2024 MIT Digital Technology and Strategy Conference: Lightning Talk - Darshana

NATALIE GIL: Thank you. Hi, everybody. Good morning. So I'm Natalie Gil. I'm a Sloan Fellow '17. My co-founder, she's Sloan Fellow '16.

I'm a systems engineer technology architect. She's an intellectual property attorney. So she's keeping our assets very safe and with a lot of value.

So we worked together to build this. We are all-women team from all the roles. This is something, because we were building something on AI, we want to be responsible. But we also want to be very conscious around what we're building and really be inclusive by design.

OK, so problem right now with all the things related to hiring is very biased, because a lot of people with good intentions, of course, we put the best and sometimes a lot more the best of things we have on our résumés, profiles, on job marketplaces, and [? leading ?] everywhere. So that doesn't help very, very good tools that are on the market, that are doing résumé screening, that are doing talent matching, because of that bias is what we put, what we reported.

So what we're doing right now is, OK, there's data inaccuracy here, so we need to solve that. So we came to one idea. After finding that there's standards right now that are being pushed globally around credentials. Those are verifiable credentials that's a standard that registers work experience, education, health, and more. And this is managed by digital wallets.

So all of you at some point, and I think right now, you may have one of those credentials already, but you don't know. I'll explain that later if you stop by, so you can take advantage of that. So what we're doing is that data is real, because it gets verifications from several parties. You can note that data.

And then we are collecting that data. So you heard some of the expositions before that AI is cool, but the problem is the data sometimes, if it's biased or it's really not super good. So what we're doing is providing those credentials as source of retraining those tools or providing our own tools. We have our own chatbots and so, to really improve the hiring process. So the key here is not to have better tools or better algorithms or better models, it's to have better data at the end.

So what we're doing right now is we have credential verification. This is very mechanical. We keep doing and we keep collecting data.

We have AI matching. And then we have two things here. One, we provide our own tools to companies that want to hire better, faster. We improve that process in 90% in efforts and time. Or we provide other platforms that are in need of this better data, like job marketplaces, HR platforms, some others, that can consume our data to do better with our tools.

We also have connection with digital wallets globally that are now deploying globally as well. So you can manage those credentials. And that we can acquire that data from there, too.

OK, so trusted data, this is number one. We also have blockchain, of course. We use it and leverage us to keep that data safe. We also have global reach.

What is the key from our customers? During the pandemic and after the pandemic, they realized that there was a lot of talent globally that they weren't able to reach. Also universities, they realized that there was a lot of global opportunities, but they need to help their students or alumni to get to those opportunities. This, of course, helps to move the talent pool around the world.

So we have a company that can get our tools or empower their own tools to get better job matches. And we can also get talent that use our chatbots to say, OK, I need to put my résumé better or, what are the opportunities worldwide that I can get based on my real profile? So that's the type of things we're doing with users and companies today. We also, as well, helping other platforms to get that data to do better matches.

OK, ask. What we're doing with companies right now, we're running pilots. Some of them are paying customers, as well, to get this to 90% better. It's not a lot of effort. We need some data, but we're getting there.

Second, academic. A lot of universities are asking us, and we're working with them, to have these credentials and get their talent exposed globally, so they can get better opportunities. Of course, any other educational institutions are welcome to come. And this is a plot twist.

We are working with other startups, not only from MIT, to get better data to these platforms, to the platforms that are running right now. So we are not the only ones collecting this data. We are not the only ones trying to get better AI. There's a lot of other companies doing this, so please join us to do that. Thank you so much for having us.