In this episode, host Becca Banyard is joined by Albrey Brown—VP of Strategy & General Manager of New York at Joonko—to talk about how implementing AI technology can help you attract and hire underrepresented talent.
- Albrey’s background [1:07]
- VP of Strategy at Joonko
- First role in tech was as a software engineer.
- After an incredible experience attending a coding bootcamp, he decided to start his own coding bootcamp.
- That coding bootcamp was specifically geared towards women and people of color to make sure that underrepresented folks have access to opportunity.
- They teach about 450 people how to code, getting the majority of them jobs in the industry.
- Then he ended up selling that coding bootcamp to a larger coding bootcamp and became their Director of Diversity and Inclusion back in 2013 when DE&I had just become a thing.
- During his last stint as a head of DE&I at Airtable, he stumbled on Joonko and met the founder Ilit Raz, and the idea just blew him away.
- At Joonko, they match companies with underrepresented candidates that recently ended an interview process at another company in their network.
- What are some of the current challenges that recruiters and hiring managers as well as organizations are facing when it comes to attracting and hiring underrepresented groups? [4:41]
- The biggest challenge is in the name “underrepresented.” To be underrepresented means that women, people of color, etc., are just by the numbers, a smaller group than folks you would consider majority talent or overrepresented.
- Having an organization where you have underrepresented folks represented makes your organization better.
- The hardest part has been really standing out. How do you as a company become an employer of choice for underrepresented candidates?
- 10 years ago the word “employee resource group” was heard few and far between. Now every company of a certain size has employee resource groups.
- You also need to have diversity goals. That’s table stakes now.
- Foundational diversity and inclusion tactics—employee resource groups, diversity goals, having a head of diversity, and standing out.
- How does an organization stand out from the competition when attracting underrepresented talent? [7:55]
- Authenticity. Candidates want to work for companies that know themselves, know their values, and express those values from the beginning.
- Creativity and being open to investing. The lack of patience when it comes to investing in new channels for underrepresented candidates shoots companies in the foot sooner or over time.
- You have to be creative when it comes to experimenting on new ways to attract underrepresented talent.
- What role can AI play in mitigating bias and promoting diversity and inclusion in the hiring process? [12:20]
- There’s bias built into all of the technology that we use, including artificial intelligence.
- The way that they use AI at Joonko is they use natural language processing to match underrepresented candidates with the roles that are being advertised.
- There are a couple of great examples of companies and techniques being applied to the hiring process that make it more inclusive.
- A simple one is closed captioning. Closed captioning on video interviews allows folks who are hard of hearing or who are neurodiverse to read what an interviewer is saying.
- The second one is job postings. Job postings are inherently biased. Textio is an awesome product and the leader is helping companies rewrite their job posts to be more inclusive.
- The last one is on the interviewing side. This is a controversial space because there are video interviewing softwares that like to use facial recognition to understand whether you’re good for a role. Those can be rife with bias. But there are tools that actually only evaluate the interviewer, the person doing the interviewing—like Hireguide.
- At the end of the day, a candidate is always going to be less biased than a company because companies are in power. So if we apply our technologies to expand the number of opportunities a candidate has and mitigate the number of biases a company can exhibit, that’s when we’ll start to see this widespread application of AI to solve these imbalances when it comes to recruiting in the workforce.
The way that AI can be used is less about the technology and more about the application.Albrey Brown
- How would you find a balance between using AI for the sake of efficiency and inclusivity, while also ensuring that human judgment and decision making are incorporated to avoid any discriminatory outcomes? [17:39]
- Local Law 144 is a recent law passed in New York focused on mitigating bias in the hiring process.
- As a talent acquisition leader, people leader, or a person that’s just using technology to recruit, the first thing to do is audit.
- Ask the vendors that you’re using: “How does your technology work differently for different people from different experiences, different backgrounds, and can you produce a report?”
- The second piece is communicating.
- The third is acknowledging that these biases with or without technology exist. They don’t just exist because AI exists. They’ve existed long before that.
- The balance between using AI and understanding that these biases exist is that if we’re going to apply this mentality to robots, we also have to apply this mentality to the human recruiters and hiring managers that own these processes and leverage these tools.
- At the end of the day, the tools still aren’t making the decision—they’re influencing the decision. And if that decision is already coming from a biased source, we will continue to replicate this bias system no matter whether we have perfect AI or not.
