Fortune | FORTUNE 前天 19:16
I’m a cybersecurity CEO who advises over 9,000 agencies and Sam Altman is wrong that the AI fraud crisis is coming—it’s already here
index_new5.html
../../../zaker_core/zaker_tpl_static/wap/tpl_guoji1.html

 

文章揭示了人工智能技术正被犯罪网络以前所未有的速度和规模用于欺诈政府福利系统,包括失业救济、灾难援助等。利用深度伪造、合成身份和大型语言模型,犯罪分子能够轻易绕过现有的、过时的反欺诈措施,如单一维度的面部识别。文章强调,这种AI驱动的欺诈比以往任何时候都更快、更便宜、更具可扩展性,已导致数十亿美元的损失,例如在疫情期间,犯罪团伙通过AI伪造身份和文件,大规模骗取失业救济金。作者指出,若不以同样的速度升级防御措施,政府系统将持续处于劣势,并呼吁采用更智能的工具和基础设施,如多层身份验证、实时数据分析和跨部门协作工具,以应对这一日益严峻的挑战。

📈 AI技术正被犯罪网络大规模用于欺诈政府福利系统,包括失业救济、灾难援助等,其速度、成本和可扩展性远超传统欺诈手段。文章指出,犯罪分子利用深度伪造、合成身份和大型语言模型,能够轻易绕过现有的、过时的反欺诈措施,如单一维度的面部识别。

💰 疫情期间的失业救济金欺诈案是AI驱动欺诈的典型案例,犯罪团伙利用AI生成的虚假身份、语音克隆和伪造文件,淹没了未能有效检测这些先进技术的系统,导致数百亿美元的损失。文章提到,仅小企业管理局的监察长估计,疫情期间的失业保险计划就损失了近2000亿美元。

🚨 除了失业救济,包括Medicaid、IRS、TANF、CHIP以及灾难救济项目也面临类似的脆弱性,特别是美国农业部SNAP项目已成为欺诈的“自助餐”,每月损失数十亿美元。文章举例,一个欺诈团伙仅用一天时间就能通过AI在多个州提交数万份虚假申请。

🚀 文章提出了“阿尔特曼法则”,即AI能力每180天翻倍,预示着AI驱动的攻击将呈指数级增长。若防御措施不跟上技术进步的速度,政府将永远处于被动挨打的境地,最脆弱的系统和依赖它们的人们将持续暴露在风险之下。

💡 为应对AI驱动的欺诈,文章呼吁采用更智能的工具和基础设施,而非增加官僚主义。这包括采用多层身份验证(而非仅面部扫描或密码)、实时数据分析、行为分析以及跨部门协作工具,以在资金拨付前识别异常。文章还强调了恢复如国家准确性清算所(National Accuracy Clearinghouse)这类有效工具的重要性,该工具曾成功拦截了数十亿美元的重复福利申报。

It is already happening and it’s not just coming for banks; it’s hitting every part of our government right now.

Every week, AI-generated fraud is siphoning millions from public benefit systems, disaster relief funds, and unemployment programs. Criminal networks are already using deepfakes, synthetic identities, and large language models to outpace outdated fraud defenses, including easily spoofed, single-layer tools like facial recognition, and they’re winning.

We saw a glimpse of this during the pandemic, when fraud rings exploited gaps in state systems to steal hundreds of billions in unemployment benefits. It wasn’t just people wearing masks to bypass facial recognition. It was AI-generated fake identities, voice clones, and forged documents overwhelming systems that weren’t built to detect them. Today, those tactics are more advanced, and fully automated.

I work with over 9,000 agencies across the country. As I testified before the U.S. House of Representatives twice this year, what we’re seeing in the field is clear. Fraud is faster, cheaper, and more scalable than ever before. Organized crime groups, both domestic and transnational, are using generative AI to mimic identities, generate synthetic documentation, and flood our systems with fraudulent claims. They’re not just stealing from the government; they’re stealing from the American people.

The Small Business Administration Inspector General now estimates that nearly $200 billion was stolen from pandemic-era unemployment insurance programs, making it one of the largest fraud losses in U.S. history. Medicaid, IRS, TANF, CHIP, and disaster relief programs face similar vulnerabilities. We have also seen this firsthand in our work alongside the U.S. Secret Service protecting the USDA SNAP program, which has become a buffet for fraudsters with billions stolen nationwide every month. In fact, in a single day using AI, one fraud ring can file tens of thousands of fake claims across multiple states, most of which will be processed automatically unless flagged.

We’ve reached a turning point. As AI continues to evolve, the scale and sophistication of these attacks will increase rapidly. Just as Moore’s Law predicted that computing power would double every two years, we’re now living through a new kind of exponential growth. Gordon Moore, Intel’s co-founder, originally described the trend in 1965, and it has guided decades of innovation. I believe we may soon recognize a similar principle for AI that I call “Altman’s Law”: every 180 days, AI capabilities double.

If we don’t modernize our defenses with the same pace as technological advancements, we’ll be permanently outmatched.

What we desperately need is smarter tools and infrastructure, not more bureaucracy. 

That means layering advanced identity verification, not just facial scans or passwords. It means using real-time data, behavioral analytics, and cross-jurisdictional tools that can flag anomalies before money goes out the door. It also means reviving what has already worked: tools like the National Accuracy Clearinghouse, which flagged billions of dollars in duplicate benefit claims across state lines before it was shut down.

AI is a force multiplier, but it can be weaponized more easily than it can be wielded for protection. Right now, criminals are using it better than we are. Until that changes, our most vulnerable systems and the people who depend on them will remain exposed.

The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune.

Introducing the 2025 Fortune 500

, the definitive ranking of the biggest companies in America. 

Explore this year's list.

Fish AI Reader

Fish AI Reader

AI辅助创作,多种专业模板,深度分析,高质量内容生成。从观点提取到深度思考,FishAI为您提供全方位的创作支持。新版本引入自定义参数,让您的创作更加个性化和精准。

FishAI

FishAI

鱼阅,AI 时代的下一个智能信息助手,助你摆脱信息焦虑

联系邮箱 441953276@qq.com

相关标签

人工智能 欺诈 政府系统 网络安全 身份验证
相关文章