People are worried about the use of AI in recruiting. Headlines warn us that artificial intelligence might amplify biases and automate unfairness. Regulators are scrambling to introduce legislation, and talent acquisition leaders are cautious about adopting these new tools. But is this fear causing us to miss the bigger picture? When implemented intentionally and responsibly, could AI become one of the most powerful tools we’ve ever had for reducing systemic bias and creating fairer hiring practices? Keep listening to find out.
Recruiting processes often prioritize speed and familiarity over fairness and inclusion and, in so doing, reinforce existing biases. With AI becoming increasingly integrated into hiring, many worry that this technology will amplify bias even more. However, some recently published research suggests this assumption doesn’t tell the whole story.
My guest this week is Torin Ellis, an experienced recruiter, DEIB strategist, and high-profile advocate for fair and inclusive hiring. Torin recently published research in collaboration with Plum, specifically highlighting how organizations that use AI in an intentional way are seeing significant improvements in diversifying their candidate slates and expanding their talent pools. He believes that AI can create a more level playing field for all candidates if it’s properly deployed. Torin also emphasizes that the risks of AI-driven biases are real, and recruiters need to approach AI thoughtfully and responsibly.
In the interview, we discuss:
• What makes recruiting systemically biased
• Democratizing access to opportunity
• How AI is diversifying slates of talent
• The dangers of relying on resumes
• Using AI intentionally to reduce bias
• Upskilling, reskilling, and driving toward equal compensation
• What are the dangers of AI?
• How are employers responding to the attacks on DE&I?
• What does the future look like
Follow this podcast on Apple Podcasts.
Follow this podcast on Spotify.
Matt Alder [00:00:00]:
People are worried about the use of AI in recruiting. Headlines warn us that artificial intelligence might amplify bias and automate unfairness. Regulators are scrambling to introduce legislation and talent acquisition leaders are cautious about adopting these new tools. But is this fear causing us to miss the bigger picture? When implemented intentionally and responsibly, could AI become one of the most powerful tools we’ve ever had for reducing systemic bias and creating fairer hiring practices? Keep listening to find out.
Matt Alder [00:00:40]:
Support for this podcast comes from Workable. Workable is the all in one hiring platform that empowers companies of all sizes to attract, evaluate and hire top talent. Effortlessly trusted by over 30,000 companies worldwide, Workable has facilitated over 1.5 million hires, streamlining recruitment with powerful automation and AI driven insights. Hire smarter, faster and with confidence. Learn more@workable.com.
Matt Alder [00:01:29]:
Hi there, welcome to episode 681 of Recruiting Future with me, Matt Alder. Recruiting processes often prioritise speed and familiarity over fairness and inclusion, and in so doing reinforce existing biases. With AI becoming increasingly integrated into hiring, many worry that this technology will amplify bias even more. However, some recently published research suggests this assumption doesn’t tell the whole story. My guest this week is Torin Ellis, an experienced recruiter, deib strategist, and high profile advocate for fair and inclusive hiring. Torin recently published research in collaboration with Plum, specifically highlighting how organizations that use AI in an intentional way are seeing significant improvements in diversifying their candidate slates and expanding their talent pools. He believes that AI can create a more level playing field for all candidates if it’s properly deployed. Torin also emphasizes that the risks of AI driven biases are real and recruiters need to approach AI thoughtfully and responsibly. Hi Torin, and welcome to the podcast.
Torin Ellis [00:02:46]:
You know I appreciate being here. Thank you ever so much. The year is moving extremely fast, but you found time to get my voice on. So Matt, I thank you.
Matt Alder [00:02:56]:
An absolute pleasure to have you on the show. And you’re right, I think we’re six weeks into the year and it feels like about eight months so far.
Torin Ellis [00:03:04]:
Indeed, yes, indeed.
Matt Alder [00:03:07]:
Absolutely. I’m gonna start with a very specific question which is what is it that makes recruiting systemically biased?
