  "Value alignment" (VA) is considered as one of the top priorities in AI
research. Much of the existing research focuses on the "A" part and not the "V"
part of "value alignment." This paper corrects that neglect by emphasizing the
"value" side of VA and analyzes VA from the vantage point of requirements in
value theory, in particular, of avoiding the "naturalistic fallacy"--a major
epistemic caveat. The paper begins by isolating two distinct forms of VA:
"mimetic" and "anchored." Then it discusses which VA approach better avoids the
naturalistic fallacy. The discussion reveals stumbling blocks for VA approaches
that neglect implications of the naturalistic fallacy. Such problems are more
serious in mimetic VA since the mimetic process imitates human behavior that
may or may not rise to the level of correct ethical behavior. Anchored VA,
including hybrid VA, in contrast, holds more promise for future VA since it
anchors alignment by normative concepts of intrinsic value.
