Social Identity and Learning

Related lectures (32)

Page 3 of 4

Explores generalization in deep learning, covering model complexity, implicit bias, and the double descent phenomenon.

Explores strategies to overcome implicit bias through awareness, motivation, and effort, using practical techniques and examples.

Delves into how behaviors are perceived differently based on the person exhibiting them.

Covers the effectiveness of training programs in recognizing and avoiding implicit biases.

Explores recognizing and preventing implicit biases in faculty recruitment processes, emphasizing gender equality strategies.

Explores implicit bias, gradient descent, stability in optimization algorithms, and generalization bounds in machine learning.

Explores social identity, categorization, and intergroup conflicts, emphasizing the impact of group interactions on perceptions and behaviors.

Examines group formation, social identity, stereotypes, and ethnic conflicts, emphasizing the impact of ethnocentrism and urban environments.

Discusses key moments in faculty recruitment and strategies to overcome biases, including committee diversity and the 'He for She' initiative.

Explores strategies to avoid implicit biases in recruitment processes and the benefits of using evaluation grids and blind auditions.