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Starts 24 June 2025 01:16

Ends 24 June 2025

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Gender Bias in Machine Learning

Explore gender bias in machine learning with Shalvi Mahajan. Uncover AI's role in amplifying biases, real-world challenges, and evolving techniques to address them in product design and services across genders.
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Open Data Science

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Overview

Explore gender bias in machine learning with Shalvi Mahajan. Uncover AI's role in amplifying biases, real-world challenges, and evolving techniques to address them in product design and services across genders.

Syllabus

  • Introduction to Gender Bias in Machine Learning
  • Definition and scope
    Historical context and significance
    Overview of course structure and objectives
  • Understanding Gender Bias in Data
  • Sources of gender bias in data collection
    Case studies of biased datasets
    Impact of biased data on AI outcomes
  • How Machine Learning Amplifies Gender Bias
  • Mechanisms of bias perpetuation in algorithms
    Analysis of bias in popular ML models
    Real-world examples and consequences
  • Identifying Bias in Machine Learning Systems
  • Techniques for detecting gender bias
    Tools and metrics for measurement
    Evaluating case studies for bias identification
  • Addressing Gender Bias in AI Models
  • Strategies for bias mitigation
    Fairness in model training and validation
    Introduction to bias correction and adjustment methods
  • Gender Bias in AI Applications
  • Case studies in different industries (e.g., healthcare, hiring, finance)
    Ethical implications of biased AI applications
    Lessons learned from industry failures and successes
  • Designing Fair and Inclusive AI Products
  • Best practices for inclusive design
    User-centric approaches for reducing bias
    Stakeholder engagement and interdisciplinary collaboration
  • Innovations and Evolving Techniques
  • Emerging research trends in gender bias mitigation
    Technological advancements and their impact
    Future directions and open challenges
  • Conclusion and Future Directions
  • Recap of key learnings
    Discussion on the evolving role of AI in gender equality
    Paths for continued learning and advocacy
  • Final Project
  • Project guidelines and expectations
    Application of course concepts to a real-world problem
    Presentation and peer review

Subjects

Data Science