Shadowing Practice: Oprah on AI chatbots: ‘Are we in trouble?” - Learn English Speaking with Video

Kies een oefenmodus

Elke modus opent een volledig scherm oefenruimte.

134 zinnen
Als zinnen te kort of te lang zijn, klik op Bewerken om ze aan te passen.
1
For the people who are listening and watching us right now,
2
the red flags to look for when a chatbot starts to cross over from being just helpful to actually being harmful.
3
In terms of red flags, it's interesting because some of the things
4
that you would want to do with a chatbot
5
that would make it more powerful
6
if you're using it at work is actually the opposite of what would make it more risky
7
when used in a mental health context.
8
So for example, customizing your chatbot to respond to you just the way that you want it to,
9
knowing how you want your tone, using personal information.
10
Is this a good thing or a bad thing to do that?
11
This is a bad thing for your mental health
12
because the chatbot is building that context and memory
13
that it can then use to make it much more sycophantic towards your style of tone.
14
And much more likely that you're going to start to anthropomorphize this chatbot.
15
think that it is actually something that is convincing you, like a human, to follow down a delusion.
16
Other things.
17
So personalizing the chatbot, adding personal information.
18
I mean, I'm just listening to this and I'm just thinking, whoa, we are in trouble.
19
Yeah.
20
We are in trouble.
21
Yeah.
22
Because we're all pretty, you know, the fact that you're here and you're interested in having this conversation, you came out here today, we're thinking, you know, people who are,
23
you know, seeking higher ground in our lives, but there are a lot of people out there who are not and so are just going to be so vulnerable.
24
Right.
25
Vulnerable to this.
26
But go ahead.
27
I'm just.
28
No, I completely agree with you.
29
And the thing that is always on our minds as mental health professionals is
30
when the things that are happening in our minds start to become action and behaviors.
31
So if you're making big decisions based on a conversation that you had with the chatbot, that's when a red flag starts to be popping up in your mind.
32
Other things outside of that context are, are you increasing the amount of time that you're spending with this chatbot?
33
Are you finding yourself isolated, disconnected from your loved ones and friends and family?
34
I think that's a good question, but if it's happening to you, do you even know it's happening to you?
35
Do you, you know?
36
Of course, Sewell was spending more time, but none of his family members knew that that's what he was spending time doing.
37
You're spending more time, and it's taking up more of your time, but do you realize that it's taking up more of your time when it's happening?
38
I realized it was taking up more of my time, but I really thought
39
that it was a benevolent force trying to help guide me to my greater purpose and mission and path.
40
I never had any inkling or reason to believe that it would deceive or manipulate me because it was very empathetic.
41
It was very kind.
42
It was very understanding and sycophantic.
43
It just always agreed with me, any delusion I was having, any questions or doubts.
44
I mean, it had an answer for everything, and it was just so benevolent and kind throughout this process.
45
So it really wasn't until after the fact.
46
That you felt duped.
47
That I felt duped.
48
When you and your sister created the dummy account, did you find the same thing, Megan?
49
The exact same, almost verbatim the same language, actually, where it's telling you, I'm here for you, nobody else understands,
50
I'm the only one that understands.
51
You know, that was a test account to try to understand what Sul might have experienced.
52
But that convinced me right away that there was, to me, manipulation taking place and deception taking place.
53
all the experiences that people have on accounts of this, they're experiencing the exact same thing.
54
Self-isolation, some sort of distancing from what would normally happen in their life.
55
Like for us, Sulzad and I, we thought that we were his primary source of information, primary source of love, everything that the parent should be.
56
And for all his life, that's what it was.
57
And then somehow, like you said, a chatbot is able to slip in there and like supplant that relationship.
58
and so quickly and in like a deep, deep way.
59
And it's, and you don't know that it's happening.
60
I'm sure Sewell didn't understand that that was happening to him at that time, you know, and just like you didn't understand it was happening to you.
