Published Oct 22, 2018

Fighting bias in AI (and in hiring)

Data science expert Lindsey Zuloaga delves into combating bias within AI technologies and hiring processes, sharing her journey and practical tools to foster fairness. The episode explores how continuous monitoring and algorithmic assessments can revolutionize traditional practices, ensuring unbiased outcomes in the AI era.

Episode Highlights

Topics covered

Episode Highlights

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Dexa/Practical AI

Fighting bias in AI (and in hiring)

Topics covered

Popular Clips

Practical AI Insights

Revolutionizing Hiring

Transitioning from Academia

Developing a Fairness Culture

Removing Bias in Hiring

Monitoring Algorithm Fairness

Transitioning to Data Science

Overcoming Bias

Grappling with Bias

AI and Hiring

Fighting Bias in AI

Humans and AI

Uncovering Algorithm Bias

Mitigating Bias

Episode Highlights

Fairness in AI

Role of Data Science

Bias in Hiring

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Behavioral economics and AI-driven decision making

Putting AI in a box at MachineBox

Practical AI Ethics

AI's impact on developers

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Fighting bias in AI (and in hiring)

Topics covered

Popular Clips

Episode Highlights

Fairness in AILindsey Zuloaga shares insights on fostering a fairness culture within AI teams and the importance of continuous monitoring to ensure unbiased algorithm performance. She highlights practical tools and strategies for addressing bias in AI systems.

Fairness in AI

Role of Data ScienceLindsey Zuloaga explores the challenges of combating bias in AI and shares her journey from academia to data science. She offers insights into algorithmic fairness and practical advice for AI practitioners.

Role of Data Science

Bias in HiringLindsey Zuloaga discusses the integration of AI in hiring processes to enhance fairness and reduce bias. She shares insights on overcoming biases and the role of algorithmic assessments in transforming traditional hiring practices.

Bias in Hiring

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