{"id":318131,"date":"2016-11-08T11:47:30","date_gmt":"2016-11-08T19:47:30","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&p=318131"},"modified":"2021-03-29T15:49:39","modified_gmt":"2021-03-29T22:49:39","slug":"messing-querying-sincerity-interactions-open-world","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/messing-querying-sincerity-interactions-open-world\/","title":{"rendered":"Are You Messing with Me? Querying About the Sincerity of Interactions in the Open World"},"content":{"rendered":"
When interacting with robots deployed in the open world, people may often attempt to engage with them in a playful manner or test their competencies. Such engagements are often associated with language and behaviors that fall outside of designed task capabilities and can lead to interaction failures. Detecting when users are driven by play and curiosity can help a robot to understand why some interactions are breaking down, respond more appropriately by conveying its capabilities to its users, and enhance perceptions of its situational awareness and social intelligence. We have been studying the intentions of everyday users in their engagement with a long-lived robot system that provides directions within an office building. We report on a pilot field-study exploring the use of direct queries to elicit the sincerity of user requests, in terms of their actual need for directions. We discuss early results from this initial study and frame research directions and design implications for robots deployed in the wild.<\/p>\n","protected":false},"excerpt":{"rendered":"
When interacting with robots deployed in the open world, people may often attempt to engage with them in a playful manner or test their competencies. Such engagements are often associated with language and behaviors that fall outside of designed task capabilities and can lead to interaction failures. Detecting when users are driven by play and […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13556],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-318131","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-artificial-intelligence","msr-locale-en_us"],"msr_publishername":"","msr_edition":"","msr_affiliation":"","msr_published_date":"2016-1-20","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"","msr_chapter":"","msr_isbn":"","msr_journal":"","msr_volume":"","msr_number":"","msr_editors":"","msr_series":"","msr_issue":"","msr_organization":"ACM. New York, NY, USA","msr_how_published":"","msr_notes":"","msr_highlight_text":"","msr_release_tracker_id":"","msr_original_fields_of_study":"","msr_download_urls":"","msr_external_url":"","msr_secondary_video_url":"","msr_longbiography":"","msr_microsoftintellectualproperty":1,"msr_main_download":"318167","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"file","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/11\/sincerity_open_world.pdf","id":"318167","title":"sincerity_open_world","label_id":"243109","label":0},{"type":"url","viewUrl":"false","id":"false","title":"https:\/\/seanandrist.files.wordpress.com\/2018\/12\/hrilb2603-andrist.pdf","label_id":"243109","label":0}],"msr_related_uploader":"","msr_attachments":[],"msr-author-ordering":[{"type":"user_nicename","value":"Sean Andrist","user_id":36443,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Sean Andrist"},{"type":"user_nicename","value":"Dan Bohus","user_id":31581,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Dan Bohus"},{"type":"text","value":"Zhou Yu","user_id":0,"rest_url":false},{"type":"user_nicename","value":"Eric Horvitz","user_id":32033,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Eric Horvitz"}],"msr_impact_theme":[],"msr_research_lab":[199565],"msr_event":[],"msr_group":[144633],"msr_project":[390800],"publication":[],"video":[],"download":[],"msr_publication_type":"inproceedings","related_content":{"projects":[{"ID":390800,"post_title":"Situated Interaction","post_name":"situated-interaction","post_type":"msr-project","post_date":"2017-07-07 12:00:28","post_modified":"2021-04-06 15:07:38","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/situated-interaction\/","post_excerpt":"The situated interaction research effort aims to enable computers to reason more deeply about their surroundings, and engage in fluid interaction with humans in physically situated settings. When people interact with each other, they engage in a rich, highly coordinated, mixed-initiative process, regulated through both verbal and non-verbal channels. In contrast, while their perceptual abilities are improving, computers are still unaware of their physical surroundings and of the \u201cphysics\u201d of human interaction. 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