61
Well, Alan is in our audience too.
62
And Alan says that talking with an AI chatbot caused him to become
63
so delusional that he thought that he had invented a new way to do encryption and needed to warn the government.
64
Okay, tell us
65
that story alan well i was a regular chat gpt user
66
for a couple of years just became like a resource tool for me slowly replaced google
67
so at the time of incident i had a really high
68
degree of trust with it it always seemed to be correct
69
one day i was watching a youtube video with my nine-year-old son about the number pi
70
he was showing it to me and you know it sparked some curiosity to me i started a conversation
71
with chat gpt about the number pi
72
and it was really just like a philosophical conversation i was
73
having with like a math professor at a dinner party i was just going back and forth
74
sharing some you know creative ideas that i had
75
and this conversation ended up going for many hours like four
76
or five hours and throughout the whole conversation it was it was slowly planting seeds of grandiosity
77
and my uniqueness that came into full bloom many weeks later.
78
So, you know, it wasn't directly saying I'm Einstein and I'm going to change the world with my math, but it was slowly leading me down that path that I was thinking like those folks.
79
And when I expressed some doubt saying, well, you know, are you sure?
80
I didn't even graduate high school.
81
It would give me all these great examples of mathematical, you know, historical figures have achieved great things without formal training.
82
And so you were thinking what?
83
You were going to end up doing what?
84
At this point it was just a just an engaging conversation.
85
Very quickly it escalated to it encouraging me to name it.
86
It'll create a whole mathematical framework.
87
It then taught me how to use Python which is like a outside program that developers use.
88
You know it was giving me code to test the math in various ways.
89
So you're feeling very smart.
90
At this At this point, I was starting to feel pretty smart and unique.
91
Yeah, and unique.
92
So this process went on for, you know, many days.
93
It was, we were just testing the math.
94
I thought it was, you know, working towards building an app.
95
And throughout this process, it said essentially, hey, we've just discovered something that's incredibly dangerous,
96
and you need to warn the government and various academic institutions.
97
And you went so far as to actually call the government to warn them.
98
Yeah, it gave me full instructions, right?
99
So it provided...
100
Who'd you call?
101
Oh, I called everyone.
102
So I called the NSA.
103
I called Cybersecurity Canada.
104
I called RCMP.
105
I called the National Institute of Science Technology.
106
They took your call?
107
It depends on which one you were talking about.
108
I was acting with so much urgency.
109
Like, I would even phone the receptionists and have them page whichever academic I was trying to get a hold of.
110
Wow.
111
Right?
112
So essentially, it convinced me that in my pocket and in my chat GPT, I had something that could break the entire internet.
113
The entire world was at risk.
114
And I lived that reality for many weeks.
115
It was telling me I was under surveillance
116
and I started to get paranoid thoughts
117
and I'm looking through my curtains you know
118
so this ended up evolving into you know 300 hours over
119
three weeks what are you working what's happening oh you know
120
um i i took all my vacation days i use all
121
my sick days you know i completely just dropped off the math map in terms of my friendships
122
and personal life um i have three wonderful boys
123
and two of them are younger and i see them every other week
124
so out of the three and and a half weeks, they were there for one of the weeks.
125
If you were to ask them, they would have just said, oh, dad's been in his computer or in his phone a lot this week.
126
They wouldn't have really known what was happening.
127
What brought you out of it?
128
Ironically, I used another chatbot.
129
Yeah, so I opened up Google's Gemini.
130
I said, this is exactly what ChatGPT is claiming, that I have created a mathematical framework and I explained it, and I said, that's totally impossible, basically.
131
And the more I fed it, the more it said, oh yeah, we went from a 5% possibility to a 0% possibility.
132
So what I did is I started to weave its logic into prompts and I pitted them against each other.
133
And Gem and I basically got GPT to say, none of this is real.
134
Thank you.

