Shadowing Practice: Don’t Start with AI, Start with the Problem - Learn English Speaking with Video
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44 משפטים
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-To build good AI products, we should start with three major steps, identifying problems that users experience, identifying how we might go about solving those problems, then identifying the technology that can help.
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The challenge is that these days, we so often start with selecting the technology and find a problem for it to solve later.
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With AI, this bad reverse order is even worse.
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More often than not, with AI, people are pressured to use AI for something, anything.
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In UX, we call this problem solutioneering.
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It's so common that we included it as our UX slogan number 18.
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Instead, we should be collecting issues that do exist, problems that users do experience.
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A good AI strategy begins with identifying unmet user needs, business challenges, or market opportunities, and then considering where AI might be a viable solution along with other alternatives.
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Let's talk about an example.
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Imagine a team at a FinTech company.
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The wrong way, the solutioneering way, starts with some sort of pressure from above.
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"We need to use AI to look innovative." The team decides to add a generic AI chatbot to their main credit card page.
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After months of work, they launch the chatbot, but users don't use it.
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Why? Because maybe the page already has a clear comparison table and customers can find what they need faster without talking to a bot.
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In this situation, the AI chatbot is a classic solution that solves no real user problem.
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A solution looking for a problem.
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Let's flip that.
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Let's take a look at an example of how we should approach building useful AI products.
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Step one, identify the user problem.
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Let's imagine that the team analyzes user data and sees that plenty of people abandon their online mortgage application halfway through.
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Through a few customer interviews, they quickly learn why.
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Customers are confused by financial jargon like APR or interest rate and feel anxious they're making the wrong choice.
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That's the problem.
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Step two, identify how to solve it.
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The goal is to reduce confusion and anxiety.
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They could create a glossary page, make explainer videos, or offer a live chat with a loan officer.
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Step three, identify the technology.
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This is where AI could actually help.
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A well-trained AI assistant could offer instant, in-context explanations for confusing terms 24-7.
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Success can be defined and would be easy to measure.
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A decrease in the number of abandoned mortgage applications.
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See the difference?
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We didn't start with AI.
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We started with a real user problem and found that AI was a fitting tool that might solve it.
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AI is just a tool that can solve problems.
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It shouldn't be assumed to be part of the solution unless you've started with the problems first and understood them clearly.
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Not only should we have identified legitimate problems, but ideally, we've had a discussion on how we'd recognize success by doing it.
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As much as we want to start with AI, we want to create good experiences.
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Start by identifying problems.
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Then, just maybe, AI could help solve those problems.
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-Thanks for watching.
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If you want to see more of our UX videos, take a look at these over here and consider subscribing to our channel.
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On our website nngroup.com, you can access our free library of over 2,000 articles.
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You can also register for one of our UX courses that offer live hands-on UX training.
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About This Lesson
In this lesson, you will focus on honing your English speaking and pronunciation skills while analyzing a video discussing the effective use of Artificial Intelligence (AI) in problem-solving. By engaging with the content, you will practice identifying key issues and exploring effective solutions in the context of technology, which enhances your comprehension and critical thinking. The aim is not only to improve your vocabulary but also to foster a deeper understanding of how to articulate ideas clearly, an essential skill in both casual and professional settings.
Key Vocabulary & Phrases
- Identify - To recognize or establish something.
- Solutioneering - A term used to describe the act of forcing a solution onto a situation.
- User Experience (UX) - The overall experience a person has when interacting with a system or product.
- Unmet needs - Needs that are not currently being satisfied.
- Confusing jargon - Technical language that is difficult for users to understand.
- AI Assistant - A program powered by artificial intelligence that helps users with various tasks.
- In-context explanations - Clear, relevant information provided within the specific scenario the user is facing.
Practice Tips
To effectively use this video for shadowing and improving your English pronunciation, follow these steps:
- Choose a shadowing app that allows you to play the video at different speeds. Start at a comfortable pace and gradually increase the speed to match the video's natural flow.
- As you listen, focus on the intonation and rhythm of the speaker's voice. Emulate their tone and stress patterns to enhance your shadow speech.
- Rewind segments that are challenging to pronounce. Practice those sections repetitively to build muscle memory.
- Record yourself while shadowing and compare your pronunciation with the original. This will help you identify areas for improvement.
- Engage with the content by discussing key vocabulary and phrases with a language partner or tutor. This active use of new words will help cement them in your memory.
By taking these targeted actions, you will not only improve your English pronunciation but also gain confidence in discussing complex topics like AI and UX, paving the way for clearer communication in both personal and professional contexts.
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 | are pressured · can be defined · be assumed |
| הווה מושלם (Present perfect) have/has + past participle — פעולה שקרתה בעבר ועדיין יש לה חשיבות או השפעה עכשיו | you've started · have identified |
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.