What does Turing mean by this statement? Planned maintenance scheduled April 23, 2019 at 00:00UTC (8:00pm US/Eastern) Announcing the arrival of Valued Associate #679: Cesar Manara Unicorn Meta Zoo #1: Why another podcast?What does $A^B$ mean?Turing-unrecognizable language - what TM does?What does sublinear space mean for Turing machines?Does this Turing Machine M decide the language of polynomials?Turing machine - infinite tape - does that thing exist?What does it mean to be Turing reducible?Does the amount of symbols a turing machine has affect what computations it can perform?What does being Turing complete mean?What does “effective enumeration” in Turing machines mean?Is this system Turing complete?
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What does Turing mean by this statement?
Planned maintenance scheduled April 23, 2019 at 00:00UTC (8:00pm US/Eastern)
Announcing the arrival of Valued Associate #679: Cesar Manara
Unicorn Meta Zoo #1: Why another podcast?What does $A^B$ mean?Turing-unrecognizable language - what TM does?What does sublinear space mean for Turing machines?Does this Turing Machine M decide the language of polynomials?Turing machine - infinite tape - does that thing exist?What does it mean to be Turing reducible?Does the amount of symbols a turing machine has affect what computations it can perform?What does being Turing complete mean?What does “effective enumeration” in Turing machines mean?Is this system Turing complete?
$begingroup$
I encountered below statement by Alan M. Turing at here:
"The view that machines cannot give rise to surprises is due, I
believe, to a fallacy to which philosophers and mathematicians are
particularly subject. This is the assumption that as soon as a fact is
presented to a mind all consequences of that fact spring into the mind
simultaneously with it. It is a very useful assumption under many
circumstances, but one too easily forgets that it is false."
I am not a native English speaker. Could anyone explain it in plain English? Thanks!
turing-machines computability computation-models
New contributor
smwikipedia is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
add a comment |
$begingroup$
I encountered below statement by Alan M. Turing at here:
"The view that machines cannot give rise to surprises is due, I
believe, to a fallacy to which philosophers and mathematicians are
particularly subject. This is the assumption that as soon as a fact is
presented to a mind all consequences of that fact spring into the mind
simultaneously with it. It is a very useful assumption under many
circumstances, but one too easily forgets that it is false."
I am not a native English speaker. Could anyone explain it in plain English? Thanks!
turing-machines computability computation-models
New contributor
smwikipedia is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
$begingroup$
perhaps, it's better suited for philosophy portal rather to hard science like CS
$endgroup$
– Bulat
3 hours ago
$begingroup$
@Bulat I was going to say the same -- and redirect to English Language Learners -- but then I realised that there is some CS-related content that can be explained in an answer, which probably wouldn't be picked up on, in other parts of Stack Exchange.
$endgroup$
– David Richerby
3 hours ago
add a comment |
$begingroup$
I encountered below statement by Alan M. Turing at here:
"The view that machines cannot give rise to surprises is due, I
believe, to a fallacy to which philosophers and mathematicians are
particularly subject. This is the assumption that as soon as a fact is
presented to a mind all consequences of that fact spring into the mind
simultaneously with it. It is a very useful assumption under many
circumstances, but one too easily forgets that it is false."
I am not a native English speaker. Could anyone explain it in plain English? Thanks!
turing-machines computability computation-models
New contributor
smwikipedia is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
I encountered below statement by Alan M. Turing at here:
"The view that machines cannot give rise to surprises is due, I
believe, to a fallacy to which philosophers and mathematicians are
particularly subject. This is the assumption that as soon as a fact is
presented to a mind all consequences of that fact spring into the mind
simultaneously with it. It is a very useful assumption under many
circumstances, but one too easily forgets that it is false."
I am not a native English speaker. Could anyone explain it in plain English? Thanks!
turing-machines computability computation-models
turing-machines computability computation-models
New contributor
smwikipedia is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
smwikipedia is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
smwikipedia is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 5 hours ago


smwikipediasmwikipedia
1063
1063
New contributor
smwikipedia is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
smwikipedia is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
smwikipedia is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$begingroup$
perhaps, it's better suited for philosophy portal rather to hard science like CS
$endgroup$
– Bulat
3 hours ago
$begingroup$
@Bulat I was going to say the same -- and redirect to English Language Learners -- but then I realised that there is some CS-related content that can be explained in an answer, which probably wouldn't be picked up on, in other parts of Stack Exchange.
