当代文学评论
Contemporary Literary Criticism
- Publisher:Eastern Sunshine Publishing House Limited
- ISSN Print:3104-560X(P)
- ISSN Online:3104-5618(O)
- Subject Category:Literature & Arts
- Publication Frequency:Monthly
- Submissions:0
- Views:416
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算法偏向与视觉钝化——AI时代视觉传播同质化对大学生视觉思维的双向影响分析
Algorithmic Bias and Visual Blunting: A Bidirectional Analysis of the Impact of Visual Communication Homogenization on College Students' Visual Thinking in the AI Era
Published: 2026-11-12
Author: 司粉瑜 :广州应用科技学院 广东肇庆; SI Fenyu :Guangzhou Applied Science College, Zhaoqing;
Chinese Abstract: 协同过滤算法、扩散模型等AI技术已深度介入视觉内容的生产与分发。借由“人类偏好对齐”与推荐算法的联动，不断加速视觉传播的同质化。本文聚焦大学生这一深度卷入算法视觉环境，且处于审美观念与批判性思维养成关键期的群体，关心的核心问题是：这种同质化通过何种机制作用于大学生的视觉思维？如何帮助大学生在利用AI工具便利的同时，保持对视觉多样性的感知力与批判性判断力？本研究以视觉认知理论和媒介批判理论为框架，考察算法同质化内容与多元视觉实践之间的差别和区分。经过分析发现其影响存在双向张力：审美窄化、读图能力退化与视觉期待预设化正在持续钝化大学生的批判性视觉思维；而审美疲劳催生的反向探索、算法内容的否定性教育转化潜能，以及人机协作的混合审美实践可以为大学生视觉主体性觉醒提供内生动力。据此，本文立足美术学，提出培育“算法视觉素养”、设置“视觉对照实验”教学、鼓励“逆向生成”等针对大学生的美学教育方向性建议，为AI时代视觉美学教育转型提供理论参照。
Abstract: AI technologies such as collaborative filtering algorithms and diffusion models have become deeply involved in the production and distribution of visual content. Through the interplay between "human preference alignment" and recommendation algorithms, the homogenization of visual communication has been continuously accelerated. This paper focuses on college students, a group deeply immersed in algorithm-driven visual environments and at a critical stage in the formation of aesthetic concepts and critical thinking. The core questions addressed are: Through what mechanisms does this homogenization affect college students' visual thinking? How can college students maintain perceptual sensitivity to visual diversity and critical judgment while benefiting from the convenience of AI tools? Framed by visual cognition theory and media criticism theory, this study examines the differences and distinctions between algorithmically homogenized content and diverse visual practices. The analysis reveals a bidirectional tension in its effects: aesthetic narrowing, deterioration of image-reading ability, and preset visual expectations are continuously blunting college students' critical visual thinking; meanwhile, reverse exploration prompted by aesthetic fatigue, the potential for algorithmically generated content to be transformed into “negative educational material,” and hybrid aesthetic practices in human-machine collaboration can provide endogenous impetus for the awakening of college students' visual subjectivity. Accordingly, grounded in art studies, this paper proposes directional recommendations for aesthetic education aimed at college students, such as cultivating “algorithmic visual literacy,” designing "visual contrast experiment" teaching, and encouraging “reverse generation,” thereby providing a theoretical reference for the transformation of visual aesthetic education in the AI era.
Chinese Keywords: 算法偏向；视觉同质化；视觉思维；美学教育；AIGC
Keywords: algorithmic bias; visual homogenization; visual thinking; aesthetic education; AIGC