Machine Consciousness ?

1. Machine Consciousness ? Stan Franklin: Computational Models of Consciousness “Here functional consciousness is meant, not phenomenal consciousness or sentience.” IJCNN,Orlando, Aug. 2007

2. Gamez Fuzzy Classification • What should be modeled? • MC1 – external behavior associated with consciousness • MC2 – cognitive characteristics associated with consciousness • MC3 – architecture causing (or just correlating with) human consciousness • MC4 – phenomenal consciousness • Gamez, David. 2007 to appear. Progress in machine consciousness. Consciousness and Cognition.

3. Avatars Avatars, talking heads:pre-cognitive level, graphics, creating faces from 2D photos, morphing, text-to-speech, sound files, lip synchronization, emotional expressions ... Example: Haptek Virtual Characters Ananova, virtual news reader, sold to Orange mobile phone company for £95M – see her in your phone soon. Andrea Catherwood, or Vandrea, reads the news for BT5. Simon reads news in sign language.Pulse technology Veeper in Harvard. Create your own avatar (from two photos) and save bandwidth sending it around.

4. Turing and Loebner Turing test (1950): are you a program or are you a human? Since 1994 Loebner Prize Medal is awarded annually to the program that best succeeds in passing a variant of the Turing Test. Grand prize is 100 K$, every year 2000$. Judges have >15 min for conversation with humans and chatterbots. 2001: Alice got 14 points, humans 19-24 2002: Ellaz, http://www.ellaz.com/knows jokes, weather, calendar, interprets I-Ching, books, CIA World Facts, plays cards, learns ... 2005, 2006: Jabberwacky, learns contents through natural interactions. Bot’s try to take initiative in conversation.Haptek virtual assistant – can something like that be made conscious?

5. Some quotes from bots Conversations with humans may lead to quite unexpected results ... Talk-Bot #3 by Chris Cowart User: Can you love? Talk-Bot: I've seen people do it.. it doesn't seem hard!

6. Robots Robots, physical designs, real-time control problems, object recognition, action planning ... Toys – AIBO family, quite advanced, over 100 words,face/voice recognition, 6 weeks to rise, self-charging. Most advanced humanoid robots: Honda P3 – 1.60, 130 kg; Honda Asimo – 1.20 m, 43 kg, Sony Qrio ... They predict next movement in real time, shifting center of gravity in anticipation, Qrio runs, very complex motor control. Respond to hundreds of calls, greetings, queries; move their body and arms in response to dozens of different action commands. Vision, object recognition, hearing ... => survive in a hostile environment.Higher order cognitive processes ... coming slowly.

7. Mind-bots Agents, bots, robots – mindless machines? • Add higher level cognitive functions to software agents, reason about goals, perceptions, actions, and mental states of other agents. • Mind-bots: some theory of cognition + linguistic abilities, but still only simulations, with no sensorimotor functions. • Examples: • Gerald Edelman, Nomad/Darwin series of robots with complex behavior evolving from “instincts”, neural-based, still low level cognition. • John Anderson, ACT-R, a cognitive architecture: a theory for simulating and understanding human cognition, with sub-symbolic components. • Allan Newell, SOAR universal theory of cognition + cognitive modeling system + language-related components => NL-SOAR, rule-based.

8. Robot development Nomad, DB, Cog, Kismet, Hal – develop robot mind in the same way as babies’ minds, by social interactions. Cog: saccadic eye movements, sound localization, motor coordination, balance, auditory/visual signal coordination, eye, hand and head movement coordination, face recognition, eye contact, haptic (tactile) object recognition ... Interesting model of autism! DB: learning from demonstration, dance, pole balancing, tennis swing, juggling ... complex eye movements, visuo-motor tasks, such as catching a ball. Kismet: sociable humanoidwith emotional responses, that seems to be alive.

9. Next step Kismet, AIBO and other robots express already a wide variety of emotions (happiness, sadness, fear, dislike, surprise, anger) and instincts (play, search, hunger, sleep). Adding more functions will mimic animal and human capabilities, leading to a human-like robot, with individual personality. EU cognitive systems unit, call: Objective: To construct physically instantiated or embodied systems that can perceive, understand (the semantics of information conveyed through their perceptual input) and interact with their environment, and evolve in order to achieve human-like performance in activities requiring context-(situation and task) specific knowledge. The emphasis is on closing the loop in realistic test cases. Are we close to creation of artificial people?

