The Crowdless Future? How Generative AI Is Shaping the Future of Human Crowdsourcing
The Crowdless Future? How Generative AI Is Shaping the Future of Human Crowdsourcing
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无人的未来？
DOI：
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发表时间：
2023
期刊：
影响因子：
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通讯作者：
K. Lakhani
中科院分区：
文献类型：
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作者：
L. Boussioux;Jacqueline N. Lane;Miaomiao Zhang;V. Jaćimović;K. Lakhani
本研究探讨产生式人工智能(AI)创造创新商业解决方案的能力，并与人类众包方法进行比较。我们发起了一项众包挑战，专注于可持续的循环经济商机。这一挑战吸引了来自无数国家和行业的各种解决方案。同时，我们使用GPT-4来生成使用三个不同提示级别的人工智能解决方案，每个级别都经过校准以模拟不同的人类人群和专家角色。145名评估员评估了从234个人类和人工智能解决方案中随机选择的10个，总共1,885个评估者-解决方案对。结果显示，人类生成的解决方案与人工智能生成的解决方案质量相当。然而，人类的想法被认为更新颖，而人工智能解决方案提供了更好的环境和财务价值。我们在丰富的解决方案文本上使用自然语言处理技术来表明，尽管人类解算器和GPT-4涵盖了相似的应用行业，但人类解决方案表现出更大的语义多样性。语义多样性和新颖性之间的联系在人类解决方案中更强，这表明人类和人工智能创造新颖性的方式不同，或者人类评估者如何检测新颖性。这项研究阐明了人类和人工智能众包在解决复杂组织问题方面的潜力和局限性，并为可能的人类-人工智能一体化方法解决问题奠定了基础。
This study investigates the capability of generative artificial intelligence (AI) in creating innovative business solutions compared to human crowdsourcing methods. We initiated a crowdsourcing challenge focused on sustainable, circular economy business opportunities. The challenge attracted a diverse range of solvers from a myriad of countries and industries. Simultaneously, we employed GPT-4 to generate AI solutions using three different prompt levels, each calibrated to simulate distinct human crowd and expert personas. 145 evaluators assessed a randomized selection of 10 out of 234 human and AI solutions, a total of 1,885 evaluator-solution pairs. Results showed comparable quality between human and AI-generated solutions. However, human ideas were perceived as more novel, whereas AI solutions delivered better environmental and financial value. We use natural language processing techniques on the rich solution text to show that although human solvers and GPT-4 cover a similar range of industries of application, human solutions exhibit greater semantic diversity. The connection between semantic diversity and novelty is stronger in human solutions, suggesting differences in how novelty is created by humans and AI or detected by human evaluators. This study illuminates the potential and limitations of both human and AI crowdsourcing to solve complex organizational problems and sets the groundwork for a possible integrative human-AI approach to problem-solving.
影响因子：
8.3
作者：
Lane JN;Ganguli I;Gaule P;Guinan E;Lakhani KR
通讯作者：
Lakhani KR