2026/3/18今日阅读
一、
原文：
People are talking a lot about artificial intelligence (AI), viewing it as a force that could reshape how society works. But there is something important missing from this discussion. It isn’t enough to ask how it will change us. We also need to understand how we shape AI and what it can tell us about ourselves.
翻译：
人们对人工智能（AI）谈论颇多，将其视为一种可能重塑社会运作方式的力量。但这场讨论中缺失了重要的一点：仅仅追问它将如何改变我们是不够的，我们还需要明白，我们是如何塑造AI的，以及它能向我们揭示关于我们自身的哪些信息。
二、
原文：
Every AI model we develop mirrors our rules and expresses our beliefs. A few years ago, while looking for new workers, a famous company gave up an AI-powered tool after finding it unfavorable to women. The AI was not designed to behave this way, instead, it was influenced by the historical data (数据) favoring men. Similarly, a recent study found that lending algorithms (算法) often offer less favorable terms to colored people, worsening long-standing unfairness in money-lending business. In both cases, AI isn’t creating new biases (偏见), it is mirroring the ones that are already present.
翻译：
我们开发的每一个AI模型都映射着我们的规则，表达着我们的信念。几年前，一家知名公司在招聘新员工时，发现一款AI工具对女性存在偏见，于是放弃了它。这款AI并非被设计成这样，而是受到了偏向男性的历史数据影响。同样，近期一项研究发现，借贷算法往往向有色人种提供更不利的条款，加剧了借贷行业中长期存在的不公。在这两个案例中，AI并非在制造新的偏见，而是在映照已经存在的偏见。
三、
原文：
These reflections (反映) give us an important chance to take a close look at ourselves. By making these problems seen and more pressing, AI challenges us to recognize and address what causes algorithmic bias. As AI continues to develop, we must ask ourselves how we as average people want to shape its role in society. We should not only improve AI models, but also make sure that AI is developed and used responsibly.
翻译：
这些反映给了我们一个审视自身的重要机会。AI让这些问题变得清晰且更紧迫，促使我们去识别并解决算法偏见的根源。随着AI不断发展，我们必须扪心自问：作为普通人，我们希望如何塑造它在社会中的角色？我们不仅要优化AI模型，更要确保AI的开发与使用是负责任的。
四、
原文：
A number of companies are already taking action. They are judging the data, rules, and beliefs that shape the behavior of AI models. Still, we cannot expect the companies to do all the work. As long as AI is trained on human data, it will reflect human behavior. That means we have to think carefully about the footprints of ourselves we leave in the world. I may value privacy, but if I give it up in a heartbeat to visit a website, the algorithms may make a very different judgment of what I really want and what is good for me. If I want meaningful human connections yet spend more time on social media and less time in the physical company of my friends, I am indirectly training AI models about the true nature of humanity.
翻译：
已有不少公司开始采取行动，他们会审核塑造AI模型行为的数据、规则和信念。但我们不能指望企业包揽一切。只要AI基于人类数据训练，它就会反映人类的行为。这意味着我们必须认真思考自己在世界上留下的“足迹”：我或许重视隐私，但如果为了访问某个网站就轻易放弃它，算法就会对我真正的需求和对我有益的事物做出截然不同的判断。如果我渴望有意义的人际联结，却花更多时间在社交媒体上、更少与朋友线下相处，我就是在间接向AI模型灌输人性的真实面貌。
五、
原文：
As AI becomes more powerful, we need to take increasing care to read our principles (原则) into the record of our actions rather than allowing the two to diverge. Recognizing this allows us to make better decisions, but only when we are prepared to look closely and take responsibility for what we see.
翻译：
随着AI变得愈发强大，我们需要更加留意将自己的原则践行于行动记录中，而非让原则与行动渐行渐远。认识到这一点能帮助我们做出更好的决策，但前提是我们愿意仔细审视，并为自己所见的一切承担责任。
我是清清，我们一起英文阅读
妈妈好好学习，孩子天天向上
If mom studies hard, the kid will make progress every day.
