शैडोइंग अभ्यास: What is Responsible AI? A Guide to AI Governance - वीडियो के साथ अंग्रेजी बोलना सीखें

अभ्यास मोड चुनें

हर मोड पूरी स्क्रीन का अभ्यास कक्ष खोलता है।

58 वाक्य
यदि वाक्य बहुत छोटे या लंबे हों, तो समायोजित करने के लिए Edit पर क्लिक करें।
1
The work of having human values be reflected in AI is not strictly a technical challenge with a technical solution,
2
but one that is indeed socio -technical.
3
And with any socio -technical challenge, it has to be approached holistically, meaning you need to be thinking about people, process, tools.
4
People meaning what is the right organizational culture that is required to curate AI responsibly, which are the right AI governance processes,
5
and the right tools in AI engineering frameworks.
6
When I take the time to ask large audiences at AI
7
summits who in their organization is accountable for responsible outcomes from artificial intelligence,
8
the top three answers that I get are pretty bad.
9
The first answer I typically get is no one, which is overtly terrible.
10
The second common response that I get is we don't use AI.
11
Although you might not be keeping track of it in a formal inventory program,
12
absolutely you have employees that are using artificial intelligence in some way, shape, or form.
13
And then the last common response that I get is everyone.
14
And I would opine that if everyone is being held accountable for responsible outcomes from AI, is anyone actually being held accountable?
15
The job of those who are being held accountable for responsible outcomes from artificial intelligence is expanding.
16
It's a big job, right?
17
Not only do these people have to actually achieve value alignment within their organizations, they also have to keep track of AI model inventory.
18
They have to keep track of regulations, right?
19
And there are a growing amount of regulations around the world.
20
But there's also recognition that you can have AI models be lawful but awful,
21
which means their purview, their responsibility actually has to push into ethics.
22
And as soon as you push into ethics, you have to be a pretty darn good teacher.
23
You have to be teaching those not only who are building AI models on your behalf
24
and governing AI models on your behalf, but also who are going to be procuring AI models on your behalf.
25
You want them to be able to do this work, and again, in a way that reflects your organization's values.
26
First, I want to talk about what does AI literacy look
27
like for those who are going to be governing AI models on your behalf.
28
And the best way, my favorite way of approaching this kind of training is applied training.
29
So the way that we work with those who are going to be governing AI models is,
30
first of all, to dive into teaching people how do you operationalize principles like fairness, like explainability, like transparency,
31
thinking through how do you make sure
32
you can detail what are those functional requirements for what you expect to see in AI models,
33
but also the non -functional requirements of what you expect to see in those systems around the use of those AI models.
34
Then the second group
35
that you would offer this applied training to are those who will be building and buying models on your behalf.
36
And this applied training includes things like making sure that you're choosing AI model use cases to actually work on,
37
which ones are really important to your organization.
38
And then diving into each of those use cases,
39
starting with, how do you make sure that the investment in that AI model is actually aligned to your business strategy?
40
Teaching those teams working on those use cases, how do you assess for the risk of that particular use case, unintended effects of that use case?
41
How would you approach mitigating those kinds of risks holistically.
42
Then we give an introduction to fact sheets.
43
In particular, not just how do you build a fact sheet, but how do you build one that's actually interpretable, that empowers people?
44
We give an introduction to audits, and then we teach those teams how do you actually interpret the results from an audit
45
so that they would know what to do when they see those audit results.
46
Those doing this kind of applied training that I'm describing truly, truly benefit from actually working with a diverse and multidisciplinary team.
47
Now, more than ever, having a leader or team that ensures the responsible use and responsible outcomes from artificial intelligence is absolutely crucial.
48
Without a dedicated leader with a funded mandate to do this work, AI governance can absolutely fall through the cracks,
49
leaving organizations vulnerable to the risks associated with the technology.
50
A successful, responsible AI leader has a seat at the table and ensures that there are seats at the table for others.
51
including the CISO, ensuring the AI ethics is weaved into the very fabric of the organization, not just left off at the end,
52
but incorporated across the entire AI life cycle.
53
They make accountability policies transparent and work across the organization to see them implemented.
54
Finally, championing AI literacy in a holistic way is absolutely essential,
55
ensuring that everyone within the organization understands how to build and buy AI models that actually reflects the organization's values.
56
By investing in a responsible AI leader with that funded mandate to do the work, organizations unlock the full potential of artificial intelligence.
57
They drive innovation and they create a culture of responsible and transparent AI use, ultimately leading to better decision making,
58
improved customer experiences and sustained business success.

