© NOKIAexymach / 10.9.2003 / PHa page: 1 From Machine Cognition to Conscious Machines Dr. Pentti O...

© NOKIA exymach / 10.9.2003 / PHa page: 1

From Machine Cognition to Conscious Machines


Dr. Pentti O A Haikonen,

Principal Scientist, Cognitive Technology

Nokia Research Center

Exystence Workshop

Machine Consciousness: Complexity Aspects


Why machine cognition?

About intelligence, understanding and cognition

A model for cognitive and thinking machines

Machine cognition and consciousness; -one sided

coins or egg and chicken?

The Outline of the Story


Many of today’s products are so complicated that the user

cannot possibly control all the involved processes, the product

itself must take care of these and leave only higher level

control and decisions to the user.

This is achieved by preprogrammed rules and algorithms that

are sometimes called embedded intelligence.

It is seen that blind algorithms are only a limited solution, more

complex context awareness, machine understanding, is

required.

Towards More Sophisticated Information Technology Products


The machine as a tool:-The user can execute an action with the machine

The machine as an automaton:-The user (or condition) can initiate action sequences

The machine as an agent:-The user can request a context dependent function

The machine as an autonomous agent:-The machine executes context dependent actions as is deemed necessary by (heuristic) set of rules

The machine as a cognitive agent:-The machine understands and is aware; is able to execute tasks requiring real intelligence and thought

Levels of Machines; One more Step to Go


Speech and language; recognition, understanding and translation

Vision; visual episode understanding, prediction

Unified sensory information understanding

Non-indexed data base search and information compilation

Improved Artificial Intelligence, artificial creativity

Personal artificial assistants and companions

Autonomous robots;

sterile nurses that do not fall ill, rescue robots, etc.

Security, defense and law enforcement

Etc.

Machine Understanding of Meaning and Context Will Enable New Possibilities


From speech recognition to speech understanding

From pattern recognition to scene understanding

From text parsing to story understanding

From statistical "learning" to cognitive learning

From numerical simulation to free imagination

What We Want: Cognitive Information Technology

or

Human-like Information Processing


GOFAI - The brain is a computer; human-like intelligence

and cognition via programs and algorithms?

Artificial Neural Networks; human-like intelligence via

statistical computing?

DSP; Systems with sensors, sensory information

represented by numeric values - processing by transforms,

filtering, etc. with partly parallel architectures.

Semantic Networks; understanding via classification and

indexing?

Traditional Models and Tools


Humans surpass the computer in everyday tasks

because humans are intelligent and are able to

understand.

But, what is intelligence and understanding?

Traditional Methods have not Provided

True Intelligence and Understanding


What is Intelligence?

No intelligence is needed if you can use this by

following the instructions only

Instruction

booklet


RIP GOFAI

Intelligence is what we use when rules do not help. This excludes the possibility of rule-based AI

What is Intelligence


Understanding is not that Simple

For instance - Episodic Understanding:

NOT tape recorder type storage and playback

BUT the ABILITY to

-Answer questions about the subject;

-what is where

-what is happening

-who is doing what to whom, etc.

-Paraphrase; describe in own words

-Detect contradictions

-Predict what happens next, what is possible

-Evaluate significance, is this good or bad

-Give reasons for present situation, Etc.

.


Understanding Necessitates the Grounding of Meaning

Real world concepts must be grounded to real world entities.

-This calls for a perception process

Concepts must be connected to other concepts.

-This calls for associative cross-connections

The general model of cognition provides these functions

and more.


The General Model of Cognition

Environment Perception process Internal process

percepts of:-environment-inner states

objects

actions

situationmatch/mismatch/novelty detection

tasks, goals, needsmemories

learned routines

predictionreasoningplanned actionjudgement

ReactionsActions

etc.

experience

relationships

emotionsemotionalevaluation


The Cognitive Model as an Associative Structure


Representation of Information or

the Power of Power Sets

The idea behind distributed signal representations:

The set of all subsets -the power set- is always larger than

the original set. Therefore a limited number of original set

members -here the basic signals- can give rise to a much

larger number of subsets -possible signal combinations-

allowing thus the representation of large number of

different cases with only limited number of basic signals.


Distributed Representations and Associative Processing

Signals and signal sets carry meaning

Individual signals correspond to elementary features

Signal sets or arrays correspond to entities

Entities can be associated together by linking the

corresponding signal arrays

An entity can be evoked by incomplete or slightly different

signal array -”the closest guess”

Also episodes, signal set sequences, can be handled


Distributed Representations and Associative Processing Go Well Together

Provided that

Combinatorial explosion is avoided by attention; a mechanism

that limits the actual connections by relevance and

importance, etc. Hence the eventual need for emotional

significance.

Interference -the false evocation of undesired signals- is

controlled, various methods exist.


environment

sensors & pre-processing

rawdistributed signals

innerprocesses

feedback

perception process

percepts

responses

The Outline of a Conscious Machine


The General Architectureperceptpreprocesssensor

preprocesssensor

preprocesssensor

preprocesssensor

Body position

Touch subsystem

Auditory subsystem

Visual subsystem

system reactions

System

perception process

perception process

perception process

perception process

perception process

neuron group

neuron group

neuron group

neuron group

neuron groupsmell, taste, pain, etc.

motor actions threshold

threshold

percept

percept

percept

percept


Characteristic Properties of the Model

Each modality works on its own and produces streams of percepts about environment and internal states.

Modalities are associatively cross-connected, therefore the activity of one modality may be reflected in the other modalities; percepts may be named and labeled, names may evoke corresponding percepts…the activity of one modality may be memorized and reported in terms of other modalities, etc.

Attention determines which percepts are accepted for further action. Attention is controlled by signal intensity and thresholds, these are controlled by e.g. emotional significance.

Pain and pleasure are system reactions that affect attention.

The flow of inner speech and inner imagery is supported.


How do we know if the machine is conscious? There may be

some telltale symptoms that we could look for.

For instance Prof. Aleksander lists five axioms:

1) sense of place,

2) imagination,

3) directed attention,

4) planning,

5) decision/emotion

In the following a rather similar list is given perhaps with

some twists.

Consciousness in the Machine?


-Does the machine have mental content that is about something?

-Is the machine able to report its mental content to itself (and others) and does it recognize the ownership of the same?

-Is the machine able to make the difference between the environment and the machine self?

-Does the machine have (episodic) sense of time?

-Does the machine bind its present experience to personal history and expected future? (“the flow of existence”)

-Is the machine aware of its own existence?

-The “hammer test” of phenomenal awareness: Does the machine feel pain?



And finally,

if the machine were to genuinely ask:

Where did I come from?

Then we would know that we are into something deep.



In this model understanding arises from the processing with

meaning -on the other hand meaning-carrying signal arrays

are intentional, a supposed prerequisite for consciousness.

Here also the cross-modality binding and reporting -hallmarks

of consciousness- arise from the requirements of cognition.

Therefore, are true cognition and consciousness connected or

separate properties?

Thus, would the proper realization of cognition automatically

result in some kind of consciousness (Or do zombies exist)?

Cognition and Consciousness; Which Comes First?


Dr. Pentti O A Haikonen, Principal Scientist, Cognitive Technology

Nokia Research Center


Thank You

for Your Attention!


-end of show-

© NOKIAexymach / 10.9.2003 / PHa page: 1 From Machine Cognition to Conscious Machines Dr. Pentti O...

Documents

Transcript of © NOKIAexymach / 10.9.2003 / PHa page: 1 From Machine Cognition to Conscious Machines Dr. Pentti O...