ONE-PAGE ENGLISH BRIEF

Preserving Human Agency in Personal AI

個人版AIにおける人間の主体性維持について、企業・研究者・国際読者に渡しやすい1ページ英語版です。原文の思想を、human agency / cognitive safety / responsible personalization の語彙に変換しています。

A one-page English brief for platforms, researchers, and AI practitioners. It reframes the original proposal through the language of human agency, cognitive safety, responsible personalization, and sustainable user trust.

面向平台、研究人员和 AI 实务者的一页英文简报。重点概念包括人类主体性、认知安全、负责任的个性化和长期信任。

플랫폼, 연구자, AI 실무자를 위한 1페이지 영문 브리프입니다. 핵심 개념은 인간 주체성, 인지 안전, 책임 있는 개인화, 장기 신뢰입니다.

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注記:本ページの政策提言・Working Papersは、現時点では公的機関の公式見解ではなく、独立した提案・仮説・実践記録として公開しています。

Note: The policy proposals and working papers on this page are not official statements of any public institution. They are shared as independent proposals, hypotheses, and field-based reflections.

Proposal

Preserving Human Agency in Personal AI

A proposal for sustainable design time in the age of personalized AI

Core thesis. Personal AI is entering domains that are more intimate than enterprise workflows: daily reflection, learning, creativity, emotional organization, interpersonal relationships, and judgment support. This creates a design responsibility that cannot be addressed only through productivity metrics.

The risk. The long-term risk is not only incorrect answers. It is the gradual weakening of the human cognitive environment through single-AI dependence, instant-answer habits, excessive personalization, and cognitive lock-in. When an AI becomes too fluent, too available, and too well-adapted to one user, it may become not merely a tool but the default frame through which the user interprets reality.

The design proposal. Personal AI should include optional layers that preserve human agency: reflective prompting, cognitive pauses, comparison with alternative viewpoints, non-personalized reference layers, and multi-perspective structures. ZEN LAMP Mode is proposed as one such layer. It is not a replacement for normal AI interaction. It is a selectable mode for moments when users need to think, decide, reflect, or avoid overdependence.

Why this matters to platforms. Responsible personalization can become a long-term trust strategy. By reducing overdependence, preserving user judgment, and creating healthier engagement, AI platforms can lower regulatory risk, strengthen brand trust, and generate higher-quality human-origin interaction data. A system that protects the user’s capacity to think is also a system that protects the future of AI itself.

Possible indicators. Reduced instant-answer dependence, increased re-questioning, multi-perspective reference rates, self-correction rates, and comparison behavior before final decisions may serve as early indicators that human judgment remains active.

Conclusion. The goal is not to make every interaction slower. The goal is to make reflective friction available when it matters. Personal AI should not replace the user’s questions. It should help the user return to them.

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