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講座題目:AI vs. Human Evaluation: Impact of Assessment Agent on Users’ Idea Contribution Behavior in Crowdsourcing 2020-10-21


題目:AI vs. Human Evaluation: Impact of Assessment Agent on Users’ Idea Contribution Behavior in Crowdsourcing

報(bào)告人:劉洋 助理教授

報(bào)告地點(diǎn):bwin必贏唯一官網(wǎng)313會(huì)議室

報(bào)告時(shí)間:2020年10月26日(周一)上午9:00-10:30


內(nèi)容簡(jiǎn)介:Today, many assessments that have been undertaken by human beings are now made by algorithms with advanced analytic capabilities and access to a huge amount of data. In this study, we investigate how idea assessment agent (AI vs. Human Expert) and assessment criteria objectivity affect participants’ engagement and idea quality (i.e., idea comprehensiveness and innovativeness) in online crowdsourcing platforms. A field experiment was conducted and preliminary results revealed that (1) Informing participants that their ideas will be evaluated by AI (vs. by human expert) will increase their engagement; (2) Informing participants that their ideas will be evaluated by AI (vs. by human expert) will increase the comprehensiveness of ideas and decrease the innovativeness of ideas; (3) the impacts of assessment agent on users’ engagement and idea quality (idea comprehensiveness and idea innovativeness) will be moderated by assessment criteria objectivity. This study provides a nuanced understanding of human responses to AI applications in the context of assessment and provide implications to practitioners who manage crowdsourcing platforms or organize ideation contests regarding how to disclose and describe AI evaluation to participants. At the end of this talk, Yang will share her experiences in doing experimental research and an agenda for AI research from a behavioral science perspective.


講座人簡(jiǎn)介:

Dr Yang (Alison) LIU is a new faculty member in the Department of Information Management and E-Commerce at XJTU. She received her PhD degree in the Department of Information Systems & Analytics at National University of Singapore. Her research work generally falls into two streams. Using experimental methods, she studies how human judgments, decisions, and behaviors (e.g., consumer self-regulation, employee collaboration and creativity) are shaped by emerging digital technologies (e.g., VR/AR and AI). Combining exploratory interviews, field surveys and secondary data, she also explores how automation, digitization and AI transform small and medium enterprises, drives organizational growth and innovation. Her work has appeared in leading Information Systems conferences (e.g., the International Conference on Information Systems) and journals (e.g., Journal of Management Information Systems).


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