Explores challenges in data assumptions, biases, and more in research, including incomplete write-ups and frustrations of newcomers.
Introduces key human rights concepts, explores discrimination, social norms, and the impact of algorithms on rights.
Covers an example of Bayesian parameter estimation and the trade-off between bias and variance in supervised learning.
Introduces the AI and FX practical course, focusing on weekly readings and discussions on ethical and legal aspects of AI.
Explores Signal Detection Theory and its impact on decision-making processes in statistics and experimental design.
