{"type":"ScholarlyArticle","title":"Fair and Explainable Dynamic Engagement of Crowd Workers","authors":[{"name":"Han Yu","slug":"han-yu","given":"Han","family":"Yu","affiliation":"School of Computer Science and Engineering , Nanyang Technological University"},{"name":"Yang Liu","slug":"yang-liu","given":"Yang","family":"Liu","affiliation":"Department of AI , WeBank"},{"name":"Xiguang Wei","slug":"xiguang-wei","given":"Xiguang","family":"Wei","affiliation":"Department of AI , WeBank"},{"name":"Chuyu Zheng","slug":"chuyu-zheng","given":"Chuyu","family":"Zheng","affiliation":"Department of AI , WeBank"},{"name":"Tianjian Chen","slug":"tianjian-chen","given":"Tianjian","family":"Chen","affiliation":"Department of AI , WeBank"},{"name":"Qiang Yang","slug":"qiang-yang","given":"Qiang","family":"Yang","affiliation":"Department of AI , WeBank; Department of Computer Science and Engineering , Hong Kong University of Science and Technology"},{"name":"Xiong Peng","slug":"xiong-peng","given":"Xiong","family":"Peng","affiliation":"Better Life Commercial Chain Share Co. Ltd"}],"abstract":"Years of rural-urban migration has resulted in a significant population in China seeking ad-hoc work in large urban centres. At the same time, many businesses face large fluctuations in demand for manpower and require more efficient ways to satisfy such demands. This paper outlines AlgoCrowd, an artificial intelligence (AI)-empowered algorithmic crowdsourcing platform. Equipped with an efficient explainable task-worker matching optimization approach designed to focus on fair treatment of workers while maximizing collective utility, the platform provides explainable task recommendations to workers' personal work management mobile apps which are becoming popular, with the aim to address the above societal challenge.","doi":"10.24963/ijcai.2019/961","url":"https://ijcai.org/proceedings/2019/961","pdf":"https://ijcai.org/proceedings/2019/0961.pdf","markdown":"https://ijcai.org/proceedings/2019/961.md","bibtex":"https://ijcai.org/proceedings/2019/bibtex/961","volume":{"slug":"2019","title":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2019","url":"https://ijcai.org/proceedings/2019/","year":2019,"location":"Macao","dates":"10-16 August 2019","editors":"Sarit Kraus","isbn":"978-0-9992411-4-1","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2019"},"section":"Demos","track":"Demos","number":961,"pages":{"first":6575,"last":6577},"keywords":["AI: Recommender Systems","Applications: Public services and social systems","AI: Planning and Scheduling"],"videos":[],"references":[{"position":1,"raw":"[AI HLEG, 2019] AI HLEG. 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