B2402 字3:25文章英國腔發布於 2026年3月14日 · 更新於 2026年3月23日

聆聽課程

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Artificial intelligence has rapidly moved from science fiction into our everyday lives, transforming the way we work and communicate.

人工智慧已迅速從科學幻想走進我們的日常生活，改變了我們工作與溝通的方式。

Tools like ChatGPT have demonstrated that machines can now generate human-like text in response to a simple prompt.

像 ChatGPT 這樣的工具已經證明，機器現在可以根據簡單的提示生成類人文本。

For many people, this technological shift has raised both excitement and concern about what the future holds.

對許多人來說，這次技術轉型引發了對未來發展的興奮與擔憂。

Understanding how these systems function is essential for anyone who wants to navigate the modern professional landscape.

了解這些系統如何運作，對於任何想要在現代職場環境中應對自如的人來說都是至關重要的。

One of the most significant effects of artificial intelligence is automation, which is reshaping industries around the globe.

人工智慧最顯著的影響之一是自動化，這正在重塑全球的產業。

Repetitive tasks that once required hours of human labor can now be completed by algorithms in a matter of seconds.

曾經需要數小時人力勞動的重複性任務，現在可以在幾秒鐘內由演算法完成。

For example, customer service chatbots can handle thousands of inquiries simultaneously without ever getting tired or frustrated.

例如，客服聊天機器人可以同時處理數千個詢問，而不會感到疲倦或沮喪。

However, this level of automation has led to growing anxiety among workers whose roles may become redundant in the near future.

然而，這種程度的自動化已導致那些在不久的將來角色可能變得多餘的勞工之間日益增長的焦慮。

The question of ethics is central to the ongoing debate about artificial intelligence and its role in society.

倫理問題是關於人工智慧及其在社會中角色的持續辯論的核心。

#10

When a machine generates content, it is often difficult to determine whether the information is accurate or biased.

當機器生成內容時，通常很難判斷資訊是準確的還是帶有偏見的。

#11

AI systems are trained on massive datasets that may contain stereotypes, outdated facts, or misleading perspectives.

人工智慧系統是在海量數據集上進行訓練的，這些數據集可能包含刻板印象、過時的事實或誤導性的觀點。

#12

As a result, the output produced by these tools can sometimes reinforce harmful assumptions rather than challenge them.

因此，這些工具產生的輸出有時可能會強化有害的假設，而不是挑戰它們。

#13

Establishing clear ethical guidelines has therefore become a priority for governments, technology companies, and educational institutions alike.

因此，建立明確的倫理準則已成為政府、科技公司以及教育機構共同的優先事項。

#14

Despite these concerns, many experts believe that artificial intelligence will create more opportunities than it eliminates.

儘管有這些擔憂，許多專家相信人工智慧創造的機會將多於它所消除的機會。

#15

New professions are already emerging in fields such as prompt engineering, AI ethics consulting, and data curation.

新的職業已經在提示工程、人工智慧倫理諮詢和數據策展等領域中出現。

#16

Workers who develop skills in critical thinking, creativity, and collaboration will likely remain highly valued in the job market.

培養批判性思考、創造力和協作能力的勞工，在就業市場中很可能仍會受到高度重視。

#17

By the time today's university students have entered the workforce, the professional landscape will have changed dramatically.

等到今天的大學生進入職場時，職業樣貌將已經發生劇烈的變化。

#18

Adapting to these changes requires a willingness to learn continuously and embrace new ways of thinking.

適應這些變化需要具備持續學習並擁抱新思維方式的意願。

#19

In conclusion, artificial intelligence and tools like ChatGPT represent a profound transformation in how humans interact with technology.

總之，人工智慧和 ChatGPT 等工具代表了人類與科技互動方式的深刻變革。

#20

While automation may eliminate certain jobs, it also opens doors to entirely new career paths and possibilities.

雖然自動化可能會消除某些工作，但它也為全新的職業道路和可能性開啟了大門。

#21

The ethical challenges surrounding AI demand careful attention from individuals, organizations, and governments worldwide.

圍繞人工智慧的倫理挑戰需要來自個人、組織和全球政府的仔細關注。

#22

Rather than fearing these developments, we should focus on understanding them and preparing ourselves for a rapidly evolving future.

我們不應該恐懼這些發展，而應專注於理解它們，並為快速演變的未來做好準備。

#23

Those who approach this era with curiosity and adaptability will be best positioned to thrive.

那些以好奇心和適應力來面對這個時代的人，將最有利於蓬勃發展。

片語表 (9 個片語)

片語包含類型標示、雙語定義、用法說明和例句。

navigate the landscape

collocation

To deal with a particular situation or environment effectively.

應對某種局勢或環境

解釋： 「Landscape」在此並非指自然風景，而是指「形勢」或「領域」。這個搭配常用於描述在複雜的職業或社會環境中找到方向並成功應對。

範例： Young professionals must learn how to navigate the digital landscape to succeed.

in a matter of

idiom

Emphasizing how short a period of time is.

僅僅在...之內

解釋： 用來強調時間極短，通常接 seconds, minutes, days 等時間單位。

範例： The software can process millions of records in a matter of minutes.

open doors to

idiom

To create new opportunities for someone.

開啟...的機會

解釋： 這是一個比喻性的說法，意指為某人創造新的可能性或進入新領域的機會。

範例： Learning a second language can open doors to international career opportunities.

be best positioned to

collocation

To be in a situation that gives one an advantage to do something.

處於最有利的地位去...

解釋： 描述某人因為具備特定條件、技能或環境，比其他人更有優勢去達成某個目標。

範例： Companies that invest in green energy are best positioned to lead the market in the next decade.

prompt

technical term

The specific text or instruction provided to an AI model to generate a response.

提示詞

解釋： 在日常英語中，'prompt' 通常意為「準時的」或「促使、激勵」。但在人工智慧領域，它專指輸入給 AI 模型（如 ChatGPT）以引發其產生輸出的指令或文字。

範例： The quality of the AI's response depends heavily on the clarity of the prompt.

redundant

technical term

No longer needed for a job because the role has been eliminated, often due to automation or restructuring.

（因崗位被裁撤而）多餘的、被裁員的

解釋： 在一般語境下，'redundant' 指「多餘的」或「重複的」。在職場與勞工法律語境中，它特指因為公司不再需要該職位（例如被機器取代）而導致員工失業，這與因表現不佳而被開除（fired）不同。

範例： Many factory workers were made redundant after the installation of new robotic arms.

landscape

technical term

The current state, situation, or environment of a particular field or industry.

局勢、前景、環境

解釋： 這個詞通常指自然界的「風景」或「地貌」。在專業語境中，它被用來比喻某個行業或領域的整體現狀、競爭環境或發展趨勢。

範例： The political landscape has shifted significantly since the last election.

trained

technical term

The process of an AI model learning patterns from a large dataset.

（模型）訓練

解釋： 通常 'train' 指教導人類技能或訓練動物。在電腦科學中，這是一個專門術語，指將海量數據輸入演算法，使其能夠識別模式並做出預測的過程。

範例： The large language model was trained on billions of pages of internet text.

data curation

technical term

The organization and integration of data collected from various sources to ensure it is useful and accurate.

數據策展 / 數據整理

解釋： 'Curation' 原指博物館或美術館館長的「策展」工作。在科技領域，它指對海量原始數據進行挑選、清理和維護，使其具備高品質以供 AI 使用。

範例： Effective data curation is essential for reducing bias in machine learning models.

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