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科技 · Technology · · 718 words · B1-B2

The Hidden Cost of AI: How Technology is Changing the Workplace

While many worry about losing their jobs to machines, a new form of digital control is already affecting workers everywhere.

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Summary · 摘要

Artificial intelligence is changing how companies manage their employees. While some workers use AI to help them with creative tasks, others are being watched by software that tracks their every move. This trend is creating a divide between those who control the technology and those who are controlled by it. Beyond the office, companies like General Motors have also faced legal trouble for tracking user data. These developments raise important questions about privacy, trust, and human dignity in the modern age.

人工智慧正在改變企業管理員工的方式。雖然有些勞工利用人工智慧協助創意任務,但其他人卻受到追蹤其一舉一動的軟體監控。這種趨勢在掌控技術者與被技術掌控者之間造成了鴻溝。在辦公室之外,通用汽車等公司也因追蹤使用者資料而面臨法律糾紛。這些發展在現代社會引發了關於隱私、信任與人類尊嚴的重要問題。

閱讀模式 ·

For years, the public debate about artificial intelligence has focused on one main fear: that machines will replace human workers and cause mass unemployment. However, according to The Guardian, this focus misses a more immediate reality. The real challenge is not just the loss of jobs, but the growing divide between two types of workers. On one side are professionals like analysts and managers who use AI as a tool to improve their skills. For these people, AI acts like a partner, helping them finish routine tasks faster and leaving more time for creative work. On the other side are workers whose daily lives are increasingly shaped by systems that watch and control them.

In many industries, AI is no longer just a tool; it has become a boss. This is often called “bossware”—software that monitors what employees do while they work. The Guardian reports that one-third of UK employers already use such technology to track online activity. These systems manage schedules, decide how long a task should take, and grade performance. In these environments, workers are not using AI to help themselves; instead, the AI is watching them to ensure they are working at maximum capacity. This shift creates a workplace that is more pressured and less human, where trust is replaced by constant digital oversight.

This trend is not limited to factory floors or delivery drivers. The Guardian notes that these methods are spreading to corporate offices, hospitals, and schools. Even software engineers at major companies report feeling pressured to use AI to increase their productivity, sometimes in ways that actually make their work slower. Furthermore, some companies are beginning to track keystrokes, mouse movements, and clicks to train their AI models. This means that even employees who currently benefit from AI might eventually find themselves under the same strict monitoring as others.

Beyond the office, the collection of personal data has also become a major legal issue. According to The Verge, General Motors (GM) recently agreed to a settlement—a legal agreement to end a dispute—after being accused of selling driver data to insurance companies. Reports indicated that the automaker shared information about speed, hard braking, and rapid acceleration with data brokers. Insurance companies then used this information to change the prices that drivers paid for their insurance.

Following a 2024 report by The New York Times, several lawsuits were filed against the company. As part of the settlement, GM must stop sharing such data with third-party brokers for five years. The company is also required to provide clear notices to drivers about what information is being collected and must ask for permission before tracking driving habits. California Attorney General Rob Bonta stated that this agreement forces the company to stop these practices, highlighting that businesses cannot simply collect data to use for purposes that customers did not agree to.

These two issues—workplace surveillance and the tracking of personal data—are connected by a common theme: the desire for control through information. Whether it is a manager tracking a worker’s clicks or a car company monitoring how a person drives, the result is a loss of privacy. As AI systems become more powerful, they can process vast amounts of information, making it easier for organizations to watch people in ways that were previously impossible.

Experts suggest that the most important issue is not just about the technology itself, but about how it affects human wellbeing. Work is about more than just earning an income; it is also about dignity and trust. When every action a person takes is measured and graded by a system they cannot control, it changes the relationship between the worker and the employer. As this technology continues to spread, society must decide how much control we are willing to give to these systems. The future of work may not be a world without jobs, but it could be a world where those jobs are much more fragmented and stressful than they are today.

選擇題練習 · Quiz

4

  1. 細節 Detail

    1.According to the article, what is a specific consequence of GM's settlement regarding driver data?

  2. 推論 Inference

    2.What can be inferred about the future of 'professional' workers who currently use AI as a tool?

  3. 單字情境 Vocabulary

    3.In the final paragraph, what does the word 'fragmented' mean in the context of the future of work?

  4. 主旨 Main Idea

    4.What is the central message of the article regarding AI and the workplace?

請回答全部 4 題後再提交

易誤解詞彙 · Words to watch

這些字字面意思和文中用法不同,或是不常見的詞性/片語。

divide noun
A significant difference or gap between two groups of people.
分歧、鴻溝。
💡 常見作動詞(分開),這裡作名詞,指群體間的差異。文中:The real challenge is not just the loss of jobs, but the growing divide between two types of workers.
grade verb
To evaluate or rate the quality of someone's work.
評分、評價。
💡 常見作名詞(等級、成績),這裡作動詞,指系統對員工表現進行評估。文中:These systems manage schedules, decide how long a task should take, and grade performance.
hard adjective
In this context, sudden or forceful (referring to braking).
猛烈的、急促的。
💡 常見作「困難的」,這裡形容煞車動作非常猛烈。文中:Reports indicated that the automaker shared information about speed, hard braking, and rapid acceleration with data brokers.

原始來源 · Sources

本文內容由 AI 從以下來源綜合改寫。事實請以原始來源為準。

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