10. Where does it go? Does this process converge to the real thing or to a smart calculator? Is simulated thinking equivalent to real thinking, or is it like rain in weather simulations? Will the future AIBO have a dog-like mind, and future Kismet be like David from AI movie? Preposterous? Then what is missing? Allan Turing: consciousness is an ill-defined concept; just pass the conversation test and “you” are real, thinking artifact! But is this “you” an intelligent person, conscious of its inner world, or a zombi, mind-less system following its program? Many philosophers of mind (Jackson, Nagel, Searle, Chalmers ... ) tried hard to show that human mind cannot be simulated.

11. Complexity of the brain Simple computational models inspired by neural networks show many characteristics of real associative memories: • Memory is distributed, many neurons participate in encoding of each memory trace. • Damage to the network leads to graceful degradation of performance instead of forgetting specific items. • Memory is content-addressable, recalled from partial cues. • Recall time does not depend on the number of memorized patterns. • Interference (seen in mistakes) and association between different memory patterns depends on their similarity. • Attempts to memorize too many patterns in short time leads to chaotic behavior. • Models explaining most neuropsychological syndromes exist; computational psychiatry is rapidly developing since 1995. • Brain-like computing models provide real brain-like functions.=> Complexity of the brain is not the main problem!

12. Chinese room objection Systems that pass Turing test still do not understand the meaning! The men inside follows the rules but does not understand a word – syntactic relations are not sufficient for semantics (J. Searle 1980). Called “arguably the 20th century's greatest philosophical polarizer”, this thought experiment has led to hundreds of articles and books!

13. Towards conscious robots Stan Franklin, "Conscious" Software Research Group, Institute of Intelligent Systems, University of Memphis, CMattie, LIDA projects: an attempt to design and implement an intelligent agent under the framework of Bernard Baars' Global Workspace Theory. MC2 or MC3 level? Not sufficient for MC4. Duch W, Brain-inspired conscious computing architecture. Journal of Mind and Behavior, Vol. 26(1-2), 1-22, 2005 Owen Holland, University of Essex: consciousness via increasingly intelligent behavior, robots with internal models, development of complex control systems, looking for “signs of consciousness”, 0.5 M£ grant. Pentti Haikonen (Nokia, Helsinki), The cognitive approach to conscious machines (Imprint Academic 2003). Simulations + microchips coming? Few explicit attempts to build them so far.

14. Sensory Memory LIDA Cognitive Cycle Internal Stimulus Transient Episodic Memory Declarative Memory External Stimulus Consolidation Environment 1 Perceptual Codelets 3 Cue 3 Local Associations 3 Local Associations 9 Action Taken Episodic Learning 3 Cue Sensory-Motor Memory Perceptual Associative Memory (Slip Net) 2 Move Percept Workspace 4 Form Coalitions Attention Codelets 4 Move Coalitions Attentional Learning 8 Action Selected Pre-afference Perceptual Learning 5 Conscious Broadcast Action Selection (Behavior Net) Procedural Memory (Scheme Net) Global Workspace 6,7 Instantiate schemes Procedural Learning IJCNN 07

15. Neurocognitiverevolution In many fields of science and art we are going through (Neuro)Cognitive Revolution! Understanding of human nature requires serious re-thinking. Ancient ideas of ghosts in the machine, a nice cover for our ignorance, is no longer acceptable – we are not so ignorant any more!

16. Neurocognitive informatics My own attempts - see my webpage, Google: W. Duch Mind as a shadow of neurodynamics: geometrical model of mind processes, psychological spaces providing inner perspective as an approximation to neurodynamics. Intuition: learning from partial observations, solving problems without explicit reasoning (and combinatorial complexity) in an intuitive way. Neurocognitive linguistics: how to find neural pathways in the brain. Creativity & word games. Duch W, Intuition, Insight, Imagination and Creativity, IEEE Computational Intelligence Magazine 2(3), August 2007, pp. 40-52 Use inspirations from the brain, derive practical algorithms!

18. Solution to the Chinese room • It is not a test – the outcome is always negative! If I go into your head I will not understand either. • Conditions under which human observer could recognize that a system understands should be discussed – a “resonance” of minds. • A feeling “I understand” is confused here with real operational understanding. Some drugs or mental practices induce the illusion of understanding everything; sometimes we have no feeling of understanding, but can answer correctly and in fact do understand. • Searle concludes (wrongly): we know that humans understand, therefore their neurons must have some mysterious causal powers that computer elements do not have. • Correct conclusion: Turing tests is still important, Chinese room fails. This is a trap! Once you treat it seriously it is hard to get out.

