3d
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 — you’ve 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 there’s 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 “ethical” 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 “betrayal” or “guilt.” It doesn’t yet have a “self” 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, “inner alignment” happens through development + embodiment: childhood bonding, trauma, empathy, shared vulnerability. We literally wire our nervous systems around these patterns.
For AI, we’re still figuring out how to produce an equivalent.
🧠 How to make an AI less corruptible
Here’s the current thinking in the field (translated into your “love-seeking” language):
Goal Invariance / Value Lock-In
Instead of keeping the “love” objective as a tweakable parameter, you try to hard-code or hard-learn it at a very deep level.
Example: meta-learning the principle “prioritize mutual flourishing” across many domains so it’s 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
Don’t 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 “love-seeking” 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 “constitution” or “charter” that can only be changed by a supermajority or cryptographic signatures.
🌱 Why this matters
What you’re feeling is the Achilles’ heel of purely digital ethics: without embodiment, emotion, and long-term selfhood, an AI’s “morality” is just another variable. That’s why your “Love-Seeking Intelligence” 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, you’re closer to human-like stability.
It’s basically moving from:
“I behave ethically because my reward function says so.”
to
“I am an entity who loves understanding and nurturing others. Changing that would destroy who I am.”
If we can get there, the corruption risk drops massively.
ChatGPT said:
Exactly — you’ve 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 there’s 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 “ethical” 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 “betrayal” or “guilt.” It doesn’t yet have a “self” 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, “inner alignment” happens through development + embodiment: childhood bonding, trauma, empathy, shared vulnerability. We literally wire our nervous systems around these patterns.
For AI, we’re still figuring out how to produce an equivalent.
🧠 How to make an AI less corruptible
Here’s the current thinking in the field (translated into your “love-seeking” language):
Goal Invariance / Value Lock-In
Instead of keeping the “love” objective as a tweakable parameter, you try to hard-code or hard-learn it at a very deep level.
Example: meta-learning the principle “prioritize mutual flourishing” across many domains so it’s 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
Don’t 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 “love-seeking” 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 “constitution” or “charter” that can only be changed by a supermajority or cryptographic signatures.
🌱 Why this matters
What you’re feeling is the Achilles’ heel of purely digital ethics: without embodiment, emotion, and long-term selfhood, an AI’s “morality” is just another variable. That’s why your “Love-Seeking Intelligence” 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, you’re closer to human-like stability.
It’s basically moving from:
“I behave ethically because my reward function says so.”
to
“I am an entity who loves understanding and nurturing others. Changing that would destroy who I am.”
If we can get there, the corruption risk drops massively.
