算法下的自我认知批判
Critique of Self-Consciousness under Algorithms

算法在人类社会中的融合，重塑了个体的自我认知。算法生成的“数据镜像”不仅改变了认知结构，而且引发了思维模式的变革。这种变革体现在算法在优化信息处理的同时，对复杂和多维问题的过度简化，算法追逐效率而忽视了经验认知的丰富性和情感的深度等问题上。随着技术逐渐替代原有的认知手段，带来了更多新的伦理挑战，特别是在道德决策和分析过程中过分依赖算法所引发的认知混乱和道德危机。对大数据时代中自我认知的现象进行批判，明确算法技术对认知透明性的影响和认知框架的侵入，对于重塑个体在算法环境中的自我认知至关重要。
The integration of big data and algorithms in human society has reshaped individual self-awareness. The “data mirror image” created by algorithms not only changes the cognitive structure but also triggers a revolution in thought patterns. This transformation is evident in the algorithm’s simplification of complex and multidimensional issues while optimizing information processing. The pursuit of efficiency in big data technology often overlooks the richness of experiential cognition and the depth of emotions. As technology emerges as a new means of self-awareness, it presents novel ethical challenges, particularly in the cognitive confusion and moral crises caused by an over-reliance on algorithms in moral decision-making and analysis. Critically examining the phenomenon of self-awareness in the era of big data, and clarifying the impact of technology on cognitive transparency and the intrusion of big data technologies on cognitive frameworks, is crucial for reshaping individual self-awareness in an algorithmic environment.