Gold-Standard AGI: 1: Normative ASI Superalignment

In order to maximise the net benefit of AGI (Artificial General Intelligence, and, in particular, agentic superintelligent AGI, a.k.a. Artificial Superintelligence, or ASI) for all humanity, without favouring any subset thereof, we imagine a Gold-Standard AGI that is practically-maximally-aligned and practically-maximally-validated. The first of these properties --- alignment --- may be decomposed into normative alignment (how do we define a final goal $\mathbf{FG}_G$ which, if pursued as intended, ensures practical-maximal-alignment?), and technical alignment (how do we build a practically-maximally-validated agent $G$ that pursues $\mathbf{FG}_G$ as intended?). This paper presents a conceptual and philosophical foundation for AGI, culminating in a proposed (and, to the best of our knowledge, novel) implementation-neutral solution to the normative AGI alignment problem in the case that $G$ is superintelligent (hence "superalignment"). The net effect of our proposed solution (the $\mathbf{TTQ}$+$\mathbf{NAP}$ combination) is to reduce the (seemingly impossible) problem of building a practically-maximally-aligned agentic superintelligence $S$ to the (much easier) problem of building an $\mathbf{NAP}$-compliant non-agentic "goal-less superintelligent-agent-under-construction" $S^-$ (where $S$ = $S^-$ + final goal $\mathbf{TTQ}$, and $S$ is practically-maximally-validated).