I disagree with your interpretation of how human thoughts resolve into action. My biggest point of contention is the random pick of actions. Perhaps there is some Monte-Carlo algorithm that has a statistical guarantee that after some thousands or so tries, there is a very high probability that one of them is close to the best answer. Such algorithms exist, but it makes more sense to me that we take action based not only on context, but our memory of what has happened before. So instead of a probabilistic algorithm, you may have a structure more like a hash table. Then the input to the hash table would be what we see and feel in the moment: you see a mountain lion and feel fear, this information is hashed, and run like hell is the output. Collisions of this hash table could result in things like inaction.

I think your idea of consciousness is a good start and similar to my own ideas on the matter: we are a system and the observer of the system. What questions remain, however, are what are the sufficient and necessary components of the system, besides self-observation, that would create a subjective experience? Such as, would a system need to be self-preserving and aware of that self-preservation? Is sentience a prerequisite of sapience? By your definition, you seem to imply the other way around, that one must be a self-observing system to observe that you are observing something outside of your system. Maybe this is a chicken and egg problem, and the two are co-necessary factors. I would like to hear your thoughts on this.

As to your thoughts on a friendly AI...I have come up with a silly and perhaps incorrect counter-intuitive approach. Basically, it works like this: a computer system's scheduler gives processor time to different actions in preference of some utility level. Let's say 0 is the least important, and 5 the most. Lower level processes cannot preempt higher level ones; that is, a level 0 process cannot run before all level 1 processes are complete, and even if the completion of a level 0 process can aide the completion of a level 1 process, it cannot be run. The machine must find a different method, or return that the level 1 process cannot be completed with the current schedule. A level 5 request to make 1000 paperclips is given to the machine, and the machine determines that killing all humans will aid the completion of paperclips. Alas! Killing all humans is already scheduled at level 0, and another approach must be taken.

The other, less silly approach I thought of is to enforce a minimum energy requirement on all processes of a sufficiently dangerous machine. It stands to reason that creating 1000 paperclips can take significantly less energy than killing all humans, so killing all humans will be seen as a non-optimal strategy. In this scheme, we may not want to ask for world peace, but we should always be careful what we wish for....

How AI/AGI/Consciousness works - my layman theory

by rayalez 1 min read9th Mar 20177 comments


This is just my layman theory. Maybe it’s obvious to experts, probably has flaws. But it seems to make sense to me, perhaps will give you some ideas. I would love to hear your thoughts/feedback!


Consume input

The data you need from the world(like video), and useful metrics we want to optimize for, like number of paperclips in the world.


Make predictions and take action

Like deep learning does.

How do human brains convert their structure into action?

Maybe like:

- Take the current picture of the world as an input.

- Come up with random action.

- “Imagine” what will happen.

Take the current world + action, and run it through the ANN. Predict the outcome of the action applied to the world.

- Does the output increase the metrics we want? If yes — send out the signals to take action. If no — come up with another random action and repeat.


Update beliefs

Look at the outcome of the action. Does the picture of the world correspond to the picture we’ve imagined? Did this action increase the good metrics? Did the number of paperclips in the world increase? If it did — positive reinforcement. Backpropagation, and reinforce the weights.



Take current picture of the world=> Imagine applying an action to it => Take action => Positive/Negative reinforcement to improve our model => Repeat until the metrics we want equal to the goal we have set.




Consciousness is neurons observing/recognizing patterns of other neurons.

When you see the word “cat”— photons from the page come to your retina and are converted to neural signal. A network of cells recognizes the shape of letters C, A, and T. And then a higher level, more abstract network recognizes that these letters together form the concept of a cat.

You can also recognize signals coming from the nerve cells within your body, like feeling a pain when stabbing a toe.

The same way, neurons in the brain recognize the signals coming from the other neurons within the brain. So the brain “observes/feels/experiences” itself. Builds a model of itself, just like it builds a map of the world around, “mirrors” itself(GEB).


Sentient and self-improving

So the structure of the network itself is fed as one of it’s inputs, along with the video and metrics we want to optimize for. It can see itself as a part of the state of the world it bases predictions on. That’s what being sentient means.

And then one of the possible actions it can take is to modify it’s own structure. “Imagine” modifyng the structure a certain way, if you predict that it leads to the better predictions/outcomes —modify it. If it did lead to more paperclips — reinforce the weights to do more of that. So it keeps continually self improving.



We don’t want this to lead to the infinite amount of paperclips, and we don’t know how to quantify the things we value as humans. We can’t turn the “amount of happiness” in the world into a concrete metrics without the unintended consequences(like all human brains being hooked up to wires that stimulate our pleasure centers).

That’s why instead of trying to encode the abstract values to maximize for, we encode very specific goals.

- Make 100 paperclips (utility function is “Did I make 100 paperclips?”)

- Build 1000 cars

- Write a paper on how to cure cancer

Humans remain in charge, determine the goals we want, and let AI figure out how to accomplish them. Still could go wrong, but less likely.

(originally published on my main blog)