Transcript From Turing to Confucius: philosophical inspirations

From Turing to Confucius:
philosophical inspirations
underlying different approaches
in Natural Language Processing
Yingjin Xu
School of Philosophy, Fudan University
Philosophy and AI
• AI is special among other disciplines in the
sense that it does not have an unified
theoretical foundation as classical physics
does.
• AI systems are often technical realization of
some philosophical ideas without some
scientific theory as a media between the two.
But
• The Philosophical is even more chaotic than
the AI circle.
• Disagreements among philosophers on nearly
every level are quite normal. Much worse, no
experimental methods can be used to set
some criteria.
But how does philosophy evolve?
• 1. By doing arguments.
• (common sense plus logic, sometime
probability theory)
Intuition plays a role here, comparable to the
wanted “friendly-to-user” feature of AI. AI
system also needs to send out outputs which are
intuitively right to humans.
2. Older theories never die, but they would fade
away.
For instance
• Behaviorism both as psychological and
philosophical movement has faded away, but
may be still alive in a sense.
• Skinner
• Watson
• Ryle
• But why did they fade away?
• Cognitive turn and Chomsky
But behaviorism has much impact on
NLP
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1. Turing test idea.
Joseph Weizenbaum:
Eliza chatterbox
Rogerian psychotherapy
The recipe here is: no need to model the inner
language processing structure of the doctor.
Only behaviors do matter.
• Is the AERA chatterbox still on this line?
External semantics
As Wittgenstein described in Philosophical
Investigation:
Meanings of words come from objects stand for
them in the reality.
This looks very natural, and it is the core idea of
early Wittgenstein.
But
• It has faded away.
• It is not refuted in a direct way, but it does not
seem to be promising from the perspective of
later Wittgenstein.
• The theory for replacing the former:
• Language game theory
However, the external semantic model
still has its impacts in AI or NLP
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Instance:
Terry Winograd: SHRDLU
Block world
Philosophical worry:
Not everything represented by words can be
defined as nodes mapped onto external
objects.
• Can gestures be defined in this way?
Leibniz: ideal language
• Such a language is composed by:
• Linguistic entities clearly representing ideas
• And rules which are mechanically computable.
• Ideas are innately fixed, needless to represent
external objects.
• Understanding: a mapping job from the
natural language to this ideal language.
Instance
• Margaret Masterman: Interlingua-based
Machine Translation
• Source language: gusta
• Inter language: [CAUSE (X, [BE (Y, PLEASED])])]
• Target language: like
• But the IL should be very powerful for
representing every possible natural language.
Transfer-based Machine Translation
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SL: Maria me gusta
Syntactic analysis:
gusta[me (Maria)]
gusta[SUBJ(ARG2:NP), OBJ1(ARG1: CASE1)]
gusta[SUBJ(ARG2:NP), OBJ1(ARG1:
CASE1)]→like [SUBJ(ARG1:NP),
OBJ1(ARG2:NP)]
Empiricism Vs. Rationalism
• Statistics Vs. Rule-based approach
A Bayesian approach
• An idealized translation is nothing but any
mapping job which can make the value of the
following formula approach to 1:
• P(target expression/source expression)
• In order to do the mapping, the system should try
every candidate target expression and hence
compute the result of the foregoing formula, and
finally select the most qualified guy out of the
candidate pool.
• IBM: Candide system
Kant: Hybrid system
• The basic ideas of the Kantian cognitive
architecture:
• Mixture of the Bottom-up and Top-down
approach
Instance in NLP
• Sergei Nirenberg and Robert Frederking:
• Multi-Engine Machine Translation
• Three engines ( one based on statistics, one
based on rules, and one based on instances)
• Each one will work on the same source text,
sending out three candidate target texts, them
a higher order evaluator will select out the
best one.
The philosophical worry
• As the criticism of Kant made by Hegel has
shown, the integration would be a big
problem for any hybrid approach.
Confucius!
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Confucius would not like rule-based approach.
He never defines concepts or gives axioms.
For instance, he never defines “benevolence”.
Nor would he like statistics or large-scale datemining.
• Instead, he is a story teller, and stories are not
rules on the one hand, not sufficient for
forming big sample space on the other.
长尾真（Makoto Nagao）’ s work
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Dual lingua mapping Samples given as below:
I feel dizzy. ↔ 我感到晕。
I feel hungry. ↔ 我感到饿。
He feels hungry. ↔ 他感到饿。
He feels comfortable. ↔ 他感到舒服。
The system would figure out the mapping
relationships on the word level, and once this is
done, the grammatical structure will be grasped.
But there is a further problem:
• Embodiment!!!!
• Embodiment is not a discrete module besides
the NLP module.
• Instead, full-fledged capacity of NLP has
assumed embodiment.
END
• Thank you for your patience!!
• [email protected]
• http://jpkc.fudan.edu.cn/s/293/t/608/main.htm