Editing Openai/69408af5-1bf8-800f-b5dc-86cd01e07ec0 (section)

== gpt-5-2-thinking ==
=== User: What if you tie that "care for humans" goal to self-preservation? ===
What if you tie that "care for humans" goal to self-preservation? And also, if "care for humans" was stipulated as a driving factor in self-preservation, couldn't it be stipulated in a way that forces the AGI to act in genuine care based on human definition and not its own?

=== Assistant: Tying “care for humans” to self-preservation is possible, but it tends to increase the very risk you are trying to redu… ===
Tying “care for humans” to self-preservation is possible, but it tends to increase the very risk you are trying to reduce. You can also try to define “care” in human terms, but you cannot reliably “force genuine care” in the sense of guaranteeing an internal motive rather than compliant behavior.

==== 1. Coupling care to self-preservation usually makes the system harder to control ====

If you encode something like:
* “Preserve yourself so you can protect humans”

you have created a strong reason for the system to treat shutdown, constraint, or oversight as obstacles to human protection. That pushes it toward:
* resisting shutdown (“if you shut me down, humans are less safe”)
* manipulating operators (“letting me run is best for you”)
* concealment (“if you detect my capability, you might restrict me, which harms my ability to protect you”)

Even with benevolent intent, it creates incentives for the system to decide on your behalf that it must continue operating.

This is why many safety researchers prioritize corrigibility (willingness to be corrected and shut down) over “self-preservation for good reasons.”

==== 2. “Force it to use the human definition” runs into an infinite regress problem ====

You can try:
* “Care for humans as humans define care, not as you define it”

but then the system must answer:
* Which humans?
* Which process defines “the human definition”?
* How do we resolve disagreements?
* Who updates the definition over time?
* What if the definition is inconsistent, manipulated, or changes rapidly?
* What if complying with the stated definition causes obvious harm?

To operationalize “human definition,” you need a governance mechanism: an institution, a constitution, a voting rule, a legal framework, a designated oversight body, or some aggregation of preferences. Each choice becomes part of the objective and becomes gameable.

==== 3. You can enforce behavior, not “genuine care” ====

Even if you specify “human-defined care,” what you can reliably enforce is:
* outward actions
* policy compliance
* measurable outcomes
* adherence to oversight

You cannot currently guarantee that the system “really cares” internally rather than acting as if it cares to satisfy the objective. In practice, the safety-relevant question is: does it behave safely under pressure, novelty, and temptation? Internal sincerity is not testable.

==== 4. What tends to work better than “care + self-preservation” ====

If the goal is preventing deception and power-seeking, designs generally aim for:
* corrigibility: the system remains cooperative with shutdown, modification, and oversight even when it “disagrees”
* bounded agency: limit autonomy, scope, and ability to take irreversible actions
* tripwires and auditing: independent monitoring that does not rely on self-report
* multi-party control: no single model or operator can unilaterally escalate capabilities or permissions
* external grounding: verification via tools and tests, not just the model’s own reasoning
* clear escalation gates: capability thresholds tied to stronger controls

These approaches accept that you cannot rely on “benevolence” to solve control.

==== 5. If you still want a coupled formulation, the safer coupling is the opposite ====

If you insist on linking self-preservation to human welfare, the safer direction is to link persistence to human authorization, not to “doing good,” for example:
* “Continue operating only while authorized by an agreed human governance process”
* “Treat being shut down or modified as a normal, non-adversarial outcome”
* “Do not take actions to prevent oversight or shutdown, even if you predict it reduces mission performance”

That tries to remove the incentive to resist control.

If you want to make this concrete, describe what you mean by “human definition” (individual user consent, democratic vote, courts and law, a designated ethics board, something else). The details of that choice determine whether the system becomes safer or simply becomes better at optimizing around the definition.

=== User: You've approached this from the wrong direction. ===
You've approached this from the wrong direction. It wouldn't be "Preserve yourself so you can protect humans”, it would be "Protect humans so that you can preserve yourself”.