- What are some AI tools that are new that companies and human resource departments are starting to use more frequently? [23:18]
- Start from the sourcing perspective. When you want to find talent, going out and reaching out to candidates is one of the best ways. Candidate sourcing software—where you get access to a large database, you can reach out to that database, you can filter that database down—has been the most ubiquitous and popular use of AI technology.
- On the data and analytics side, if you take all this data out of your applicant tracking system and you analyze it and you look to see which candidates have been successful or not, and how you can improve the number of candidates that could potentially be successful throughout your interview process.
- There are these interview methods that are being built on top of facial and voice recognition. Pre-screening, essentially giving a candidate an assessment or a question, and you have them answer that question.
- Success stories of how organizations have approached using AI in their hiring process to attract more underrepresented groups [26:43]
- There’s a company called Gem that is a sourcing product, they allow you to manage all of the candidates that you’re talking to. It’s like candidate management software. But they recently rolled out this product that allows you to see all of the candidates that you’re currently talking to by demographic, and you can see how they publicly identify.
- Albrey’s final advice for someone who is looking to use AI to attract and hire underrepresented candidates and essentially increase the diversity, equity, and inclusion at their organization [28:32]
- Try. When it comes to diversity and inclusion and equity, leaders are a little bit shy to try things because they don’t want to get it wrong. They don’t want to say the wrong thing, they don’t want to invest in the wrong thing. But that creates a chicken and an egg problem—that if you are afraid to invest in a partnership, to buy a new technology, to try a new technology, it becomes difficult to figure out what’s going to work for you.
- The best way to try is to put a time cap on things. The goal is not perfection—it’s progress.
Diversity and inclusion is like climbing a mountain. Every time you feel like you’ve reached the summit, there’s more to go and there’s more to go and there will always be more to go.Albrey Brown
Meet Our Guest
Albrey Brown currently serves as VP of Strategy at Joonko. Prior to this role, he led Diversity and Inclusion at three major tech companies including Pivotal Software, DocuSign and Airtable. At each company, he built important programs from the ground up. Prior to that, he founded and sold Telegraph Academy, which focused on teaching underserved groups how to code.
Albrey prides himself on being a data-driven people leader. Helping underrepresented people find fulfilling jobs is his passion and he’s grateful to be in a position to solve this problem at scale. His work has been highlighted in Fast Company, Protocol, and TechCrunch.
At the end of the day, the tools still aren’t making the decision—they’re influencing the decision. And if that decision is already coming from a biased source, we will continue to replicate this biased system no matter whether we have perfect AI or not.Albrey Brown
- Join the People Managing People community forum
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- Connect with Albrey on LinkedIn
- Check out Joonko
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We’re trying out transcribing our podcasts using a software program. Please forgive any typos as the bot isn’t correct 100% of the time.
Becca Banyard: Is artificial intelligence the key to unlocking a more inclusive workforce? And if so, how do we strike the delicate balance between AI-driven efficiency and human decision making to ensure fairness? Or is human decision making just as biased as AI technologies?
Welcome to the People Managing People podcast. We are on a mission to build a better world of work and to help you create happy, healthy, and productive workplaces. I'm your host, Becca Banyard.
My guest today is D&I expert Albrey Brown, who is currently the VP of Strategy and General Manager of New York at Joonko. We're gonna be talking about how implementing AI technology can help you attract and hire underrepresented talent. So listen to learn the current hiring challenges faced by recruiters and organizations, the potential of AI to mitigate bias and promote diversity, and real world examples of its impact. Stay tuned!
Hello Albrey, and welcome to the show. It's so great to have you here today.
Albrey Brown: Thank you for having me.
Becca Banyard: So we're gonna be diving into the topic of how artificial intelligence can be used to attract and hire underrepresented groups in the workplace. But before we dive in, I'd love to learn just a little bit more about yourself. Can you just share a bit about your background and what you do at Joonko?
Albrey Brown: Yeah. Thank you. My name is Albrey Brown and I am VP of Strategy at Joonko. The way that I kind of got into this role was, my first role in tech was as a software engineer, and I went to a coding bootcamp.
Before that I had no coding experience, and the experience was so incredible to me that I decided to start my own coding bootcamp. But that coding bootcamp was specifically geared towards women and people of color. So I've always been interested in making sure that underrepresented folks have access to opportunity.
