Transformation functions and the paradox of Utopia

2022-05-15

A standard narrative of the utopians can be somewhat formally deduced as such:

(1) There exists a current state of the world, say, `S(t)`, with the life of all people being sub-optimal, say, `avg(P(t)) <<< THRESH`; where `P(t)` is the wellness of people in `S(t)` and `THRESH` is some global threshold of wellness of all the people in the world.

(2) There will be a better ideal utopian world `S(t+1)`, where `P(t+1) >= THRESH` or ideally, `P(t+1) >>> THRESH`.

Given the above two statements as the axiomatic statements of the utopians, the missing element seems to be an understanding of the nature of the function that transforms `S(t)` into `S(t+1)`. Clearly, `S(t+1)` is dependant on `S(t)`? And clearly we must need multiple iterations `t, t+1, t+2,... t + n` until really `S(t+n) > S(t)`; because it might be impossible that one epoch yields a better `S`?

``````S(t+1) = transform_world(current_state = S(t))

def transform_world(current_state: S) -> S:
# what happens here?
# does this have side effects?
# how does it affect P(t)?
``````

Then, `∀ p ∈ P`, what will `p(t+1)` be? The question of course is; what is acceptable? Must it be that `p(t+1) > p(t) ∀ p ∈ P`? or is it good enough that for `i ∈ P` and `j ∈ P`, `j(t+1) >>> i(t+1)`, where `len(i) >>> len(j)`, however of course satisfying the utopian condition of `P(t+1) = i(t+1) + j(t+1) >>> THRESH >>> P(t)`?

If you know of any literature that extensively talks about the algorithm of the tranformation function itself, i.e. the actual inner details of `transform_world()` and the resulting `S` in each iteration than the usual ones which usually state that `S(t)` is bad, but `S(t+1)` can be better immediately -- then please write to [email protected].

If you wish to contribute to develop this thought experiment further, write to [email protected]; or discuss this post on /r/philosophy.