Progress in Machine consciousness David Gamez Consciousness and

Progress in Machine consciousness David Gamez, Consciousness and Cognition vol. 17, pp. 887 -910, 2007 Software Agent 2009. 04. 09 Seunghyun Lee

Contents • Introduction • Classification of Machine Consciousness – MC 1, MC 2, MC 3, and MC 4 • Research Projects • Relationship with Other Areas • Criticisms • Issues and Potential Benefits 1 S FT COMPUTING @ YONSEI UNIV. KOREA

Introduction • Machine consciousness – Test theories of consciousness using computer models – Create more intelligent machines that might actually have phenomenal states – “Artificial consciousness”, “digital sentience” • Breaking machine consciousness into four areas Category Associated Subject MC 1 External behavior MC 2 Cognitive characteristics MC 3 Architecture MC 4 Phenomenally consciousness 2 S FT COMPUTING @ YONSEI UNIV. KOREA

Classification of Machine Consciousness • MC 1(External behavior) – Goal Replicate conscious human behavior 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 dialog – Large lookup table / zombie robot – Example • Turing Test 3 S FT COMPUTING @ YONSEI UNIV. KOREA

Classification of Machine Consciousness • MC 2(Cognitive characteristics) – Goal Research on connection between consciousness and cognitive characteristics – Imagination, emotion, and self – Metzinger’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 4 S FT COMPUTING @ YONSEI UNIV. KOREA

Classification of Machine Consciousness • MC 3 (Architecture) – Goals Simulation of architectures related to human consciousness – Global workspace(Baar), neural synchronization(Crock) • MC 4(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 themselves – System based on biological neurons 5 S FT COMPUTING @ YONSEI UNIV. KOREA

Axioms and Neural Representation Modeling Research Project • Five axioms(Alekxsander, Dunmall, 2003) 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 • Kernel Architecture(Alekxsander, 2005) 6 S FT COMPUTING @ YONSEI UNIV. KOREA

CRONOS Research Projects <CRONOS> <SIMNOS> • Main focus of this project – Cognitive, architectural and phenomenal aspects of machine consciousness (MC 2~4). • Constitution – CRONOS, SIMNOS, biologically inspired visual system, Spike. Stream 7 S FT COMPUTING @ YONSEI UNIV. KOREA

CRONOS Research Projects • Approach 1(Holland, 2003) – Focus on internal model – Test • • SIMNOS as an internal model of 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 part • Learns the association between the eye’s position and a visual stimulus – Emotional system • Negative object ‘imagination’ mode inhibit sensory input and motor output – Cognitive characteristic(MC 2), neural correlated architecture(MC 3) 8 S FT COMPUTING @ YONSEI UNIV. KOREA

Cog Research Projects • Brooks, Breazeal et al. (1998) • Constitution – 4 cameras, 2 microphones, and many piezoelectric touch sensors – A 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 coordination • Relation – Joint attention, theory of mind (MC 1) – Cog’s emotional system(MC 2) • Limit – Many individual human behaviors are implemented – Active all together incoherence and interference S FT COMPUTING @ YONSEI UNIV. KOREA 9

Cyber. Child Research Projects • Simulated infant(Cotterill, 2000) • Controlled by a biologically inspired neural system – Premotor cortex, supplementary motor cortex, frontal eye fields, thalamic nuclei, hippocampus and amygdala – Interconnection : based on anatomical connectivity • Simulation – Blood glucose measurement, milk, urine – Sustain avoiding discomfort • Goal – Identify neural correlates of consciousness • Relation – Neural correlates of consciousness(MC 3), (MC 4) 10 S FT COMPUTING @ YONSEI UNIV. KOREA

Khepera models Research Projects • Approach 1(Holland Goodman, 2003) – Test the role of internal model in consciousness – Using 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(MC 2) 11 S FT COMPUTING @ YONSEI UNIV. KOREA

Khepera models Research Projects • Approach 2(Ziemke et al. , 2005) – Imagination – Using simple neural network – Constitution • Sensorimotor 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 input – MC 2 12 S FT COMPUTING @ YONSEI UNIV. KOREA