Torin Ellis [00:03:15]:
Wow, that’s such a great question and I want to give a concise response, but seeing as though I’ve been recruiting since 1993 for the four, four and a half years that I was in corporate America. I started an agency in 1998 and ran that from 98 to 2010. And then I went and started doing consulting with recruiting teams around diversity pipelines and representation. And so I think in the 20 seconds that I’ve been talking, I think the thing that makes it challenging for so many is comfort. We’re not willing to be uncomfortable, we’re not willing to challenge the status quo. We just simply want to do our best to abide by the rules. And Matt, when I say that, I say that sincerely because most recruiters just want to do the right thing. They want to find people, fill the requisition and move on to the next. And so what I’ve tried my best to extol over the last 15 or so years of consulting is how do you challenge the status quo? How do you tell people that time to fill is aggressively a disservice to the desire to have representation? So I think it’s challenging the status quo, absolutely.
Matt Alder [00:04:39]:
I mean, I think that that makes kind of perfect sense. And it’s really interesting because the assumption’s always been over the last few years that as AIs kind of come onto the scene and got more sophisticated and it’s kind of being used deeper and deeper into the recruiting process, there’s a real assumption that increases bias or is going to increase bias, or it has the risk of increasing bias, not reducing it. And you’ve recently published a fantastic bit of research, really interesting report. Do employers believe this? Do they think that AI is inherently biased? What’s the kind of the feedback you’ve got from asking that question?
Torin Ellis [00:05:17]:
So it’s an umbrella question, and I’m not mincing words with you, but when we say employees, then that’s the collect. And I don’t believe that the collective is represented in one question or one response. I believe that there are employees that do have reservation. They are reticent around the introduction, the presence of artificial intelligence in their organization, or as it applies to them in their journey. But I also believe that there is a set of employees that are aggressively curious and they are exploring how do I leverage this technology, how do I make it so that not only am I more efficient, but that I remain a valuable contributor to the organization. So no matter what the scheme looks like in terms of employee composition, contingent, full time, agile, compartmentalized, project based, I find that I will have a space here. And then I believe that there’s a third contingent and that third group of individuals are going to wake up one day and they’re going to ask themselves what in the world has just happened? They’re not reticent, they’re not curious. They’re just simply working through the motions right now. And they are going to wake up and the train is going to have hit them. And one of the things that I say to people on stages now when I’m speaking is I don’t believe that human resources is doing a good enough job around protecting the employee. Here’s the reason why do I have time to respond?
Matt Alder [00:06:50]:
Of course, always. Yeah.
Torin Ellis [00:06:52]:
The reason I believe that human resources is being a bit derelict, being a bit irresponsible, and I mean that affectionately, is because Sam Altman asked a question in January of 2024. He was on a podcast and he asked the question, how long will it be before we have a one person unicorn, meaning a one person company doing or have a valuation of a billion dollars? A one person company with a valuation of $1 billion. Now you got to know Matt, if they are asking the question, then they are aggressively working towards the answer. And that is going to prompt every other leader. Fortune 1014, Fortune 1500, it doesn’t matter. Every other CEO is going to ask themselves then, if we can have one person doing a billion dollars, then why do I have 200,000? Why do I have 20,000 employees? Why do I have 10,000 employees? So every organization is going to be looking at how do I decrease my head count and implement and deploy AI solutions. So I believe every single HR person should be doing more to make sure that every employee in the organization is at least aware of AI. And then what they do with that information is totally up to them.
Matt Alder [00:08:17]:
Yeah, I think that’s a, that’s an incredibly important point because, yeah, that level of education just, just isn’t out there at the moment. And in terms of recruiting, because as I say, the report you’ve written is, is all about how AI can help reduce bias in the recruiting process. Is that something that you think employers are already kind of thinking or already sort of utilizing AI in that kind of way?
