Presentation on theme: "Interactive Empiricism: The Philosopher in the Machine Ron Chrisley COGS/Informatics University of Sussex."— Presentation transcript:
Interactive Empiricism: The Philosopher in the Machine Ron Chrisley COGS/Informatics University of Sussex
Take-home message Philosophy & Engineering: A two-way interaction 1.Some philosophical breakthroughs may only come about through attempting to design and build working systems (engineering helps philosophy) 2.Building complex systems (e.g. an artificial consciousness) might require incorporating scientists and philosophers into the design, modelling: –How they affect the system dynamics –How they system dynamics affect them
Direction 1: Engineering conceptual change
Conceptual problems Not all limitations on our scientific understanding are a matter of insufficient data E.g., consciousness: –Naturalist intuition: consciousness (like everything else) is at root a physical phenomenon –"Zombie hunch": It is possible for there to be a creature physically identical to you, but nobody's home
Conceptual change Best diagnosis: It is our concept of consciousness that is to blame One solution: change our concept of consciousness, so that we no longer suffer from the zombie hunch
Conceptual conceptual change? But it seems unlikely that this conceptual change could itself come about purelyconceptually, merely by, e.g.: –Acquiring more beliefs –Philosophical argumentation –Reading journal articles
Non-conceptual conceptual change Rather, problems of consciousness seem to require a non-conceptual development in our concepts (Bad) examples of non- conceptual change: –Getting hit on the head –Undergoing neurosurgery –Taking drugs?!
Non-conceptual conceptual change Better: change that is non- conceptual, but still: –Rational –Justified –Based on experience of the subject matter What kind of change/learning could this be?
Concepts as skills Wittgenstein: What underlies being able to move between ways of seeing something (e.g. duck-rabbit) is the "mastery of a technique" Then (some) concept acquisition is like skill acquisition –Just as one can't read/argue/theorize your way to knowing how to ride a bike… –…so also with some concepts; one must experience the phenomenon to understand it
Interactive empiricism But not just passive experience (normal empiricism) Rather, interaction: mastery of how one's experiences of the subject change in the light of one's different interventions (interactive empiricism)
Interaction is essential to… Perception (O'Regan and Noë: Sensory-motor contingency theory ) Consciousness (Hurley: Consciousness In Action) Cognition (Bickhard: "Interactivism: A Manifesto") Mammalian visual development (Held and Hein)
Meta cognitive science: Theorist as subject A science of human cognition in general should apply to the cognition of cognitive scientists in particular If the cognitive science is right that cognition is essentially interactive… …then doing cognitive science (or AI) should be as well
Engineering as interaction But what kind of interaction? Perception of brain states (one's own and others') during manipulation (social, physical, etc.)? –Limited –(compare doing something similar with a computer) Better: attempt to design and build cognitive systems, and observe them working (or failing to!): Engineering
An aside: The Mary problem Jackson's Knowledge Argument against a physical science of consciousness –Mary knows everything the physical sciences can tell us about colour, but has never seen red –Will she acquire some knowledge when she sees red for the first time? –Yes, she will learn what it is like to see red –So there is knowledge of consciousness the physical sciences cannot provide
Solving the Mary problem But science is essentially interactive So although Mary may have read every possible book about color vision… …she doesn't have all the knowledge involved in doing color science Or rather, if we assume that she has all such knowledge, then it is a contradicition to also assume that she has never interacted with redness (i.e., seen red)
Direction 2: The philosopher in the machine
We are a part of the systems we build Just as interaction can have a crucial, beneficial effect on the theorist/philosopher… …so also can it have such an effect on the system being designed/built
We are a part of the systems we build Q: What has been the biggest engineering advance in AI in the last 20 years? A: Kismet's eyebrows (Breazeal et al)
Interacting with Kismet Kismet could only learn to visually track objects if trained on suitable stimuli This required a trainer to wave objects in front of Kismet at a certain speed, distance, etc. How to ensure this efficiently? Exploit affective responses in the trainer: if trainer gets too close, Kismet jumps back, and raises eyebrows Trainer readjusts without having to be instructed, understand physics of the system, etc.
Combining directions 1 and 2 If we are part of the system, then not only can we have a beneficial causal effect on the robot's performance, but vice versa Thus, instead of trying to design an AI/machine consciousness in one step… …why not instead design a system S1 so that it will prompt conceptual changes in us… …that will enable us to design an S2 that will prompt changes in us… …that will enable us to design an S3… …and so on?
Frank Herbert's prescience In the science fiction novel Destination: Void, the author of Dune speculated that the best way to create a machine consciousness might be to design a situation in which: –Carefully engineered people (clones) –In a carefully engineered technological environment (computers, spaceship, neural wetware) –Are manipulated and motivated to find a way to create machine consciousness (e.g., they will die if they don't!) –A crucial part of the project is for the challenges they face and the technology they build to play a role in them figuring out what consciousness is (conceptual change!)
From fiction to fact? Perhaps it is not too far-fetched to suggest that something like this could be developing –Not just work like Kismet –But also, e.g., the search for creative technologies: environments, document systems, brain wave induction devices etc. that facilitate insight –Synthetic phenomenology: interactive familiarity with a robotic system as a way of developing a means of specifying linguistically inexpressible experiential content (e.g., Chrisley and Parthemore)
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