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從失范到規(guī)范:生成式人工智能的監(jiān)管框架革新
網(wǎng)絡安全與數(shù)據(jù)治理
劉學榮
吉林大學法學院
摘要: 生成式人工智能在技術變革下引發(fā)的失范性風險,,對既有人工智能監(jiān)管框架提出了挑戰(zhàn),。從底層技術機理出發(fā),,可知當前生成式人工智能呈現(xiàn)出“基礎模型-專業(yè)模型-服務應用”的分層業(yè)態(tài),,分別面臨算法監(jiān)管工具失靈,、訓練數(shù)據(jù)侵權風險加劇、各層級間法律定位不明,、責任界限劃分不清等監(jiān)管挑戰(zhàn),。為此需以分層監(jiān)管為邏輯內核,對我國既有人工智能監(jiān)管框架進行革新,。在監(jiān)管方式上應善用提示工程,、機器遺忘等科技監(jiān)管工具;在責任劃定上應進行主體拆解與分層回溯,,從而規(guī)范“基礎模型-專業(yè)模型-服務應用”的分層監(jiān)管框架,,以期實現(xiàn)有效監(jiān)管,促進生成式人工智能的高質量發(fā)展。
中圖分類號:D922,;TP399文獻標識碼:ADOI:10.19358/j.issn.2097-1788.2024.06.009
引用格式:劉學榮.從失范到規(guī)范:生成式人工智能的監(jiān)管框架革新[J].網(wǎng)絡安全與數(shù)據(jù)治理,,2024,43(6):58-63,,71.
From illegal to legal: evolving regulatory frameworks for generative artificial intelligence
Liu Xuerong
School of Law, Jilin University
Abstract: The risk of aberration caused by generative artificial intelligence under technological change challenges the existing artificial intelligence regulatory system. Starting from the underlying technical mechanism, it can be seen that the current generative artificial intelligence presents a hierarchical format of "basic model-professional model-service application", and faces regulatory challenges such as the failure of algorithm supervision tools, the intensified risk of training data infringement, the unclear legal positioning between different levels, and the unclear division of responsibility boundaries. Therefore, it is necessary to take layered regulation as the logical core and reform the existing artificial intelligence regulatory framework in China. In the way of supervision, we should make good use of technology supervision tools such as prompt engineering and machine forgetting. In the delineation of responsibilities, the main body should be disassembled and hierarchical backtracking should be carried out, so as to standardize the hierarchical regulatory framework of "basic model-professional model-service application", in order to achieve effective supervision and promote the healthy and high-quality development of generated artificial intelligence.
Key words : generative artificial intelligence; algorithm black box; technical supervision; legal responsibility

引言

隨著人工智能的迭代升級,,對其進行的深層監(jiān)管不僅關系到法律治理實效,也直接影響到技術發(fā)展與應用安全,。生成式人工智能作為當前新質生產(chǎn)力發(fā)展的主要驅動力,,需加以重點關注。相較于傳統(tǒng)的人工智能,,生成式人工智能因其深度學習屬性而使技術原理變得更加復雜且難以理解,,并由此導致算法黑箱、算法歧視,、算法異化,、算法權力失范等過去人工智能算法模型中常見的技術伴生風險問題更為嚴峻。與此同時,,算法解釋,、算法審計、算法評估等過去對人工智能進行法律監(jiān)管的傳統(tǒng)工具在生成式人工智能面前也面臨著失靈風險,,法律監(jiān)管體系的穩(wěn)定性與安全性都受到了極大的沖擊,。

雖然我國人工智能法律監(jiān)管始終走在世界前沿,并形成了具有中國特色的算法模型監(jiān)管體系[1],,但就目前針對生成式人工智能以及深度合成算法推出的監(jiān)管規(guī)定,,仍主要停留在人工智能模型治理衍生出的信息安全層面,偏重服務應用監(jiān)管而輕視底層技術監(jiān)管[2],,無法克服因人工智能模型的技術升級而產(chǎn)生的監(jiān)管困境,。

在技術失控風險日益嚴重,現(xiàn)有方案又無法實現(xiàn)有效監(jiān)管的雙重困境下,,生成式人工智能的監(jiān)管難度急劇增長,。面對生成式人工智能蓄勢待發(fā)的落地應用,需要針對性的法律監(jiān)管方案對風險進行治理,。因此,,本文將從生成式人工智能的底層技術出發(fā),首先對其采用的算法模型進行技術穿透,,在解析技術原理后清晰定位生成式人工智能的監(jiān)管困境,,而后在底層技術特征的基礎之上挖掘生成式人工智能技術監(jiān)管的可行路徑,彌補當前生成式人工智能法律監(jiān)管工具的失靈,,并結合生成式人工智能的底層運行機理與相應的運行主體進行精準分層責任落實,,避免因“技術中立”濫用而引發(fā)法律責任逃避問題,,以實現(xiàn)底層技術與分層主體有機協(xié)調的法律監(jiān)管模式。


本文詳細內容請下載:

http://forexkbc.com/resource/share/2000006049


作者信息:

劉學榮

(吉林大學法學院,,吉林長春130000)


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