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Sunday, October 22 • 3:40pm - 4:10pm
How Machine Learning Can Eliminate Hiring Biases and Identify the Right Candidate For a Job

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Hiring the right developer for a job has been a challenge for a long time and is getting worse because of the demand. It’s a time-consuming process. According to Amazon's CTO Werner Vogels, engineers spend 30% of their time on evaluating talent; time that could be better spent on building products.

Not only that, the traditional recruiting methods, like resumes and face-to-face interviews, are susceptible to unconscious biases against candidates. These are social stereotypes about certain groups of people that are ingrained in people without poor intentions.However, these biases can cost someone their job. Machine Learning can help eliminate some of the biases that are inherently found in traditional recruiting tactics.

This talk is about how we are working to extract purely objective features from a typical technical interview and automate them through machine learning models. Ultimately, companies can eliminate bias and reduce effort in their hiring process.

avatar for Shiv Muddada

Shiv Muddada

Engineering Manager, HackerRank
Shiv Muddada is one of the founding engineers of HackerRank and currently head engineering at its headquarters in Palo Alto. HackerRank creates opportunities for developers by helping companies find great developers based on their skills instead of pedigree.In the past five years... Read More →

Sunday October 22, 2017 3:40pm - 4:10pm PDT
Room E Room E