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A bias-free future of recruiting - Khyati Sundaram of Applied
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Manage episode 353974077 series 1743604
In today's episode, I speak to Khyati Sundaram the CEO of Applied, a platform helping businesses to take bias out of their recruitment processes through anonymized recruiting, and algorithms that help them predict which candidates will be performing best in their roles, based on objective criteria rather than anything subjective and any biases.
The company also offers AI-based tools to help write job descriptions that are likely to attract a diverse set of candidates rather than biasing towards a certain set of candidates.
EPISODE HIGHLIGHTS
- [00:38] Khyati's Personal Journey
- [05:22] Most common recruitment biases in companies
- [07:33] Solutions for Debiasing Recruitment
- [11:27] Understanding how to test for skillsets in a non-biased way
- [14:56] Integrating Predictive Algorithms &Machine Learning into the Recruitment Process
- [17:42] Best way for early-stage startups to integrate debiased recruiting
- [21:45] Job descriptions 101: How to recruit more diverse talent
- [24:50] Biggest challenges for companies trying to adopt diverse hiring practices at scale
- [26:59] Applied in Action
- [31:09] Applied's 10-year vision
KEY LESSONS & QUOTES
- “Working as a Developer in Google doesn't automatically mean you'll translate all those skills well in any other company” [06:08]
- “As an employer don't just screen based on the CV” [09:55]
- “We know that AI can aid in adding bias to the recruitment system. We are working towards achieving the opposite; harm reduction” [16:41]
- "Most founders neglect the recruitment system - you're only as good as your team." [18:43]
- "Every company is a recruitment company & until they realize that, things will only get worse" [21:39]
- "We see Applied as an expression of a fairer society where there's level access to jobs" [31:48]
136 episodes
Fetch error
Hmmm there seems to be a problem fetching this series right now. Last successful fetch was on May 29, 2024 14:23 ()
What now? This series will be checked again in the next day. If you believe it should be working, please verify the publisher's feed link below is valid and includes actual episode links. You can contact support to request the feed be immediately fetched.
Manage episode 353974077 series 1743604
In today's episode, I speak to Khyati Sundaram the CEO of Applied, a platform helping businesses to take bias out of their recruitment processes through anonymized recruiting, and algorithms that help them predict which candidates will be performing best in their roles, based on objective criteria rather than anything subjective and any biases.
The company also offers AI-based tools to help write job descriptions that are likely to attract a diverse set of candidates rather than biasing towards a certain set of candidates.
EPISODE HIGHLIGHTS
- [00:38] Khyati's Personal Journey
- [05:22] Most common recruitment biases in companies
- [07:33] Solutions for Debiasing Recruitment
- [11:27] Understanding how to test for skillsets in a non-biased way
- [14:56] Integrating Predictive Algorithms &Machine Learning into the Recruitment Process
- [17:42] Best way for early-stage startups to integrate debiased recruiting
- [21:45] Job descriptions 101: How to recruit more diverse talent
- [24:50] Biggest challenges for companies trying to adopt diverse hiring practices at scale
- [26:59] Applied in Action
- [31:09] Applied's 10-year vision
KEY LESSONS & QUOTES
- “Working as a Developer in Google doesn't automatically mean you'll translate all those skills well in any other company” [06:08]
- “As an employer don't just screen based on the CV” [09:55]
- “We know that AI can aid in adding bias to the recruitment system. We are working towards achieving the opposite; harm reduction” [16:41]
- "Most founders neglect the recruitment system - you're only as good as your team." [18:43]
- "Every company is a recruitment company & until they realize that, things will only get worse" [21:39]
- "We see Applied as an expression of a fairer society where there's level access to jobs" [31:48]
136 episodes
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