企业大型语言模型:知识特征、风险和组织活动

Q1 Economics, Econometrics and Finance
Daniel E. O'Leary
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引用次数: 0

摘要

自从OpenAI的ChatGPT发布以来,人们对生成型人工智能系统产生了极大的兴趣和担忧。本文研究了企业使用大型语言模型的一些特点、风险和局限性。在这样做的过程中,我们研究了组织的影响,继续了对该主题的长期研究。本文研究了对专业知识的影响,对同一查询的多个相关但不同的响应的组织含义,与敏感信息和知识产权相关的潜在问题,以及一些可能不适合大型语言模型的应用。我们还调查了代理为了自身利益而操纵这些大型语言模型中内容的可能性。最后,我们研究了“ChatBot Enterprise”版本的新兴现象,包括此类企业大型语言模型的一些含义和关注点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enterprise large language models: Knowledge characteristics, risks, and organizational activities

Since the release of OpenAI's ChatGPT, there has been substantial interest in and concern about generative AI systems. This paper investigates some of the characteristics, risks, and limitations with the enterprise use of enterprise large language models. In so doing, we study the organizational impact, continuing a long line of research on that topic. This paper examines the impact on expertise, the organizational implications of multiple correlated but different responses to the same query, the potential concerns associated with sensitive information and intellectual property, and some applications that likely would not be appropriate for large language models. We also investigate the possibility of agents potentially manipulating the content in these large language models for their own benefit. Finally, we investigate the emerging phenomenon of “ChatBot Enterprise” versions, including some of the implications and concerns of such enterprise large language models.

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来源期刊
Intelligent Systems in Accounting, Finance and Management
Intelligent Systems in Accounting, Finance and Management Economics, Econometrics and Finance-Finance
CiteScore
6.00
自引率
0.00%
发文量
0
期刊介绍: Intelligent Systems in Accounting, Finance and Management is a quarterly international journal which publishes original, high quality material dealing with all aspects of intelligent systems as they relate to the fields of accounting, economics, finance, marketing and management. In addition, the journal also is concerned with related emerging technologies, including big data, business intelligence, social media and other technologies. It encourages the development of novel technologies, and the embedding of new and existing technologies into applications of real, practical value. Therefore, implementation issues are of as much concern as development issues. The journal is designed to appeal to academics in the intelligent systems, emerging technologies and business fields, as well as to advanced practitioners who wish to improve the effectiveness, efficiency, or economy of their working practices. A special feature of the journal is the use of two groups of reviewers, those who specialize in intelligent systems work, and also those who specialize in applications areas. Reviewers are asked to address issues of originality and actual or potential impact on research, teaching, or practice in the accounting, finance, or management fields. Authors working on conceptual developments or on laboratory-based explorations of data sets therefore need to address the issue of potential impact at some level in submissions to the journal.
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