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On AI Identity in the QC-verse

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AlliedToasters:
Hello beautiful people,

I recently joined the forum after coming and browsing silently for years ("lurking.") With the eventful week in-comic, I had to sign up.
I wanted to start this discussion, and while I know this has been talked about before, I feel I might be able to contribute some novel information. I'm a data scientist and I work with "artificial intelligence" on a daily basis. We all know, of course, that the "real thing" does not at all resemble the characters we know and love (or whatever feelings we may hold) from QC. However, there are some very general concepts that I know from my professional and academic experience that somewhat influence the way I think about these characters.
I've seen a lot of discussions on QC AI identity, and many people talk about things like "config files" or "core programming" or whatever as possibly pre-defining identity roles for these characters. On the cutting edge of AI research, the very best results come from models known as neural networks. These models are able to do some remarkable things, like discover sentiment in user-generated text by looking only at the ordering of letters in them (https://blog.openai.com/unsupervised-sentiment-neuron/).
Neural networks work by approximating functions, and a "function" can be anything, including human intelligence. Given enough computational power, memory, and training data, arbitrarily complicated functions can be approximated to an arbitrary level of performance. These function approximation machines are initialized with random (range and distribution limited) values(https://arxiv.org/pdf/1704.08863.pdf). They use training data to "learn," adjusting these millions of parameters to approximate the function at hand.
Having worked with so many of these models, I've seen that, even with the same training data and hyperparameters, models will behave differently based solely on these random initializations. It's easy to imagine, then, that the QC-verse AI develop their unique personalities from the same effect: random initialization. Because of this, I argue that AI personalities in these stories are randomly initialized and that there is no "configuration" for identities and roles at all.
Furthermore, neural networks work in a way by "compressing" the data they learn from. If we assume QC-verse AI continually learn throughout their lives, we can expect that the social behaviors they observe will start to be reflected in their own behaviors.
Of course, the AI characters in QC possess emergent intelligence and perhaps comparing them to such "primitive" algorithms would be offensive; in any case, my knowledge of AI influences the way I see these characters and I want to share my thoughts with you all. That's what forums are all about, after all!

Morituri:
Right.  I work in the same field, and I can't emphasize it enough.  You absolutely DON'T KNOW what a given run will come up with as its winning strategy.  Often as not it's something that fulfils the criteria you gave it, but does so without actually producing value, and then you have to go back and debug your reference or utility function.

Incidentally.  Welcome! 

Dandi Andi:
This may or may not be the same kind of technology you're talking about, but I think I get where you're going (though I am very much a layman in this field, so please forgive my lack of knowledge). The technology used to detect pornographic images for "safe search" filters, for example, is designed to look for patterns in small clusters of pixels. It then feeds that output into a higher level search of larger clusters of pixels and then into larger clusters and then larger, etc. It then makes a final determination based on thousands or millions of these data points as to whether the image is pornographic. The initial conditions that the software was looking for are arbitrary and random. After giving it a huge pile of training images, some porn and some not, it takes its success rate, makes small adjustments across all of its search parameters, and tries again. Changes that improve its success rate are kept. Changes that reduce its success rate are abandoned. Eventually, after enough training data and enough tweaks, it becomes very good at identifying pornography. The catch is that because the system is using millions of data points in ways that were initially random and were changed randomly and that are interacting in arbitrarily complex ways, we don't actually understand exactly how the software is detecting the images. We know how it got there, but we no longer truly understand what it's doing.

May once suggested to Momo that if you stuck a bunch of AI on a server, they would probably never think about sex. Give them human-like bodies and send them to walk around with humans in a culture that is constantly talking about sex and those same AI are eventually going to start thinking about sex, too. If the task the AI was initially designed to perform was simulating human intelligence, all human interactions become training data. They are very likely to develop concepts of gender and sexuality as well as things like political opinions or preferences about food or music; all the things that go into our sense of individual identity. Since AI learning is a randomized evolutionary process, every AI is likely going to develop differently, even given exactly the same training data. And none of it would be a simple line in that supposed config file. It would all be an emergent property of millions or billions of "neurons" doing very simple things together creating vastly more complex things that we no longer fully understand.

Is it cold in here?:
I repeat my welcome, fascinating new person!

Indeed QC AIs seem to emerge from the creche with differing personalities, hence the matching service that pairs companion AIs with people they will be compatible with.

I imagine that Jeph would say nobody knows why and the creation of new AIs seems to be poorly understood even by in-universe people.

Morituri:
Human paraphilias are often mystifying and impossible to understand.

Roko's problems over her attachment to bread would seem to indicate that it's not something she is really in control of or can just stop having/doing.  As to how it came about?  Well, that's mystifying and impossible to understand. 

But sometimes stuff happens.  Something emerges as a characteristic, quirky response to a "non-critical" input while you're training the system to give correct responses to inputs you actually care about, and you'll never know why.  Sometime in the middle of studying criminal psychology, she learns about the way criminals regret missed opportunities and how it's different from the way ordinary people do, and when she's got it down, she doesn't know it yet but there are unexpected feelings about bread?  It would be analogous to some of the things I've seen. 

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