We’ve had it all wrong.


All this time, we’ve had it all wrong.

Artificial Intelligence (AI) has been a science for over 50 years now, and in that time has accomplished some amazing things – computers that beat human players at chess and Jeopardy, find the best routes for delivery trucks, optimize drug delivery, and many other feats.  Yet the elusive holy grail of “true AI”, or “sentient AI”, “artificial general intelligence” – by whatever name, the big problem – has remained out of our grasp.

Look at what the words actually say though – artificial intelligence.  Are we sure that intelligence is really the crucial aspect to creating a sentient machine?

I claim that we’ve had it wrong.  Think about it: intelligence is a mere mechanical form, a set of axioms that yield observations and outcomes.  Hypothesis, action, adjustment – ad infinitum.  The theory has been if we could just create the recursively self-optimizing intelligence kernel, BOOM! – instant singularity.  And we’d have our AGI to run our robots, our homes, our shipping lanes, and everything imaginable.

The problem with this picture is that it assumes intelligence is the key underlying factor.  It is not.

I claim the key factor is…

…wait for it…

Consciousness.

Consciousness might be defined as how ‘aware’ an entity is of itself and its environment, which might be measured by how well it was able to distinguish things like where it ends and its environment begins, a sense of agency with reference to past actions it performed, and a unified experience of its surroundings that gives it a constantly evolving sense of ‘now’.  This may overlap with intelligence, but it is a different goal: looking in the mirror and thinking “that’s me” is different than being able to beat humans at chess.  A robot understanding “I broke the vase” is different than an intelligence calculating the Voronoi diagram of the pottery’s broken pieces lying on the floor.

Giulio Tononi’s work rings a note in harmony with these ideas.  Best of all, he and others discuss practically useful metrics of consciousness.  Whether Integrated Information Theory is the root of all consciousness or not is immaterial; the point is that this is solid work in a distinctly new direction, and approaches the fundamental problems of AI in a completely new way.

Tononi’s work may be a viable (if perhaps only approximate) solution to the binding problem, and in that way could be immensely useful in designing systems that have a persisting sense of their evolving environment, leading us to sentience.  It is believable that intelligence may be an emergent property of consciousness, but it seems unlikely that intelligence alone is the ingredient for consciousness itself, and that somehow a certain ‘amount’ of intelligence will yield sentience.  One necessarily takes precedence over the other.

Given this, from now on I’ll be focusing my work on Artificial Consciousness, which will differ from Artificial Intelligence namely in its goals and performance metrics: instead of how effectively an agent solved a problem, how aware it was of its position in the problem space; instead of how little error it can achieve, how little ambiguity it can achieve in understanding its own boundaries of existence (where the program ends and the OS begins, where the robot’s body ends and the environment begins).

I would urge you to read Tononi’s work and Adam Barrett’s work here.  My Information Theory Toolkit (https://github.com/MaxwellRebo/ittk) has several of the functions you’ll need to start experimenting on systems with a few more lines of code (namely, use Kullback-Leibler divergence).

In the coming months, I’ll be adding ways to calculate the Information Integration of abstracted systems, or its Phi value.  This is NP-Hard, so it will have to remain in the domain of small systems for now.  Nonetheless, I believe if we start designing systems with the intent of maximizing their integration, it will yield some system topologies that have more beneficial properties than our usual ‘flat’ system design.

Artificial Intelligence will no doubt continue to give us great advances in many areas, but I for one am embarking on a quest for something subtly but powerfully different: Artificial Consciousness.

Note: If you have some programming skill and would like to contribute to the Information Theory Toolkit, please fork the repository and send me an email so we can discuss possibilities.  I’ll continue to work on this as I can.

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