在GenAI提示中应该使用哪些场景构建特征?

IF 3 3区 管理学 Q1 ECONOMICS
Tuomo Kuosa, Eljas Aalto
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引用次数: 0

摘要

本文讨论了在场景构建中使用GenAI时的提示过程,特别是大型语言模型(LLM)。它围绕着不同类型的场景及其特征,在人工智能生成的场景和人工智能辅助的场景之间,例如在专家知识建模和计量经济学中,以及如果想要获得高质量,目标明确的场景,需要有一个结构化的多步骤提示程序。这些步骤自然取决于所选择的方法和所寻求的结果,但是有一些原则可以帮助建立良好的提示。其中一个原则是在提示时选择正确的场景构建特征和正确的顺序。为此,本文提供了一个三步类型来指定场景类型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
What scenario-building characteristics should be used in GenAI prompting?
This article discusses the prompting process when using GenAI, especially large language models (LLM) in scenario building. It revolves around the different types of scenarios and their characteristics, between AI-generated scenarios and AI-assisted scenarios, e.g. in Expert knowledge modelling and in Econometrics, and the necessity to have a structured multistep prompting procedure in case one wants to get good quality, well-targeted scenarios. These steps naturally depend on the chosen methodology and the outcome that is sought, yet there are some principles that help set up good prompting. One of these principles is choosing the right scenario-building characteristics and the correct order of these when prompting. For this purpose, this article provides a three-step typology for specifying the scenario types.
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来源期刊
Futures
Futures Multiple-
CiteScore
6.00
自引率
10.00%
发文量
124
期刊介绍: Futures is an international, refereed, multidisciplinary journal concerned with medium and long-term futures of cultures and societies, science and technology, economics and politics, environment and the planet and individuals and humanity. Covering methods and practices of futures studies, the journal seeks to examine possible and alternative futures of all human endeavours. Futures seeks to promote divergent and pluralistic visions, ideas and opinions about the future. The editors do not necessarily agree with the views expressed in the pages of Futures
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