构思
基石
领域(数学)
创造力
过程(计算)
计算机科学
构造(python库)
数据科学
众包
人工智能
知识管理
管理科学
工程设计过程
设计过程
工作(物理)
人机交互
计算创造力
启发式
信息处理
机器人学
相关性(法律)
设计科学
设计工具
操作化
认知科学
作者
Moran Lazar,Hila Lifshitz,Charles Ayoubi,Hen Emuna
标识
DOI:10.5465/amj.2023.1307
摘要
Does “eureka” still ring true in the algorithmic age? This paper investigates algorithmic design and its impact on idea generation. The use of algorithms transforms knowledge work processes, redefining experts’ roles across industries. While experts are typically viewed as the cornerstone of knowledge work, an emerging debate is underway about whether expertise is still necessary in the idea generation process for creativity and innovation. Integrating creativity, expertise in knowledge work, and algorithmic design literatures, we theorize on the interplay between expertise and algorithmic design in idea generation. We suggest that the prevailing algorithmic design, focusing on information exploitation, is misaligned with the recombinant innovation processes needed for idea generation, especially for experts. We design an exploration-based modification to the prevalent exploitation-based algorithm—Google Search. We hypothesize that when using exploration-based algorithms, experts can overcome confirmation bias and generate more creative ideas through recombinant innovation. Moving beyond the individual level, experts are central to bursting “ideation bubbles”—clusters of similar ideas—thus enhancing idea diversity. We test our theory in a laboratory study and a field experiment through a global ideation challenge in sustainability launched on Freelancer. Findings offer insights into designing and using algorithms to augment human expertise for innovation.
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