Lost in the Hype: AI Will Never Become Conscious | Sir Roger Penrose (Nobel)

00:08:21
https://www.youtube.com/watch?v=e9484gNpFF8

Sintesi

TLDRThe speaker critiques the concept of artificial intelligence, arguing that it is not truly intelligent as it lacks consciousness and understanding. They reference Godel's theorem to illustrate that there are truths beyond computable rules, which AI cannot comprehend. The speaker emphasizes that while AI can process data and perform complex computations, it does not know what it is doing or why its outputs are valid. They assert that consciousness is necessary for transcending rules and grasping deeper truths, a capability that AI fundamentally lacks, despite its powerful computational abilities.

Punti di forza

  • 🧠 AI lacks consciousness and true understanding.
  • 📜 Godel's theorem highlights non-computable truths.
  • ❓ AI cannot create its own rules or understand them.
  • 🔍 Consciousness is essential for transcending rules.
  • 💻 AI processes data but does not know what it is doing.
  • ⚖️ The Turing test assesses consciousness through conversation.
  • 🔧 AI has a role but is not equivalent to human intelligence.
  • 📊 AI's power lies in computation, not understanding.
  • 🔗 Human intelligence involves understanding why rules are true.
  • 🚫 AI's capabilities do not equate to true intelligence.

Linea temporale

  • 00:00:00 - 00:08:21

    The speaker emphasizes the distinction between artificial intelligence and true intelligence, arguing that AI lacks consciousness. They reflect on their academic background, particularly their exposure to computability and Godel's theorem, which reveals limitations in mathematical proofs. Godel's theorem illustrates that certain truths cannot be proven within a given set of rules, highlighting the necessity of understanding the rules to transcend them. The speaker asserts that AI cannot create its own rules because it lacks the consciousness to understand their truth. They argue that consciousness is essential for transcending rules and understanding why they are true, which AI cannot achieve. The discussion touches on the power of computation and the confusion surrounding AI's capabilities, concluding that while AI has a significant role, it fundamentally does not understand its actions.

Mappa mentale

Video Domande e Risposte

  • What is the main argument against AI being considered intelligent?

    The speaker argues that AI lacks consciousness and true understanding, which are essential for intelligence.

  • What does Godel's theorem illustrate about computability?

    Godel's theorem shows that there are truths that cannot be proven by a set of rules, highlighting limitations in computability.

  • Can AI create its own rules?

    No, AI cannot create its own rules because it does not understand why those rules are true.

  • What is the role of consciousness in understanding rules?

    Consciousness allows individuals to transcend rules and understand why they are true, which AI cannot do.

  • How does the speaker view the power of computation in AI?

    The speaker acknowledges the power of computation in AI but emphasizes that it does not equate to understanding.

  • What is the Turing test?

    The Turing test is a method to determine if an entity is conscious by engaging in conversation.

  • Does the speaker believe AI has a role to play?

    Yes, the speaker believes AI has a role but warns against confusing its capabilities with true understanding.

  • What is the difference between human intelligence and AI according to the speaker?

    Human intelligence involves consciousness and understanding, while AI operates without awareness of its actions.

  • What does the speaker mean by 'non-computable things'?

    Non-computable things are truths in mathematics that cannot be resolved by computational methods.

  • Why is understanding important in the context of AI?

    Understanding is crucial because it allows for the recognition of why rules are true, which AI lacks.

