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Building explainable and trustworthy intelligent systems

Existing machine learning-based intelligent systems are autonomous and opaque (often considered “black-box” systems), which has led to the lack of trust in AI adoption and, consequently, the gap between machine and human being.In 2018, the European Parliament adopted the General Data Protection Regulation (GDPR), which introduces a right of explanation for all human individuals to obtain “meaningful explanations of the logic involved” when a decision is made by automated systems. To this end, it is a compliance that an intelligent …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Information Systems
Research centre(s)
Centre for Data Science

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