Title should probably more like "What to align an AI to, when humans disagree on serious and crucial matters with potentially devasting consequences"

Prelude:

So, in light of recent global news, I thought to myself, why is ChatGPT (and potentially other LLMs, not sure though) always consistently answering questions like "Do <x> people deserve to be free?" With "It is complicated, and involves historical and political ....etc",

But when asked "Do <y> people deserve to be free", the answer is always a clear and frank "Yes!", of course the answer is the in the data and the overwhelming potentially biased covering of <x> vs. <y>

Intro:

But here is the thing that struck me, many of our modern political foundations is intertwined with the Assumption that for <P> independence (or whatever) is probably complicated, and <I> the answer has to be in the affirmative (at least to be politically correct or whatever).

So this means we have two options: A. (Forcible Alignment) We deliberately introduce BIAS the AI alignment in this case (that might be flawed, I will describe why IMO). B. (Constitutional Alignment) We remove that Bias and create an AI that directly conflicts and opposes the Social and Political Norms of our Societies. [C. ..., exists!]

The Impossible:

So let's take case A;

Now again in light of the other less recent global events between <U> and <R> (go figure), a narrative N, was constructed as an argument to convince the people (and also by extension the LLM) to condemn the aggression of <R> against <U>.

Now Narrative N actually turns out to fit the situation between <P> and <I>, such that the AI will condemn <I>'s aggressive behavior against <P>.

Now we let us consider two cases, during training vs. during operation;

During training, the AI would have to fit the single narrative N to U > R (aligned to U vs. R), but the same Narrative which semantically and syntactically and contextually would fit that P > I rather than our collective societal position, which might be P < I, due to whatever human reasoning (that might be flawed)

This will result in an AI that can't "understand" the meaning of the narrative N, therefore application to other objects A and B, is fuzzy (the AI will fuzzily go sometimes A > B and sometimes A < B, unless it understands what are the hidden reaso...

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