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戈特海默提出兩黨關於人工智慧安全和中國模式限制的法案

眾議員喬許·戈特海默 (Josh Gottheimer) 宣布了《美國人工智慧安全法案》和《中國防火牆法案》,提議對先進人工智慧模型進行強制發布前安全審查,並禁止中國開發的開放權重模型在聯邦設備中使用。

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Source-provided image accompanying Gottheimer introduces bipartisan bills for AI security and Chinese model restrictions
來源參考來源記錄
出版商
wrnjradio.com
來源連結
wrnjradio.comhttps://wrnjradio.com/gottheimer-announces-bipartisan-bills-aimed-at-ai-security-chinese-developed-models/
來源類型
連結來源-主要來源狀態尚未確定。
背景60 秒內了解這一點

從這裡開始

關鍵術語

護欄
限制不安全或不必要的模型行為的規則、檢查和控制。
人工智慧安全
該領域專注於減少人工智慧系統中的有害行為、故障和誤用風險。
重量
一個學習的數值,用來縮放通過神經網路的訊號。
測試一下自己人工智慧道德測驗

發生了什麼事

U.S. Rep. Josh Gottheimer (D-N.J.) announced two bipartisan bills on Friday: the American AI Security Act, which mandates a national security review for advanced AI models before release, and the China FIREWALL Act, which prohibits federal agencies from using Chinese-developed open- AI models. The bills are co-led by Republican Representatives Mike Lawler and Nick LaLota, respectively.

Rep. Josh Gottheimer announced the American AI Security Act and the China FIREWALL Act during an event at Fairleigh Dickinson University in Teaneck, New Jersey. The American AI Security Act, co-led by Rep. Mike Lawler (R-N.Y.), would require developers of certain advanced AI models to submit their technology to the National Security Agency for a mandatory pre-release review. The review would assess whether the model could be used to conduct serious cyberattacks or assist in developing chemical, biological, or radiological weapons. The proposal sets a 30-day deadline for this review, with one 30-day extension permitted, and allows for an expedited appeal process for companies.

The China FIREWALL Act, co-led by Rep. Nick LaLota (R-N.Y.), would prohibit the use of Chinese-developed open- AI models on government-issued devices and bar federal agencies from purchasing software that relies on these models. According to Gottheimer’s office, this bill expands upon existing restrictions on the DeepSeek model included in the fiscal 2026 National Defense Authorization Act by covering a broader range of Chinese-developed open-weight models. Gottheimer also announced plans to send a letter to National Cyber Director Sean Cairncross to seek information regarding the administration’s AI cybersecurity clearinghouse and its capacity to address autonomous AI-driven cyberattacks.

Gottheimer emphasized that there are currently no mandatory requirements for pre-deployment testing of frontier AI models, comparing the lack of regulation to standards in banking, food safety, and medicine. He stated that the goal is not to stifle innovation but to ensure safe deployment. He called on House leadership to bring Congress back before the election to consider these measures, noting that he has led more than a dozen bipartisan AI bills in the current Congress.

來源詳情: wrnjradio.com ↗

為什麼這很重要

These proposals represent a significant legislative push to institutionalize and national security protocols. By mandating pre-deployment reviews by the NSA and restricting foreign-developed models in federal systems, the bills aim to address critical vulnerabilities in cyber and biological security. This marks a concrete step toward regulatory that go beyond voluntary industry standards, potentially setting a precedent for how the U.S. government manages frontier AI risks.

The introduction of these bills signals a shift toward mandatory, government-led oversight of frontier AI capabilities, specifically targeting dual-use risks in cyber and biological domains. The involvement of the NSA in pre-release reviews is a notable escalation from previous proposals that relied on voluntary industry self-regulation or broader executive orders.

The restriction on Chinese-developed open- models in federal systems reflects growing concerns about supply chain security and the potential for adversarial exploitation of AI infrastructure. By expanding beyond specific models like DeepSeek to a broader class of open-weight models, the legislation aims to create a more comprehensive barrier against foreign influence in critical government systems.

The bipartisan nature of the bills, with Republican co-sponsors, suggests a level of cross-party consensus on the need for AI security . This could facilitate faster legislative progress compared to more polarized policy areas, although the specific technical and operational details of the NSA review process remain a point of potential friction with the tech industry.

Interactive Mechanism

互動機制:它實際上是如何運作的

以互動方式探索這項發展背後的基礎技術。

Agent Lifecycle Stage:
1
User Intent & Planning: "Audit customer refund request #4092 and settle payment."
2
Tool Calling: Emits structured JSON call crm_get_transaction(id='4092').
3
Guardrail & Verification:🛡️ Paused: High-value action requires human operator sign-off.
4
Final Settlement: Refund recorded, email receipt dispatched, and audit log stored.
Core takeaway: An AI agent is not just a language model—it is a closed loop of planning, tool invocation, and environment feedback. Production systems require self-healing retries and strict human approval guardrails.
互動式概念檢查+10 Points
AI Ethics Quiz

Why can ethical evaluation not be reduced to one model score?

接下來看什麼

Monitor whether House leadership schedules these bills for a vote before the upcoming election, as Gottheimer has explicitly called for this. Also watch for reactions from AI developers regarding the feasibility of the 30-day NSA review timeline and the specific technical criteria that will define 'covered' models under the security act.

The immediate next step is whether House leadership agrees to schedule a vote on these bills before the election, as requested by Gottheimer. Without a floor vote, the bills may stall in committee or be delayed until the next congressional session.

Industry reactions to the 30-day NSA review timeline will be crucial. AI developers may argue that this timeframe is insufficient for thorough security evaluation, potentially leading to lobbying efforts to modify the review process or the definition of 'covered' models.

The scope of the China FIREWALL Act will be closely watched, particularly how 'open-' models are defined and whether the ban applies to models that are fine-tuned or hosted on third-party platforms. This could have significant implications for federal agencies that currently use open-source AI tools for various applications.

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