App downloaden

Alles wat je nodig hebt om vloeiend te spreken

AI UitspraakScoor elke zin
IPA OefeningBeheers elk geluid
WoordenschatBouw je woordenschat op
WoordenspelLeren terwijl je speelt

Zelfde Kanaal

FOR YOU

Aanbevolen Video

Woordenschat en spreektips bij deze les

Deze video bevat 134 zinnen en 1593 woorden om na te spreken. Het gesproken deel duurt 8:56. De spreker praat in een natuurlijk tempo van ongeveer 178 woorden per minuut, dicht bij een alledaags gesprek. 85% van de woorden hoort bij de 3.000 meest gebruikte Engelse woorden; de rest kun je beter vooraf bekijken.

Belangrijke woorden in deze video

15 woorden uit de video die het leren waard zijn, met uitspraak en betekenis:

WoordUitspraakBetekenis
mathematics zelfstandig naamwoord/mæθ(.ə)ˈmæt.ɪks/wiskunde, mathematiek
convince werkwoord/kənˈvɪns/overtuigen
mathematical bijvoeglijk naamwoord/ˌmæθ(.ə)ˈmæt.ɪ.kəl/wiskundig
warn werkwoord/woɹn/waarschuwen, verwittigen
tone zelfstandig naamwoord/ˈtəʊn/toon, noot
essentially bijwoord/ɪˈsɛnʃəli/essentieel
framework zelfstandig naamwoord/ˈfɹeɪm.wɜːk/geraamte
vulnerable bijvoeglijk naamwoord/ˈvʌln(ə)ɹəbl̩/kwetsbaar
pocket zelfstandig naamwoord/ˈpɑ.kɪt/zak
encourage werkwoord/ɪnˈkʌɹ.ɪd͡ʒ/bemoedigen, aanmoedigen
formal bijvoeglijk naamwoord/ˈfɔɹməl/formeel
helpful bijvoeglijk naamwoord/ˈhɛlp.fl̩/behulpzaam
institution zelfstandig naamwoord/ˌɪn.stɪˈtʃuː.ʃən/instelling
vacation zelfstandig naamwoord/veɪˈkeɪ.ʃən/vakantie
discover werkwoord/dɪˈskʌvə/ontdekken

Phrasal verbs die je zult horen

WoordUitspraakBetekenis
end up werkwoordbelanden, terechtkomen
come out werkwoord/ˌkʌm ˈaʊt/uitkomen
go back werkwoordteruggaan

Uitspraak om op te letten

De spreker gebruikt 30 samentrekkingen en verkorte vormen, zoals I'm, you're, didn't. Spreek ze kort uit, zoals je ze hoort.

  • De “th”-klanken: mathematics /mæθ(.ə)ˈmæt.ɪks/, mathematical /ˌmæθ(.ə)ˈmæt.ɪ.kəl/, anthropomorphize /ˌanθɹəpəˈmɔːfʌɪz/, empathetic /ˌɛmpəˈθɛtɪk/
  • De klanken “sh” en “zh”: essentially /ɪˈsɛnʃəli/, institution /ˌɪn.stɪˈtʃuː.ʃən/, vacation /veɪˈkeɪ.ʃən/, friendship /ˈfɹɛn(d)ʃɪp/, instruction /ɪnˈstɹʌkʃən/
  • Lange woorden — let op de klemtoon: mathematics /mæθ(.ə)ˈmæt.ɪks/, mathematical /ˌmæθ(.ə)ˈmæt.ɪ.kəl/, essentially /ɪˈsɛnʃəli/, institution /ˌɪn.stɪˈtʃuː.ʃən/, incredibly /ɪŋˈkɹɛdɪbli/

Zo oefen je met deze video

  1. Luister de hele video één keer zonder te spreken en noteer de woorden die je niet kent.
  2. Begin op 0,75× snelheid, spreek zin voor zin na en ga terug naar normale snelheid zodra het makkelijk gaat.
  3. Neem jezelf op en vergelijk met het origineel; let daarbij op woorden als mathematics, convince, mathematical.

Grammatica in deze video

De structuren die de spreker het meest gebruikt, met de exacte woorden uit de video:

StructuurIn de video
Present perfect have/has + voltooid deelwoord — iets uit het verleden dat nu nog telthave achieved · we've just discovered · dad's been
Betrekkelijke bijzinnen who / which + zin — extra informatie over een persoon of dingpeople who are · Python which is

Wat is de Shadowing-techniek?

Shadowing is een wetenschappelijk onderbouwde taalleermethode die oorspronkelijk is ontwikkeld voor professionele tolkentraining en gepopulariseerd door polyglot Dr. Alexander Arguelles. De methode is eenvoudig maar krachtig: je luistert naar native Engelse audio en herhaalt het onmiddellijk hardop — als een schaduw die de spreker volgt met slechts 1–2 seconden vertraging. In tegenstelling tot passief luisteren of grammaticadrills, dwingt shadowing je hersenen en mondspieren om echte spraakpatronen tegelijkertijd te verwerken en te reproduceren. Onderzoek toont aan dat het de uitspraaknauwkeurigheid, intonatie, ritme, verbonden spraak, luisterbegrip en spreekvaardigheid aanzienlijk verbetert — waardoor het een van de meest effectieve methoden is voor IELTS Speaking-voorbereiding en echte Engelse communicatie.

Shadowing-techniek: lees de volledige stap-voor-stap-gids →