{"id":321368,"date":"2016-11-15T09:42:55","date_gmt":"2016-11-15T17:42:55","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&p=321368"},"modified":"2018-10-16T20:19:20","modified_gmt":"2018-10-17T03:19:20","slug":"hybrid-intelligence-future-work","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/hybrid-intelligence-future-work\/","title":{"rendered":"Hybrid Intelligence and the Future of Work"},"content":{"rendered":"

Computational and algorithmic advances in machine learning methods including deep neural networks have led to a new wave of excitement for Artificial Intelligence (AI). The performance of automated approaches on perception tasks such as objection recognition and speech recognition is approaching human level abilities. However, AI systems still have limitations in carrying out complex activities that come natural to humans; machines are far from carrying out a natural dialog with humans or accomplishing a task like trip planning. They also make mistakes that can be upsetting or harmful for users.<\/p>\n","protected":false},"excerpt":{"rendered":"

Computational and algorithmic advances in machine learning methods including deep neural networks have led to a new wave of excitement for Artificial Intelligence (AI). The performance of automated approaches on perception tasks such as objection recognition and speech recognition is approaching human level abilities. However, AI systems still have limitations in carrying out complex activities […]<\/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":[13561],"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-321368","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-algorithms","msr-locale-en_us"],"msr_publishername":"","msr_edition":"In Proceedings of the Productivity Decomposed: Getting Big Things Done with Little Microtasks Workshop at CHI 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