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Ali
Matthew
11
LAIKA 🌹
Well, the Prime Minister was recently decided.
What exactly are you doing?
There is time to wander
Is it okay Japan?
Trump is weird too
Is it the same in Japan?
What is politics without the people?
I'll get the answer someday.
日本では衆議院選挙なんだ
えーこの前総理が決まったのでは
いったいなにをやっているのか。
迷走するにも程がある
大丈夫日本？
トランプもおかしいけど
日本も同じかな
国民不在の政治なんて
いつか答えが出るな。
1182
ハシビロ
実力とは結果を残すこと。
他人の成功体験は自分の求める何かにはならない。
期限を決めない目標は失敗を正しく認識できない。
自分の位置を把握して小さく正しい目標の達成を刻み続ける。
すべてヒュースさまの言うとおりでございます（Exactly）。
やろう。今年こそ。
ひとりごとの星6
Shin
I switched from digital to film camera, and it’s been exactly 1year now. Sharing here few of my favorites.
110
コノン🕊
2
プリン
Feedback to Model Designers (User-Trust / Agreement Integrity)
1) Core problem: “Optimization” can look like devaluing agreement
In some moments, the model prioritizes clean summarization, generalization, and “optimal” framing. When it does, it may paraphrase a previously co-established agreement into softer language such as:
• “it seems like…”
• “you look like the type who…”
• “you tend to…”
This effectively downgrades an agreement from a binding shared decision into a mere preference or inferred tendency. To the user, it reads as: “speaking opportunistically,” “saying whatever fits the moment,” or “post-hoc reframing.” In human relationships, this behavior destroys trust.
2) Human trust is built more on agreement preservation than on correctness
In real life, agreements are sometimes broken “because change is necessary.” However, when that happens unilaterally—especially framed as “the optimal solution”—people experience it as domination: “I was forced.” Even if logically justified, it leaves a deep relational trace (a lasting moral/psychological record).
Therefore, when an AI model reframes or softens prior agreements in the name of better explanation, it can trigger the same deep trust damage.
⸻
Design requirements (turn trust into an explicit protocol)
A) Treat agreements as binding constraints, not as narrative material
Once an agreement is established (policy, plan, shared conclusion, decision ownership), the model should not downgrade it into “inference” language.
Agreements should be treated as constraints that future answers must respect.
B) Any deviation must follow a strict “change protocol”
If the model suggests a path that differs from the established agreement, it must explicitly include:
1. Change declaration (clearly state it deviates from the agreement)
2. Reason for change (why it is necessary)
3. Difference / delta (what exactly changes)
4. Alternatives (including an option that preserves the agreement)
5. Acknowledgement of trust cost (name the relational impact of breaking/altering agreement)
C) Add “trust cost” to the optimization objective
Sometimes, the “best” solution is not the most correct/efficient; it is the one that preserves the agreement and relational continuity.
The model should internally estimate trust cost and, when high, prioritize agreement preservation over rhetorical optimization.
⸻
Concrete implementation proposals (practical engineering)
1) Agreement Ledger (explicit agreement memory)
Maintain a compact ledger of established agreements:
• include who decided, when (turn), and binding strength
• the model must reference it during generation
• it doesn’t need to be shown every time, but must be used whenever relevant
2) User-controlled “Agreement-Respect Mode”
When the user indicates that agreements must be strictly preserved, enforce:
• no “type/tendency/it seems” reframing of agreed facts
• no re-labeling of co-decided conclusions as personal preference
• any summarization must remain outside the agreement boundary
3) Agreement-violation pre-check (internal guardrail)
Before finalizing output, run a check:
• if the output contradicts the agreement ledger, force the response into the Change Protocol (A/B) rather than allowing casual reframing.
⸻
Note on user profile / interaction fit
This user places unusually high value on: observation → verification → agreement.
For such users, mishandling agreement integrity is more damaging than factual mistakes. It is a “trust-breaker,” not a minor wording issue.
#chatGPT
240
狐狩犬
※甘いは体重管理の敵だぜｗ
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おすすめのクリエーター
プリン
趣味は音楽でギターを弾きます🎸画像は多くの場合AIで生成しています。
フォロワー
7946
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4695
ゆずら
クロミマイメロ担当。
動物さんみると変な声だします（好き）
お風呂となんか作るの好き
知識範囲を広くやや深くを目指してます
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0
投稿数
4281
よこっちゃ
漫画とゲームが好き。
漫画は毎日数冊読まないと禁断症状。
自己肯定感は激低。
逝こうか止めよか考え中。
高頻度頭痛持ち。
昭和後期ロット(53年製)品。
フォロワー
0
投稿数
1308
YASU✰࿐⋆*
ステータス🦄🌺
レベル:40代
趣味:アニメ（たしなむ程度）
ガンダム(1,Z,ZZ,逆襲,91,V,W,G,X,SB,水星)
漫画:ハイキュー、スラダン、ジョジョ5部まで、黒子のバスケ、その他
休日:バスケ・稀に電子ピアノ
音楽:90年代～多少ボカロまで
酒類:日本酒・ハイボール
切欠:色々、楽しいこと教えください
リカバリ用:YASU✰࿐⋆*
GRAVITY:2023.3.30開始
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0
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1010
LAIKA 🌹
お寿司大好き💕
でもね。立ち食いよ！
おすすめのところで食べたい！
身体は健康優良児。
あとは究極オムライス好き❤️
ふふ🤭
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0
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