由 英语数字智库 了解更多雅思：科技数字类词汇目录
适用人群：科技行业从业者、考研、雅思高阶学习者
外刊素材来源：
《MIT Technology Review（麻省理工科技评论）（美国科技期刊）》
报刊原版标题：
Digital Privacy Governance and AI Safety Regulations
一、英文改编正文
The explosive deployment of generative artificial intelligence systems
has raised urgent concerns over personal data collection,
information leakage
and the hidden risks embedded inside large model outputs.
AI models are trained on massive datasets scraped from websites,
books and user-generated content,
some of which contain private personal information,
copyrighted materials
and biased narratives that may distort factual judgments.
Digital privacy governance sets clear rules to define what types of data
can be legally gathered, stored and processed during AI development,
requiring tech developers to obtain valid consent
before using individuals’ personal records for model training.
Robust AI safety frameworks are designed to identify harmful outputs,
prevent the abuse of AI tools for disinformation,
fraud or automated cyberattacks,
and build guardrails to limit the system
from generating dangerous instructions.
Researchers adopt red-teaming testing methods
to simulate malicious users and probe
potential vulnerabilities within AI systems,
discovering hidden flaws before these
models are released to commercial users and the public.
Cross-border data flows create complicated regulatory challenges,
because privacy protection standards differ widely among nations and regions.
Global tech organizations must coordinate diverse compliance requirements
when delivering AI services across multiple jurisdictions.
Balancing technological innovation with public safety and individual privacy
remains a central dilemma for legislators and tech leaders.
Well-designed regulations do not intend to block AI progress,
but to foster responsible innovation that protects citizens’ rights
while unlocking the economic potential of intelligent technologies.
二、完整译文
生成式人工智能系统的大规模落地应用，
引发了各界对于个人数据采集、信息泄露
以及大模型输出内容潜藏风险的紧迫担忧。
AI模型依托从网页、
书籍和用户原创内容中抓取的海量数据集完成训练，
部分数据包含私人信息、受版权保护的素材
以及可能扭曲事实判断的偏见叙述。
数字隐私治理制定明确规则，界定AI研发过程中，
哪些类型的数据可以被合法采集、存储与处理，
要求技术开发者在使用个人档案训练模型前，
必须获取用户的有效授权。
完善的AI安全框架旨在识别有害输出内容，
防范AI工具被滥用于虚假信息传播、诈骗或是自动化网络攻击，
同时设置安全防护边界，限制系统生成危险指令。
研究人员采用红队测试方法，
模拟恶意使用者，探查AI系统内部潜在漏洞，
在模型面向商业用户与公众发布之前，找出隐藏缺陷。
跨境数据流动带来复杂的监管难题，
因为不同国家和地区的隐私保护标准差异巨大。
跨国科技企业在多个司法辖区提供AI服务时，
必须协调各不相同的合规要求。
兼顾技术创新、公共安全与个人隐私，
始终是立法者与科技行业领导者面临的核心难题。
设计合理的监管条例并非为阻碍AI发展，
而是培育负责任的创新模式，在保护公民权利的同时，
释放智能技术的经济潜力。
三、核心重点词汇短语
1. governance
/ˈɡʌvənəns/
治理，管理
名词(n.)
2. regulation
/ˌreɡjuˈleɪʃn/
规范，法规
名词(n.)
3. consent
/kənˈsent/
许可，同意
名词(n.)
4. vulnerability
/ˌvʌlnərəˈbɪləti/
漏洞，脆弱点
名词(n.)
5. jurisdiction
/ˌdʒʊərɪsˈdɪkʃn/
司法管辖区，管辖范围
名词(n.)
6. disinformation
/ˌdɪsˌɪnfəˈmeɪʃn/
虚假信息
名词(n.)
7. compliance
/kəmˈplaɪəns/
合规，遵从
名词(n.)
8. embedded
/ɪmˈbedɪd/
内嵌的，嵌入的
形容词(adj.)
四、长难句分层拆解
原句1
The explosive deployment of generative
artificial intelligence systems
has raised urgent concerns over personal data collection,
information leakage and the hidden
risks embedded inside large model outputs.
句子主干：
Deployment has raised concerns
分层修饰成分：
The explosive
前置定语，修饰落地应用
of generative artificial intelligence systems
后置介词定语，限定部署对象
urgent
前置定语，修饰担忧
over personal data collection,
information leakage and the hidden risks
介词短语作后置定语，说明担忧的三类事项
embedded inside large model outputs
过去分词后置定语，修饰潜藏风险，说明风险存在位置
原句2
AI models are trained on massive datasets scraped from websites,
books and user-generated content,
some of which contain private personal information,
copyrighted materials
and biased narratives that may distort factual judgments.
句子主干：
AI models are trained on datasets,
some of which contain information, materials and narratives
分层修饰成分：
massive
前置定语，修饰数据集
scraped from websites, books and user-generated content
过去分词后置定语，描述数据集的来源
some of which
非限制性定语从句，指代前面的数据集
private personal、copyrighted、biased
多层前置定语分别修饰信息、素材、叙述内容
that may distort factual judgments
定语从句，修饰偏见叙述，说明其造成的影响
原句3
Robust AI safety frameworks are designed to identify harmful outputs,
prevent the abuse of AI tools for disinformation,
fraud or automated cyberattacks,
and build guardrails to limit the system
from generating dangerous instructions.
句子主干：
Frameworks are designed to identify outputs,
prevent abuse and build guardrails
分层修饰成分：
Robust AI safety
多层前置定语，修饰安全框架
harmful
前置定语，修饰输出内容
of AI tools
后置介词定语，修饰滥用行为
for disinformation, fraud or automated cyberattacks
介词短语作目的状语，说明滥用AI的用途
to limit the system from generating dangerous instructions
不定式作后置定语，修饰guardrails，说明防护边界的作用
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