摘要
为应对人工智能生成内容(AIGC)对学术体系的冲击,学界普遍引入AIGC检测系统,用AI检测模型来对抗AI生成模型。但这场技术竞赛的天平并未倒向检测方。现有AIGC检测系统的可靠性备受质疑,受制于生成模型快速迭代、对抗性攻击等技术难题,其长期效用也面临严峻考验。更深层的问题在于,“黑箱”机制导致AIGC检测的可解释性不足,难以提供足够完整、清晰并符合人类逻辑的判断依据,由此引发信任缺失、公平成疑、难以归责等伦理问题。此外,AIGC检测还面临相似性与概率方面的认识论难题:一方面,AIGC与人类作品之间并不存在严格的界限,两者之间存在固有的相似性;另一方面,检测结果是基于相似性给出的概率值,该值只能采用主观概率解释,缺乏客观性,因而也难以判断其正误。AIGC检测的内在缺陷可能导致大量资源消耗、劣胜优汰、幸者生存、人类主体性丧失等负面影响。因此,在AI无法取代人类进行原创性思考的当下,更合理的应对策略是利用AI提升作品质量,同时明确AIGC检测的辅助性地位,而不是让它成为超越人类的判官。
In response to the impact of AI-Generated Content(AIGC)on academic system,the academic communities have widely adopted AIGC detection systems,using AI detection models to counter AI-generated models.However,the balance of this technology competition has not tilted in favor of the detectors.The reliability of current AIGC detection systems is highly questioned,and their long-term efficacy is severely tested by technical challenges such as the rapid iteration of generative models and adversarial attacks.A deeper issue lies in the insufficient explainability of AIGC detection due to the“black box”mechanisms,making it difficult to provide sufficiently complete,clear,and logically sound grounds for judgments,thereby causing ethical problems such as trust loss,questionable fairness,and difficulty in attribution.Furthermore,AIGC detection also confronts epistemological challenges in terms of similarity and probability:there is no strict boundary between AIGC and human works,as they share inherent similarities;detection results are probabilistic values based on similarity,which can only be explained subjectively and lack objectivity,making it difficult to determine their correctness.These intrinsic flaws of AIGC detection may lead to negative consequences,such as significant resource consumption,survival of the inferior and the fortunate,and a loss of human subjectivity.Therefore,in the current situation where AI cannot replace humans for original thinking,a more rational response strategy is to use AI to improve the quality of works,while clarifying the auxiliary role of AIGC detection,rather than making it a judge beyond humans.
作者
陈千千
吕天择
Chen Qianqian;Lv Tianze
出处
《天府新论》
2025年第6期80-88,154,共10页
New Horizons from Tianfu
基金
教育部人文社会科学研究青年项目“国别比较视角下的中国式现代化技术进路研究”(编号:23XJC710008)。
