CHARLIE - Challenging Bias in Big Data user for AI and Machine Learning

The main objective of the CHARLIE project was to empower students, young people, and educators to critically understand and address algorithmic bias in digital systems and their impact on society....

The main objective of the CHARLIE project was to empower students, young people, and educators to critically understand and address algorithmic bias in digital systems and their impact on society. By implementing the project, we aimed to develop inclusive, multilingual, and competence-based educational resources aligned with EU frameworks and adapted to EQF levels 2 (youth), 4 (adult education), and 6 (higher education). These resources were designed to help learners—particularly those from disadvantaged or underrepresented groups—acquire the knowledge, skills, and attitudes necessary to recognize, question, and counter the biases and inequalities that algorithms can reinforce. Additionally, the project sought to strengthen the role of teachers, trainers, and youth workers by providing parallel materials and tools to support their educational practice in promoting ethical thinking, critical digital literacy, and civic engagement. Through this dual approach, CHARLIE aimed to contribute to building a more inclusive, transparent, and democratic digital society, fully aligned with European values and strategic priorities such as digital transformation, inclusion, and ethical education.