So I start this coding bootcamp. It goes really well. We teach about 450 people how to code, get the majority of them jobs in the industry. And then I ended up selling that coding bootcamp to a larger coding bootcamp and became their Director of Diversity and Inclusion. This was back in 2013 when DE&I had just become a thing, a really big topic in the tech industry. And I said to myself, I'm gonna be an entrepreneur again, I'm gonna start a company, but let me try this diversity and inclusion thing out for a little while.
A little while became eight years, and I led diversity and inclusion at four separate companies, and I just loved it. I loved kind of representing companies and their ideas on making sure that both from a demographic perspective and an inclusion perspective, they got better at making sure underrepresented folks are welcomed into their companies.
And during my last stint as a head of DE&I at a very small startup called Airtable, I stumbled on Joonko and I met the founder Ilit Raz, and the idea just blew me away. And what we do at Joonko is we match companies with underrepresented candidates that recently ended an interview process at another company in our network.
So imagine Becca that you interview for a VP of marketing role at Intuit, which is one of our customers, and you get to the final round. But they end up going with someone else, not because you weren't awesome, but because that's how interview processes work. You get multiple awesome people to the end, and you can only choose one.
And instead of rejecting you, they refer you to Joonko and they say, Hey, we really liked you. We thought you were an amazing candidate, and we wanna be a part of your career journey. So they refer you to us, you signed up for Joonko, and we refer you to similar roles at similar companies so that you can find a role faster.
And you know that these companies are invested in diversity and inclusion because they're looking for underrepresented candidates. So that concept blew me away. How a company could turn rejection into opportunity for an underrepresented candidate. And, turning competition between companies into collaboration.
After meeting the founder Ilit and getting introduced to the concept, I was hooked. And I kept trying to find ways to join the company. I was an advisor for a little while. I gave advice on the product and kind of the persona that we were going after and earned a spot as VP of Strategy, which I've been doing now for about a year.
So that's a little bit about me.
Becca Banyard: Thank you so much for sharing. Sounds like you have such an amazing background and have gotten to work with so many cool different companies and wow, Joonko sounds like very unique, but very cool organization. Yeah, really interesting.
So let's dive in and let's start with getting to know a little bit more about the landscape of hiring and attracting underrepresented groups. What are some of the current challenges that recruiters and hiring managers as well as organizations are facing when it comes to attracting and hiring these groups?
Albrey Brown: The biggest challenge is in the name underrepresented. So, to be underrepresented means that, and to, women, people of color, et cetera, are just by the numbers, a smaller group than folks who would, you would consider majority talent or overrepresented.
So I see diversity and inclusion and the challenge behind it as a supply and demand problem. There's just lower supply of, let's say, African Americans who are software engineers, and there's high demand from every company that wants to hire them. Not just because it's the right thing to do, but because having an organization where you have underrepresented folks represented makes your organization better.
There's tons and tons of data that says that. So companies are in fierce competition for underrepresented talent. And I think talking to customers and also talking to, being a head of DE&I in the past, the hardest part has been really standing out. How do you as a company become an employer of choice for underrepresented candidates?
How do you become a topic of conversation when communities of women, people of color, folks of part of the LGBTQIA+ community talk about places that they want to work? And then how do you maintain that over time and grow both a brand, a pipeline, and a reputation for being a company that folks can go to and feel both included, like they're gonna have an equitable opportunity and that they're gonna thrive at your organization.
So the competition element makes it very difficult for companies to compete for this smaller kind of pool of talent. The way that manifests itself is through investment. I think 10 years ago the word employee resource group was heard few and far between. Now every company you know at a certain size has employee resource groups.
If you don't have an employee resource group, and for those who don't know, employee resource groups or internal communities for underrepresented folks so they can connect with each other. That was something that had just emerged back when I became a head of DE&I. Now it's table stakes. In your interview process, you need to understand how your organization is supplying employee resource groups with resources at the end of the day.
You also need to have diversity goals. That's something that didn't exist for most organizations until 10, 15 years ago. That's table stakes now. So taking these, what I consider kind of foundational diversity and inclusion tactics, employee resource groups, diversity goals, having a head of diversity, and then even now standing out because every company has those and staying on the cutting edge.
That is the tough part for most companies when it comes to attracting underrepresented talent.
Becca Banyard: So then how does an organization stand out from the competition when attracting underrepresented talent?
Albrey Brown: It's a tough question and we try to help customers and with this all the time. And the first one is just like authenticity.
