Artificial Consciousness

1. Artificial Consciousness Group 3 Mohit, Raghuvar, Avin, Aniruddha

2. What is Consciousness? • Consciousness denotes being awake and responsive to one's environment; this contrasts with being asleep or being in a coma • Being self-aware • Derives from Latin conscienta which primarily means moral conscience

3. Aspects of Consciousness • Awareness • Awareness of one's environment and one's own existence • Anticipation • The ability to predict foreseeable events • Learning • The ability to learn from experience

4. Aspects of Consciousness (contd) • Sentience • Utilization of sensory organs • Sapience • Ability of an entity to act with judgment

5. Types of consciousness • Phenomenal • Experience (Qualia) • Hard part • Access • Verbal report • Reasoning • Control of behavior • Easy part

6. Hard Problem of Consciousness • Explain how flows and electrochemical processes in the brain give rise to the inner experience of subjective awareness. • Neural correlate of Consciousness

7. Artificial Consciousness (AC) • Consciousness in machine • Engineering artifacts which possess • Self awareness • Wisdom • Ability to learn • Ability to Sense

8. Why Artificial Consciousness? • Creating machines resembling human beings • Understanding the nature of consciousness • Implementing more efficient control systems.

9. Goals of Artificial Consciousness • Twofold target in Artificial Consciousness: • The nature of phenomenal consciousness • The active role of consciousness in controlling and planning the behaviour of an agent • Important Question • Is Artificial Consciousness possible?

10. Outline • Raghuvar • Why AC may not be possible? • Avin • How to build a Conscious System? • Aniruddha • Applications and Future Work

11. Several key questions... Can computers think or do they just calculate? Is consciousness a human prerogative? Does consciousness depend on the material that comprises the human brain, or can computer hardware replicate consciousness? Is simulation of consciousness the same as consciousness?

12. Turing test Test for machine’s ability to demonstrate intelligence Machine and human in separate room converse with a human interrogator Goal is to convince him that you are human Annual competition : Loebner Prize ($100,000) to computer that passes : no winners yet!

13. Turing Test :implications • Main argument: • If a computer can portray itself as a human successfully, then essentially there is no difference between a human and a computer • Ability to actively process linguistic syntax, infer context, have the notion of ‘self’, deal with a finite knowledge base and moral questions • The computer is conscious!!....or is it?

14. Chinese Room

15. Chinese Room • Person inside the room is a non-speaker of Chinese • He is given Chinese symbols corresponding to questions • Instruction book in English telling him which symbol he has to output corresponding to the input • To the outside world, he’s an excellent speaker of Chinese

16. Searle, 1984 Brains cause minds. Syntax is not sufficient for semantics. Computer programs are entirely defined by their formal, or syntactical, structure. Minds have mental contents; specifically, they have semantic contents.

17. Searle’s argument If Strong AI is true, then there is a program for Chinese such that if any computing system runs that program, that system thereby comes to understand Chinese I could run a program for Chinese without thereby coming to understand Chinese. Therefore Strong AI is false. Widely debated by philosophers and scientists. No conclusion as to whether it is possible to develop a truly conscious machine

18. Computational Barrier • Minimum level of computation necessary to achieve human like consciousness: can be calculated using Neural networks • The human brain has about 1012 neurons, and each neuron makes about 103 synaptic connections with other neurons, on average, for a total of 1015 synapses.  • Neural Network : each synapse : 4bytes • 1015 synapses : 4million GB • Add auxiliary variables : 5 million GB ! • Minimum prerequisite : Necessary, not sufficient condition

19. Consciousness System - Imitation and Self-others distinction • System for generating consciousness • Implementation of imitation behavior important as the first stage of study of consciousness • Distinguish between self and others • Consciousness generated by consistency of cognition and behavior

20. Structure of a Consciousness System • Consciousness System comprises of : • Cognition System • Behavior System • Primary Representation • Symbolic Representation

21. Cognition System • Information enters the consciousness system at Input and reaches the Cognition System • Used for neural computation together with the information from BL (internal information) • Derived information transmitted to RL (cognized information) • Language labels have different areas for condition of self and others

22. Behavior System • Behavior information from BL passes to the Behavior System • Information added to input and sensory information by neural computation • Resultant information is transmitted to Output to implement a behavior

23. Primary Representation • Common area for the cognition and behavior system • Behavior learning during cognition and cognition learning during behavior • Each piece of information is correctly related to language labels of symbolic representation • The consciousness system brings a process of artificial thoughts as information is circulated

24. Example – Human Language • Conversation between self and other • Input: the speech of both self and the other • Somatic sensation that self is talking is fed back as input • Behavior of a new language label (through circulation) gives rise to thinking and expectations • Possible to offer new topics for conversation.

