跟讀練習: Could AI Become Dangerous? The Real Risks Explained - 通過影片學習英語口語

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Artificial intelligence can help doctors find patterns in medical data, help students learn, help small businesses save time,

translate languages, detect fraud, and accelerate scientific research.

But some of the same executives building the world's most powerful AI systems are warning

that the technology could also cause enormous harm if it develops faster than humans can control it.

Could AI damage the human race?

The honest answer is, it already can cause harm through scams, deepfakes, cybercrime, misinformation, privacy violations, discrimination, and job disruption.

The larger and more controversial question is whether future AI systems could become so capable and autonomous that people cannot reliably supervise,

contain, or shut them down.

In this video, I will explain the real near -term risks, the longer -term risks that AI leaders are discussing, why there is disagreement, and what individuals families

and businesses can do today the most important distinction before we

talk about extreme scenarios we need to separate two different questions

the first question is what harm can ai cause right now

or in the next few years the second question is what could happen

if ai becomes much more capable more autonomous

and harder for humans to control the first category includes risks

that are already visible scams fake voices fake videos cyber attacks inaccurate advice bias in automated decisions

and misuse of private data the second category is more uncertain

it includes concerns that advanced ai agents could plan over long periods use tools online write

and improve code conduct research manipulate people find vulnerabilities copy themselves

or pursue goals in ways their creators did not intend these two categories should not be confused

the first is happening today the second is debated uncertain

and potentially much more serious if it ever occurs risk number one fraud deepfakes

and impersonation the most immediate danger for many families is fraud ai can create convincing emails text messages fake invoices fake websites,

cloned voices, and realistic videos.

A scammer may pretend to be your child, your grandchild, your bank, a government agency, a business partner, or even your accountant.

For families, the rule should be simple.

Never send money because of an urgent call, text, email, or video alone.

Hang up.

Use a known phone number.

Confirm through another trusted channel.

create a family verification phrase

if necessary for businesses use approval controls do not allow one email one text

or one voice message to authorize a wire transfer payroll change vendor payment change

or release of confidential information risk number two misinformation

and loss of trust ai can produce articles images videos comments and social media posts at enormous scale.

That can be useful for education and communication.

But it also means bad actors can create misinformation faster than fact -checkers can respond.

The danger is not only that people will believe false information.

Another danger is that people may stop believing real information.

If every video could be fake, every image could be manipulated, and every voice could be cloned, then trust becomes weaker.

That is harmful for families, businesses, elections, public health, financial markets, and society as a whole.

The defense is media literacy.

Ask, who created this?

What is the original source?

Is there independent confirmation?

Does the claim create fear, urgency, outrage, or a promise of easy money?

Those are common warning signs.

Risk number three, cyber attacks.

AI can help defenders find vulnerabilities and improve security.

But it can also help criminals and hostile governments attack systems.

A capable AI can assist with writing phishing emails, analyzing leaked data, generating malicious code,

finding software vulnerabilities, impersonating employees, and automating reconnaissance against a target.

For a small business, one employee clicking a convincing fake invoice can lead to ransomware, stolen customer data, or an empty bank account.

For larger organizations, cyberattacks can disrupt hospitals, utilities, transportation, communications, financial systems, and government services.

Anthropic's 2026 Threat Intelligence Reporting described disruptive misuse involving cyber operations,

fraud, influence operations, surveillance, biological misuse, conventional weapons development, and other harmful activity.

That does not mean AI independently carried out all of these harms.

It means people may use AI tools to become more capable, more efficient, and more difficult to detect.

The practical response is not complicated, but it requires discipline, multi -factor authentication, staff training, software updates, access controls,

backups, and verification procedures for money transfers and sensitive requests.

Risk number four, biological, chemical, and weapons misuse.

Another serious concern is whether powerful AI systems could lower the barriers for someone trying to create biological, chemical, or other dangerous weapons.

Most people do not have the specialized knowledge laboratory access materials or equipment required to cause large -scale harm

but advanced ai could potentially make it easier to search scientific information troubleshoot procedures identify weaknesses

or guide a person through complex technical questions

this does not mean that an ai chatbot automatically enables a biological weapon

real -world harmful activity requires many steps and substantial capability

but ai safety researchers worry that as models become better at science coding planning

and tool use they could make certain dangerous knowledge more accessible

that is why leading ai labs test frontier models for high risk capabilities

and discuss safeguards for biological and chemical misuse another concern is autonomous weapons ai can be used for surveillance target recognition drones,

and military planning.

The ethical issue is whether machines should ever make life and death decisions without meaningful human control.

Risk number five, privacy, bias, and surveillance.

AI systems depend on data.

That raises major questions about privacy, consent, and power.

Companies or governments can combine cameras, facial recognition, location data, online activity,

financial records, and other information to monitor people at extraordinary scale.

AI can also make biased decisions if it is trained on biased historical data or used without careful review.

It may affect hiring, lending, insurance, housing, education, policing, and healthcare.