$endgroup$
– David Richerby
3 hours ago
add a comment |
$begingroup$
perhaps, it's better suited for philosophy portal rather to hard science like CS
$endgroup$
– Bulat
3 hours ago
$begingroup$
@Bulat I was going to say the same -- and redirect to English Language Learners -- but then I realised that there is some CS-related content that can be explained in an answer, which probably wouldn't be picked up on, in other parts of Stack Exchange.
$endgroup$
– David Richerby
3 hours ago
$begingroup$
perhaps, it's better suited for philosophy portal rather to hard science like CS
$endgroup$
– Bulat
3 hours ago
$begingroup$
perhaps, it's better suited for philosophy portal rather to hard science like CS
$endgroup$
– Bulat
3 hours ago
$begingroup$
@Bulat I was going to say the same -- and redirect to English Language Learners -- but then I realised that there is some CS-related content that can be explained in an answer, which probably wouldn't be picked up on, in other parts of Stack Exchange.
$endgroup$
– David Richerby
3 hours ago
$begingroup$
@Bulat I was going to say the same -- and redirect to English Language Learners -- but then I realised that there is some CS-related content that can be explained in an answer, which probably wouldn't be picked up on, in other parts of Stack Exchange.
$endgroup$
– David Richerby
3 hours ago
add a comment |
2 Answers
2
active
oldest
votes
$begingroup$
Mathematicians and philosophers often assume that machines (and here, he probably means "computers") cannot surprise us. This is because they assume that once we learn some fact, we immediately understand every consequence of this fact. This is often a useful assumption, but it's easy to forget that it's false.
He's saying that systems with simple, finite descriptions (e.g., Turing machines) can exhibit very complicated behaviour and that this surprises some people. We can easily understand the concept of Turing machines but then we realise that they have complicated consequences, such as the undecidability of the halting problem and so on. The technical term here is that "knowledge is not closed under deduction". That is, we can know some fact $A$, but not know $B$, even though $A$ implies $B$.
Honestly, though, I'm not sure that Turing's argument is very good. Perhaps I have the benefit of writing nearly 70 years after Turing, and my understanding is that the typical mathematician knows much more about mathematical logic than they did in Turing's time. But it seems to me that mathematicians are mostly quite familiar with the idea of simple systems having complex behaviour. For example, every mathematician knows the definition of a group, which consists of just four simple axioms. But nobody – today or then – would think, "Aha. I know the four axioms, therefore I know every fact about groups." Similarly, Peano's axioms give a very short description of the natural numbers but nobody who reads them thinks "Right, I know every theorem about the natural numbers, now. Let's move on to something else."
$endgroup$
1
$begingroup$
Historically, the early 20th century had a strong academic belief in "solving" mathematics. E.g., Hilbert's program, and Whitehead+Russel's Principia Mathematica. Godel's work resolved that quest negatively, but I imagine it took some time for academia to fully embrace this notion; even fully acknowledging the correctness of Godel, people would still remember the grand ideas of Hilbert. I think Turing writing only two decades after Godel would be addressing his audience with this context in mind.
$endgroup$
– BurnsBA
8 mins ago
add a comment |
$begingroup$
Just an example - given chess rules, anyone should immediately figure the best strategy to play chess.
Of course, it doesn't work. Even people aren't equal, and computers may outperform us due to their better abilities to make conclusions from the facts.
$endgroup$
add a comment |
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2 Answers
2
active
oldest
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2 Answers
2
active
oldest
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active
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active
oldest
votes
$begingroup$
Mathematicians and philosophers often assume that machines (and here, he probably means "computers") cannot surprise us. This is because they assume that once we learn some fact, we immediately understand every consequence of this fact. This is often a useful assumption, but it's easy to forget that it's false.
He's saying that systems with simple, finite descriptions (e.g., Turing machines) can exhibit very complicated behaviour and that this surprises some people. We can easily understand the concept of Turing machines but then we realise that they have complicated consequences, such as the undecidability of the halting problem and so on. The technical term here is that "knowledge is not closed under deduction". That is, we can know some fact $A$, but not know $B$, even though $A$ implies $B$.
Honestly, though, I'm not sure that Turing's argument is very good. Perhaps I have the benefit of writing nearly 70 years after Turing, and my understanding is that the typical mathematician knows much more about mathematical logic than they did in Turing's time. But it seems to me that mathematicians are mostly quite familiar with the idea of simple systems having complex behaviour. For example, every mathematician knows the definition of a group, which consists of just four simple axioms. But nobody – today or then – would think, "Aha. I know the four axioms, therefore I know every fact about groups." Similarly, Peano's axioms give a very short description of the natural numbers but nobody who reads them thinks "Right, I know every theorem about the natural numbers, now. Let's move on to something else."