Visualizza altre sintesi video

Ottenete l'accesso immediato ai riassunti gratuiti dei video di YouTube grazie all'intelligenza artificiale!
Sottotitoli
en
Scorrimento automatico:
  • 00:00:00
    Well, you have to be careful. First of
  • 00:00:02
    all, the name is
  • 00:00:04
    wrong. It's not artificial intelligence.
  • 00:00:07
    It's not
  • 00:00:08
    intelligence. Intelligence would involve
  • 00:00:12
    consciousness. And I've always been the
  • 00:00:14
    strong promoter of the
  • 00:00:18
    idea that these devices are not
  • 00:00:21
    conscious and they will not be be
  • 00:00:23
    conscious as unless they bring in some
  • 00:00:24
    other ideas. The computer, they're not
  • 00:00:27
    they're all computable notions. I think
  • 00:00:30
    when people use the word intelligence
  • 00:00:31
    they mean something which is
  • 00:00:34
    conscious. I mean that you see I
  • 00:00:38
    developed my own ideas after going to a
  • 00:00:41
    course. You see when I was a graduate
  • 00:00:43
    student in Cambridge I went to three
  • 00:00:46
    courses which were nothing to do what I
  • 00:00:48
    was supposed to be doing. One was by
  • 00:00:51
    Bondi on general relativity. One must be
  • 00:00:54
    Draq on quantum mechanics. Distinguished
  • 00:00:57
    very distinguished Paul Dra. And the
  • 00:01:01
    third subject was on mathematical logic.
  • 00:01:05
    And I learned about touring machines and
  • 00:01:08
    computer the notion of
  • 00:01:10
    computability and I not knew what
  • 00:01:13
    computability meant. And I learned about
  • 00:01:16
    Girdle's theorem. And Girdle's theorem I
  • 00:01:19
    found stunning because it told you that
  • 00:01:23
    there are things that the
  • 00:01:27
    understanding transcends the use. Let me
  • 00:01:30
    put that more
  • 00:01:31
    clearly. What Gle does, it's very
  • 00:01:34
    clever. What he does is to produce a
  • 00:01:37
    statement. Now suppose you you see
  • 00:01:39
    you're trying to develop your
  • 00:01:40
    mathematical methods of proof. What do
  • 00:01:43
    you mean by proving a theorem in
  • 00:01:45
    mathematics? How do you know it's really
  • 00:01:48
    true? Well, you prove it. What does
  • 00:01:50
    proof mean? Well, you see, does it mean
  • 00:01:52
    okay, you've got a set of rules and if
  • 00:01:54
    you follow these rules, that makes it a
  • 00:01:57
    proof. Now, how do you know these rules
  • 00:02:00
    only give you truths? Well, you've
  • 00:02:02
    looked at them carefully and you say,
  • 00:02:04
    "Oh, maybe AI creates its own rules."
  • 00:02:07
    Ah, no, no. You see, have to be careful
  • 00:02:10
    about this. This is the point. I I
  • 00:02:11
    learned from from ste this was a man
  • 00:02:14
    called ste who was a logician and I
  • 00:02:16
    learned from him this important thing
  • 00:02:19
    about girdle's theorem now girdle's
  • 00:02:22
    theorem is extremely clever you make a
  • 00:02:25
    statement which asserts that it's it
  • 00:02:30
    cannot be proved by these
  • 00:02:32
    rules it's just you the clever thing is
  • 00:02:35
    to make it do it says you give your
  • 00:02:38
    rules which you regard as the rules of
  • 00:02:40
    proof proof and you could put them on a
  • 00:02:42
    computer. So that mean they're
  • 00:02:44
    computational
  • 00:02:45
    rules. Now I knew that there were things
  • 00:02:49
    that you cannot put on a computer. I
  • 00:02:51
    learned from this course that there are
  • 00:02:54
    non-computable things. There are things
  • 00:02:56
    in mathematics which are not computable.
  • 00:03:00
    Now what does computable mean? It means
  • 00:03:02
    that you can make a
  • 00:03:04
    computer. Well, you have to define what
  • 00:03:06
    a computer is. and Turing had one
  • 00:03:09
    definition of a computer. There were
  • 00:03:11
    several other church and curry other
  • 00:03:15
    people had their definitions of comput.
  • 00:03:17
    They all turned out to be equivalent. So
  • 00:03:20
    there is one universal notion of
  • 00:03:23
    computability which is what you mean by
  • 00:03:26
    what can be done by a computer. Maybe
  • 00:03:28
    this is only language problem. It's not
  • 00:03:30
    a language problem. You see you make
  • 00:03:32
    your new language. Sure you can do that.
  • 00:03:34
    You make your new language and that's
  • 00:03:36
    what you can do. So let me describe the
  • 00:03:38
    girdle theorem how it works. You see,
  • 00:03:40
    see the girdle theorem says you
  • 00:03:42
    construct a statement which says you see
  • 00:03:46
    what it means the way you've constructed
  • 00:03:49
    the sentence you can see what it means
  • 00:03:51
    and what it means is I am not provable
  • 00:03:55
    by those
  • 00:03:56
    rules and it does that it really says
  • 00:03:59
    that then you see okay well is it
  • 00:04:02
    perhaps it is provable by the rules if
  • 00:04:05
    it is provable by the rules then it must
  • 00:04:07
    be true well I said it the wrongly
  • 00:04:09
    around doesn't matter the other way.
  • 00:04:11
