The 'Algorithmic Bias' EQF6 course competence matrix serves as a foundational element for two other critical components: the 'Ethical AI Micro Credential' EQF4 competence matrix and the 'Learning Outcomes for Adults and Youth EQF2 (Serious Game)' learning outcomes. These three components are interconnected and designed to complement and reinforce each other, ensuring a comprehensive understanding and application of ethical AI principles across various educational levels and contexts.
The 'Algorithmic Bias' course competence matrix lays the groundwork for the development of the 'Ethical AI Micro Credential' EQF4 competence matrix. By providing a strong foundation in understanding algorithmic biases and their implications, this course empowers learners to delve deeper into the ethical dimensions of AI as they progress to the EQF4 level. The 'Ethical AI Micro Credential' EQF4 competence matrix builds upon the initial competencies, expanding the scope to include broader ethical considerations and practical applications of ethical AI principles in various sectors and scenarios.
Simultaneously, the 'Algorithmic Bias' course competence matrix also informs the 'Learning Outcomes for Adults and Youth EQF2 (Serious Game)' learning outcomes. This connection ensures that the fundamental concepts and skills developed in the course are accessible and engaging for learners at the EQF2 level. The serious game format is designed to introduce these critical topics in a manner that is both entertaining and educational, fostering a deeper understanding of algorithmic bias and ethical AI principles among a wider audience.
This course focuses on understanding and addressing algorithmic biases, equipping professionals, academics, and students with knowledge and practical skills to identify, mitigate, and manage biases in AI systems. It emphasizes the ethical, social, and technical implications of algorithmic biases across sectors like healthcare, education, finance, and government. By completing this program, participants will gain a comprehensive understanding of algorithmic biases, their societal impact, and effective strategies to address them, fostering more equitable and ethical use of algorithms in decision-making processes.
This educational program is designed for professionals, academics and students, equiping participants with the knowledge and skills to address biases ethically and responsibly and explores the foundational concepts of algorithmic bias, including its causes and manifestations while emphasizing essential ethical principles such as non-maleficence, fairness, transparency, accountability, and respect for human rights. Participants will delve into practical approaches for minimizing harm, enhancing fairness, ensuring transparency, and promoting accountability in AI systems. The program also investigates the role of legal frameworks, stakeholder collaboration, and interdisciplinary approaches in ethical AI development.
Through interactive activities and scenarios, Charlie's House fosters critical thinking and problem-solving skills, enabling learners to identify biases in AI applications and explore ethical principles like fairness, transparency, and accountability. Participants engage with real-life examples, collaborate to address bias-related challenges, and reflect on their own perspectives and responsibilities in AI use. Upon completion, learners will have a foundational understanding of algorithmic bias, improved teamwork and communication skills, and a heightened sense of ethical awareness and civic responsibility in advocating for fair and accountable AI systems.
Webinar - UIB, November 2023, Spain
On this page, take a look at the materials developed
Interactive eLearning Screens
(include incorporated expert videos and booklets at the end of each unit)
Formative assessment exercises
Summative assessment tests
Interactive concept maps
Online summative assessment
Support PowerPoint presentations
Handbook
Multiple choice quizzes
Open answer formative assessment
Expert videos
Case study
Project-based exercises
On this page, take a look at the materials developed
Ethical AI micro credential course - Challenging Bias in Big Data user for AI and Machine Learning
Interactive eLearning Screens
(include incorporated summative quizzes and booklets in each unit)
