亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

GenAI against humanity: nefarious applications of generative artificial intelligence and large language models

人性 生成语法 人工智能 计算机科学 认知科学 哲学 心理学 神学
作者
Emilio Ferrara
出处
期刊:Journal of computational social science [Springer Nature]
被引量:21
标识
DOI:10.1007/s42001-024-00250-1
摘要

Abstract Generative Artificial Intelligence (GenAI) and Large Language Models (LLMs) are marvels of technology; celebrated for their prowess in natural language processing and multimodal content generation, they promise a transformative future. But as with all powerful tools, they come with their shadows. Picture living in a world where deepfakes are indistinguishable from reality, where synthetic identities orchestrate malicious campaigns, and where targeted misinformation or scams are crafted with unparalleled precision. Welcome to the darker side of GenAI applications. This article is not just a journey through the meanders of potential misuse of GenAI and LLMs, but also a call to recognize the urgency of the challenges ahead. As we navigate the seas of misinformation campaigns, malicious content generation, and the eerie creation of sophisticated malware, we’ll uncover the societal implications that ripple through the GenAI revolution we are witnessing. From AI-powered botnets on social media platforms to the unnerving potential of AI to generate fabricated identities, or alibis made of synthetic realities, the stakes have never been higher. The lines between the virtual and the real worlds are blurring, and the consequences of potential GenAI’s nefarious applications impact us all. This article serves both as a synthesis of rigorous research presented on the risks of GenAI and misuse of LLMs and as a thought-provoking vision of the different types of harmful GenAI applications we might encounter in the near future, and some ways we can prepare for them.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
3秒前
8秒前
9秒前
科研通AI6.3应助KamilahKupps采纳,获得10
12秒前
体贴以筠发布了新的文献求助10
13秒前
猴哥发布了新的文献求助10
16秒前
斯文莺发布了新的文献求助10
17秒前
DrN完成签到,获得积分10
20秒前
23秒前
24秒前
111完成签到 ,获得积分10
25秒前
沉静乾完成签到,获得积分10
27秒前
不攻自破发布了新的文献求助10
29秒前
华仔应助inRe采纳,获得10
30秒前
YOG完成签到,获得积分10
38秒前
47秒前
48秒前
小马甲应助那行laxg采纳,获得10
49秒前
斯文败类应助科研通管家采纳,获得10
50秒前
Hello应助科研通管家采纳,获得20
50秒前
大模型应助科研通管家采纳,获得10
50秒前
汉堡包应助科研通管家采纳,获得10
50秒前
50秒前
inRe发布了新的文献求助10
51秒前
小休完成签到 ,获得积分10
52秒前
熊小松发布了新的文献求助10
53秒前
57秒前
KamilahKupps发布了新的文献求助10
58秒前
大神瓜完成签到,获得积分10
59秒前
科研通AI6.2应助huizi采纳,获得10
1分钟前
熊小松完成签到,获得积分10
1分钟前
1分钟前
1分钟前
1分钟前
GingerF应助dihele采纳,获得100
1分钟前
周周粥完成签到 ,获得积分10
1分钟前
1分钟前
那行laxg发布了新的文献求助10
1分钟前
huizi发布了新的文献求助10
1分钟前
1分钟前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Modern Epidemiology, Fourth Edition 5000
Kinesiophobia : a new view of chronic pain behavior 5000
Molecular Biology of Cancer: Mechanisms, Targets, and Therapeutics 3000
Digital Twins of Advanced Materials Processing 2000
Propeller Design 2000
Weaponeering, Fourth Edition – Two Volume SET 2000
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 纳米技术 化学工程 生物化学 物理 计算机科学 内科学 复合材料 催化作用 物理化学 光电子学 电极 冶金 细胞生物学 基因
热门帖子
关注 科研通微信公众号,转发送积分 6012210
求助须知:如何正确求助?哪些是违规求助? 7566558
关于积分的说明 16138721
捐赠科研通 5159173
什么是DOI,文献DOI怎么找? 2762977
邀请新用户注册赠送积分活动 1742036
关于科研通互助平台的介绍 1633873