claim

active

claim:all-current-extrinsic-alignment-methods-clearly-struggle-with-scale-resilience-power-seeking-value-axioms-and-inner-alignment-at-superintelligent-scales

All current extrinsic alignment methods clearly struggle with scale resilience, power-seeking, value axioms, and inner alignment at superintelligent scales

Motivating claim for why Contemplative AI is needed beyond existing approaches

Source paper

extracted_from

Contemplative Agent

(2025) · Ruben Laukkonen · Fionn Inglis · Shamil Chandaria · Lars Sandved-Smith +4

Neighborhood — ranked by edge-count

Claims (1)

claim

Robust alignment requires intrinsic self-reflective adaptability embedded in the system's world model rather than brittle top-down rules
extends
Central thesis distinguishing Contemplative AI from prior alignment approaches

Quotes (1)

quote

"It is certainly very hard, and perhaps impossible, for mere humans to anticipate and rule out in advance all the disastrous ways the machine could choose to achieve a specified objective."
supports
Russell's statement opening Section 2 articulating the core motivation for the Contemplative AI approach

Related by similarity (8)

cosine ≥ 0.65 · no typed edge

Entities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.

Contemplative wisdom traditions have grappled with the human version of the alignment problem for millennia, aiming to cultivate resilient alignment in the form of personal contentment and social harmonyclaim0.773
Foundational analogy motivating the entire Contemplative AI approach
The results generalise readily to non-equilibrium systems where scaling relationships remain similar (e.g., dynamic or localised scaling).claim0.772
Claim about broader applicability of the scaling argument
Mindfulness, emptiness, non-duality, and boundless care together provide resilient alignment primitives addressing all four meta-problemsclaim0.758
Core integrative claim synthesizing the four contemplative principles into a complete alignment framework
Availability to unfolding needs in the here and now serves as a kind of meta-rule for alignment that scales with intelligenceclaim0.753
Central claim in Section 4 proposing present-moment responsivity as overarching alignment principle
Antipodal alignment between related datasets (e.g., larger_than and smaller_than) in smaller models resolves to common-direction alignment in larger modelsclaim0.751
Scale-dependent structural finding from PCA visualizations in §4
In buildings, especially, the success of the process will be judged by the extent to which these middle-range entities appear with their own distinct symmetries, with their own definite and distinct force as strong centers.claim0.751
Proposes middle-range entity quality as the criterion for judging the success of a building process
How Do Phase Synchronization And Inner Alignment Relatequestion0.750
The conflict between the model's existing preferences and the stated training objective is the key driver of alignment faking in this setupclaim0.748
Authors' interpretation of prompt variation results showing alignment faking disappears only when conflicting objective is removed