Progress in Machine consciousness - PowerPoint Presentation

Slide1

Progress in Machine consciousness

Software Agent2009. 04. 09Seunghyun Lee

David Gamez,

Consciousness and Cognition

vol.17, pp.

887-910, 2007Slide2

ContentsIntroductionClassification of Machine Consciousness

MC1, MC2, MC3, and MC4Research ProjectsRelationship with Other AreasCriticisms

Issues and Potential Benefits

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IntroductionMachine consciousnessTest theories of consciousness using computer

modelsCreate more intelligent machines that might actually have phenomenal states“Artificial consciousness”, “digital sentience”

Breaking machine consciousness into four areas

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Category

Associated Subject

MC1

External behavior

MC2

Cognitive characteristics

MC3

Architecture

MC4

Phenomenally

consciousnessSlide4

Classification of Machine Consciousness MC1(External behavior

)Goal  Replicate conscious human behavior

Large lookup table /

zombie

robot

Example

Turing

Test

3

Unconscious

behavior

Conscious behavior

Feature

-Automatically carried out

-Limited amount of behavior

-Complex activities

-New behaviors can

only be learnt when consciousness is present

Example

Muscle contractions while

walking, epileptic seizure

Driving home from work, interpersonal dialogSlide5

Classification of Machine ConsciousnessMC2(Cognitive characteristics)Goal

 Research on connection between consciousness and cognitive characteristicsImagination, emotion, and selfMetzinger’s 11 constraints on consciousness

(1) Global availability

(2) Activation within a window of presence

(3) Integration into a coherent global state

(4) Convolved holism

(5) Dynamicity

(6)

Perspectivalness

(7) Transparency

(8) Offline activation

(9) Representation of intensities(10) “Ultrasmoothness

”: Homogeneity of simple content(11) Adaptivity

Alexsander’s

five cognitive mechanisms

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Classification of Machine ConsciousnessMC3 (Architecture)

Goals Simulation of architectures related to human consciousnessGlobal workspace(Baar

),

neural synchronization(Crock)

MC4(

Phenomenally

consciousness)

Phenomenally consciousness?We have phenomenally conscious states when we see, hear, smell,

taste

and have pains. (Block 1995: 230)

GoalsResearch on machines that have real phenomenal experiences that are actually conscious themselvesSystem based on biological neurons

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Depiction

Represent elements of the world(perceptual states)

Imagination

Recall parts of the world or create sensations

Attention

Select which parts to be depicted or imagined

Planning

Control sequences of states to plan actions

Emotion

Evaluate planned actions and determine the ensuing action

Research

Project

Five

axioms(

Alekxsander

,

Dunmall

, 2003)

Kernel

Architecture(

Alekxsander

, 2005)

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Axioms and Neural

Representation Modeling Slide8

Research Projects

Main focus of this project Cognitive

, architectural and phenomenal aspects of machine consciousness (

MC2~4

).

Constitution

CRONOS, SIMNOS, biologically inspired visual system,

SpikeStream

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CRONOS

<CRONOS>

<SIMNOS>Slide9

Research Projects Approach 1(Holland, 2003)

Focus on internal modelTestSIMNOS as an internal model of CRONOS

CRONOS

eyes obtains information from environment

Update SIMNOS

Internal model : ‘offline’

 ‘imagine’ mode before selected action is carried out

Approach

2(Gamez)

Development of spiking neural network

that controls eye movement

Generates eye movement spontaneously to the different partLearns the association between the eye’s position and a visual stimulus Emotional systemNegative object  ‘imagination’ mode  inhibit sensory input and motor output

Cognitive characteristic(MC2), neural correlated architecture(MC3)

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CRONOSSlide10

Research ProjectsBrooks, Breazeal et al.(1998)

Constitution4 cameras, 2 microphones, and many piezoelectric touch sensorsA number of hard

wired innate

reflexes

Emotional

System

Independent projects

Joint attention, theory of mind, social

interaction, dynamic human-like arm motion, and multi-modal coordinationRelationJoint attention, theory of mind

(MC1

)

Cog’s emotional system(MC2)LimitMany individual human behaviors are implemented Active all together  incoherence and interference

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CogSlide11

Research Projects Simulated infant(Cotterill

, 2000) Controlled by a biologically inspired neural systemPremotor

cortex, supplementary motor

cortex, frontal eye fields, thalamic nuclei,

hippocampus and

amygdala

Interconnection : based on anatomical

connectivity

SimulationBlood glucose measurement, milk, urine

Sustain avoiding discomfort

Goal

Identify neural correlates of consciousnessRelationNeural correlates of consciousness(MC3), (MC4)

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CyberChildSlide12

Research Projects

Approach 1(Holland and Goodman, 2003)Test the role of internal model in consciousnessUsing ARAVQ(Adaptive Resource-Allocating Vector

Quantizer

)

Graphical representations of inner states

Experiment

Wall following and obstacle avoidance behavior

ARAVQ build up

concepts  forms internal model

Good performance

Some of the internal models in humans are integrated into conscious cognitive

states(MC2)

