[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-85003-en":3,"doc-seo-85003-105":29,"detail-sidebar-cat-0-en-105":94},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":11,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":13,"seo_description":14,"update_tm":27,"read_time":28},85003,13056703019404,"Miles","https://ap-avatar.wpscdn.com/davatar_29158cc5080c5b710cf443261637dec0",8,"Research & Report","Two-Player Alternate Uses Test: A Controlled Testbed for Interactive Human-AI and Human-Human Co-Creation","Two-Player Alternate Uses Test (AUT) introduces a controlled, two-participant platform to compare human–human and human–AI co-creation under matched, interactive conditions, while using calibrated non-interactive baselines. The testbed decomposes co-creative performance into participant traits, partner perceptions, and content dynamics. An in-person pilot with 62 participants shows GPT-4-backed originality equals human partnering under matched time limits. Moderation effects include BAS Drive and cognitive outsourcing, plus a seeding intervention.","Two-Player Alternate Uses Test: A Controlled Testbed for Interactive Human–AI and Human–Human Co-Creation  \nControlled, Interactive Human-AI Co-Creation  \nBabak Hemmatian¹, Anita Keshmirian², Yijun Lin, Shravan Ramamoorthy³, Mostafa Jahadakbar⁴, Elena Khuri-Reid⁴, Jingyu Wang⁵, Sina Hadjarab⁶, Sigrid Veum², Pranav Gupta⁴, Deepak Somaya⁴, Lav Varshney⁴  \n¹AI Innovation Institute, Stony Brook University ²Forward College Berlin ³Alinea ⁴University of Illinois Urbana-Champaign ⁵University of California San Diego ⁶University of Chicago  \nControlled research on AI ideation typically compares independent agents, while field studies of human–AI collaboration sacrifice experimental control. We introduce a controlled, two-player extension of the Alternate Uses Test (AUT) that enables comparison of human–human and human–AI co-creation under matched interactive conditions, alongside calibrated non-interactive baselines. The platform supports decomposition of performance into three typically confounded factors: participant traits, partner perceptions, and content dynamics. An in-person pilot (N = 62) demonstrates its utility. Under matched time limits, originality with a GPT-4 partner is statistically equivalent to that with a human partner. Approach motivation (BAS Drive) moderates whether interactive partnership benefits originality, and self-reported cognitive outsourcing predicts lower originality specifically in human–human dyads. Prior exposure to highly creative ideas improves later performance, suggesting a “seeding” intervention. We release the platform, code, and dataset as a shared testbed for controlled studies of human–AI co-creation.  \nCCS CONCEPTS • Human-centered computing → Human computer interaction (HCI); Interactive systems and tools; Empirical studies in HCI; • Applied computing → Psychology.  \nAdditional Keywords and Phrases: human–AI co-creation; collaborative creativity; creativity support tools; creative cognition; generative AI; perspective taking; Alternate Uses Test  \n1 INTRODUCTION  \nLarge language models are deployed for creative tasks once thought exclusive to humans, and a psychology of AI creativity has emerged. Two research traditions dominate. Experimental work places humans and LLMs in parallel divergent-thinking tasks and compares their independent outputs (e.g., [14, 26]), yielding clean causal identification but no purchase on what happens during co-creation. Field studies of human–AI teaming in contexts like classrooms and workplaces (e.g., [3, 6]) preserve ecological validity but sacrifice experimental control over the interaction. The middle ground, controlled study of real-time co-creation between a human and an AI compared with human-human interaction, is less studied.  \nA handful of recent studies begin to close this gap. Doshi and Hauser [8] show that one-shot exposure to AI-generated story ideas raises individual originality while narrowing collective diversity, without conversation between participant and AI. Ashkinaze et al. [1] scale this passive-exposure paradigm to a large dynamic experiment. Shaer et al. [23] embed an LLM in asynchronous group brainwriting and validate LLM-based idea evaluation. Closest in design, Maier et al. [17] randomize interaction structure in one-on-one human–AI chat. Each isolates a different slice of the problem, but none preserves a classical divergent-thinking task across matched human–human, human–AI, and non-interactive conditions in a single apparatus so that interactivity, partner identity, conversation structure, and content exposure can be disentangled.  \nThis gap connects to a long-running C&C concern with creativity as a situated, dynamically unfolding interactive process. Prior C&C work has quantified interaction dynamics in open-ended co-creation [5] and articulated design principles for socially interactive systems [16]; more recent work frames turn-taking, contribution type, communication, and feedback as the dimensions that shape human–AI co-creat","cbCaivw5cmab7EnQ","https://ap.wps.com/l/cbCaivw5cmab7EnQ","pdf",818672,2,1,"English","en",105,"# Introduction\n## Contributions","[{\"question\":\"AUT为什么需要从单人版本扩展到“双人”版本？\",\"answer\":\"传统研究要么缺少互动控制，要么缺少现实性对比。双人AUT在同一装置下匹配交互条件，用于同时拆分互动性、伙伴身份与内容暴露对结果的影响。\"},{\"question\":\"平台如何实现对“互动”和“非互动”条件的公平比较？\",\"answer\":\"平台在固定时间限制与匹配指令下运行两名参与者的共享聊天；第三种非互动条件用预先评分的创意集合替代现场伙伴，以便与校准基线进行对照。\"},{\"question\":\"试点结果表明人类与GPT-4的原创性表现是否存在差异？\",\"answer\":\"在匹配时间限制下，与GPT-4伙伴的原创性与与人类伙伴的原创性在统计上等价。BAS Drive会调节互动伙伴是否带来原创性收益，而认知外包会在“人-人”对中降低原创性。\"},{\"question\":\"哪些因素会影响互动协作对原创性的作用？\",\"answer\":\"BAS Drive会调节互动伙伴对原创性的收益；自报的认知外包能预测更低原创性，且该效果特定出现在人-人组合中。此前接触高度创意点子也会通过“种子”干预提升后续表现。\"}]",1784200169,20,{"code":4,"msg":30,"data":31},"ok",{"site_id":24,"language":23,"slug":32,"title":13,"keywords":33,"description":14,"schema_data":34,"social_meta":89,"head_meta":91,"extra_data":93,"updated_unix":27},"two-player-alternate-uses-test-a-controlled-testbed-for-interactive-human-ai-and-human-human-co-creation","",{"@graph":35,"@context":88},[36,52,67],{"@type":37,"itemListElement":38},"BreadcrumbList",[39,43,46,49],{"item":40,"name":41,"@type":42,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":44,"name":45,"@type":42,"position":20},"https://docshare.wps.com/document/","Document",{"item":47,"name":12,"@type":42,"position":48},"https://docshare.wps.com/document/research-report/",3,{"item":50,"name":13,"@type":42,"position":51},"https://docshare.wps.com/document/two-player-alternate-uses-test-a-controlled-testbed-for-interactive-human-ai-and-human-human-co-creation/85003/",4,{"url":50,"name":13,"@type":53,"author":54,"headline":13,"publisher":56,"fileFormat":59,"inLanguage":23,"description":14,"dateModified":60,"datePublished":61,"encodingFormat":59,"isAccessibleForFree":62,"interactionStatistic":63},"DigitalDocument",{"name":9,"@type":55},"Person",{"url":40,"name":57,"@type":58},"DocShare","Organization","application/pdf","2026-07-23","2026-07-16",true,{"@type":64,"interactionType":65,"userInteractionCount":20},"InteractionCounter",{"@type":66},"ViewAction",{"@type":68,"mainEntity":69},"FAQPage",[70,76,80,84],{"name":71,"@type":72,"acceptedAnswer":73},"AUT为什么需要从单人版本扩展到“双人”版本？","Question",{"text":74,"@type":75},"传统研究要么缺少互动控制，要么缺少现实性对比。双人AUT在同一装置下匹配交互条件，用于同时拆分互动性、伙伴身份与内容暴露对结果的影响。","Answer",{"name":77,"@type":72,"acceptedAnswer":78},"平台如何实现对“互动”和“非互动”条件的公平比较？",{"text":79,"@type":75},"平台在固定时间限制与匹配指令下运行两名参与者的共享聊天；第三种非互动条件用预先评分的创意集合替代现场伙伴，以便与校准基线进行对照。",{"name":81,"@type":72,"acceptedAnswer":82},"试点结果表明人类与GPT-4的原创性表现是否存在差异？",{"text":83,"@type":75},"在匹配时间限制下，与GPT-4伙伴的原创性与与人类伙伴的原创性在统计上等价。BAS Drive会调节互动伙伴是否带来原创性收益，而认知外包会在“人-人”对中降低原创性。",{"name":85,"@type":72,"acceptedAnswer":86},"哪些因素会影响互动协作对原创性的作用？",{"text":87,"@type":75},"BAS Drive会调节互动伙伴对原创性的收益；自报的认知外包能预测更低原创性，且该效果特定出现在人-人组合中。此前接触高度创意点子也会通过“种子”干预提升后续表现。","https://schema.org",{"og:url":50,"og:type":90,"og:title":13,"og:site_name":57,"og:description":14},"article",{"robots":92,"canonical":50},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":95},[96,100,104,108,113,118,123,126,130,133,137],{"id":21,"doc_module":4,"doc_module_name":45,"category_name":97,"show_sort_weight":98,"slug":99},"Story & Novel",90,"story-novel",{"id":20,"doc_module":4,"doc_module_name":45,"category_name":101,"show_sort_weight":102,"slug":103},"Literature",80,"literature",{"id":51,"doc_module":4,"doc_module_name":45,"category_name":105,"show_sort_weight":106,"slug":107},"Exam",70,"exam",{"id":109,"doc_module":4,"doc_module_name":45,"category_name":110,"show_sort_weight":111,"slug":112},5,"Comic",60,"comic",{"id":114,"doc_module":4,"doc_module_name":45,"category_name":115,"show_sort_weight":116,"slug":117},6,"Technology",50,"technology",{"id":119,"doc_module":4,"doc_module_name":45,"category_name":120,"show_sort_weight":121,"slug":122},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":45,"category_name":12,"show_sort_weight":124,"slug":125},30,"research-report",{"id":127,"doc_module":4,"doc_module_name":45,"category_name":128,"show_sort_weight":28,"slug":129},9,"Religion & Spirituality","religion-spirituality",{"id":28,"doc_module":4,"doc_module_name":45,"category_name":131,"show_sort_weight":28,"slug":132},"World Cup","world-cup",{"id":134,"doc_module":4,"doc_module_name":45,"category_name":135,"show_sort_weight":134,"slug":136},10,"Lifestyle","lifestyle",{"id":138,"doc_module":4,"doc_module_name":45,"category_name":139,"show_sort_weight":109,"slug":140},19,"General","general"]