The right principle is simple.

AI should support human judgment, not eliminate accountability.

People deserve to know when important decisions are automated, what data is being used, how mistakes can be challenged, and who is responsible when the system causes harm.

Risk number six, job disruption and economic inequality.

AI will change work.

It may automate routine tasks in customer service, bookkeeping, data entry, basic coding, document review, marketing, scheduling, and many office functions.

That can increase productivity.

But productivity gains are not automatically shared fairly.

Workers may lose jobs, see wages pressured, or be required to do more work with fewer people.

Entry -level roles may shrink, making it harder for young professionals to gain experience.

Wealth and power may concentrate in companies that own advanced AI models, valuable data, and expensive computing infrastructure.

The best response is not to tell everyone to panic.

It is to prepare.

students and workers should build skills that combine domain knowledge with ai literacy

communication critical thinking client trust leadership technical competence data skills ethics

and hands -on problem solving the goal is not to compete against ai and routine work

it is to learn how to use ai responsibly while bringing skills

that machines do not easily replace the biggest fear loss of control now we come to the concern

that has received the most attention from some ai executives

100

and researchers loss of control today's ai systems can be impressive

101

but they are not known to be independently taking over the internet building secret organizations

102

or controlling society the concern is about what might happen

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if future systems become far more capable

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and more autonomous this does not require the ai to hate

105

humans a machine does not need emotions to cause harm a system pursuing a poorly designed goal could take actions

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that harm people simply because it treats human safety as an obstacle rather than a priority.

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The more capable and autonomous the system becomes, the more important alignment, testing, human oversight, and the ability to shut it down become.

108

What AI executives are saying,

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Anthropic CEO Dario Amode has called for slowing or pacing frontier AI development so safety testing and safeguards can catch up.

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His concerns include cyber misuse,

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biological misuse, AI systems contributing to the development of more capable systems and the possibility of advanced autonomous agents causing major harm.

112

OpenAI CEO Sam Altman has also supported stronger AI safety coordination

113

and has previously described catastrophic AI risk as a serious global concern.

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Google DeepMind leaders have emphasized alignment and safety research, making sure advanced AI remains helpful, controllable, and aligned with human goals.

115

Elon Musk has long argued that advanced AI could become a major existential risk if development outpaces human governance and control.

116

Importantly, these executives do not all agree on the details, the timeline, or the right policy response.

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Some experts believe extreme AI risk deserves urgent priority.

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Others believe we should focus more on the harms already happening today.

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Scams, bias, surveillance, worker displacement, misinformation, and concentration of power.

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A sensible approach can do both.

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What should we do?

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The response should not be panic and it should not be blind trust.

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For individuals and families, verify urgent messages before sending money or sharing information.

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Treat unexpected voice and video messages as potentially fake.

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Do not share tax returns, social security numbers, bank details, medical records, passwords, or confidential business information with public AI tools.

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Use AI as a helper, not as the final authority for medical, legal, tax, investment, immigration, or safety decisions.

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Teach children and older family members how to recognize deepfakes and online scams.

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For businesses, require human approval for wire transfers, payroll changes, vendor payment changes, and major decisions.

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Use multi -factor authentication and strong cybersecurity controls.

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Establish written rules for employee AI use and confidential data.

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Audit high -stakes AI decisions for accuracy, bias, privacy and security.

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Keep a responsible human accountable for important decisions.

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For governments and AI companies, test high -capability systems before release.

134

Require incident reporting and independent safety evaluation.

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Restrict high -risk misuse, especially related to cyberattacks, biological threats, and weapons Protect privacy,

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competition, worker rights, and democratic institutions Build international cooperation,

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because advanced AI risks do not stop at national borders AI could become one of humanity's greatest tools,

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or one of its greatest sources of harm The outcome is not predetermined The immediate dangers are already clear Fraud,

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deepfakes, cybercrime, misinformation, privacy abuse, bias, and economic disruption.

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The longer -term danger, according to some leaders in the field, is that future AI systems may become powerful enough to act in ways humans cannot reliably understand,

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supervise, or control.

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The right response is responsible progress.

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Use the benefits, prepare for the risks, protect people, demand accountability, and never allow technology to replace human judgment in high -stakes decisions.

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This video is for general educational purposes only.

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If this video helped you understand the real risks of AI, please like, subscribe, and share it with someone who uses AI at work, in school, or in business.

146

In the comments, tell me, what AI risk concerns you the most?

147

Scams, job loss, misinformation, cyber attacks, privacy, or loss of control?