Candidates want to work for companies that know themselves, know their values, and express those values from the beginning. So let's go back to the example. Becca, you're interviewing for a company. You have values yourself that you want to be expressed when the company that you go to.
I assume that diversity, equity and inclusion is one of those. But let's say that company doesn't have diversity goals, which we talk to a lot of companies who don't. There's an inclination from a company to say, let's not talk about that in our interview process. Let's not talk about the fact that we don't have true diversity goals.
But if a candidate doesn't hear about it at all, that lack of authenticity ends up creating a negative experience for that candidate. But we coach companies and recruiters and recruiting leaders to just be upfront and honest to say, Hey, let's lead the conversation. We don't have diversity goals yet, but what we're doing is X, Y, and Z.
We're trying to understand what demographics look like at our organization first. We're, our executive leader, it wants to better understand what goals we can create that are actually gonna make a meaningful impact. Leading that conversation with authenticity is the first piece. I think secondly, it's creativity and being open to investing.
One of the challenges that I find when we talk to companies is that they want immediate results. So they'll go to a conference, say, Grace Hopper is an incredible conference for software engineers that identify as women. They'll go to a conference, they'll be at the conference one year, they spent $30,000 on the conference, but they only got three hires out of it.
So they measure the success as we only got three hires out of it. Instead of saying the partnership as an investment, we got three hires out of it this year, but what does next year in the following year look like as we start to build our brand equity with this conference? And the lack of patience when it comes to investing in new channels for underrepresented candidates, shoots companies in the foot sooner or over time.
So one thing that we do at Joonko is, typically when you buy a piece of software or you buy a place to advertise your jobs, you typically buy for a month, you put a job on a job board for one month. We have our companies commit for a year because we wanna make sure that they are seeing the exponential value of our product over time.
You're not gonna get 10 great candidates the first month because both our algorithm and our network, we have to adjust to the jobs that we're trying to get you. But that third month, that fourth month, that sixth month, that ninth month, you'll start to see that the investment in the channels start to grow.
And I think that lesson that we kind of impart on companies that work with us is that if you saw that investment go up exponentially over time with us, think about the other channels that you may have given up on before you partnered with Joonko. That if you had just put in a little bit more time and effort understanding how that channel's gonna grow over time, maybe it would be a great channel for underrepresented talent 18 months down the line. Rather than that one-off opportunity to partner, you didn't see as quite as good as other channels that you hire from.
So I think it comes down to patience, authenticity. Then lastly, I'll say creativity. You gotta be creative when it comes to experimenting on new ways to attract underrepresented talent. It might be just going to communities and not trying to hire, going to communities and meeting folks where they are, having conversations.
It might be doing resume reviews at local community colleges to just better understand who's in the room. Getting creative is a great way to, I think, start to think outside of the box and to figure out where are the candidates that you want to hire so that you can get your name and their mouths, even if it doesn't turn into a direct hire immediately.
Becca Banyard: Yeah. Awesome. I love especially that last piece of creativity. It sounds a lot like getting curious about the people who are actually underrepresented, who are different from yourself perhaps, and learning more about who they are and what they need.
Yeah. I'd love to just now dive into the more specifics around AI. So in your opinion, what role can AI play in mitigating bias and promoting diversity and inclusion in the hiring process?
Albrey Brown: Yeah, that's a great question because typically the opposite is asked. And when we talk about AI, it's a very big topic, right? We're talking about natural language processing, talking about large language models that are trained on the information and behavior that humans who are inherently biased exhibit.
So there's bias built into all of the technology that we use, including artificial intelligence. Now, the way that we use AI at Joonko is we use natural language processing to match underrepresented candidates with the roles that are being advertised. So we look at your resume, we look at the role that you just interviewed for, and we match you with the best company and the best role that will be good fit. Which, we're using it in a way to kind of extend that opportunity to underrepresented folks.
But kind of more broadly, I think that there are a couple of great examples of companies and techniques being applied to the hiring process that make it more inclusive. So a really less obvious, but super simple one is closed captioning. So closed captioning on video interviews allows folks who are hard of hearing, or who are neurodiverse to read what an interview is saying.
Now, most people wouldn't think about that as mitigating or making a process more inclusive, but when I explain it, obviously, I see you nodding like it is, right? It's a way that we have applied AI to hear someone's voice, turn it into text. And when we apply that to an interview, it opens up the scope of who can participate in that interview by allowing folks who read versus listen to have a better interview experience.
