Ashu Garg: How To Leverage AI To Recognize And Improve Diversity In Hiring 


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Ashu Garg works with startups across the enterprise stack. He is particularly excited about how machine learning and deep learning are reinventing existing software categories and creating new consumer experiences. Ashutosh has invested in AI-enabled business applications (such as marketing technology and HR technology), data platforms, data center infrastructure, security & privacy, as well as online video. Before joining Foundation Capital in 2008, Ashutosh was the general manager for Microsoft’s online-advertising business and led field marketing for the software businesses. Previously, Ashutosh worked at McKinsey & Company, helping technology companies scale their go-to-market efforts. Earlier in his career, Ashutosh founded, one of the first search engines in Asia, set up Unilever’s Nepal operations, and led the marketing and pre-sales teams at Cadence Design Systems.

Ashutosh has a bachelor’s degree from the Indian Institute of Technology (IIT) in New Delhi and an MBA from the Indian Institute of Management at Bangalore, where he received the President’s Gold Medal.

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Here’s the timestamps for the episode:

(00:00) – Introduction

(01:31) – was created in 2016 as a talent intelligence platform that is being used by the leading enterprises across the globe to hire, engage, and retain a diverse workforce.

(04:21) – Large enterprises’ number one challenge is people. They are not able to hire fast enough. Enterprises should think about diversity, about their own biases, to understand what talent exists. We added exits to bring the right people on board and that is where data and AI comes into play.

(05:43) – We can’t keep looking for people who have done the work. We have to look at the people who can do the work, and that is a fundamental shift in the mindset.

(09:00) – We need to reach out to the people who may not have had all the privileges that we have and support them. We have to look at people beyond what we perceive for their face color, age.

(10:14) – Machines have the ability to forget and ignore. We have our biases because of the lack of knowledge. Knowledge and moving out of biases can really help us solve this problem when hiring candidates.

(11:59) – There has to be an audit process to ensure that your algorithms are not going crazy and that they are doing the right thing. Let’s use them to help humans do a better job.

(13:53) – It’s all about humans. These systems are designed to come in and replace humans. In that case, not only are you taking the snitch system correctly, you’re teasing that: I really don’t need to worry about humans, and that has to be front and center.

(16:00) – One of the things Eightfold believes is that it’s not that people are good or bad, or one is better or worse, but who is the best fit for which flow in that company.

(18:24) – You have to really assess the people at their full potential.

(22:32) – What is trying to do through machines is help hiring managers understand that candidates past, be able to dig deeper with you, look at the peer group of the community to see what their peer group is doing today.

(25:27) – Some of the success stories of the companies that we know today in the world come from combining experience with young talent.

(27:26) – The talent market rate landscape is completely going to go through a massive shift in next 18 months. This is also a good time to hire great talent, because many people are looking up.