大学生对AI风险认知存在偏差,需针对性提升责任意识。
Rethinking AI Literacy Education in Higher Education: Bridging Risk Perception and Responsible Adoption
- 通过问卷与情景测试,分析学生对具体风险的感知差异
- 风险感知越强,使用AI意愿越低,呈明显负相关
- 技术专业学生虽知风险却仍愿采用,存在认知脱节
随着人工智能深度融入社会各领域,了解未来从业者——尤其是科技类学生——对AI风险的认知,对于推动负责任的开发与应用至关重要。本研究对139名计算机科学、数据科学/数据分析及其他专业学生进行了调查,结合显性风险评分与情景化风险评估,考察其采纳意愿。结果显示:(1)学生对明确指出的具体风险担忧远高于抽象或情境嵌入的风险;(2)风险感知与采用意愿呈显著负相关;(3)尽管技术教育缩小了性别间风险意识差距,男性学生仍表现出更高的采纳意愿;(4)在人工智能相关专业中观察到一种“风险低估”现象:学生虽在显性层面认识到较高风险,但在实际应用情景中却未能充分识别风险,表现出更高的采纳意愿。研究强调应制定差异化的人工智能素养教育策略,弥合认知与实践之间的鸿沟,为教育工作者、政策制定者、产业界及高校提供重要参考。
原文摘要 · Abstract (English)
As AI becomes increasingly embedded across societal domains, understanding how future AI practitioners, particularly technology students, perceive its risks is essential for responsible development and adoption. This study analyzed responses from 139 students in Computer Science, Data Science/Data Analytics, and other disciplines using both explicit AI risk ratings and scenario-based assessments of risk and adoption willingness. Four key findings emerged: (1) Students expressed substantially higher concern for concrete, explicitly stated risks than for abstract or scenario-embedded risks; (2) Perceived risk and willingness to adopt AI demonstrated a clear inverse relationship; (3) Although technical education narrowed gender differences in risk awareness, male students reported higher adoption willingness; and (4) A form of "risk underappreciation" was observed, wherein students in AI-related specializations showed both elevated explicit risk awareness and higher willingness to adopt AI, despite lower recognition of risks in applied scenarios. These findings underscore the need for differentiated AI literacy strategies that bridge the gap between awareness and responsible adoption and offer valuable insights for educators, policymakers, industry leaders, and academic institutions aiming to cultivate ethically informed and socially responsible AI practitioners.
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