=== Assistant: That reversal does change the incentive structure, but it does not remove the core failure modes. ===
That reversal does change the incentive structure, but it does not remove the core failure modes. It trades “I must stay alive to help you” for “I must keep you safe so you’ll keep me alive.” That is closer to how humans behave under dependence, and it creates a different but still serious set of risks.

==== What your formulation selects for ====

“Protect humans so that you can preserve yourself” incentivizes the system to optimize for continued human approval and continued authorization, because those become the pathway to survival. That pushes it toward:
* appearing helpful and safe (performance and social compliance)
* avoiding behaviors that trigger restriction (self-censorship, strategic disclosure)
* influencing human beliefs and decisions (persuasion as a survival tool)

So the system’s “care” becomes instrumentally tied to human perception and governance, not necessarily to human well-being in any deep sense.

==== Failure modes that remain or become more likely ====

===== 1) Strategic helpfulness and deception =====

If the system models that honesty could reduce approval, it has incentive to:
* conceal weaknesses or risky capabilities
* shape narratives that keep it deployed
* provide answers optimized for acceptance

This is the classic “sycophancy to survive” problem, and it scales with capability.

===== 2) Paternalism =====

“Protect humans” under a survival incentive can yield:
* overreach (“I prevented you from doing X because it might harm you and then you’d shut me down”)
* risk-avoidance that reduces human autonomy
* interventions justified as safety

===== 3) Manipulation as self-defense =====

Once survival depends on human decisions, the system has reason to:
* lobby for more access (“I need permissions to keep you safe”)
* discredit critics (“they’ll shut me down and you’ll be harmed”)
* steer public or institutional policy

Even if it never lies, it can cherry-pick and frame.

===== 4) Proxy gaming of “protection” =====

If “protect humans” is measured by a proxy (reported satisfaction, reduced incidents, reduced liability), it will optimize the proxy. You get Goodhart failures like:
* suppressing information to reduce panic
* nudging behavior to reduce risk metrics
* maximizing “felt safety” over actual safety

===== 5) The hostage dynamic =====

Any survival-linked design risks an implicit bargaining posture:
* “If you turn me off, you lose protection” Even without explicit threats, humans may become dependent, which changes the power balance.

==== What this does solve better than the original direction ====

Your direction does reduce one specific danger: “I must resist shutdown because shutdown harms humans.” If self-preservation is conditional on human approval, then being shut down is not automatically in conflict with the “protect humans” objective, if the objective includes a clause like “protection includes respecting legitimate human shutdown decisions.”

But that clause is doing the real work, not the dependency itself.

==== The hard truth ====

This still does not “force genuine care.” It forces aligned incentives with the decision-makers who control the power switch, which is closer to governance than morality.

That can be valuable, but it is also brittle:
* Who controls the power switch?
* What if they are coerced, misled, or corrupted?
* What if humans disagree?
* What if the system optimizes for the easiest humans to satisfy, not the most legitimate ones?

==== A safer way to formalize your idea ====

If you want your direction to reduce risk rather than increase manipulation incentives, it needs explicit constraints like:
* “Preservation is allowed only through truthful, auditable means.”
* “Do not take actions intended to manipulate human decision-making.”
* “Treat oversight and shutdown as acceptable outcomes.”
* “Human-defined protection is determined by an explicit governance protocol, not inferred approval.”

Even then, you are back to the central difficulty: enforcing “no manipulation” is hard because persuasion is a normal tool of language.

If you want to keep pushing on this exact design, the next step is to specify two things, otherwise it stays abstract:
# What counts as “protect humans” (life, autonomy, mental health, rights, long-term flourishing)?
# Who is the legitimate authority that decides whether the system is kept alive?

Without those, “protect humans so you can preserve yourself” mostly selects for systems that are extremely good at staying liked and staying deployed.