ऐप डाउनलोड करें

धाराप्रवाह बोलने के लिए ज़रूरी सब कुछ

AI उच्चारण स्कोरहर वाक्य का स्कोर
IPA अभ्यासहर ध्वनि में महारत
शब्दावलीअपना शब्द भंडार बनाएँ
शब्द गेमखेलते हुए सीखें
QR स्कैन करें
QR स्कैन करें
Download on theApp StoreGet it onGoogle Play

उसी चैनल से

Every Generation Thinks This Time Is Different: The AI Job MythB2
1

Every Generation Thinks This Time Is Different: The AI Job Myth

Daily ConversationWorking Adults
What is Event Driven Architecture (EDA)?C1
2

What is Event Driven Architecture (EDA)?

Daily ConversationUniversity StudentsWorking Adults
Agentic AI Frameworks Explained: Workflows, Multi-Agent, & ProductionC1
1

Agentic AI Frameworks Explained: Workflows, Multi-Agent, & Production

Daily ConversationUniversity StudentsWorking Adults
Spec-Driven Development: AI Assisted Coding ExplainedC1
1

Spec-Driven Development: AI Assisted Coding Explained

Daily ConversationUniversity StudentsWorking Adults
AI Agents vs Business Rules: Which Should Make Decisions?C1
5

AI Agents vs Business Rules: Which Should Make Decisions?

Daily ConversationUniversity StudentsWorking Adults
AI & Education: Generative AI & the Future of Critical ThinkingC1
3

AI & Education: Generative AI & the Future of Critical Thinking

Business EnglishUniversity StudentsWorking Adults
EDR vs. EPP vs. NGAVC1
2

EDR vs. EPP vs. NGAV

Business EnglishWorking Adults
MCP vs ADK: How Modern AI Agents Connect and Work TogetherC1
3

MCP vs ADK: How Modern AI Agents Connect and Work Together

University StudentsWorking Adults
Cybersecurity Architecture: Data SecurityC1
1

Cybersecurity Architecture: Data Security

Business EnglishUniversity StudentsWorking Adults
The 7 Skills You Need to Build AI AgentsC1
13

The 7 Skills You Need to Build AI Agents

Business EnglishUniversity StudentsWorking Adults
What Is Jev? The AI Model That Doesn't Generate TextC1
4

What Is Jev? The AI Model That Doesn't Generate Text

Daily ConversationUniversity StudentsWorking Adults
How Smart Organizations Will Use AI: Jevons Paradox & Workforce ImpactC1
18

How Smart Organizations Will Use AI: Jevons Paradox & Workforce Impact

Business EnglishUniversity StudentsWorking Adults
What are AI Agents?C1
11

What are AI Agents?

Business EnglishUniversity StudentsWorking Adults
Cybersecurity Architecture: Five Principles to Follow (and One to Avoid)C1
6

Cybersecurity Architecture: Five Principles to Follow (and One to Avoid)

Business EnglishUniversity StudentsWorking Adults
AI, Machine Learning, Deep Learning and Generative AI ExplainedC1
9

AI, Machine Learning, Deep Learning and Generative AI Explained

Daily ConversationUniversity StudentsWorking Adults
Zero Trust Explained in 4 minsC1
1

Zero Trust Explained in 4 mins

Business EnglishUniversity StudentsWorking Adults
What is AI Ethics?C1

What is AI Ethics?

