AI-induced hyper-learning in humans

IF 6.3 2区 心理学 Q1 PSYCHOLOGY, MULTIDISCIPLINARY
Moshe Glickman , Tali Sharot
{"title":"AI-induced hyper-learning in humans","authors":"Moshe Glickman ,&nbsp;Tali Sharot","doi":"10.1016/j.copsyc.2024.101900","DOIUrl":null,"url":null,"abstract":"<div><div>Humans evolved to learn from one another. Today, however, learning opportunities often emerge from interactions with AI systems. Here, we argue that learning from AI systems resembles learning from other humans, but may be faster and more efficient. Such ‘hyper learning’ can occur because AI: (i) provides a high signal-to-noise ratio that facilitates learning, (ii) has greater data processing ability, enabling it to generate persuasive arguments, and (iii) is perceived (in some domains) to have superior knowledge compared to humans. As a result, humans more quickly adopt biases from AI, are often more easily persuaded by AI, and exhibit novel problem-solving strategies after interacting with AI. Greater awareness of AI's influences is needed to mitigate the potential negative outcomes of human-AI interactions.</div></div>","PeriodicalId":48279,"journal":{"name":"Current Opinion in Psychology","volume":"60 ","pages":"Article 101900"},"PeriodicalIF":6.3000,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Opinion in Psychology","FirstCategoryId":"102","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352250X24001131","RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PSYCHOLOGY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0

Abstract

Humans evolved to learn from one another. Today, however, learning opportunities often emerge from interactions with AI systems. Here, we argue that learning from AI systems resembles learning from other humans, but may be faster and more efficient. Such ‘hyper learning’ can occur because AI: (i) provides a high signal-to-noise ratio that facilitates learning, (ii) has greater data processing ability, enabling it to generate persuasive arguments, and (iii) is perceived (in some domains) to have superior knowledge compared to humans. As a result, humans more quickly adopt biases from AI, are often more easily persuaded by AI, and exhibit novel problem-solving strategies after interacting with AI. Greater awareness of AI's influences is needed to mitigate the potential negative outcomes of human-AI interactions.
人工智能诱导人类超常学习
人类的进化是为了相互学习。但如今,学习机会往往出现在与人工智能系统的互动中。我们认为,向人工智能系统学习类似于向其他人学习,但可能更快、更有效。之所以会出现这种 "超学习",是因为人工智能(i)具有高信噪比,有利于学习;(ii)具有更强的数据处理能力,能够生成有说服力的论据;(iii)(在某些领域)被认为拥有比人类更丰富的知识。因此,人类更快地接受人工智能的偏见,往往更容易被人工智能说服,并在与人工智能互动后表现出新颖的问题解决策略。要减轻人类与人工智能互动可能产生的负面结果,就需要提高对人工智能影响的认识。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Current Opinion in Psychology
Current Opinion in Psychology PSYCHOLOGY, MULTIDISCIPLINARY-
CiteScore
12.10
自引率
3.40%
发文量
293
审稿时长
53 days
期刊介绍: Current Opinion in Psychology is part of the Current Opinion and Research (CO+RE) suite of journals and is a companion to the primary research, open access journal, Current Research in Ecological and Social Psychology. CO+RE journals leverage the Current Opinion legacy of editorial excellence, high-impact, and global reach to ensure they are a widely-read resource that is integral to scientists' workflows. Current Opinion in Psychology is divided into themed sections, some of which may be reviewed on an annual basis if appropriate. The amount of space devoted to each section is related to its importance. The topics covered will include: * Biological psychology * Clinical psychology * Cognitive psychology * Community psychology * Comparative psychology * Developmental psychology * Educational psychology * Environmental psychology * Evolutionary psychology * Health psychology * Neuropsychology * Personality psychology * Social psychology
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信