How generative AI models such as ChatGPT can be (mis)used in SPC practice, education, and research?
An exploratory study
Publication date
2023-06-16
Document type
Forschungsartikel
Author
Organisational unit
Scopus ID
Publisher
Taylor & Francis
Series or journal
Quality Engineering
ISSN
Periodical volume
36
Periodical issue
2
First page
287
Last page
315
Part of the university bibliography
✅
Language
English
Keyword
Artificial intelligence
Innovation engineer
Large-language models
Prompt engineering
Abstract
Generative Artificial Intelligence (AI) models such as OpenAI’s ChatGPT have the potential to revolutionize Statistical Process Control (SPC) practice, learning, and research. However, these tools are in the early stages of development and can be easily misused or misunderstood. In this paper, we give an overview of the development of Generative AI. Specifically, we explore ChatGPT’s ability to provide code, explain basic concepts, and create knowledge related to SPC practice, learning, and research. By investigating responses to structured prompts, we highlight the benefits and limitations of the results. Our study indicates that the current version of ChatGPT performs well for structured tasks, such as translating code from one language to another and explaining well-known concepts but struggles with more nuanced tasks, such as explaining less widely known terms and creating code from scratch. We find that using new AI tools may help practitioners, educators, and researchers to be more efficient and productive. However, in their current stages of development, some results are misleading and wrong. Overall, the use of generative AI models in SPC must be properly validated and used in conjunction with other methods to ensure accurate results.
Version
Published version
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