25. Consciousness through Imitation • Mirror neurons • Brain of monkeys • Neuron fires when implementing a certain behavior by itself or upon observing others with the same behavior • Primary representation equivalent to mirror neuron • Imitation occurs while information circulates through primary and symbolic representation • Circulation of information through external models and one’s own brain is necessary for imitation

26. Learning in a Consciousness System (b) c) Neural Network (NN) of a conscious system

27. Features of NN in a consciousness system • Two structural features to implement consistency of cognition and behavior • Recursiveness - Somatic sensation of behavior of self is fed back to enhance learning efficiency • Presence of a common area for cognition and behavior and data circulation • Imitation learning and cognition of behavior of self and others possible • Back propagation (BP) method of supervised learning used for NN learning through simulation

28. Ongoing Research Hot research area in AI Several serious attempts to make conscious machines Franklin’s Intelligent Distribution Agent Ron Sun's cognitive architecture CLARION Haikonen’s cognitive architecture Cognitive Robots

29. Intelligent Distribution Agent • Negotiate new assignments for sailors in the US Navy • Interacts with Navy databases and communicates with the sailors via natural language email dialog • Based on Global Workspace Theory - Baars • Relies heavily on codelets • Not attributed as conscious

30. CLARION • Fundamental structures of the human mind • Distinction between conscious and unconscious mental processes • Bottom-up learning - learning that involves acquiring first implicit knowledge and then acquiring explicit knowledge on its basis) • Successful in accounting for a variety of psychological data • Skill learning tasks : SRT, AGL, PC, CI

31. Haikonen’s cognitive architecture • Rule-based computing inadequate for achieving AC • A special cognitive architecture • Artificial neuron • A low-complexity implementation of the architecture proposed (2004) • Not capable of AC – but exhibit emotions as expected

32. Conscious Robots Evolution of Conscious Robots: • Simple reflex • Simple reflex with memory • Perception with meaning and associative memory • Perception with associative memory and report • The robot perceives itself perceiving

33. Looking Ahead • Robots • References in Movies • The Matrix • I, Robot

34. Cognitive Robots • Sensors, path planning, and manipulator design and control vs ability to reason, act and perceive • Able to “know what they are doing” • Consciousness per se does not make any sense unless accompanied by end to end processes like perception and behavior. • Future cognitive robots will be able to interact with humans, acting and learning in unpredictable environments.

35. Cognitive Robots Applications • Service robots, social robots, and personal assistance robots (like Maggie) • Assistant robots for disabled people (like Asibot) • Human-like performing robots (like Manfred) • Autonomous space exploration robots and robotic assistance for orbital assembly and repair (like Robonaut) • Robocup players • Autonomous emergency and rescue robots (like BEAR)

36. Kismet, the Sociable Robot AIBO, Robot pet dog

37. Open questions • Someday, when machines claim they are conscious, will we believe them? • Will we be able to “test” consciousness? • Could machines become “deluded” that they are conscious? • Could the World Wide Web be a form of Consciousness?

38. Summary • Artificial consciousness will lead to intelligent and more useful agents • Difficult to understand and validate • Attempts to model consciousness through a neural network • Field of intensive research and philosophical debate in the years to come

39. References • Block, N. On a confusion about a function of consciousness. Behavioral and Brain Sciences 18 (2): 227-287, 1995 • Buttazzo, G. Artificial Consciousness: Utopia or Real Possibility? Spectrum IEEE Computer 18: 24-30, 2001 • Conscious Robot That Distinguishes between Self and Others and Implements Imitation Behavior 18th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems,2005 • Franklin ,S. IDA: A Conscious Artifact? Journal of Consciousness Studies 10:47-66,2003 • Wikipedia