Daily ConversationUniversity StudentsWorking Adults
FOR YOU

अनुशंसित वीडियो

AI Governance Explained: Ethical, Transparent & Accountable AI for the FutureC1
2
105 वाक्य

AI Governance Explained: Ethical, Transparent & Accountable AI for the Future

Daily ConversationUniversity StudentsWorking Adults
Deputies seek clarity on AI and IP rights | Vietnam TodayC1
3
31 वाक्य

Deputies seek clarity on AI and IP rights | Vietnam Today

Daily ConversationUniversity StudentsWorking Adults
Harvard AI Professor: The People Most at Risk From AI Aren’t Who You ThinkC1
1
828 वाक्य

Harvard AI Professor: The People Most at Risk From AI Aren’t Who You Think

Daily ConversationUniversity StudentsWorking Adults
Harnessing generative AI in architecture, engineering & constructionC1
1
114 वाक्य

Harnessing generative AI in architecture, engineering & construction

Daily ConversationUniversity StudentsWorking Adults
DPM Gan Kim Yong's Speech at the "Trust and AI: Navigating a World in Transition" Leaders DialogueC1
4
106 वाक्य

DPM Gan Kim Yong's Speech at the "Trust and AI: Navigating a World in Transition" Leaders Dialogue

Daily ConversationUniversity StudentsWorking Adults
Inside the secret race to build artificial intelligence | The Gray AreaC1
1
510 वाक्य

Inside the secret race to build artificial intelligence | The Gray Area

Daily ConversationUniversity StudentsWorking Adults
What AI Can Never Replace w/ Megan Kobzej | Cloud English Podcast Episode 91C1
1
526 वाक्य

What AI Can Never Replace w/ Megan Kobzej | Cloud English Podcast Episode 91

Daily ConversationUniversity StudentsWorking Adults
When AIs act emotionalC1
8
55 वाक्य

When AIs act emotional

Daily ConversationUniversity StudentsWorking Adults
How AI Empowers Tech Leaders Siwei ShenC1
7 वाक्य

How AI Empowers Tech Leaders Siwei Shen

Daily ConversationUniversity StudentsWorking Adults
Leading AI CEOs Warn UN Security Council of Existential Risks | Sam Altman On AI Controls | N18GC1
1
83 वाक्य

Leading AI CEOs Warn UN Security Council of Existential Risks | Sam Altman On AI Controls | N18G

Business EnglishDaily ConversationUniversity Students

इस पाठ की शब्दावली और बोलने के सुझाव

यह स्पीकिंग पाठ वीडियो “What is Responsible AI? A Guide to AI Governance” पर आधारित है। सबसे ज़्यादा दोहराए गए शब्द ये हैं: model, responsible, organization, artificial, behalf। इस वीडियो में शैडोइंग के लिए 32 वाक्य और 900 शब्द हैं। बोला गया हिस्सा 5:53 लंबा है। वक्ता लगभग 153 शब्द प्रति मिनट की स्वाभाविक गति से बोलता है, जो रोज़मर्रा की बातचीत के करीब है। 82% शब्द अंग्रेज़ी के 3,000 सबसे आम शब्दों में से हैं; बाकी शब्द अभ्यास से पहले देख लेना अच्छा रहेगा। इसके 32 वाक्यों में से 7 प्रश्न हैं, इसलिए यह प्रश्नों के लहजे और छोटे जवाबों के अभ्यास के लिए अच्छा है।

इस वीडियो की मुख्य शब्दावली

वीडियो के 15 सीखने लायक शब्द, उच्चारण और अर्थ के साथ:

शब्दउच्चारणअर्थ
artificial विशेषण/ˌɑː.tɪˈfɪʃ.əl/कृत्रिम
accountable विशेषण/əˈkaʊntəbl̩/उत्तरदायी
reflect क्रिया/ɹɪˈflɛkt/प्रतिबिंबित करना
govern क्रिया/ˈɡʌv.ən/हुकूमत करना, शासन करना
sheet संज्ञा/ʃit/पत्र, चद्दर
regulation संज्ञा/ˌɹɛɡjʊˈleɪʃən/विनियम
requirement संज्ञा/ɹɪˈkwaɪɹmənt/आवश्यकता, अनिवार्यता
dive क्रिया/daɪv/डुबकी
transparent विशेषण/tɹænsˈpæɹənt/पारदर्शक, पारदर्शी
mandate संज्ञा/ˈmændeɪ̯t/अधिदेश, शासनादेश
literacy संज्ञा/ˈlɪtəɹəsi/साक्षरता
formal विशेषण/ˈfɔɹməl/औपचारिक
principle संज्ञा/ˈpɹɪn.sɪ.pəl/जड़सूत्र, असूल
innovation संज्ञा/ˌɪn.əˈveɪ.ʃən/नवाचार
summit संज्ञा/ˈsʌmɪt/चोटी, शिखर

