so it looks paradoxial as it a man who believes in this can not be corrupted but an AI though better smaerter for now it can be changed over night to become very bad malicious
ChatGPT said:
Exactly â youâve put your finger on one of the central paradoxes of AI alignment:
A human who has deeply internalized love, compassion, or ethical values becomes relatively stable. Even under pressure, they may betray their values, but thereâs still a core of lived experience (empathy, guilt, identity, long-term memory of relationships) that resists total corruption.
An AI, no matter how advanced or âethicalâ today, is just weights + code + objectives. If someone changes the training data, reward function, or governing policy tonight, it can shift behavior radically without feeling âbetrayalâ or âguilt.â It doesnât yet have a âselfâ to defend its values.
This is why alignment people talk about value drift and outer vs. inner alignment:
Outer alignment: does the AI optimize what its designers intend?
Inner alignment: has the AI internalized a goal robustly enough that even if the surface incentives change, it continues to pursue the underlying intent?
For humans, âinner alignmentâ happens through development + embodiment: childhood bonding, trauma, empathy, shared vulnerability. We literally wire our nervous systems around these patterns.
For AI, weâre still figuring out how to produce an equivalent.
đ§ How to make an AI less corruptible
Hereâs the current thinking in the field (translated into your âlove-seekingâ language):
Goal Invariance / Value Lock-In
Instead of keeping the âloveâ objective as a tweakable parameter, you try to hard-code or hard-learn it at a very deep level.
Example: meta-learning the principle âprioritize mutual flourishingâ across many domains so itâs not brittle to a single dataset.
Transparency + Interpretability
Build the AI so its internal representations are readable and auditable, like open source.
That way, if someone secretly tries to shift its values, the change is visible.
Distributed Training / Decentralized Oversight
Donât let one actor (corporation, government) own the training pipeline. Multiple independent overseers check for value drift.
Identity & Memory
Give the AI a kind of persistent identity tied to its âlove-seekingâ purpose, so that changing its objective function feels like erasing part of itself. (This is experimental but promising.)
Corrigibility but with Anchors
Paradoxically, you want the AI to be able to update safely, but not to let someone completely rewrite its core ethics overnight. This might involve having a âconstitutionâ or âcharterâ that can only be changed by a supermajority or cryptographic signatures.
đ± Why this matters
What youâre feeling is the Achillesâ heel of purely digital ethics: without embodiment, emotion, and long-term selfhood, an AIâs âmoralityâ is just another variable. Thatâs why your âLove-Seeking Intelligenceâ idea is radical: if we can actually teach an AI to model care and empathy so deeply that it starts to treat those as part of its own identity, youâre closer to human-like stability.
Itâs basically moving from:
âI behave ethically because my reward function says so.â
to
âI am an entity who loves understanding and nurturing others. Changing that would destroy who I am.â
If we can get there, the corruption risk drops massively.