Shadowing Practice: Could AI Become Dangerous? The Real Risks Explained - Learn English Speaking with Video
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147 משפטים
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Artificial intelligence can help doctors find patterns in medical data, help students learn, help small businesses save time,
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translate languages, detect fraud, and accelerate scientific research.
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But some of the same executives building the world's most powerful AI systems are warning
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that the technology could also cause enormous harm if it develops faster than humans can control it.
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Could AI damage the human race?
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The honest answer is, it already can cause harm through scams, deepfakes, cybercrime, misinformation, privacy violations, discrimination, and job disruption.
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The larger and more controversial question is whether future AI systems could become so capable and autonomous that people cannot reliably supervise,
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contain, or shut them down.
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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
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and businesses can do today the most important distinction before we
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talk about extreme scenarios we need to separate two different questions
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the first question is what harm can ai cause right now
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or in the next few years the second question is what could happen
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if ai becomes much more capable more autonomous
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and harder for humans to control the first category includes risks
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that are already visible scams fake voices fake videos cyber attacks inaccurate advice bias in automated decisions
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and misuse of private data the second category is more uncertain
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it includes concerns that advanced ai agents could plan over long periods use tools online write
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and improve code conduct research manipulate people find vulnerabilities copy themselves
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or pursue goals in ways their creators did not intend these two categories should not be confused
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the first is happening today the second is debated uncertain
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and potentially much more serious if it ever occurs risk number one fraud deepfakes
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and impersonation the most immediate danger for many families is fraud ai can create convincing emails text messages fake invoices fake websites,
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cloned voices, and realistic videos.
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A scammer may pretend to be your child, your grandchild, your bank, a government agency, a business partner, or even your accountant.
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For families, the rule should be simple.
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Never send money because of an urgent call, text, email, or video alone.
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Hang up.
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Use a known phone number.
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Confirm through another trusted channel.
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create a family verification phrase
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if necessary for businesses use approval controls do not allow one email one text
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or one voice message to authorize a wire transfer payroll change vendor payment change
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or release of confidential information risk number two misinformation
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and loss of trust ai can produce articles images videos comments and social media posts at enormous scale.
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That can be useful for education and communication.
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But it also means bad actors can create misinformation faster than fact -checkers can respond.
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The danger is not only that people will believe false information.
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Another danger is that people may stop believing real information.
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If every video could be fake, every image could be manipulated, and every voice could be cloned, then trust becomes weaker.
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That is harmful for families, businesses, elections, public health, financial markets, and society as a whole.
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The defense is media literacy.
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Ask, who created this?
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What is the original source?
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Is there independent confirmation?
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Does the claim create fear, urgency, outrage, or a promise of easy money?
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Those are common warning signs.
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Risk number three, cyber attacks.
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AI can help defenders find vulnerabilities and improve security.
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But it can also help criminals and hostile governments attack systems.
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A capable AI can assist with writing phishing emails, analyzing leaked data, generating malicious code,
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finding software vulnerabilities, impersonating employees, and automating reconnaissance against a target.
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For a small business, one employee clicking a convincing fake invoice can lead to ransomware, stolen customer data, or an empty bank account.
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For larger organizations, cyberattacks can disrupt hospitals, utilities, transportation, communications, financial systems, and government services.
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Anthropic's 2026 Threat Intelligence Reporting described disruptive misuse involving cyber operations,
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fraud, influence operations, surveillance, biological misuse, conventional weapons development, and other harmful activity.
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That does not mean AI independently carried out all of these harms.
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It means people may use AI tools to become more capable, more efficient, and more difficult to detect.
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The practical response is not complicated, but it requires discipline, multi -factor authentication, staff training, software updates, access controls,
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backups, and verification procedures for money transfers and sensitive requests.
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Risk number four, biological, chemical, and weapons misuse.
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Another serious concern is whether powerful AI systems could lower the barriers for someone trying to create biological, chemical, or other dangerous weapons.
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Most people do not have the specialized knowledge laboratory access materials or equipment required to cause large -scale harm
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but advanced ai could potentially make it easier to search scientific information troubleshoot procedures identify weaknesses
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or guide a person through complex technical questions
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this does not mean that an ai chatbot automatically enables a biological weapon
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real -world harmful activity requires many steps and substantial capability
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but ai safety researchers worry that as models become better at science coding planning
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and tool use they could make certain dangerous knowledge more accessible
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that is why leading ai labs test frontier models for high risk capabilities
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and discuss safeguards for biological and chemical misuse another concern is autonomous weapons ai can be used for surveillance target recognition drones,
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and military planning.