Torin Ellis [00:08:41]:
Yeah, I mean, they are, absolutely. You know, what we found inside of the report are that organizations that have decided to deploy AI. And by the way, before I say that, let me say I want to go back to something you said. Yes, AI does have the potential of causing harm. I get that. I’m not trying to gloss over that. That will be something that we talk about in Q4 of this year. But I wanted to approach the subject using the word reducing purposefully because I Wanted to invite people into the read rather than perpetuate the negative. And the concern, at least for this first time out, that that’s the first thing. Now, as it relates to entities inside of the study, you know, we. We actually queried a number of individuals, organizations. I would say that of those that are using artificial intelligence, they are seeing incredible returns as it relates to diversifying their slates of talent. They are seeing incredible returns as it relates to extending the perimeter of consideration. I think about Plum and what Caitlin McGregor has done, you know, over at that organization. And she really, really, really wanted to democratize access, that that was the central focus for her starting and establishing the organization. And Plum has done an amazing job of leveraging their assessment in place of a resume, which changes the recruiting process. In the beginning, I’m not saying that resumes are no good, but what I am saying is that so many recruiters have relied only on the resume, which may not demonstrate, which may not capture and highlight all that I bring to the equation. And so I know that leveraging AI in a way that allows candidates to really unfold who they are, have those rich and robust conversations, it allows a recruiter to be even more confident in saying, you know what? Matt Torin doesn’t look on paper like we need him to, but look at my notes, look at what we exchanged in the discovery in my first call with him, that prescreen, you really should be giving him a consideration. And so I believe that AI does have extreme potential in, I would say, leveraging the playing field for applicants and candidates across geographies.
Matt Alder [00:11:07]:
100% agree with you. And I think, yeah, particularly some of the stuff that Plum are doing, it’s kind of really fantastic in terms of just making recruiting work better and make it, you know, make it fairer. And by doing that, you know, you’re extending the candidate pools, you’re getting better matches for the skills that you need, all those kind of things. Are there other kind of specific areas where AI is helping so obviously kind of removing resumes, assessment, those kind of things? There are other things that other areas that it can currently do that could be used to sort of help with this bias issue?
Torin Ellis [00:11:37]:
Yeah, absolutely. So, you know, inside of our research, we. We really found that, like, 27% of the respondents are specifically using AI to reduce bias. Now, one, I’d like to see that number go up. That was one of the disappointments in the report. And when I say that, Matt, I mean these organizations, when they went to the marketplace and they were going to make this buy in decision, they didn’t include in that discovery questions specific to diversity and inclusion. It just happened to be able to help them in reducing bias. I want us to be more intentional. So when we are asking that battery of questions from our vendors, I do want a set of questions in there that specifically target diversity inclusion across the entire franchise. Now, when you ask other ways. Learning and development. In addition to candidate screening, we can leverage AI to do personalized learning and development. If we step outside of recruiting and you go to your local doctor’s office, one of the things that you appreciate about that relationship is a personalized plan. Your doctor is not prescribing something that someone else is doing per se. They are making a prescription based on your diagnosis. And I believe that we can do a far better job in terms of learning and development, upskilling, reskilling our employee base by leveraging AI. And we can do that in a very personalized way. We can absolutely use AI to equate equal compensation. Why is it that in 2025 we are still celebrating international women in terms of equal payday in March for white women, equal payday for black women in August, and equal payday for Latino women in September? Why are we still having that discussion in 2025 when we can leverage AI, do a compensation analysis across the entire organization and level people up the way that they should be? I certainly believe that we can do it in performance evaluations. Listen, there’s a continuity of people that say we should do away with performance evaluations. Okay, that’s cool. But if they stay in the organization, then let’s find ways to leverage AI so we can reduce some of the bias, some of the friction, and we can have a level playing field in terms of how people are being evaluated. So certainly there are a number of ways that we can deploy artificial intelligence across the entire employee life cycle and make it so that it’s a better experience, better culture, higher productivity, extended retention.
Matt Alder [00:14:26]:
You mentioned that you’re going to cover some of the dangers around AI later in the year. But just give us a kind of a quick preview because what’s the flip side of this? What are some of the issues that people should also be looking out for when they’re. When they’re sort of looking at AI across the organization?
