comments
Respond
Comment on the article
Add a citation
Reply with an article
Start a new topic
Edit
Edit article
Delete article
Share
Invite
Link
Embed
Social media
Avatar
View
Graph
Explorer
Focus
Down
Load 1 level
Load 2 levels
Load 3 levels
Load 4 levels
Load all levels
All
Dagre
Focus
Down
Load 1 level
Load 2 levels
Load 3 levels
Load 4 level
Load all levels
All
Tree
SpaceTree
Focus
Expanding
Load 1 level
Load 2 levels
Load 3 levels
Down
All
Down
Radial
Focus
Expanding
Load 1 level
Load 2 levels
Load 3 levels
Down
All
Down
Box
Focus
Expanding
Down
Up
All
Down
Article ✓
Outline
Document
Down
All
Page
Canvas
Time
Timeline
Calendar
Updates
Subscribe to updates
Get updates
Past 24 hours
Past week
Past month
Past year
Pause updates
Contact us
Programs that learn can overcome the barrier
If a computer is given the ability to learn it can generate semantics from low-level syntax.
Note
: Also, see the "Can physical symbol systems learn as humans do?" arguments on map 3.
RELATED ARTICLES
Explain
⌅
Artificial Intelligence
Artificial Intelligence☜A collaboratively editable version of Robert Horns brilliant and pioneering debate map Can Computers Think?—exploring 50 years of philosophical argument about the possibility of computer thought.☜F1CEB7
⌃
Can computers think? [1]
Can computers think? [1]☜Can a computational system possess all important elements of human thinking or understanding? ☜FFB597
⌃
Yes: physical symbol systems can think [3]
Yes: physical symbol systems can think [3]☜Thinking is a rule governed manipulation of symbolic representational structures. In humans, symbol systems are instantiated in the brain, but the same symbol systems can also be instantiated in a computer. ☜59C6EF
⌃
The Chinese Room Argument [4]
The Chinese Room Argument [4]☜Instantiation of a formal program isnt enough to produce semantic understanding or intentionality. A man who doesnt understand Chinese, can answer written Chinese questions using an English rulebook telling him how to manipulate Chinese symbols.☜EF597B
⌃
The Syntax-Semantics Barrier
The Syntax-Semantics Barrier☜Axiom 1: programs are formal (syntactic). Axiom 2: human minds have mental contents (semantics). Axiom 3: syntax by itself is neither constitutive of nor sufficient for semantics. Conc: programs are neither constitutive of nor sufficient for minds.☜98CE71
■
Programs that learn can overcome the barrier
Programs that learn can overcome the barrier☜If a computer is given the ability to learn it can generate semantics from low-level syntax.☜EF597B
↳
Internal semantics in syntactic networks that learn
Internal semantics in syntactic networks that learn☜A network of appropriately connected syntactical symbols—which can learn by deriving consequences from inputs—possesses internal semantics and can be said to understand as human understanding seems to result from the same kind of internal semantics.☜98CE71
↳
Semantics can emerge from programs that learn
Semantics can emerge from programs that learn☜A system with sufficiently complex learning mechanisms can possess semantics if it meets a principle of inductive adequacy: ie the system should possess inductive mechanisms capable of producing all the knowledge constructs it uses in its behaviour.☜98CE71
↳
Learning programs don't help
Learning programs don't help☜The syntax-semantics barrier is not overcome by complex learning procedures. A liver is complex but it doesnt understand anything. Making a program complex wont give it understanding either.☜EF597B
□
Barrier's a problem for Searle's theory too
Barrier's a problem for Searle's theory too☜Searle insists intentionality is caused by and realised in brains. But intentional systems are made of parts that lack intentionality. This applies as much to brain neurons as to computer parts.☜EF597B
□
Notion of semantic hookup is problematic
Notion of semantic hookup is problematic☜Searle thinks semantics only arises when symbols are given meaning by being hooked up to the world. But many traditional puzzles show that merely syntactic use of language and symbols can generate linguistic competence with no semantic hookup.☜EF597B
□
Searle's 3rd axiom requires scientific research
Searle's 3rd axiom requires scientific research ☜Searles 3rd axiom assumes syntax cant produce semantics. But this assumption is exactly what is at issue in classical AI. Its an empirical issue that cant be decided in advance of scientific research—and begs the question of machine thought.☜EF597B
□
Semantics may result from Godelian self-reference
Semantics may result from Godelian self-reference☜The Chinese Room argument ignores the possibility of machines that can have semantics by virtue of self-reference. Godels theorem shows how machines can encode their own syntax and thus reflect on their own programs.☜EF597B
□
Syntax can generate natural meanings
Syntax can generate natural meanings ☜Reliable causal connections between the syntactic system and the world are sufficient to to generate natural meanings.☜EF597B
□
The Empiricist Reply
The Empiricist Reply☜Empirical evidence suggests semantics can emerge from low-level syntax—e.g. a barcode reader. Similarly, high-level semantics may emerge from a robot with a self organising network that makes reasonable inferences from implicit information.☜EF597B
□
The Luminous Room argument
The Luminous Room argument ☜Searles Chinese Room attempts to answer a scientific question by appealing to our naive intuitions about the mind. Paul and Patricia Churchland challenge its validity by imagining a similar thought experiment directed against James Maxwells elect☜EF597B
□
Graph of this discussion
Graph of this discussion☜Click this to see the whole debate, excluding comments, in graphical form☜dcdcdc
Enter the title of your article
Enter a short (max 500 characters) summation of your article
Click the button to enter task scheduling information
Open
Enter the main body of your article
Prefer more work space? Try the
big editor
Enter task details
Message text
Select assignee(s)
Due date (click calendar)
RadDatePicker
RadDatePicker
Open the calendar popup.
Calendar
Title and navigation
Title and navigation
<<
<
July 2024
>
<<
July 2024
S
M
T
W
T
F
S
27
30
1
2
3
4
5
6
28
7
8
9
10
11
12
13
29
14
15
16
17
18
19
20
30
21
22
23
24
25
26
27
31
28
29
30
31
1
2
3
32
4
5
6
7
8
9
10
Reminder
No reminder
1 day before due
2 days before due
3 days before due
1 week before due
Ready to post
Copy to text
Enter
Cancel
Task assignment(s) have been emailed and cannot now be altered
Lock
Cancel
Save
Comment graphing options
Choose comments:
Comment only
Whole thread
All comments
Choose location:
To a new map
To this map
New map options
Select map ontology
Options
Standard (default) ontology
College debate ontology
Hypothesis ontology
Influence diagram ontology
Story ontology
Graph to private map
Cancel
Proceed
+Comments (
0
)
- Comments
Add a comment
Newest first
Oldest first
Show threads
+Citations (
0
)
- Citations
Add new citation
List by:
Citerank
Map
+About
- About
Entered by:-
David Price
NodeID:
#815
Node type:
OpposingArgument
Entry date (GMT):
8/2/2006 4:55:00 PM
Last edit date (GMT):
8/2/2006 4:55:00 PM
Show other editors
Incoming cross-relations:
0
Outgoing cross-relations:
0
Average rating:
0
by
0
users
Enter comment
Select article text to quote
Cancel
Enter
welcome text
First name
Last name
Email
Skip
Join
x
Select file to upload