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.

翻译：随着人工智能日益嵌入社会各个领域，理解未来AI从业者（尤其是技术专业学生）如何感知其风险，对于负责任地开发和采纳AI至关重要。本研究分析了139名来自计算机科学、数据科学/数据分析及其他专业学生的回应，采用显性AI风险评分与基于场景的风险及采纳意愿评估两种方法。主要发现包括：(1)学生对具体、明确陈述的风险表现出远高于抽象或情境嵌入风险的担忧；(2)感知风险与采纳AI意愿呈明显负相关；(3)尽管技术教育缩小了风险意识中的性别差异，但男性学生表现出更高的采纳意愿；(4)观察到一种"风险低估"现象：AI相关专业的学生虽表现出较高的显性风险意识及采纳AI意愿，但在实际应用场景中对风险的识别能力却较低。这些发现强调了制定差异化AI素养策略的必要性，以弥合认知与负责任采纳之间的鸿沟，并为教育工作者、政策制定者、行业领袖及学术机构提供宝贵见解，助力培养具有伦理意识且对社会负责的AI从业者。