022000},"source":"Crossref","is-referenced-by-count":9,"title":["Interacting with Large Language Models: A Case Study on AI-Aided Brainstorming for Guesstimation Problems"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7913-7349","authenticated-orcid":false,"given":"Vildan","family":"Salikutluk","sequence":"first","affiliation":[{"name":"Centre for Cognitive Science, Technical University of Darmstadt, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3571-6848","authenticated-orcid":false,"given":"Dorothea","family":"Koert","sequence":"additional","affiliation":[{"name":"Centre for Cognitive Science, Technical University of Darmstadt, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1355-7663","authenticated-orcid":false,"given":"Frank","family":"J\u00e4kel","sequence":"additional","affiliation":[{"name":"Centre for Cognitive Science, Technical University of Darmstadt, Germany"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","HHAI 2023: Augmenting Human Intellect"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA230081","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,6,24]],"date-time":"2023-06-24T01:35:07Z","timestamp":1687570507000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA230081"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,6,22]]},"ISBN":["9781643683942","9781643683959"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia230081","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,6,22]]}}}