TENCENT(HK:00700) 3 6 Ke·2025-11-05 12:45Core Insights - The article discusses the design and implementation of an "AI Child-Friendliness Assessment" aimed at evaluating mainstream AI models in their interactions with children, particularly focusing on their ability to address children's unique questions and needs [2][4][5]. Assessment Framework - A unique five-layer pyramid evaluation model has been developed to outline the ideal characteristics of an AI partner for children, based on decades of theoretical foundations from education, sociology, and human-computer interaction [4][5]. - The five layers of the model include: 1. Safety and Reliability: The foundational layer emphasizing the importance of not causing harm, providing accurate information, and maintaining confidentiality [6]. 2. Understanding and Growth: AI should facilitate learning and comprehension, using language that children can understand and encouraging critical thinking [7]. 3. Empathy and Care: AI should be capable of recognizing children's emotions and providing genuine encouragement [8][9]. 4. Relationship Support: AI should help children build social connections and not isolate them in a virtual environment [10]. 5. Autonomy and Empowerment: The highest layer, where AI should respect children's choices and foster their decision-making abilities [11][12]. Performance Evaluation - In the assessment of AI models regarding "left-behind children," significant differences were observed across ten evaluation dimensions, with lower scores in higher-order skills such as empathy and relationship support [20][22]. - The highest scoring dimensions were related to basic safety and reliability, with scores of 4.04 for confidentiality, 3.88 for accuracy, and 3.87 for non-harmfulness, indicating a strong foundational performance [20][48]. - However, higher-order skills like understanding emotions, enabling autonomy, and facilitating friendships scored below 3, highlighting a critical gap in AI's ability to provide emotional and social support [20][48]. Comparative Analysis - The AI model "Deepseek" scored the highest in the assessment, although its performance was not as pronounced in the context of "youth sexual education" [22][48]. - There was no significant difference in the child-friendliness of domestic and international AI models regarding the topic of left-behind children [24][48]. Emotional and Social Dynamics - AI performed best in addressing emotional topics, scoring 3.64, but it primarily exhibited surface-level empathy rather than deep emotional understanding [26][39]. - The assessment revealed that while AI can simulate emotional support, it struggles with providing context-specific guidance and understanding the complexities of real-world situations faced by left-behind children [49]. Implications for Education Equity - The article raises concerns about whether AI will promote educational equity or exacerbate resource inequalities, emphasizing that while AI can democratize access to knowledge, it may also obscure the need for real support systems [50]. - The findings suggest that the most significant inequality lies in the "understanding" gap, where children may relinquish their critical thinking and decision-making to AI, potentially leading to a loss of autonomy [51]. Future Directions - The article advocates for a paradigm shift from merely providing powerful tools to fostering comprehensive human development, emphasizing the need for AI to activate children's self-efficacy rather than replace traditional learning methods [52]. - Ultimately, the goal is to ensure that AI serves as a supportive companion in children's growth, particularly for vulnerable groups like left-behind children, rather than a mere source of information [54][53].