{"title":"机器、心理学和假设生成:对 Banker 等人(2024 年)的评论。","authors":"Jonah Berger","doi":"10.1037/amp0001258","DOIUrl":null,"url":null,"abstract":"<p><p>Advances in machine learning and artificial intelligence are revolutionizing many aspects of human life, and as Banker et al. (2024) illustrate, generative artificial intelligence may also facilitate hypothesis generation in academic research. But while it is easy to imagine this idea generating some alarm (i.e., hypothesis generation may seem like the most creative, human part of research), their work actually raises an even more important question: Why should we believe that the current (human) method of hypothesis generation is somehow ideal in the first place? This article discusses the implications of their work and outlines how automated content analysis and machine learning can also help researchers determine what hypotheses deserve attention in the first place. (PsycInfo Database Record (c) 2024 APA, all rights reserved).</p>","PeriodicalId":12,"journal":{"name":"ACS Chemical Health & Safety","volume":null,"pages":null},"PeriodicalIF":2.9000,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Machines, psychology, and hypothesis generation: Commentary on Banker et al. (2024).\",\"authors\":\"Jonah Berger\",\"doi\":\"10.1037/amp0001258\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Advances in machine learning and artificial intelligence are revolutionizing many aspects of human life, and as Banker et al. (2024) illustrate, generative artificial intelligence may also facilitate hypothesis generation in academic research. But while it is easy to imagine this idea generating some alarm (i.e., hypothesis generation may seem like the most creative, human part of research), their work actually raises an even more important question: Why should we believe that the current (human) method of hypothesis generation is somehow ideal in the first place? This article discusses the implications of their work and outlines how automated content analysis and machine learning can also help researchers determine what hypotheses deserve attention in the first place. (PsycInfo Database Record (c) 2024 APA, all rights reserved).</p>\",\"PeriodicalId\":12,\"journal\":{\"name\":\"ACS Chemical Health & Safety\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2024-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Chemical Health & Safety\",\"FirstCategoryId\":\"102\",\"ListUrlMain\":\"https://doi.org/10.1037/amp0001258\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Chemical Health & Safety","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1037/amp0001258","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
引用次数: 0
摘要
机器学习和人工智能的进步正在彻底改变人类生活的许多方面,正如Banker等人(2024年)所言,生成式人工智能也可以促进学术研究中的假设生成。不过,尽管很容易想象这一想法会引起一些恐慌(也就是说,假设生成似乎是研究中最具创造性、最人性化的部分),但他们的工作实际上提出了一个更重要的问题:我们为什么要相信目前(人类)提出假设的方法是最理想的?本文讨论了他们工作的意义,并概述了自动内容分析和机器学习如何帮助研究人员确定哪些假设首先值得关注。(PsycInfo Database Record (c) 2024 APA,保留所有权利)。
Machines, psychology, and hypothesis generation: Commentary on Banker et al. (2024).
Advances in machine learning and artificial intelligence are revolutionizing many aspects of human life, and as Banker et al. (2024) illustrate, generative artificial intelligence may also facilitate hypothesis generation in academic research. But while it is easy to imagine this idea generating some alarm (i.e., hypothesis generation may seem like the most creative, human part of research), their work actually raises an even more important question: Why should we believe that the current (human) method of hypothesis generation is somehow ideal in the first place? This article discusses the implications of their work and outlines how automated content analysis and machine learning can also help researchers determine what hypotheses deserve attention in the first place. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
期刊介绍:
The Journal of Chemical Health and Safety focuses on news, information, and ideas relating to issues and advances in chemical health and safety. The Journal of Chemical Health and Safety covers up-to-the minute, in-depth views of safety issues ranging from OSHA and EPA regulations to the safe handling of hazardous waste, from the latest innovations in effective chemical hygiene practices to the courts'' most recent rulings on safety-related lawsuits. The Journal of Chemical Health and Safety presents real-world information that health, safety and environmental professionals and others responsible for the safety of their workplaces can put to use right away, identifying potential and developing safety concerns before they do real harm.