Implicit Bias Awareness Seminar: What the Course is About

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Related lectures (31)

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Explores the impact of gender on engineering students' group work experiences, emphasizing the need to address implicit biases and stereotypes.

Generalization in Deep Learning

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

Overcoming Implicit Biases: Recognize, Avoid, Act

Explores strategies to recognize and overcome implicit biases through controlled cognition and breaking stereotypical associations.

Understanding Generalization: Implicit Bias & Optimization

Explores the trade-off between complexity and risk in machine learning models, the benefits of overparametrization, and the implicit bias of optimization algorithms.

Avoiding Implicit Biases in Faculty Recruitment: Part 1

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

Introduction to Implicit Biases

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

Implicit Biases: Recognizing and Avoiding

Explores implicit biases, focusing on recognizing and avoiding them through the Implicit Association Test (IAT).

Implicit Bias Awareness: What's the Problem?

Delves into implicit bias training effectiveness, gender stereotypes, and leadership positions.

Implicit Bias in Recruitment: Recognize and Avoid

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

Avoiding Implicit Bias in Faculty Hiring

Covers strategies to avoid implicit bias in faculty hiring and promote gender diversity.