本論文探討法國、臺灣與中國的Z世代求職者如何感知、應對並回應人工智慧(AI)於招 聘流程中日益增長的影響力。本文立基於演算法治理、職涯建構理論與文化緊密—鬆散 理論三項理論架構，採取跨國性的質性研究設計，透過對五位Z世代青年(含本國籍與外 籍身分)進行半結構式深度訪談，以理解其於AI驅動下求職經驗之脈絡與應對方式。研 究發現，儘管AI招聘工具標榜效率與實力主義，其實際運作卻引入了更多的資訊不透 明、標準化程序與排除性邏輯，而這些特徵往往深受各國意識形態與文化規範所調節。 這些演算法系統並非文化中立，其運作方式與公平性認知、軟實力評估與身分展現等面 向密切相關，進而形塑Z世代對職涯的偏好建構與因應策略。值得注意的是，「外來者」身 分會加劇求職者所感受到的障礙，並影響其採取順應或抵抗AI系統的策略。透過主題式 分析法，本研究揭示了AI招聘場域中，科技、文化與身分交織所構成的細緻而情感密集 的現實。本研究不僅豐富了有關數位勞動與演算法公平性的學術討論，亦為政策制定 者、雇主與職涯輔導者提供實務建議，以推動更具公平性的AI與人力協同招聘實踐。研 究結果強調:在設計與治理影響青年經濟未來之AI系統時，必須納入文化與意識形態脈 絡的考量。

This thesis explores how Generation Z job seekers across France, Taiwan, and China perceive, navigate, and respond to the growing influence of artificial intelligence (AI) in recruitment processes. Positioned at the intersection of algorithmic governance, career construction theory, and cultural tightness–looseness frameworks, the study adopts a qualitative, cross-national approach grounded in semi-structured interviews with five young adults, both nationals and foreigners, engaged in AI-driven job searches. The research reveals that while AI recruitment tools promise efficiency and meritocracy, they introduce new forms of opacity, standardization, and exclusion that are deeply mediated by national ideologies and cultural norms. Far from being culturally neutral, these algorithmic systems interact with varied expectations around fairness, soft skills, and identity, shaping how Gen Z job seekers construct career preferences and coping strategies. Notably, experiences of foreignness compound perceived barriers and influence strategies of adaptation or resistance. Through thematic analysis, this thesis illuminates the nuanced, emotionally charged realities of algorithmic hiring as a site where technology, culture, and identity converge. The findings contribute to academic discussions on digital labor and algorithmic fairness and offer practical insights for policymakers, employers, and career counselors aiming to foster equitable AI-human collaboration in hiring. This study underscores the critical need to consider cultural and ideological contexts in designing and governing AI systems that shape young people’s economic futures.