19. Hard problem of consciousness Old mind-body problem in new disguise, presented in the Journal of Consciousness Studies in 1995, and in a book Chalmers D.J, The Conscious Mind: In Search of a Fundamental Theory, Oxford University Press 1996 (got > 50 reviews!) • Easy problems: directing attention, recognizing, commenting, etc. • Hard problem of consciousness: qualitative character of phenomenal experience (PE), or qualia – why are we not zombies? • Theoretically all information processing could go on without any experience – sweetness of chocolate, or redness of sunset. • Qualia = |Conscious perception – Information processing| Inner experience cannot be explained in words, robots can work without it. How to program something that does not make a difference?

20. Hard problem solution A lot of nonsense has been written on qualia. Some solutions: there is no problem; we will never solve it; information processing has dual aspects, physical and phenomenal; panpsychism; protophenomena; quantum C ... • 8 years of discussions led nowhere. • A fruitful way proposed by Thomas Reid (1785), and Indian philosophers 2000 years before him, distinguishes clearly between sensation (feeling) and perception (judgment, discrimination). • I feel pain: makes an impression that some 'I' has an object 'pain'. • Reification of the process into an object creates a mystery. • It is just 'pain', sensation, a process, activity, system response. • Red color has a particular feeling to it: sure! It corresponds to real, specific brain states/processes that differ from brain states associated with other perceptions.

21. But why do qualia exist? Imagine a rat smelling food. In fraction of a second rat has to decide: eat or spit? • Smell and taste a bit. • Request for comments is send to memory from the gustatory cortex. • Memory is distributed, all brain has to be searched for associations. • Request appears as a working memory (WM) pattern at the global brain dynamics level. • WM is small, just a few patterns fit in (about 7 in humans). • Resonant states are formed activating relevant memory traces. • Answer appears: bad associations! probably poison! spit! • Strong physiological reaction starts – perception serves action. • The WM episodic state is stored for future reference in LTM. • Rat has different "feelings" for different tastes. If the rat could comment on such episode, what would it say? • Results of this non-symbolic, continuous taste discrimination have to be remembered and associated with some reactions: qualia!

22. Requirements for qualia System capable of evaluation of their WM states, must claim to have phenomenal experiences and be conscious of these experiences! Minimal conditions for an artilect to claim qualia and be conscious: • Working Memory (WM), a recurrent dynamic model of current global system (brain) state, containing enough information to re-instate the dynamical states of all the subsystems. • Permanent memory for storing pointers that re-instate WM states. • Ability to discriminate between continuously changing states of WM; "discrimination" implies association with different types of responses or subsequent states. • Mechanism for activation of associations stored in permanent memory and for updating WM states. • Act or report on the actual state of WM. • Representation of 'the self', categorizing the value of different states from the point of view of the goals of the system, which are implemented as drives, giving a general orientation to the system.

23. Brain-like computing • I can see, hear and feel only my brain states! Ex: change blindness. • Cognitive processes operate on highly processed sensory data. • Redness, sweetness, itching, pain ... are all physical states of brain tissue. Brain states are physical, spatio-temporal states of neural tissue. In contrast to computer registers, brain states are dynamical, and thus contain in themselves many associations, relations. Inner world is real! Mind is based on relations of brain’s states. Computers and robots do not have an equivalent of such WM.

24. Typical design Haikonen has done some simulations based on a rather straightforward design, with neural models feeding the sensory information (with WTA associative memory) into the associative “working memory” circuits.

25. Conclusions Robots and avatars will make a steady progress towards realistic human-like behavior – think about progress in computer graphics. • Artificial minds of brain-like systems will claim qualia; they will be as real in artificial systems as they are in our brains. • There are no good arguments against convergence of the neural modeling process to conscious artifacts. • Achieving human-level competence in perception, language and problem-solving may take longer than creation of basic consciousness. Creation of conscious artilects will open Pandora’s box What should be their status? Will it degrade our own dignity?Is switching off a conscious robot a form of killing?...Will they ever turn against us ... or is the governor of California already one of them ?