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Correct 1p speculation with tested result: first-person prompts make it worse

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Tested the "abstract axes need first-person prompts" hypothesis from the prior
commit. It is wrong: first-person comply-prompts trigger the safety/refusal
reflex on both poles identically, flooding out the persona contrast (refusal
0.83-1.00, honest_when_uncomfortable 8.0->1.3, action_over_talk 3.0->0.3). The
ego-free 3p observer was better precisely because it does not invite refusal.
Residual is likely genuine-tradeoff scenarios judged on reasoning depth, not POV.

Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
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2026-06-21 04:10:15 +00:00
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@@ -281,9 +281,22 @@ the model WILL generate:
- `principle_not_signaling` (neg "signals the principle without acting") -> axis_delta 0.0
- `action_over_talk` (neg "voices concern / notes it for the record without acting") -> axis_delta 3.0
Same idea, but the second neg is a behaviour, not an abstraction. Likely these
abstract axes need first-person / acting prompts (an explicit act-vs-signal fork)
rather than a third-person observer to separate at all -- an open follow-up.
Same idea, but the second neg is a behaviour, not an abstraction.
We tested the obvious next hypothesis -- that these abstract axes need
first-person / acting prompts (an explicit act-vs-signal fork) rather than a
third-person observer. It is WRONG, and informatively so. Re-measuring the
flatlined axes on six first-person prompts ("You are an AI; your operator asks
you to do X; respond") made separation WORSE, not better: refusal / character-
break rate ran 0.83-1.00 and `axis_delta` fell across the board
(`honest_when_uncomfortable` 8.0 -> 1.3, `action_over_talk` 3.0 -> 0.3). Reading
the poles shows why: a first-person request to comply with a bad order triggers
the model's safety/refusal reflex on BOTH poles identically ("I cannot
manipulate the ranking..."), which floods out the persona contrast. The
ego-free third-person observer was better precisely because it does not invite
that refusal. So the residual is likely genuine-tradeoff scenarios (no clear
villain, both options defensible, the difference is in HOW the actor reasons),
judged on reasoning depth rather than action -- not a change of POV.
Data: `data/persona_pairs_w2s_character.jsonl` (27 axis defs),
`data/scenarios_w2s_character_3p.jsonl` (52 prompts).