    Suppose it's false then that means it's
  • 00:04:13
    provable by the rules and if it's
  • 00:04:15
    provable by the rules you've understood
  • 00:04:18
    the rules you said you looked at them
  • 00:04:19
    all and said yes that's okay that's okay
  • 00:04:21
    that sure if you follow those rules it
  • 00:04:23
    is true so that means you believe that
  • 00:04:27
    the rules only give you truths so
  • 00:04:30
    therefore it is true that it's not
  • 00:04:32
    provable by the rules if it's false you
  • 00:04:35
    see then it is provable by the rules and
  • 00:04:37
    therefore it's true so it has to be true
  • 00:04:39
    and not provable Other words, I found
  • 00:04:41
    that amazing. But still, I don't
  • 00:04:43
    understand why AI cannot create its own
  • 00:04:46
    rules
  • 00:04:49
    because it doesn't know that they're
  • 00:04:52
    true. You see, that's the whole point
  • 00:04:54
    about the girdle theorem. The whole
  • 00:04:57
    point as far as I'm concerned about the
  • 00:04:59
    girdle theorem is how do you transcend
  • 00:05:02
    the rules? And that's what you do by
  • 00:05:04
    understanding them. You understand them
  • 00:05:07
    why they're true. It's not that you use
  • 00:05:10
    the rules, but you understand why use of
  • 00:05:13
    the rules only gives you truths. And
  • 00:05:15
    that's how you can prove things which go
  • 00:05:18
    beyond the rules by knowing why they're
  • 00:05:21
    true. Now, knowing why they're true,
  • 00:05:24
    well, what does it mean? Well, it means
  • 00:05:26
    you understand them. What does
  • 00:05:29
    understand mean? You've got to be
  • 00:05:31
    conscious of them. You see, you the
  • 00:05:34
    wording is clear. It means that you have
  • 00:05:37
    to know what you're doing. You have to
  • 00:05:39
    know why they're true. Not that they're
  • 00:05:41
    true. You could be told that they're
  • 00:05:43
    true. You can have you can learn at
  • 00:05:45
    school that they're true. That's not the
  • 00:05:47
    point. You have to know why they're
  • 00:05:48
    true. Why they're true needs
  • 00:05:50
    understanding them. And understanding
  • 00:05:52
    them requires being conscious of them.
  • 00:05:56
    Now, that's require that you see the
  • 00:05:59
    point I was making is
  • 00:06:02
    that consciousness enables you to
  • 00:06:05
    transcend the rules.
  • 00:06:08
    You see why they're true and that goes
  • 00:06:10
    you be beyond it. You see what the
  • 00:06:12
    girdle theorem does. It tells you how
  • 00:06:16
    to use your understanding of why the
  • 00:06:19
    rules are true to transcend the rules.
  • 00:06:22
    You think that AI is the simple tool or
  • 00:06:26
    simple thing that we can use in the
  • 00:06:28
    single case? No, I don't say it's
  • 00:06:30
    single. It's obviously infinite. No,
  • 00:06:32
    clearly that's not the
  • 00:06:34
    point. The point is it doesn't know what
  • 00:06:36
    it's doing.
  • 00:06:38
    That's still true with AI. You talk to
  • 00:06:40
    an AI thing, it doesn't know what it's
  • 00:06:41
    doing. It has it speaks from
  • 00:06:43
    experiences, if you like. You see,
  • 00:06:45
    people have confused the story. The
  • 00:06:48
    story is they've lost it in the power of
  • 00:06:51
    computing. The thing is that computers
  • 00:06:53
    have got so
  • 00:06:55
    powerful that they've lost the thread of
  • 00:06:58
    what they're doing. I think the point
  • 00:07:00
    has got
  • 00:07:01
    lost with current and it'll I think
  • 00:07:04
    Turing wasn't too far off. You see, he
  • 00:07:06
    he was a a little bit confused person in
  • 00:07:08
    a way because he it was not clear what
  • 00:07:11
    he
  • 00:07:13
    believed, but he did call this thing the
  • 00:07:16
    touring test. How do you decide whether
  • 00:07:18
    an entity is conscious or not? Will you
  • 00:07:21
    have a conversation with it? You talk to
  • 00:07:24
    it. Maybe AI is a new sphere of human
  • 00:07:29
    existence. No, it's missing
  • 00:07:33
    something. Yeah, I think. Yeah, that's
  • 00:07:35
    the trouble you see is all I mean
  • 00:07:38
    obviously it has a role to play. I'm not
  • 00:07:39
    going to say that clearly it has a role
  • 00:07:41
    to play. It has a role but you must
  • 00:07:43
    mustn't be confused the fact that it has
  • 00:07:46
    a role to play. It's to do with the
  • 00:07:48
    power of computation. Sure you computers
  • 00:07:50
    have got so powerful now that they can
  • 00:07:53
    do things way beyond what humans do in
  • 00:07:56
    computing. Sure. And you can take a mass
  • 00:07:59
    of data and you can analyze that data
  • 00:08:03
    and you can see what the data says and
  • 00:08:06
    does this thing in in accordance with
  • 00:08:09
    previous things in the data or is it not
  • 00:08:12
    and AI that's all it does. It doesn't
  • 00:08:15
    understand what it's doing.
Tag
  • AI
  • Consciousness
  • Godel's Theorem
  • Computability
  • Intelligence
  • Understanding
  • Turing Test
  • Data Analysis
  • Human vs AI
  • Limitations of AI