与人工智能合作开发仪器:可能性与陷阱

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2024-09-17 DOI:10.1016/j.newideapsych.2024.101121
Ronald A. Beghetto , Wendy Ross , Maciej Karwowski , Vlad P. Glăveanu
{"title":"与人工智能合作开发仪器:可能性与陷阱","authors":"Ronald A. Beghetto ,&nbsp;Wendy Ross ,&nbsp;Maciej Karwowski ,&nbsp;Vlad P. Glăveanu","doi":"10.1016/j.newideapsych.2024.101121","DOIUrl":null,"url":null,"abstract":"<div><p>Recent advances in generative artificial intelligence (AI), specifically large language models (LLMs), provide new possibilities for researchers to partner with AI when developing and refining psychological instruments. In this paper we demonstrate how LLMs, such as OpenAI's ChatGPT 4 model, might be used to support the development of new psychometric scales. Partnering with AI for the purpose of developing and refining instruments, however, comes with its share of potential pitfalls. We thereby discuss throughout the paper that instrument development and refinement start and end with human judgment and expertise. We open with two use-cases that describe how we used LLMs in the development and refinement of two new psychological instruments. Next, we discuss possibilities for where and how researchers can use LLMs in the process of instrument development more broadly, including considerations for maximizing the benefits of LLMs and addressing the potential hazards when working with LLMs. Finally, we close by offering initial suggestions for psychology researchers interested in partnering with LLMs in this capacity.</p></div>","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Partnering with AI for instrument development: Possibilities and pitfalls\",\"authors\":\"Ronald A. Beghetto ,&nbsp;Wendy Ross ,&nbsp;Maciej Karwowski ,&nbsp;Vlad P. Glăveanu\",\"doi\":\"10.1016/j.newideapsych.2024.101121\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Recent advances in generative artificial intelligence (AI), specifically large language models (LLMs), provide new possibilities for researchers to partner with AI when developing and refining psychological instruments. In this paper we demonstrate how LLMs, such as OpenAI's ChatGPT 4 model, might be used to support the development of new psychometric scales. Partnering with AI for the purpose of developing and refining instruments, however, comes with its share of potential pitfalls. We thereby discuss throughout the paper that instrument development and refinement start and end with human judgment and expertise. We open with two use-cases that describe how we used LLMs in the development and refinement of two new psychological instruments. Next, we discuss possibilities for where and how researchers can use LLMs in the process of instrument development more broadly, including considerations for maximizing the benefits of LLMs and addressing the potential hazards when working with LLMs. Finally, we close by offering initial suggestions for psychology researchers interested in partnering with LLMs in this capacity.</p></div>\",\"PeriodicalId\":2,\"journal\":{\"name\":\"ACS Applied Bio Materials\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2024-09-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Applied Bio Materials\",\"FirstCategoryId\":\"102\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0732118X24000497\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MATERIALS SCIENCE, BIOMATERIALS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"102","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0732118X24000497","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
引用次数: 0

摘要

生成式人工智能(AI),特别是大型语言模型(LLMs)的最新进展,为研究人员在开发和完善心理测量工具时与 AI 合作提供了新的可能性。在本文中,我们将展示如何利用 LLM(如 OpenAI 的 ChatGPT 4 模型)来支持新心理测量量表的开发。然而,与人工智能合作开发和完善工具也有其潜在的隐患。因此,我们将在本文中讨论,工具的开发和完善始于人类的判断和专业知识,也终于人类的判断和专业知识。我们以两个使用案例开篇,描述了我们如何在两个新的心理工具的开发和完善过程中使用 LLM。接下来,我们讨论了研究人员在工具开发过程中在哪些方面以及如何更广泛地使用 LLM 的可能性,包括如何最大限度地发挥 LLM 的优势,以及在使用 LLM 时如何应对潜在的危险。最后,我们为有兴趣以这种身份与法律硕士合作的心理学研究人员提供了初步建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Partnering with AI for instrument development: Possibilities and pitfalls

Recent advances in generative artificial intelligence (AI), specifically large language models (LLMs), provide new possibilities for researchers to partner with AI when developing and refining psychological instruments. In this paper we demonstrate how LLMs, such as OpenAI's ChatGPT 4 model, might be used to support the development of new psychometric scales. Partnering with AI for the purpose of developing and refining instruments, however, comes with its share of potential pitfalls. We thereby discuss throughout the paper that instrument development and refinement start and end with human judgment and expertise. We open with two use-cases that describe how we used LLMs in the development and refinement of two new psychological instruments. Next, we discuss possibilities for where and how researchers can use LLMs in the process of instrument development more broadly, including considerations for maximizing the benefits of LLMs and addressing the potential hazards when working with LLMs. Finally, we close by offering initial suggestions for psychology researchers interested in partnering with LLMs in this capacity.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
期刊最新文献
A Systematic Review of Sleep Disturbance in Idiopathic Intracranial Hypertension. Advancing Patient Education in Idiopathic Intracranial Hypertension: The Promise of Large Language Models. Anti-Myelin-Associated Glycoprotein Neuropathy: Recent Developments. Approach to Managing the Initial Presentation of Multiple Sclerosis: A Worldwide Practice Survey. Association Between LACE+ Index Risk Category and 90-Day Mortality After Stroke.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1