  Prior work has explicated the coloniality of artificial intelligence (AI)
development and deployment through mechanisms such as extractivism, automation,
sociological essentialism, surveillance, and containment. However, that work
has not engaged much with alignment: teaching behaviors to a large language
model (LLM) in line with desired values, and has not considered a mechanism
that arises within that process: moral absolutism -- a part of the coloniality
of knowledge. Colonialism has a history of altering the beliefs and values of
colonized peoples; in this paper, I argue that this history is recapitulated in
current LLM alignment practices and technologies. Furthermore, I suggest that
AI alignment be decolonialized using three forms of openness: openness of
models, openness to society, and openness to excluded knowledges. This
suggested approach to decolonial AI alignment uses ideas from the argumentative
moral philosophical tradition of Hinduism, which has been described as an
open-source religion. One concept used is vi\'{s}e\d{s}a-dharma, or particular
context-specific notions of right and wrong. At the end of the paper, I provide
a suggested reference architecture to work toward the proposed framework.