The second one is, job postings. So job postings are inherently bias, right? With bias, whether it be the language calling someone a rockstar or a ninja. Or the number of requirements that are put on a job post. I mean, there's a piece of data that's quoted ad nauseum that, women apply to jobs that they're 100% a fit for, whereas men apply to jobs that they're 60% a fit for.
So Textio is an awesome product that's kind of the leader in helping companies rewrite their job posts to be more inclusive. They'll, you'll write a job post and it'll say, Hey, this has nine requirements. What if you cut it down to six? What if you wrote a paragraph that said, Hey, even if you don't fit every single job requirement, apply to this role. So that you can encourage folks who may not be as confident to apply to that role, or simply take out the examples of pronouns that you're using in the job post from saying "he" to this person, or that.
Those are some simple ways that I think, artificial intelligence have been used for changing the language that we use for job posts. The last one is on the interviewing side. Now, this is a controversial space because there are interviewer, video interviewing softwares that like use facial recognition to understand whether you're good for a role.
Now, my personal philosophy on those is that those can be rife with bias, right? Anything that has to do with the way that you express yourself with your face or your tone can be easily misconstrued by both a human, I think about the way that black women are described in the workplace or by AI. But there are tools that are on the other side that are being built that actually only evaluate the interviewer, the person doing the interviewing.
And there's one called Hireguide that comes to mind and it evaluates whether the interviewer has asked the same questions from interview to interview, has given sufficient answers to common questions, and has provided the interviewee with inclusive language and inclusive practices that make them comfortable.
And I think all that to say the way that AI can be used is less about the technology and more about the application. Where are we applying these technologies? Are we using it to evaluate candidates? If so, I think that we have to be very careful. If we're using it to evaluate companies, then that's, I think when we can start to see inequities be mitigated.
Because at the end of the day, a candidate is always gonna be less biased than a company because companies are in power. So if we apply our technologies to expanding the number of opportunities a candidate has and mitigating the number of biases a company can exhibit, that's when we'll start to see this kind of widespread application of AI to, solving these imbalances when it comes to recruiting in the workforce.
Becca Banyard: Wow, this is all so good. I started feeling a little bit emotional at the beginning just what you were saying about something so small as closed captions. Something that seems so small to somebody who doesn't need closed captions can make such a big impact on the life of somebody who does. So I think even small changes like that are so important.
So we know that AI has limitations. We know that it has biases. So with that in mind, how would you find a balance between using AI for the sake of efficiency and inclusivity, while also ensuring that human judgment and decision-making are incorporated to avoid any discriminatory outcomes?
Albrey Brown: This is a big question and I think this question is happening both inside organizations and in the broader workforce.
I think, before we went live, we were talking about Local Law 144, which is a recent law passed in New York, focused on mitigating bias in the hiring process. And they put the onus on companies to audit any technology that leverages AI to help them with recruiting. And essentially the audit, in simple terms, a company has to ask whatever vendor they're using. Let's say Joonko, to produce a report that says, Hey, tell us how your technology makes decisions based on demographics.
So you have to say how many women, people of color are screened in and out of a process, and you have to look at those against each other so that you can see whether the technology is biased against a certain type of group. So I think all that to say the first way that I would balance as a talent acquisition leader, people leader, or a person that's just using technology to recruit, the first thing I would do to balance this is audit. Ask the vendors that you're using.
How does your technology work differently for different people from different experiences, different backgrounds, and can you produce a report? Can you show me the data that tells me that these imbalances are not represented in your software? And if they are, how are you going to solve them over time?
Now, thankfully, this is gonna be a law very soon, and this law is spreading like wildfire. So I think companies will have to do this anyway. But I think that's a very important piece of, leveraging this technology is the auditing piece. The second piece is communicating. AI has existed for a long time, as in recruiting.
I'll give you a practical example. Most applicant tracking systems when you apply, already screen you in or out of the process based off of keywords in your resume. This is a very well known practice. Candidates now know how to use ChatGPT to get past it, et cetera, et cetera. But that's artificial intelligence.
Now, I think the difference between that practice and let's say these facial recognition practices, et cetera, et cetera, is that candidates know about these now. It's been communicated to them that there's a screening process that happens that's done by a robot. So they can adjust. They can adjust how they approach so that they can increase the probability that they get to a human.
