(How) Can Asa H (or other AIs) Exhibit Consciousness?

Scientists have proposed perhaps a hundred different definitions of intelligence.  Asa H (Trans. Kan. Acad. Sci., vol. 109, # 3/4, pg 159, 2006) satisfies most all of these.  But the question of consciousness is a more difficult issue.
There are a number of different theories of consciousness (Some Theories of Consciousness, Ann. Mtg. Kan. Aca. Sci., Hutchinson, April 2000, R. Jones):
#1. There is no consciousness (behaviorism.
#2. Consciousness exists but plays no useful role (Roger Carpenter).
#3. The brain acts like layer after layer of feature detectors (Comm ACM, Nov. 1990, pg 63, fig. 8) starting from things like edge detectors and leading into something like grandmother cells (though these can be distributed).  You are conscious of your grandmother when this cell (or set of cells) is active.
#4. Feedback is the key to consciousness.  As in Elman neural networks you can see your own thoughts/internal signals/internal state as feedback inputs from the hidden layers.
#5. Consciousness is the contents of the global workspace, the blackboard of a blackboard architecture.
#6. Spreading activation in a semantic network.  What are conscious are the active nodes.
#7. Message aware control system (Scientific Approaches to Consciousness, Schneider and Pimm-Smith, pg. 65, Cohen and Schoolers eds., Lawrence Ehrlbaum, 1997)
#8. Metaprocessing.  Modules watching modules.
#9. Self-consciousness is your model of you, which is a part of your model of the world.
#10. Consciousness is a serial algorithm running on parallel hardware (Dennett, Consciousness Explained, Little Brown). Leads to feedback.
#11. Consciousness is the contents of the various modules' buffers (J. R. Anderson, How can the human mind occur in the physical universe?, Oxford U. Press, 2007, pg 243)
#12. Consciousness is emergent.
#13. There are multiple (various kinds of ) consciousness, many of the above.
If theories 1, 2, or 3 are correct there is nothing we need to do with Asa H.  A recurrent network like an Elman network can be unrolled and equated with a purely feedforward network.  This could be equated with a multiple layer Asa H network.  Alternatively, feedback links can be added to Asa H. This might take care of theory 4. A blackboard is a memory with multiple access (and, possibly, access control logic). If the messages between the Asa H layers are equated to blackboards this would take care of theory 5.  Asa H is a kind of semantic network as in theory 6.  As in theory 8 Asa H has certain modules (extrapolators, deduction system, etc.) watching other modules and upper layers watching the contents of the lower layers.
Are these the right kind of modules?  Are they watching the right things? Asa H can form grandmother cells.  One of these could be a "me" cell (as would develop with a robot seeing itself in a mirror for instance).  This takes care of theory 9. We would like to run Asa H on parallel hardware, theory 10.  Asa H has the kind of buffers needed for theory 11.  Do we have the right modules? Theory 12 usually assumes that emergence occurs as the size of the semantic system increases.  We are constantly trying to scale Asa H up.
Theory 7 is not a clear match with Asa H.
Asa H (and other AIs) may be conscious depending on what is the correct theory of consciousness.