$endgroup$
1
$begingroup$
Historically, the early 20th century had a strong academic belief in "solving" mathematics. E.g., Hilbert's program, and Whitehead+Russel's Principia Mathematica. Godel's work resolved that quest negatively, but I imagine it took some time for academia to fully embrace this notion; even fully acknowledging the correctness of Godel, people would still remember the grand ideas of Hilbert. I think Turing writing only two decades after Godel would be addressing his audience with this context in mind.
$endgroup$
– BurnsBA
8 mins ago
add a comment |
$begingroup$
Mathematicians and philosophers often assume that machines (and here, he probably means "computers") cannot surprise us. This is because they assume that once we learn some fact, we immediately understand every consequence of this fact. This is often a useful assumption, but it's easy to forget that it's false.
He's saying that systems with simple, finite descriptions (e.g., Turing machines) can exhibit very complicated behaviour and that this surprises some people. We can easily understand the concept of Turing machines but then we realise that they have complicated consequences, such as the undecidability of the halting problem and so on. The technical term here is that "knowledge is not closed under deduction". That is, we can know some fact $A$, but not know $B$, even though $A$ implies $B$.
Honestly, though, I'm not sure that Turing's argument is very good. Perhaps I have the benefit of writing nearly 70 years after Turing, and my understanding is that the typical mathematician knows much more about mathematical logic than they did in Turing's time. But it seems to me that mathematicians are mostly quite familiar with the idea of simple systems having complex behaviour. For example, every mathematician knows the definition of a group, which consists of just four simple axioms. But nobody – today or then – would think, "Aha. I know the four axioms, therefore I know every fact about groups." Similarly, Peano's axioms give a very short description of the natural numbers but nobody who reads them thinks "Right, I know every theorem about the natural numbers, now. Let's move on to something else."
$endgroup$
1
$begingroup$
Historically, the early 20th century had a strong academic belief in "solving" mathematics. E.g., Hilbert's program, and Whitehead+Russel's Principia Mathematica. Godel's work resolved that quest negatively, but I imagine it took some time for academia to fully embrace this notion; even fully acknowledging the correctness of Godel, people would still remember the grand ideas of Hilbert. I think Turing writing only two decades after Godel would be addressing his audience with this context in mind.
$endgroup$
– BurnsBA
8 mins ago
add a comment |
$begingroup$
Mathematicians and philosophers often assume that machines (and here, he probably means "computers") cannot surprise us. This is because they assume that once we learn some fact, we immediately understand every consequence of this fact. This is often a useful assumption, but it's easy to forget that it's false.
He's saying that systems with simple, finite descriptions (e.g., Turing machines) can exhibit very complicated behaviour and that this surprises some people. We can easily understand the concept of Turing machines but then we realise that they have complicated consequences, such as the undecidability of the halting problem and so on. The technical term here is that "knowledge is not closed under deduction". That is, we can know some fact $A$, but not know $B$, even though $A$ implies $B$.
Honestly, though, I'm not sure that Turing's argument is very good. Perhaps I have the benefit of writing nearly 70 years after Turing, and my understanding is that the typical mathematician knows much more about mathematical logic than they did in Turing's time. But it seems to me that mathematicians are mostly quite familiar with the idea of simple systems having complex behaviour. For example, every mathematician knows the definition of a group, which consists of just four simple axioms. But nobody – today or then – would think, "Aha. I know the four axioms, therefore I know every fact about groups." Similarly, Peano's axioms give a very short description of the natural numbers but nobody who reads them thinks "Right, I know every theorem about the natural numbers, now. Let's move on to something else."
$endgroup$
Mathematicians and philosophers often assume that machines (and here, he probably means "computers") cannot surprise us. This is because they assume that once we learn some fact, we immediately understand every consequence of this fact. This is often a useful assumption, but it's easy to forget that it's false.
He's saying that systems with simple, finite descriptions (e.g., Turing machines) can exhibit very complicated behaviour and that this surprises some people. We can easily understand the concept of Turing machines but then we realise that they have complicated consequences, such as the undecidability of the halting problem and so on. The technical term here is that "knowledge is not closed under deduction". That is, we can know some fact $A$, but not know $B$, even though $A$ implies $B$.
