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Although prior research has explored techniques to facilitate collaboration during human-robot interaction, the work described here aims to forge productive partnerships prior to human-robot interaction, drawing upon team-building activities\u2019 aid in establishing effective human teams. Through a 2 (group membership: ingroup and outgroup) \u00d73 (robot error: main task errors, side task errors, and no errors) online study (\n            <jats:italic>N=62<\/jats:italic>\n            ), we demonstrate that (1) a non-social pre-task exercise can help form ingroup relationships; (2) an ingroup robot is perceived as a better, more committed teammate than an outgroup robot (despite the two behaving identically); and (3) participants are more tolerant of negative outcomes when working with an ingroup robot. We discuss how pre-task exercises may serve as an active task failure mitigation strategy.\n          <\/jats:p>","DOI":"10.1145\/3611657","type":"journal-article","created":{"date-parts":[[2023,8,31]],"date-time":"2023-08-31T11:28:01Z","timestamp":1693481281000},"page":"1-21","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["Forging Productive Human-Robot Partnerships Through Task Training"],"prefix":"10.1145","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0470-1229","authenticated-orcid":false,"given":"Maia","family":"Stiber","sequence":"first","affiliation":[{"name":"Johns Hopkins University, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6183-2482","authenticated-orcid":false,"given":"Yuxiang","family":"Gao","sequence":"additional","affiliation":[{"name":"Johns Hopkins University, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6272-1100","authenticated-orcid":false,"given":"Russell","family":"Taylor","sequence":"additional","affiliation":[{"name":"Johns Hopkins University, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6838-3701","authenticated-orcid":false,"given":"Chien-Ming","family":"Huang","sequence":"additional","affiliation":[{"name":"Johns Hopkins University, USA"}]}],"member":"320","published-online":{"date-parts":[[2024,1,30]]},"reference":[{"key":"e_1_3_2_2_2","unstructured":"Unity. 2019. 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