Local Wisdom in Algorithms: The Epistemology of Guidance Career Skills, Cultural Values, and the Dialectic of Humans with Artificial Intelligence

Abstract

This study aims to explore in depth the epistemology of career skills from a phenomenological perspective in which artificial intelligence (AI) dominates. The background of this study is based on a fundamental shift in the way knowledge and expertise are formed and interpreted in the modern job market, which is increasingly influenced by AI. Specifically, this article investigates how individuals interpret and internalize their career knowledge amid the availability of AI-powered algorithms and platforms. Using interpretive phenomenology, this study involved in-depth interviews with six professionals across sectors who rely on AI in their daily work. Participants were selected through purposive sampling. Data analysis was conducted using Colaizzi's framework, which focuses on identifying essential themes from participants' life experiences. Results show that interaction with AI has created a "hybrid epistemology" in which human intuitive knowledge integrates dialectically with data and recommendations from machines. Further discussion suggests that this creates epistemic tension, where trust in personal intuition competes with the validity of algorithmic data. The main conclusion is that career counselors and practitioners need to develop a new framework that takes this duality of knowledge into account. The recommendation from this study is the need for a career approach that focuses not only on developing technical skills, but also on strengthening individual self-reflection and epistemic literacy to navigate an increasingly complex and AI-driven career landscape. In the educational context, these findings implicitly reinforce the urgency for career guidance services to dynamically systematically prepare students and university students to build cognitive autonomy ahead of the AI-integrated workforce.