Scaling up analogical innovation with crowds and AI
Scaling up analogical innovation with crowds and AI
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DOI：
10.1073/pnas.1807185116
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发表时间：
2019-02-05
影响因子：
11.1
通讯作者：
Shahaf, Dafna
中科院分区：
文献类型：
--
作者：
Kittur, Aniket;Yu, Lixiu;Shahaf, Dafna
类比--跨领域发现和应用深层结构模式的能力--一直是人类科技创新的基础。如今，通过将类比从单个人的头脑中移出，并将其分布在许多信息处理器(包括人和机器)中，加速创新的机会越来越大。这样做有可能克服认知定势，扩大到大型想法存储库，并支持具有多个约束的复杂问题。在这里，我们展望了可扩展类比创新的未来，以及使用群体和人工智能(AI)来增强创造力的第一步，这些创造力定量地展示了该方法的前景，以及实现这一愿景的关键核心挑战。
Analogy-the ability to find and apply deep structural patterns across domains-has been fundamental to human innovation in science and technology. Today there is a growing opportunity to accelerate innovation by moving analogy out of a single person's mind and distributing it across many information processors, both human and machine. Doing so has the potential to overcome cognitive fixation, scale to large idea repositories, and support complex problems with multiple constraints. Here we lay out a perspective on the future of scalable analogical innovation and first steps using crowds and artificial intelligence (AI) to augment creativity that quantitatively demonstrate the promise of the approach, as well as core challenges critical to realizing this vision.