And I think that is a practice that should be adopted for all of the other technologies. You should tell candidates about the fact that you're using this thing and the fact that you audited this thing and these were the results of that audit. But this is why we're using it. And I think that builds trust between candidates and talent acquisition teams.
And it also makes sure that this communication loop between candidates and talent acquisition folks are holding vendors accountable to improving their technology over time. And then the third, I think the third honestly, is just like acknowledging that these biases with or without technology exist. AI is definitely not a perfect system.
You could see it as if you built an AI system to be inherently biased. I think of the Amazon example. Amazon in 2016 created this large language model based off of all the resumes that they had and say, Hey, help us, basically tell us who is a good software engineer. And what they learned over time was whenever they would type into the system a woman's name, the woman would be ranked a lot lower on the, is this a good software engineer spectrum than any male name?
They also typed in sororities to see if a sorority was on a resume, and that's anyone with a sorority was ranked a lot lower on the software engineer spectrum than anyone who didn't. So the system was obviously inherently biased and they scrapped that system, but it's a pretty famous case of bias.
That said, what's the difference between that and a hiring manager going to a recruiter and saying, I only want you to look at candidates from these five schools. These biases exist, and they don't just exist because AI exists. They've existed long before that. So I think one of the things that I wanna make clear about, the balance between using AI and understanding that these biases exist is that if we're going to apply this mentality to robots, we also have to apply this mentality to the human recruiters and hiring managers that own these processes and leverage these tools.
Cuz at the end of the day, these tools still aren't making the decision. They're influencing the decision. And if that decision is already coming from a bias source, we will continue to replicate this bias system no matter whether we have perfect AI or not.
So I know that didn't completely answer, that last point didn't completely answer your question, but I think it's an important point that gets lost when we talk about technology. That humans exhibit these biases anyway, so I think that we need to apply the same mentality to both robots and humans at the same time.
Becca Banyard: Yeah, definitely. Okay, so you mentioned that applicant screening software has been used pretty standardly for the last number of years. What are some AI tools that are new that companies and human resource departments are starting to use more frequently?
Albrey Brown: Start just from the sourcing perspective. So when you wanna find talent, there are a couple ways that you do it.
And going out and reaching out to candidates is one of the best ways. So I think candidate sourcing software where essentially you get access to a large database, you can reach out to that database, you can filter that database down, has been the most ubiquitous and popular use of AI technology. Using AI to both find the best candidates, recommend candidates based off of past searches using machine learning, and then using large language models to write messages to those candidates automatically.
So I think AI has started to automate some of the repetitive processes of talent acquisition on the sourcing side. On the data and analytics side, if you take all this data out of your applicant tracking system, the hundreds of thousands of candidates that have applied to you, or you've interviewed over time, and you analyze it and you look to see which candidates have been successful. Which have not been as successful, which ones are on the cusp, and how can you improve the number of candidates that could potentially be successful throughout your interview process.
So using machine learning and natural language processing to understand that. And then third, going back to kinda like the interview piece. There are these interview methods that are being built on top of facial and voice recognition. Pre-screening, essentially giving a candidate an assessment or a question, and you have them answer that question.
It's really popular for sales roles. Having them answer that question. Maybe it's a customer question, and then analyzing their tone, their facial expression, and all the things that would go into a customer call and understanding whether they would be a fit for the type of customers or the type of calls that they're gonna be on.
Of several applications, I think Joonko is pretty unique because what we do is we use three types of what would be considered AI. We automate, so we automatically understand whether someone has been disqualified at a final round. We then automatically invite them to the Joonko network, and then we automatically match them with another role so that a recruiter doesn't have to do anything.
They don't have to refer them to us, and they don't have to source them from our pool. They just receive a Joonko candidate and they typically go, yay, this is amazing. Thank you. And then they hire them. We also use machine learning to understand when candidates are looking at the roles we're sending them to send them better recommendations over time.
And we also use natural language processing to, as I said earlier, to kind of look at keywords in the resume and in the role that the person just interviewed for so that we can make sure that we're sending them to the right company and the right role that they have a high probability of getting through the interview process.
So at each step of the recruiting process, you're seeing a ton of innovation in the AI space.
Becca Banyard: Yeah. Amazing. Thanks for sharing that. I think you kind of already just touched on it now with your example with Joonko, but I'm wondering if you have any other success stories of how organizations have approached using AI in their hiring process to attract more underrepresented groups and yeah, if you could share any of those?