Honestly, though, I'm not sure that Turing's argument is very good. Perhaps I have the benefit of writing nearly 70 years after Turing, and my understanding is that the typical mathematician knows much more about mathematical logic than they did in Turing's time. But it seems to me that mathematicians are mostly quite familiar with the idea of simple systems having complex behaviour. For example, every mathematician knows the definition of a group, which consists of just four simple axioms. But nobody – today or then – would think, "Aha. I know the four axioms, therefore I know every fact about groups." Similarly, Peano's axioms give a very short description of the natural numbers but nobody who reads them thinks "Right, I know every theorem about the natural numbers, now. Let's move on to something else."
edited 7 mins ago
answered 3 hours ago


David RicherbyDavid Richerby
70.5k16107197
70.5k16107197
1
$begingroup$
Historically, the early 20th century had a strong academic belief in "solving" mathematics. E.g., Hilbert's program, and Whitehead+Russel's Principia Mathematica. Godel's work resolved that quest negatively, but I imagine it took some time for academia to fully embrace this notion; even fully acknowledging the correctness of Godel, people would still remember the grand ideas of Hilbert. I think Turing writing only two decades after Godel would be addressing his audience with this context in mind.
$endgroup$
– BurnsBA
8 mins ago
add a comment |
1
$begingroup$
Historically, the early 20th century had a strong academic belief in "solving" mathematics. E.g., Hilbert's program, and Whitehead+Russel's Principia Mathematica. Godel's work resolved that quest negatively, but I imagine it took some time for academia to fully embrace this notion; even fully acknowledging the correctness of Godel, people would still remember the grand ideas of Hilbert. I think Turing writing only two decades after Godel would be addressing his audience with this context in mind.
$endgroup$
– BurnsBA
8 mins ago
1
1
$begingroup$
Historically, the early 20th century had a strong academic belief in "solving" mathematics. E.g., Hilbert's program, and Whitehead+Russel's Principia Mathematica. Godel's work resolved that quest negatively, but I imagine it took some time for academia to fully embrace this notion; even fully acknowledging the correctness of Godel, people would still remember the grand ideas of Hilbert. I think Turing writing only two decades after Godel would be addressing his audience with this context in mind.
$endgroup$
– BurnsBA
8 mins ago
$begingroup$
Historically, the early 20th century had a strong academic belief in "solving" mathematics. E.g., Hilbert's program, and Whitehead+Russel's Principia Mathematica. Godel's work resolved that quest negatively, but I imagine it took some time for academia to fully embrace this notion; even fully acknowledging the correctness of Godel, people would still remember the grand ideas of Hilbert. I think Turing writing only two decades after Godel would be addressing his audience with this context in mind.
$endgroup$
– BurnsBA
8 mins ago
add a comment |
$begingroup$
Just an example - given chess rules, anyone should immediately figure the best strategy to play chess.
Of course, it doesn't work. Even people aren't equal, and computers may outperform us due to their better abilities to make conclusions from the facts.
$endgroup$
add a comment |
$begingroup$
Just an example - given chess rules, anyone should immediately figure the best strategy to play chess.
Of course, it doesn't work. Even people aren't equal, and computers may outperform us due to their better abilities to make conclusions from the facts.
$endgroup$
add a comment |
$begingroup$
Just an example - given chess rules, anyone should immediately figure the best strategy to play chess.
Of course, it doesn't work. Even people aren't equal, and computers may outperform us due to their better abilities to make conclusions from the facts.
$endgroup$
Just an example - given chess rules, anyone should immediately figure the best strategy to play chess.
Of course, it doesn't work. Even people aren't equal, and computers may outperform us due to their better abilities to make conclusions from the facts.
answered 3 hours ago
BulatBulat
841511
841511
add a comment |
add a comment |
smwikipedia is a new contributor. Be nice, and check out our Code of Conduct.
smwikipedia is a new contributor. Be nice, and check out our Code of Conduct.
smwikipedia is a new contributor. Be nice, and check out our Code of Conduct.
smwikipedia is a new contributor. Be nice, and check out our Code of Conduct.
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$begingroup$
perhaps, it's better suited for philosophy portal rather to hard science like CS
$endgroup$
– Bulat
3 hours ago
$begingroup$
@Bulat I was going to say the same -- and redirect to English Language Learners -- but then I realised that there is some CS-related content that can be explained in an answer, which probably wouldn't be picked up on, in other parts of Stack Exchange.
$endgroup$
– David Richerby
3 hours ago