解析生成式AI的演进与社会影响,为信息系统研究提供新方向。
Generative Artificial Intelligence: Evolving Technology, Growing Societal Impact, and Opportunities for Information Systems Research
- 从符号主义到连接主义,剖析生成式AI的系统性特征。
- 揭示人机生态中生成式AI的深层变革潜力,预测其未来影响。
- 面向信息系研究者,构建可落地的跨领域研究框架。
生成式人工智能(GenAI)基于大语言模型及相关算法,持续迅猛发展,引发对技术潜在影响的广泛关注。尽管普遍认为其将重塑商业与社会,但其区别于以往AI技术的显著特征及其变革潜力仍不明确,信息系统(IS)研究者如何应对亦未清晰。本文旨在通过考察人工智能的发展趋势,分析当前并预测未来影响。现有文献或过于技术化,或缺乏深度,难以支撑对GenAI影响的全面理解。为此,本文从系统性社会技术视角,弥合技术与组织研究之间的鸿沟,探讨GenAI的独特属性,包括从符号主义向连接主义的演进,以及人机生态系统的深层结构性特征。通过回溯人工智能的采纳、适应与应用历程,提出在信息系统研究背景下,针对商业与社会各层面的未来研究方向。本文致力于推动形成结构化的研究议程,支持由新一代AI驱动的创新战略与运营实践。
原文摘要 · Abstract (English)
The continuing, explosive developments in generative artificial intelligence (GenAI), built on large language models and related algorithms, has led to much excitement and speculation about the potential impact of this new technology. Claims include AI being poised to revolutionize business and society and dramatically change personal life. However, it remains unclear exactly how this technology, with its significantly distinct features from past AI technologies, has transformative potential. Nor is it clear how researchers in information systems (IS) should respond. In this paper, we consider the evolving and emerging trends of AI in order to examine its present and predict its future impacts. Many existing papers on GenAI are either too technical for most IS researchers or lack the depth needed to appreciate the potential impacts of GenAI. We, therefore, attempt to bridge the technical and organizational communities of GenAI from a system-oriented sociotechnical perspective. Specifically, we explore the unique features of GenAI, which are rooted in the continued change from symbolism to connectionism, and the deep systemic and inherent properties of human-AI ecosystems. We retrace the evolution of AI that proceeded the level of adoption, adaption, and use found today, in order to propose future research on various impacts of GenAI in both business and society within the context of information systems research. Our efforts are intended to contribute to the creation of a well-structured research agenda in the IS community to support innovative strategies and operations enabled by this new wave of AI.
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