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Aigc生成內容的權威性與品質控制科學知識生成中的驗證與評價機制探討

Author

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  • 陳明

    (南京師範大學,江蘇 南京,210023)

Abstract

人工智慧生成內容(AIGC)技術持續高速演進推動知識生產與傳播模式發生深度轉型,AIGC 在文本創制、圖像生成、資料解析與科研協助等多領域落地大幅提升資訊處理效能與知識創造速率,AIGC 在內容品質與權威特質方面的潛在隱患逐步顯現,科學知識生產與公共傳播領域中其內容真實屬性、可靠特質與可驗證屬性等問題亟需回應。本文系統梳理 AIGC 的技術發展背景與應用現狀從內容品質管控、權威特質驗證與評價機制構建三個維度解析其核心技術邏輯與制度約束條件,研究表明當前 AIGC 內容在真實屬性評估、倫理責任界定與標準化治理方面仍存在明顯缺口集中表現為事實核驗機制不足、演算法偏見積澱與統一品質評估架構缺失。文章進一步探析 AIGC 內容權威性的社會認知基礎與科學驗證機制的結構性難題提出通過搭建可解釋性演算法體系、健全多層次驗證機制、建立跨行業品質基準與倫理治理架構優化 AIGC 知識生成的可信程度,本文認為 AIGC 的未來發展取向應聚焦 “科學驗證 — 品質評估 — 社會信任” 三維聯動推動人工智慧從 “資訊生成” 邁向 “知識生產” 實現技術創新與認知可靠屬性的動態平衡。

Suggested Citation

  • 陳明, 2025. "Aigc生成內容的權威性與品質控制科學知識生成中的驗證與評價機制探討," Explorations in Modern Science, Brilliance Publishing Ltd., vol. 1(2), pages 12-29, December.
  • Handle: RePEc:ctz:exmsci:v:1:y:2025:i:2:p:12-29
    DOI: 10.53104/xdkxts.2025.01.02.002
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