IUI WorkshopsPub Date : 2023-03-07DOI: 10.48550/arXiv.2303.03927
Cristina Gena, Sara Capecchi
{"title":"Mental State Attribution to Educational Robots: An Experience with Children in Primary School 235-242","authors":"Cristina Gena, Sara Capecchi","doi":"10.48550/arXiv.2303.03927","DOIUrl":"https://doi.org/10.48550/arXiv.2303.03927","url":null,"abstract":"The work presented in this paper was carried out in the context of the project Girls and boys: one day at university promoted by the City of Turin together with the University of Turin. We were responsible for two educational activities on robotics and coding hosted at the Computer Science Department, which made one of its laboratories available for this kind of lesson. At the conclusion of the lab's sessions, children compiled the Attribution of Mental State (AMS) questionnaire, which is a measure of mental states that participants attribute to robots, namely the user's perception of the robot's mental qualities as compared to humans. We distributed the questionnaires both to children attending the educational robotics lab and to children performing coding activities. Results show that the first group attributed higher mental qualities to the robots, compared to the attribution given by children that did not have a direct experience with a robot.","PeriodicalId":357517,"journal":{"name":"IUI Workshops","volume":"200 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115660219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
IUI WorkshopsPub Date : 2023-01-13DOI: 10.48550/arXiv.2301.05578
Justin D. Weisz, Michael J. Muller, Jessica He, Stephanie Houde
{"title":"Toward General Design Principles for Generative AI Applications 130-144","authors":"Justin D. Weisz, Michael J. Muller, Jessica He, Stephanie Houde","doi":"10.48550/arXiv.2301.05578","DOIUrl":"https://doi.org/10.48550/arXiv.2301.05578","url":null,"abstract":"Generative AI technologies are growing in power, utility, and use. As generative technologies are being incorporated into mainstream applications, there is a need for guidance on how to design those applications to foster productive and safe use. Based on recent research on human-AI co-creation within the HCI and AI communities, we present a set of seven principles for the design of generative AI applications. These principles are grounded in an environment of generative variability. Six principles are focused on designing for characteristics of generative AI: multiple outcomes&imperfection; exploration&control; and mental models&explanations. In addition, we urge designers to design against potential harms that may be caused by a generative model's hazardous output, misuse, or potential for human displacement. We anticipate these principles to usefully inform design decisions made in the creation of novel human-AI applications, and we invite the community to apply, revise, and extend these principles to their own work.","PeriodicalId":357517,"journal":{"name":"IUI Workshops","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127544054","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}