Course overview
Deep Learning systems raise a series of related questions about the nature of intelligence and reasoning, bounded rationality, learning, ethical reasoning, emotion, human sociality and, ultimately, cognition itself. This course looks at those issues in depth. It is suitable for computer scientists interested in contextualizing their work in a wider theoretical and practical framework and others interested in acquiring a deeper understanding of Machine Learning. No knowledge of coding or relevant mathematics is assumed.
Topics covered may include the ethics of human AI interaction, AI in warfare and medicine, the psychology of large language models and the scope and nature of explainability in AI. Because the field moves fast, we will draw on current research as the course evolves. Students from any background should come away with a deeper understanding not only of DLANNs but of the nature of thought itself.
Course learning outcomes
- Understand the nature of machine learning and its relationship to other forms of computation
- relate their understanding to wider issues about the nature of cognition including reasoning, decision making learning and mental representation
- assess the strengths weaknesses and prospects of machine learning in a variety of domains
- understand the ethical implications of deep learning
- Express their understanding in a variety of written forms
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