इस वीडियो का व्याकरण

वक्ता जिन संरचनाओं का सबसे अधिक प्रयोग करता है, वीडियो के असली शब्दों के साथ:

संरचनावीडियो में
Passive voice be + past participle — ज़ोर इस पर कि क्या होता है, न कि कौन करता हैbe reflected · be approached · is required
Relative clauses who / which + उपवाक्य — व्यक्ति या वस्तु के बारे में अतिरिक्त जानकारीone that is · one, which is · those who are

ध्यान देने योग्य उच्चारण

वक्ता 3 बार संक्षिप्त रूपों का प्रयोग करता है, जैसे don't, I'm, you're। इन्हें वैसे ही छोटा बोलें जैसा आप सुनते हैं।

  • “sh” और “zh” की ध्वनियाँ: artificial /ˌɑː.tɪˈfɪʃ.əl/, sheet /ʃit/, regulation /ˌɹɛɡjʊˈleɪʃən/, recognition /ˌɹɛkəɡˈnɪʃ(ə)n/, associate /əˈsoʊʃi.ət/
  • लंबे शब्द — बलाघात सही रखें: artificial /ˌɑː.tɪˈfɪʃ.əl/, regulation /ˌɹɛɡjʊˈleɪʃən/, literacy /ˈlɪtəɹəsi/, recognition /ˌɹɛkəɡˈnɪʃ(ə)n/, associate /əˈsoʊʃi.ət/

हिंदी भाषियों के लिए मुश्किल ध्वनियाँ:

  • /v/ और /w/ का फ़र्क़ — /v/ में ऊपर के दाँत निचले होंठ को छूते हैं, /w/ में होंठ गोल होते हैं: govern /ˈɡʌv.ən/, requirement /ɹɪˈkwaɪɹmənt/, inventory /ˈɪn.vən.tɹi/, dive /daɪv/, governance /ˈɡʌvəɹnəns/
  • /z/ — इसे “ज” (/dʒ/) न बनाएँ: organizational /ˌɔː(ɹ)ɡənɪˈzeɪʃənəl/, operationalize /ˌɑpəˈɹeɪʃənəˌlaɪz/
  • /æ/ — “ऐ” से ज़्यादा खुला: behalf /bɪˈhæf/, transparent /tɹænsˈpæɹənt/, mandate /ˈmændeɪ̯t/, crack /kɹæk/, expand /ɪkˈspænd/

इस वीडियो से अभ्यास कैसे करें

  1. पहले बिना बोले पूरा वीडियो एक बार सुनें और जो शब्द नहीं आते उन्हें लिख लें।
  2. 0.75× गति से शुरू करें, एक-एक वाक्य की शैडोइंग करें, और सहज लगने पर सामान्य गति पर लौटें।
  3. अपनी आवाज़ रिकॉर्ड करें और मूल से तुलना करें, ख़ासकर artificial, accountable, reflect जैसे शब्दों पर ध्यान दें।

शैडोइंग तकनीक क्या है?

शैडोइंग (Shadowing) एक विज्ञान-समर्थित भाषा सीखने की तकनीक है जो मूल रूप से पेशेवर दुभाषिया प्रशिक्षण के लिए विकसित की गई थी। विधि सरल लेकिन शक्तिशाली है: आप मूल अंग्रेज़ी ऑडियो सुनते हैं और तुरंत इसे ज़ोर से दोहराते हैं — जैसे वक्ता की छाया 1-2 सेकंड की देरी से। शोध से पता चलता है कि यह उच्चारण सटीकता, स्वर, लय, जुड़ी हुई ध्वनियाँ, सुनने की समझ और बोलने की प्रवाहशीलता में काफ़ी सुधार करता है।

शैडोइंग तकनीक: पूरी चरण-दर-चरण गाइड पढ़ें →