Technology Ethics科技伦理
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#1
Rarely has a technological advancement provoked such widespread ethical debate as artificial intelligence.
很少有技术进步能像人工智能那样引发如此广泛的伦理辩论。
#2
The unprecedented capacity of AI systems to collect, analyze, and exploit personal data raises fundamental questions about individual privacy.
人工智能系统收集、分析和利用个人数据的前所未有的能力，引发了关于个人隐私的根本性问题。
#3
Governments, corporations, and civil society organizations are now grappling with how to establish meaningful regulation.
各国政府、企业和公民社会组织目前正致力于解决如何建立有意义的规范这一问题。
#4
Seldom do we encounter a challenge that so profoundly intersects technology, philosophy, and human rights.
我们很少遇到一个在技术、哲学和人权领域交织得如此深远的挑战。
#5
At the heart of the debate lies the issue of data privacy.
这场辩论的核心在于数据隐私问题。
#6
Every interaction with a digital platform generates a trail of personal information.
与数字平台的每一次互动都会产生个人信息的踪迹。
#7
Were individuals fully aware of how their data is harvested, many would reconsider their online behavior.
倘若个人充分意识到他们的数据是如何被搜集的，许多人将会重新考虑他们的网络行为。
#8
Sophisticated algorithms can infer sensitive details about a person's health, political beliefs, and financial status.
复杂的算法可以推断出关于一个人的健康状况、政治信仰和财务状况等敏感细节。
#9
This surveillance-like capacity has prompted advocates to demand stricter ethics standards across the technology sector.
这种具监视性质的能力已促使倡议者要求在整个科技产业建立更严格的伦理标准。
#10
The concept of digital rights has emerged as a cornerstone of contemporary ethical discourse.
数字权利的概念已成为当代伦理叙事的基石。
#11
It is imperative that citizens be granted transparent access to information about how their data is used.
公民必须获得透明的渠道，以了解其数据的使用方式。
#12
Not only should individuals have the right to delete their personal records, but they should also control automated decisions.
个人不仅应有权删除其个人记录，还应能控制自动化决策。
#13
The European Union's General Data Protection Regulation represents a landmark attempt to codify these principles into enforceable law.
欧盟的《通用数据保护条例》代表了将这些原则编纂成具法律强制力之法律的里程碑式尝试。
#14
However, critics argue that regulation alone cannot keep pace with the rapid evolution of AI technologies.
然而，批评者认为，单凭法规无法跟上人工智能技术快速演进的步伐。
#15
Algorithmic bias constitutes another pressing ethical concern that demands immediate attention from policymakers and developers alike.
算法偏见构成了另一个迫切的伦理疑虑，需要政策制定者与开发者共同的立即关注。
#16
Should an AI system perpetuate discriminatory patterns embedded in historical data, the consequences could be devastating for marginalized communities.
倘若人工智能系统使嵌入在历史数据中的歧视模式持续下去，其后果对弱势群体而言可能是毁灭性的。
#17
Facial recognition software, for instance, has demonstrated significantly higher error rates for people of color.
例如，人脸识别软件对有色人种的错误率明显较高。
#18
It is precisely this kind of systemic inequity that undermines public trust in technological innovation.
正是这种系统性的不平等，削弱了公众对技术创新的信任。
#19
Addressing such bias requires not merely technical solutions but a fundamental rethinking of how datasets are curated.
解决此类偏见不仅需要技术解决方案，还需要从根本上重新思考数据集的策划方式。
#20
Ultimately, the ethical governance of AI will require sustained collaboration among technologists, ethicists, legislators, and the general public.
最终，人工智能的伦理治理将需要技术专家、伦理学家、立法者以及一般大众之间的持续合作。
#21
No single stakeholder can bear the full burden of ensuring that innovation serves humanity rather than exploiting it.
没有任何单一利益相关者能够独自承担确保创新是服务于人类而非剥削人类的全部重担。
#22
Had we anticipated these dilemmas a decade ago, we might have established more robust safeguards.
若我们在十年前就预见了这些困境，我们或许已经建立了更稳健的防护机制。
#23
Nevertheless, it is not too late to forge a path toward responsible innovation.
尽管如此，现在要开辟出一条通往负责任创新的道路还不算太晚。
#24
Only through transparent dialogue and comprehensive regulation can society harness the benefits of AI while safeguarding fundamental privacy and digital rights.
唯有通过透明的对话与全面的监管，社会才能在利用人工智能益处的同时，守护基本的隐私与数字权利。