Threatened by AI: Analyzing Users’ Responses to the Introduction of AI in a Crowd-Sourcing Platform

IF 5 3区 管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE
Mikhail Lysyakov, Siva Viswanathan
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引用次数: 3

Abstract

As artificial intelligence (AI) solutions are being rapidly deployed, they increasingly compete with human labor. This study examines designers’ strategies in response to the threat from the introduction of an AI system for simple logo designs in a crowdsourcing design platform. We find that, although designers with lower abilities are more likely to exit the platform, designers with higher abilities move away from the locus of threat in the lower-tier contests and switch to more-complex design contests after the introduction of the AI system. More interestingly, we find that, although unsuccessful designers respond to the threat from AI by increasing their participation across multiple contests, successful designers become more focused (i.e., they substantially increase the number of submissions within a contest) and more quality oriented (i.e., they increase emotional content and complexity of their designs) after the AI launch. Our findings show how designers can learn from the behaviors of the more successful designers to differentiate themselves from AI systems by leveraging the more-abstract design attributes. Platform operators would benefit from adopting better segmentations strategies: with AI solutions for simple design tasks, hybrid AI + human solutions for less-complex design tasks, and skilled human designers competing primarily for the more-complex design tasks.
人工智能的威胁:分析用户对在众包平台引入人工智能的反应
随着人工智能(AI)解决方案的迅速部署,它们与人类劳动力的竞争日益激烈。本研究考察了设计师在众包设计平台中引入简单标志设计的人工智能系统所带来的威胁时所采取的策略。我们发现,虽然能力较低的设计师更有可能退出平台,但在引入AI系统后,能力较高的设计师会在较低级别的竞赛中远离威胁,转而参加更复杂的设计竞赛。更有趣的是,我们发现,尽管不成功的设计师通过增加参与多个竞赛来应对AI的威胁,但成功的设计师在AI发布后变得更加专注(例如,他们在竞赛中大幅增加提交的数量),更加注重质量(例如,他们增加了设计的情感内容和复杂性)。我们的研究结果表明,设计师可以从更成功的设计师的行为中学习,通过利用更抽象的设计属性将自己与AI系统区分开来。平台运营商将受益于采用更好的细分策略:人工智能解决方案用于简单的设计任务,人工智能+人类混合解决方案用于不太复杂的设计任务,熟练的人类设计师主要负责更复杂的设计任务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
9.10
自引率
8.20%
发文量
120
期刊介绍: ISR (Information Systems Research) is a journal of INFORMS, the Institute for Operations Research and the Management Sciences. Information Systems Research is a leading international journal of theory, research, and intellectual development, focused on information systems in organizations, institutions, the economy, and society.
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