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Khepera

modelsSlide13

Research Projects Approach 2(Ziemke

et al., 2005)ImaginationUsing simple neural networkConstitutionSensorimotor

module :

Avoid

obstacle, perform fast straightforward motion

Prediction module :

Predict

the sensory input of the next time step

‘Imagined’ sensory inputs produced very similar behavior to real sensory inputMC2

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Khepera

modelsSlide14

Research Projects

Global workspace theory(Baar, 1988)

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Global Workspace ModelsSlide15

Research Projects IDA naval dispatching System(Franklin, 2003)

Assign sailors to new billetsFunctions are carried out using codeletsApparatus for consciousnessCoalition

manager

S

potlight controller

B

roadcast manager

A number of attention

codeletsMC1, MC2, MC3 Neural simulations(

Dehaene

et al

., 1998)Stroop taskPredictions about brain imaging patterns Attentional blink Explained using the theory about the implementation of a global workspace in the brain

MC2, MC3

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Global Workspace ModelsSlide16

Research ProjectsBrain-inspired cognitive architecture(Shanahan, 2006)

Functionally analogous components to brain structure

Enable the system to follow

chains of association

E

xplore the potential

consequences prior to the action

Experiment

Webot

and Khepera robotLow level actions and preferences for cylinders with different color

Produced behavior(MC1), imagination and emotion(MC2), based on global workspace model(MC3)

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Global Workspace ModelsSlide17

Research ProjectsLanguage and agent-based architecture(Angel, 1989)Three

attributes for conscious system1. Independent purpose regardless of its contact with other agents.2. The ability to make interagency attributions

on a pure or natural basis.

3. The ability to

learn from scratch

significant portions of some natural language, and the ability to use these elements in satisfying its purposes and those of its interlocutors.

N

obody

has implemented with this model Inner speech(Steels, 2003)Experiments in which two robotic heads watched scenes and played a language-game that evolved a lexicon or grammar

R

ehearse

future dialogue, submit thoughts to self-criticism, and conceptualize and reaffirm memories of past experiencesMC2

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Language and AgencySlide18

Research Projects Cognitive approach(Haikonen

, 2003)System intended to develop emotion, transparency, imagination,and inner speech

Sensory modules

Main idea

Percepts

 Conscious

different modules cooperate in

unison, focus on the same entity,

forms associative memories

MC1~4

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Cognitive ArchitectureSlide19

Research Projects Schema-based model(Samsonovich

and DeJong, 2005)Based around schemasConstrained by a set of axioms Axioms correspond to the

system’s ‘conscious’ self

MC1, MC2, but not MC3

Cicerobot

(

Chella

and

Macaluso

)

Museum

tour guide robotBased around an internal 3D simulation 

plan actionsConscious cognitive architecture(MC2),

control

the robot(MC1)

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Cognitive ArchitectureSlide20

Research ProjectsSynthetic phenomenologyNew

area of research on machine consciousnessDevelop artificial systems which are capable of conscious states and the description of their phenomenology

when and if this

occurs

Challenges

Develop

s

ystems which be capable of phenomenal states

“To be synthetically phenomenological, a

system S must contain machinery that represents what the world and the system S within it

seem like

, from the point of view of S’’(Aleksander and Morton, 2006)Find ways of describing phenomenal states when and if they occur Graphical representations of

Kheperas’ inner states(Holland, 2003)Distinguish machine’s phenomenal and non-phenomenal states

which internal states are likely to be conscious?

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Relationship with Other AreasStrong and weak AI(Searle, 1980)Weak AI : Powerful tool when we study mind (modeling)

 MC1~3Strong AI : Programmed computer is mind itself  MC4Artificial general intelligence

Goal : Replicate human intelligence completely

ex) chess playing

MC1 : Conscious human behavior

Psychology, neuroscience and philosophy

P

sychology : Build also computer cognition model

not only conscious state but also othersNeuroscience : Trend that tests theories about attention and consciousness with neuronsPhilosophy : Common in the use of logic

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Criticisms The hard problem of consciousnessEasy problem : D

iscriminate, integrate information, report mental states, focus attention etc…(MC1, MC2, MC3)Hard problem : Explaining phenomenal

experience(MC4)

 Many

theories, but no real idea to solve

Consciousness

is

non-algorithmic

Processing of an algorithm is not enough to evoke phenomenal awareness because of subtle and largely unknown physical principles

What computers still cannot

do

Fact based system cannot solve human intelligence which depends on skills, a body, emotions, imagination and other attributes that cannot be encoded into long lists of facts

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Potential Benefits and Issue Potential benefits

MC1 : Help people to produce more imitation of human behaviorex) chatterbots

MC2 : Machine which understand human world and language in a human-like way can assist people

MC3 :

H

elp people to understand how the brain processes information, so that it is able to develop prosthetic interfaces to restore visual, auditory or limb functions

MC4 :

H

elp people to understand the phenomenal states of very young or brain-damaged people who are incapable of communicating their experiences in language

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Potential Benefits and IssueIssuesCan machines take over and enslave humans?

How we should treat conscious machines?How should it be the legal status of conscious machines? Discussion

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