Making High-Level AI Design Decisions Explicit Using a Binary Stream System-Designation Approach
CoRR(2024)
Abstract
Some crucial decisions in AI design tend to be overlooked or factor choices
are assumed implicitly. The question often answered first is what the AI will
do, not how it will interact with the rest of the world. This reduces our
understanding of the possible types of AI that can be developed and their
potential impacts on humanity. As an initial AI taxonomy, I present binary
choices for 10 of the subjectively most separable and influential high-level
design factors, then give brief examples of several of the 1024 possible
systems defined by those choices. This supports a simple binary stream approach
to system designation based on translating the stream of choices into decimal
notation, giving a short-hand way of referring to systems with different
properties that meet specialized needs. Further, underspecified or generic
systems can be designated using the binary stream approach as well, a
notational feature that supports modeling the impacts of AI systems with
selected characteristics.
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