Global Workspace Models Research Projects • Global workspace theory(Baar, 1988) 13 S FT COMPUTING @ YONSEI UNIV. KOREA

Global Workspace Models Research Projects • IDA naval dispatching System(Franklin, 2003) – Assign sailors to new billets – Functions are carried out using codelets – Apparatus for consciousness • • Coalition manager Spotlight controller Broadcast manager A number of attention codelets – MC 1, MC 2, MC 3 • Neural simulations(Dehaene et al. , 1998) – Stroop task • Predictions about brain imaging patterns – Attentional blink • Explained using theory about the implementation of a global workspace in the brain – MC 2, MC 3 14 S FT COMPUTING @ YONSEI UNIV. KOREA

Global Workspace Models Research Projects • Brain-inspired cognitive architecture(Shanahan, 2006) – Functionally analogous components to brain structure – Enable the system to follow chains of association – Explore the potential consequences prior to the action – Experiment • Webot and Khepera robot • Low level actions and preferences for cylinders with different color – Produced behavior(MC 1), imagination and emotion(MC 2), based on global workspace model(MC 3) 15 S FT COMPUTING @ YONSEI UNIV. KOREA

Language and Agency Research Projects • Language and agent-based architecture(Angel, 1989) – Three attributes for conscious system 1. 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. – Nobody 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 – Rehearse future dialogue, submit thoughts to self-criticism, and conceptualize and reaffirm memories of past experiences – MC 2 16 S FT COMPUTING @ YONSEI UNIV. KOREA

Cognitive Architecture 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 – MC 1~4 17 S FT COMPUTING @ YONSEI UNIV. KOREA

Cognitive Architecture Research Projects • Schema-based model(Samsonovich and De. Jong, 2005) – Based around schemas – Constrained by a set of axioms – Axioms correspond to the system’s ‘conscious’ self – MC 1, MC 2, but not MC 3 • Cicerobot(Chella and Macaluso) – Museum tour guide robot – Based around an internal 3 D simulation plan actions – Conscious cognitive architecture(MC 2), control the robot(MC 1) 18 S FT COMPUTING @ YONSEI UNIV. KOREA

Research Projects • Synthetic phenomenology – New area of research on machine consciousness – Develop artificial systems which are capable of conscious states and the description of their phenomenology when and if this occurs – Challenges • Develop systems 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? 19 S FT COMPUTING @ YONSEI UNIV. KOREA

Relationship with Other Areas • Strong and weak AI(Searle, 1980) – Weak AI : Powerful tool when we study mind (modeling) MC 1~3 – Strong AI : Programmed computer is mind itself MC 4 • Artificial general intelligence – Goal : Replicate human intelligence completely • ex) chess playing – MC 1 : Conscious human behavior • Psychology, neuroscience and philosophy – Psychology : Build also computer cognition model not only conscious state but also others – Neuroscience : Trend that tests theories about attention and consciousness with neurons – Philosophy : Common in the use of logic S • FT COMPUTING @ YONSEI UNIV. KOREA 20

Criticisms • The hard problem of consciousness – Easy problem : Discriminate, integrate information, report mental states, focus attention etc…(MC 1, MC 2, MC 3) – Hard problem : Explaining phenomenal experience(MC 4) 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 21 S FT COMPUTING @ YONSEI UNIV. KOREA

Potential Benefits and Issue • Potential benefits – MC 1 : Help people to produce more imitation of human behavior ex) chatterbots – MC 2 : Machine which understand human world and language in a human-like way can assist people – MC 3 : Help people to understand how the brain processes information, so that it is able to develop prosthetic interfaces to restore visual, auditory or limb functions – MC 4 : Help people to understand the phenomenal states of very young or brain-damaged people who are incapable of communicating their experiences in language 22 S FT COMPUTING @ YONSEI UNIV. KOREA

Potential Benefits and Issue • Issues – Can machines take over and enslave humans? – How we should treat conscious machines? – How should it be the legal status of conscious machines? • Discussion 23 S FT COMPUTING @ YONSEI UNIV. KOREA