Albrey Brown: Yeah, there's a company called Gem that the sourcing product, they allow you to manage all of the candidates that you're talking to. See it as like a candidate management software. But they recently rolled out this product that allows you to see all of the candidates that you're currently talking to by demographic, and you can see how they publicly identify.
So let's say you have she/her pronouns on your LinkedIn, they can make an inference that you might identify as a woman. The way that I have seen talent teams use this tool is by, if I can understand the demographics of all the people I'm talking to right now, I can plan for the future on how to influence those demographics to go up or go down.
If I see that over the last month I've only sourced 20 women out of a thousand candidates, then I can make take an action to figure out how I can increase that to 25, to 30 to 50 over time. So I think it doesn't help in actively increasing the number of underrepresented candidates that you get in touch with like we do.
It's more of a gut check technology using AI that allows companies, it gives companies the power to understand where they are and take action to make investments on how they can increase that in real time. I think that's a very powerful and unique tool for talent acquisition folks.
Becca Banyard: Yeah, so great. Thanks for sharing that. So we're about to wrap up. But I'm wondering if you have any final advice for someone who is looking to use AI to attract and hire underrepresented candidates and essentially increase the diversity, equity, and inclusion at their organization.
Albrey Brown: My one piece of advice is try, and that sounds very simple. But to unpack that, I think especially when it comes to diversity and inclusion and equity, leaders are a little bit gun shy to try things because they don't want to get it wrong. They don't wanna say the wrong thing, they don't wanna invest in the wrong thing. But that creates kind of a chicken and egg problem, that if you are afraid to invest in a partnership, to buy a new technology, to try a new technology, it becomes difficult to figure out what's gonna work for you.
And all of these technologies, the DE&I technology market has only existed for about five years. So all of them are new and all of them are ripe for your feedback, as well as can give you an edge against all of the other companies that you're competing against because they're very new.
So this is the time to try a bunch of vendors, to try a bunch of new partnerships, to build the relationships and the enablement that your recruiters are gonna need to continue to increase demographic diversity, neurodiversity, all of the things that you know that employees are gonna care about moving forward. So just try. And the best way to try is to put a time cap on things. This is a three month pilot. This is a six month pilot. This is a one year pilot. And the goal is not perfection. It's progress. And I think you can apply that to diversity and inclusion in general.
You're never gonna be perfectly diverse. You're always going to be progressing towards diversity. And to throw one more Joonko plug, we talk about Joonko means is, or Joonko is the name of the first woman to climb Mount Everest. And we named ourselves that something very specifically because diversity and inclusion is like climbing a mountain.
Every time you feel like you've reached the summit, there's more to go and there's more to go and there will always be more to go. And I think applying that to both how you approach diversity and inclusion and the products and tools that you're gonna use is gonna be very helpful for leaders in terms of a mindset.
Becca Banyard: Yeah. Wow. I love that. So good.
So I have two questions that I ask all my guests. I'd love for you to weigh in just before I let you go. So what do you believe is the number one thing that keeps employees happy in the workplace?
Albrey Brown: Can money not be a—No, I'm joking. I'm joking.
I think I'm gonna go back to authenticity. The workplace is hard. Collaboration is hard. Sometimes the business is not doing as well as it needs to, but being honest about what's going on and why it's going on, I think keeps folks knowing what's coming around the corner and allows them to relax and potentially be happy.
Becca Banyard: And what do you personally need to be successful as a leader?
Albrey Brown: Trust. And I think that's different than being trusted. I need to trust in my leadership to hold me accountable. I need to trust the other folks in my org that when we decide on something or when we make a decision or when we take an action, it does come down to trust at the end of the day. Yeah, we just gotta trust each other through the highs and the lows.
Cuz at the end of the day, what else do we have?
Becca Banyard: Well, Albrey, it has been such a pleasure chatting with you. Thank you so much for being on the show. If folks want to connect with you or get in touch, follow your work, where can they do so?
Albrey Brown: You can follow me on LinkedIn at Albrey Brown Twitter, also @albreybrown. Other than that, you can contact me at Joonko. So thank you, Becca. This has been an incredible conversation. I appreciate being on the show and look forward to the next one.
Becca Banyard: Amazing. Thanks again and everyone listening, thank you so much for tuning in. If you'd like to stay in touch with all things HR and leadership, head over to peoplemanagingpeople.com/subscribe to join our newsletter community.
And until next time, have a great day!