CHARLIE - Challenging Bias in Big Data user for AI and Machine Learning
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<< Objectives >>The CHARLIE project aims at challenging the bias in big data used for AI and machine learning by bringing a greater level of awareness regarding the negative impacts of the lack of a critical and ethical approach to techEd. CHARLIE main objectives are to linked with the increase capacity of HE institutions, its teachers and its students to provide learning opportunities that meet society needs and creating synergies between HE institutions, AE organisations and Youth organisations.<< Implementation >>- Development activities (Competency Matrices, OERs, toolkits, policy recommendation)- Implementation activities (pilots, external stakeholders consultations, webinars)- Quality and Evaluation (peer-reviews, quality checks)- Communication and promotion (webinars, national and international conferences)<< Results >>-Competency Matrices for the learning programmes - EQF6 (HE), EQF4 (AE), EQF2 (Youth)-Algorithmic Bias course (HE)-Algorithmic Bias toolkit for synchronous sessions (HE)-Guideline for boosting the capacity of university administrators/management (HE)-Webinars to foster peer-learning and discuss the role of HE institutions in techEd-Ethical AI microcredential for Adult learners-Digital Serious game for Youth-Policy recommendation for recognition of microcrential in HE
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