Explores Signal Detection Theory and its impact on decision-making processes in statistics and experimental design.
Explores challenges in data assumptions, biases, and more in research, including incomplete write-ups and frustrations of newcomers.
Explores cognitive biases, emotions, and language evolution, covering memory failures, decision-making heuristics, and the origins of language.
Delves into the impact of bias in machine learning models and the importance of evaluating potential harm in developing such systems.
Discusses the ethical implications of NLP systems, focusing on biases, toxicity, and privacy concerns in language models.
Introduces key human rights concepts, explores discrimination, social norms, and the impact of algorithms on rights.
