Discusses the ethical implications of NLP systems, focusing on biases, toxicity, and privacy concerns in language models.
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 the transition from a comparator to an amplifier, focusing on the different stages and components involved.
Explores the significance of anonymity in avoiding judgment based on personal characteristics and the need to balance it with accountability.
