算法時代法律適應性困境與動態構建

在智能算法通過自主學習、深度學習並顯著增強其社會適應性的趨勢下，法律規範的靈活性不足而難以適應社會動態變遷的局限性日益顯現，導致出現法律規範的適用性困境，甚至在某些領域法律面臨被邊緣化的危機。算法時代法律適應性困境源於規範結構的靜態化特徵，立法者完全可以通過運用動態體系論方法，對法律規範進行結構性改造和優化。立法者有必要運用動態體系論方法在法律條款中設置彈性要素，使法律規範獲得“學習”的能力;法律解釋機關應適時加強對法律規範中要素的解釋，實現要素間的動態協動，使法律規範適應不斷變化的現實;法律適用者將動態體系化的法律規範轉換為算法代碼，實現智能化的法律實施機制，可以從根本上破解算法時代法律的適應性困境。

As intelligent algorithms continue to evolve through autonomous and deep learning, significantly enhancing their adaptability to social contexts, the limitations of legal norms—particularly their lack of flexibility—have become increasingly apparent. This rigidity gives rise to mounting difficulties in the applicability of legal norms and, in some domains, even threatens to marginalize the law itself. The adaptability dilemma faced by law in the algorithmic era stems from the static nature of legal norm structures. However, this challenge can be addressed through the application of a dynamic systems theory approach to structurally reform and optimize legal norms. Legislators should incorporate flexible elements into statutory provisions, enabling legal norms to“learn”and evolve. Judicial interpretative bodies must strengthen the interpretation of legal elements to promote dynamic interplay among them, thereby ensuring the law's responsiveness to ever-changing realities. Legal practitioners, in turn, should translate these dynamically systematized legal norms into algorithmic code, laying the foundation for an intelligent legal implementation mechanism. Such an approach offers a fundamental solution to the challenge of legal adaptability in the algorithmic age.