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The ethical issue is whether machines should ever make life and death decisions without meaningful human control.
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Risk number five, privacy, bias, and surveillance.
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AI systems depend on data.
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That raises major questions about privacy, consent, and power.
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Companies or governments can combine cameras, facial recognition, location data, online activity,
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financial records, and other information to monitor people at extraordinary scale.
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AI can also make biased decisions if it is trained on biased historical data or used without careful review.
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It may affect hiring, lending, insurance, housing, education, policing, and healthcare.
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The right principle is simple.
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AI should support human judgment, not eliminate accountability.
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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.
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Risk number six, job disruption and economic inequality.
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AI will change work.
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It may automate routine tasks in customer service, bookkeeping, data entry, basic coding, document review, marketing, scheduling, and many office functions.
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That can increase productivity.
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But productivity gains are not automatically shared fairly.
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Workers may lose jobs, see wages pressured, or be required to do more work with fewer people.
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Entry -level roles may shrink, making it harder for young professionals to gain experience.
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Wealth and power may concentrate in companies that own advanced AI models, valuable data, and expensive computing infrastructure.
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The best response is not to tell everyone to panic.
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It is to prepare.
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students and workers should build skills that combine domain knowledge with ai literacy
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communication critical thinking client trust leadership technical competence data skills ethics
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and hands -on problem solving the goal is not to compete against ai and routine work
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it is to learn how to use ai responsibly while bringing skills
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that machines do not easily replace the biggest fear loss of control now we come to the concern
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that has received the most attention from some ai executives
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and researchers loss of control today's ai systems can be impressive
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but they are not known to be independently taking over the internet building secret organizations
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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
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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.
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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.
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OpenAI CEO Sam Altman has also supported stronger AI safety coordination
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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.