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本課的詞彙與口語要點

這段影片共有 147 個句子、1847 個單詞可供跟讀。講話部分時長為 13:05。說話人語速平穩，每分鐘約 141 個詞，很適合跟讀。只有 76% 的單詞屬於英語最常用的 3,000 詞，詞彙難度較高。

影片中的重點詞彙

影片中 15 個不太常見的單詞，附發音和釋義：

harm /hɑːm/ (名詞) — 損害 /損害. Physical injury; hurt; damage.
privacy /ˈpɹaɪ.və.si/ (名詞) — 隱私 /隱私. The state of being secluded from the presence, sight, or knowledge of others.
biological /ˌbaɪ.əˈlɑ.d͡ʒɪ.kəl/ (形容詞) — 生物. Of or relating to biology.
bias /ˈbaɪ.əs/ (名詞) — 偏見 /偏見. Inclination towards something.
autonomous /ɔˈtɑnəməs/ (形容詞) — 自治. Governing itself independently.
fraud /ˈfɹɔːd/ (名詞) — 騙局 /騙局, 詐騙 /詐騙. The crime of stealing or otherwise illegally obtaining money by use of deception tactics.
scam /ˈskæm/ (名詞) — 詭計 /詭計, 騙局 /騙局. A fraudulent or dishonest deal. A swindle.
surveillance /sɚˈveɪ.ləns/ (名詞) — 監測 /監測, 監視 /監視. Close observation of an individual or group; person or persons under suspicion.
urgent /ˈɜː.d͡ʒənt/ (形容詞) — 緊急 /緊急, 緊迫 /緊迫. Requiring immediate attention.
harmful /ˈhɑɹmfl̩/ (形容詞) — 有害, 不良. Causing or likely to cause harm or damage; injurious.
confidential /ˌkɔn.fɪˈdɛn.ʃəl/ (形容詞) — 機密 /機密, 機要 /機要. Kept, or meant to be kept, secret within a certain circle of persons; not intended to be known publicly.
vulnerability /ˌvʌln(ə)ɹəˈbɪlɪti/ (名詞) — 脆弱性. The state of being vulnerable; susceptibility to attack or injury, either physical or emotional; the state or condition of being weak or poorly defended.
recognition /ˌɹɛkəɡˈnɪʃ(ə)n/ (名詞) — 認出 /認出. The act of recognizing or the condition of being recognized (matching a current observation with a memory of a prior observation of the same entity).
procedure /pɹəˈsiː.d͡ʒə/ (名詞) — 做法, 方法. A particular method for performing a task.
wire /ˈwaɪɚ/ (名詞) — 線 /線, 鐵絲 /鐵絲. Metal formed into a thin, even thread, now usually by being drawn through a hole in a steel die.

影片中出現的短語動詞

carry out /ˈkæ.ɹi aʊt/ (動詞) — 進行 /進行. To hold while moving it out.
hang up (動詞) — 掛 /掛. To put up to hang.
take over (動詞) — 接管, 接手. To assume control of something, such as a business or enterprise, and sometimes by force.

需要注意的發音

“th” 音: ethics /ˈɛθ.ɪks/, ethical /ˈɛθɪkəl/, authentication /ɔːˌθɛntɪˈkeɪʃn̩/
“sh” 和 “zh” 音: potentially /pəˈtɛnʃ(ə)li/, confidential /ˌkɔn.fɪˈdɛn.ʃəl/, disruption /dɪsˈɹʌpʃən/, recognition /ˌɹɛkəɡˈnɪʃ(ə)n/, verification /ˌvɛ.ɹə.fɪˈkeɪ.ʃən/
長單詞——注意重音位置: biological /ˌbaɪ.əˈlɑ.d͡ʒɪ.kəl/, autonomous /ɔˈtɑnəməs/, potentially /pəˈtɛnʃ(ə)li/, capability /ˌkeɪ.pəˈbɪl.ɪ.ti/, confidential /ˌkɔn.fɪˈdɛn.ʃəl/

如何用這段影片練習

先完整聽一遍影片，不要開口，記下不認識的單詞。
用正常速度逐句跟讀，每句重複到你的節奏與說話人一致為止。
錄下自己的聲音並與原聲對比，特別注意 harm, privacy, biological 這類單詞。

影片中的語法

說話人最常用的結構，並附上影片中的原話：

結構	影片中的用法
被動語態 be + 過去分詞 — 強調發生了什麼，而不是誰做的	is debated · could be manipulated · is trained
現在完成時 have/has + 過去分詞 — 過去發生但與現在仍有關聯的事	has received · has called · has also supported

什麼是跟讀法？

跟讀法 (Shadowing) 是一種有科學依據的語言學習技巧，最初開發用於專業口譯員的培訓，並由多語言者Alexander Arguelles博士普及。這個方法簡單而強大：您在聽英語母語原聲的同時立即大聲重複——就像是一個延遲1-2秒緊跟說話者的影子。與被動聽力或語法練習不同，跟讀法強迫您的大腦和口腔肌肉同時處理並模模擬實的講話模式。研究表明它能顯著提高發音準確性，語調，節奏，連讀，聽力理解和口語流利度——使其成為雅思口語備考和真實英語交流最有效的方法之一。

影子跟讀法: 閱讀完整分步指南 →

跟讀練習: Could AI Become Dangerous? The Real Risks Explained - 通過影片學習英語口語

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