構造経路から逆算する理解の定義
知識伝達の三経路と人間・機械の共有理解
DOI:
https://doi.org/10.51094/jxiv.6852キーワード:
知識伝達、 潜在通信、 表現の整列、 モデルマージ、 AIアライメント、 科学的理解、 知性共生抄録
理解とは何かという問いは、理解を欠いた知識獲得がほとんど存在しないために、対照群なしに論じられてきた。本稿は、AIが持ちうる第三の知識伝達経路「構造経路」がその対照群を与えることを示し、理解を逆算的に定義する。知識が主体の間を移動する経路は、経験から重みを変えるパラメータ経路と、記号を介して受け手が構造を再構成する記号経路に大別されてきたが、重み共有、モデルマージ、表現の整列、潜在通信といった技術は、学習済みの構造を少数のアンカーで受け手に直接接合する構造経路の萌芽である。この経路は再構成を省くので、受け手は構造を使えるが理解していない。この差から、主体 X が構造 S を理解しているとは、X 自身の語彙で書かれた生成器が存在し、S の圧縮記述から S を再生成できることだと定義できる。定義は再生成、反事実への応答、境界の認識という三つの試験で検証でき、主体相対的であり、人間にも機械にも同じ形で適用される。帰結として、発見と理解の分離は人間と機械の間だけでなく機械同士の間でも起き、記号経路と勾配学習が副産物として備えていた整合性検査は構造経路には内蔵されない。本稿は、接合の後に受け手自身の語彙で再構成し直す事後再構成、接合面検査、多様性の維持、孤児構造を作らない来歴の保持を要件として提示し、人間と機械の共有理解をアンカーの集合として特徴づける。2026年にAIによる科学的発見が人間の理解から分離した事例は、この枠組みの初期の顕在化と位置づけられる。
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