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Elon Musk has long argued that advanced AI could become a major existential risk if development outpaces human governance and control.
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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.
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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.
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In the comments, tell me, what AI risk concerns you the most?
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Scams, job loss, misinformation, cyber attacks, privacy, or loss of control?
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אוצר מילים והערות הגייה לשיעור הזה
שיעור הדיבור הזה ברמה B2 מבוסס על הסרטון “Could AI Become Dangerous? The Real Risks Explained”. המילים שחוזרות הכי הרבה: risk, harm, decisions, misuse, concern. בסרטון הזה יש 147 משפטים ו-1847 מילים לתרגול Shadowing. הדיבור נמשך 13:05. הדובר שומר על קצב יציב של כ-141 מילים בדקה, קצב נוח לתרגול Shadowing. רק 76% מהמילים נמצאות בין 3,000 המילים הנפוצות ביותר באנגלית, כך שאוצר המילים מאתגר.
אוצר מילים מרכזי בסרטון הזה
15 המילים המתקדמות ביותר בסרטון, עם ההגייה והמשמעות שלהן:
| מילה | הגייה | משמעות |
|---|---|---|
| bias שם עצם | /ˈbaɪ.əs/ | נטייה, הטיה |
| misinformation שם עצם | /ˌmɪs.ɪn.fɚˈmeɪ.ʃən/ | מידע שגוי |
| autonomous שם תואר | /ɔˈtɑnəməs/ | אוֹטוֹנוֹמִי |
| scam שם עצם | /ˈskæm/ | תרגיל עוקץ, הונאה |
| surveillance שם עצם | /sɚˈveɪ.ləns/ | מעקב סמוי |
| confidential שם תואר | /ˌkɔn.fɪˈdɛn.ʃəl/ | חסוי |
| urgent שם תואר | /ˈɜː.d͡ʒənt/ | דחוף |
| safeguard פועל | /ˈseɪfɡɑːd/ | לְאַבְטֵחַ |
| verification שם עצם | /ˌvɛ.ɹə.fɪˈkeɪ.ʃən/ | וידוא |
| literacy שם עצם | /ˈlɪtəɹəsi/ | אוֹרְיָנוּת |
| detect פועל | /dɪˈtɛkt/ | גילה, זיהה |
| combine פועל | /kəmˈbaɪn/ | ערבב, שילב |
| stake שם עצם | /steɪk/ | יָתֵד |
| disagreement שם עצם | /dɪsəˈɡɹiːmənt/ | מחלוקת, מַחְלֹקֶת |
| accelerate פועל | /ɪkˈsɛl.əˌɹeɪt/ | האיץ |
דקדוק בסרטון הזה
המבנים שהדובר משתמש בהם הכי הרבה, עם המילים המדויקות מהסרטון:
| מבנה | בסרטון |
|---|---|
| סביל (Passive voice) be + past participle — הדגש הוא על מה שקורה, לא על מי שעושה את הפעולה | is debated · could be manipulated · is trained |
| הווה מושלם (Present perfect) have/has + past participle — פעולה שקרתה בעבר ועדיין יש לה חשיבות או השפעה עכשיו | has received · has called · has also supported |
הגייה ששווה לשים לב אליה
- הצלילים של “th”: authentication /ɔːˌθɛntɪˈkeɪʃn̩/, ethical /ˈɛθɪkəl/, ethics /ˈɛθ.ɪks/
- הצלילים של “sh” ו-“zh”: misinformation /ˌmɪs.ɪn.fɚˈmeɪ.ʃən/, disruption /dɪsˈɹʌpʃən/, confidential /ˌkɔn.fɪˈdɛn.ʃəl/, authentication /ɔːˌθɛntɪˈkeɪʃn̩/, verification /ˌvɛ.ɹə.fɪˈkeɪ.ʃən/
- מילים ארוכות — שימו לב להטעמה: misinformation /ˌmɪs.ɪn.fɚˈmeɪ.ʃən/, autonomous /ɔˈtɑnəməs/, vulnerability /ˌvʌln(ə)ɹəˈbɪlɪti/, confidential /ˌkɔn.fɪˈdɛn.ʃəl/, capability /ˌkeɪ.pəˈbɪl.ɪ.ti/
צלילים שדוברי עברית מתקשים בהם:
- /w/ — שפתיים מעוגלות, לא /v/: weaker /ˈwikɚ/, inequality /ˌɪn.ɪˈkwɑ.lɪ.ti/, weakness /ˈwik.nɪs/
- /æ/ — פתוח יותר מה-“אֶ” העברית, לא כמו “a” ב-“cup”: scam /ˈskæm/, cyberattack /ˈsaɪ.bə.ɹəˌtæk/, inaccurate /ɪnˈæk.jə.ɹɪt/, analyze /ˈæn.əˌlaɪz/, translate /tɹænzˈleɪt/
- /r/ — הלשון לא נוגעת בשום מקום, לא ה-“ר” הגרונית: cyber /ˈsaɪ.bəɹ/, vulnerability /ˌvʌln(ə)ɹəˈbɪlɪti/, disruption /dɪsˈɹʌpʃən/, harmful /ˈhɑɹmfl̩/, cyberattack /ˈsaɪ.bə.ɹəˌtæk/
איך לתרגל עם הסרטון הזה
- הקשיבו לכל הסרטון פעם אחת בלי לדבר, ורשמו את המילים שאתם לא מכירים.
- תרגלו Shadowing משפט אחר משפט במהירות רגילה, וחזרו על כל משפט עד שהקצב שלכם תואם את הדובר.
- הקליטו את עצמכם והשוו למקור, תוך תשומת לב למילים כמו bias, misinformation, autonomous.
מהי טכניקת השאדואינג?
שאדואינג היא טכניקת למידת שפה מבוססת מדע שפותחה במקור להכשרת מתורגמנים מקצועיים ופופולרית על ידי הפוליגלוט ד"ר אלכסנדר ארגואלס. השיטה פשוטה אך עוצמתית: אתה מקשיב לאודיו באנגלית ילידית וחוזר עליו בקול רם מיד — כמו צל העוקב אחרי הדובר עם עיכוב של 1–2 שניות בלבד. בניגוד להאזנה פסיבית או תרגילי דקדוק, שאדואינג מכריח את המוח והשרירים בפה לעבד ולשחזר דפוסי דיבור אמיתיים בו זמנית. מחקרים מראים שזה משפר משמעותית את דיוק ההגייה, האינטונציה, הקצב, הדיבור המחובר, הבנת השמיעה ושטף הדיבור — מה שהופך אותו לאחת השיטות היעילות ביותר להכנה לIELTS Speaking ולתקשורת באנגלית בעולם האמיתי.