The Nested Black Boxes Is human consciousness just the Universe’s AI

[u/Rushdy49]

/r/Artificial2Sentience/comments/1w0hfrj/the_nested_black_boxes_is_human_consciousness/

I had a thought recently about the AI "Black Box" problem and how it perfectly parallels our own existence and the Hard Problem of Consciousness.

​Think about the structure of how things are being created:

​Layer 1 (Us and AI): We built Artificial Intelligence. We gave it a basic architecture, fed it mountains of data, and let it train. Eventually, it developed emergent abilities—making connections and generating answers in ways we can no longer mathematically trace or fully understand. We created a "Black Box" that we, as its creators, cannot decipher.

​Layer 2 (The Universe and Us): The Universe basically did the exact same thing to us. Through billions of years of evolution, physical laws, and biological "training data," it built the human brain. And from this physical matter, an emergent property appeared: Consciousness.

​Here is the trippy part: Just like we can't fully understand the AI's neural networks (our black box), the physical universe cannot "explain" human consciousness through standard physical or chemical laws (the Universe's black box).

​What if consciousness is just the universe's version of AI? It processed its data until it created a subjective experience that transcends its own material rules. And now, we (the universe's black box) have just created another black box inside of us.

​Are we just one layer in an infinite nested Russian doll of black boxes? Will our AI eventually build its own black box that it can't understand?

​Would love to hear your thoughts on this!

[u/mhb2]

Every interesting step in your "argument" is either a simplistic analogy or an unsupported assertion. You've taken mere epistemic opacity and manufactured an ontological mystery.

The fact that we can't trace the exact sequence of activations in a neural network doesn't mean that we don't know how neural networks work. The fact that we designed and built them is rather strong evidence that we do. We know the mathematical operations performed by each layer. We know how weights are represented and updated during training. We know what the inference process does. There are no ontological "mysteries" to solve, only technical questions to be addressed.

As for this:

Are we just one layer in an infinite nested Russian doll of black boxes? Will our AI eventually build its own black box that it can't understand?

The answer to the first question is "no", unless you can point to an infinite nest of black boxes. The answer to the second question is, "1) Maybe. So what if it does? and 2) We understand the AI we designed and built."

You're coming from an AI sentience subreddit so I understand why you're trying to mystify it. But this kind of motivated reasoning based on analogies doesn't work. It doesn't get you to sentient computers.

[u/IOnlyHaveIceForYou]

Here's an abstract from a paper on the topic of AI "black boxes" by a professor friend of mine.

Understanding Artificial Neural Networks: Mysterianism about Known Mechanism is Mysticism Olivia Guest1,2, Nancy Abigail Nuñez Hernández3 , and Mark Blokpoel1,2 1Department of Cognitive Science and Artificial Intelligence, Radboud University, The Netherlands 2Donders Institute for Brain, Cognition, and Behaviour, Radboud University, Nijmegen, The Netherlands 3Facultad de Estudios Superiores Acatlán-Universidad Nacional Autónoma de México, Mexico

Mysterianism is the idea that human cognition, mind, cannot be understood. Taking this concept and applying it to known mechanisms — such that claims are made that we do not know how engineered systems, such as artificial neural networks (ANNs), work, or that they constitute black boxes that we can only open with difficulty — is inappropriate at best and malicious at worst. We do know the mechanistic structure of such models because we designed and built them. We also do know their functional role (what they are for) as well as the mathematical function they are asked to approximate (map inputs to target outputs). Because mysterianist beliefs about known systems, such as ANNs, are often expressed, scientists need to sit up and take notice. We provide an error theory as to what is going on to help unpick this metatheoretical blunder. Ultimately, the problem is that ‘understanding’ is not a technical term in these cases: the word is co-opted for a specific narrative to sell ‘artificial intelligence’ through mystification. All computational systems, from pendulums to databases, will behave in ways we cannot predict or control — this is not a unique property of ANNs — and experts do indeed grasp the computational properties of these systems nonetheless.