Torin Ellis [00:14:41]:
Yeah, absolutely. So again, AI continuing to perpetuate. Remember in the recruiting days, we would say that recruiters only look at a resume for six seconds. So I, I believe that if we have the wrong people programming our solutions, we can use AI to discount individuals because of the sorority or the fraternity that they belong to. We can use AI to discount individuals because they don’t necessarily have the right zip code or the right academic institution inside of their resume. We, we can use AI to, to discount individuals because they are from a particular geography, if you will. So all of the ways, all of the ways that AI has the ability to be positive, they can absolutely turn on you and be negative. And so I want to make sure that we are protecting that human centered AI. I want that to be what we put our flag on as it relates to how we deploy it in the human resources and the talent acquisition spaces.
Matt Alder [00:15:46]:
And I suppose it comes back to what you said about employees because I think that there has been a tendency, because people are so fearful of some of the negative aspects of this to kind of ignore it altogether or say we’re not going to look at that at the moment. Actually there’s a huge amount of positives. But as you say, there’s also the opportunity to shape this, to shape this and make it more human. And so is this something that every TA leader and every HR leader should be engaging with?
Torin Ellis [00:16:13]:
Yeah, listen, let me tell you. We, we talked to organizations that were small businesses, mid sized organizations, all the way up to enterprise organizations. I believe more than 30% of the respondents of the report came from enterprise organizations. And I believe every single talent acquisition team, no matter how it is composed one person, 10 people, whether you have recruiting coordinators, whether you are a full desk recruiter, it doesn’t matter to me what your activity is, your, your role. I believe as an individual it is incumbent upon you to understand how these technologies can be leveraged, that you are asking questions, how is it causing harm? Where is the data coming from that is influencing what we are doing? Whether it be in our prescreen, whether it be in our communications strategy, whether it be in our follow up architecture, whether it be in our onboarding procedure. It doesn’t matter to me. I believe that we should be leveraging AI. We should be considering how it is or is not causing harm and then be willing to recalibrate, calibrate as necessary. I think one of the challenges that too many organizations struggle from is their reaction time. You see that things are not operating or unfolding the way that you had predicted, but we wait a bit too long to react. I know I’ve been guilty, I’ve been guilty in my entrepreneurial days of not responding quick enough. And I’m agile. So imagine I’m agile. I’m telling you transparently, I’ve Been vulnerable to a slow reaction, being flat footed. And I believe the larger the organization, the more that that is present. And that can be something that, you know, is really detrimental to the forward progression of any particular organization.
Matt Alder [00:18:07]:
No, 100%. I think that’s, it’s such a big issue going back right to the beginning of the conversation where we said that it already feels like it’s been a really, feels like it’s been a really long year. I mean, the scale and speed of attacks on DNI from the US government or the US President in particular, I mean, they’ve been jaw dropping to watch, although perhaps not unexpected considering his kind of first term. How are employers feeling? How are employers responding to that? What are you, what are the kind of conversations you’re having with employers? What are people thinking? What are people saying?
Torin Ellis [00:18:40]:
Yeah, depending on who you are and where you sit in that equation, your proximity to diversity and inclusion work, you have those that are fragile, you know, feeling as if, you know, we’re spending too much time talking about diversity and inclusion that, you know, that chip is, has passed and, you know, let’s move on to something different. It’s challenged right now. But I believe humanity will win. I believe there are more people that want positive human experience, cultures that are supportive, leaders that are supportive, inspiring and resourceful. I believe that there are more people that want belonging and equity than not. And so DNI will always be present.
Matt Alder [00:19:25]:
I 100% agree with you. And I think just from a recruiting perspective, as we’ve already said, if you kind of make it fairer, if you rethink the way recruiting works, it makes it better for everyone. It makes the process better, it makes people feel seen, it makes people able to be judged on what they can do and their potential and things like that. And that to me is just so kind of fundamental. I can’t see why people wouldn’t want that and wouldn’t want to move towards that.
Torin Ellis [00:19:54]:
And what I want, you know, is for people to not be, you know, disingenuous. What, what I want is for people to, to not take a position that is demeaning to other individuals. When, when you say I want mei meritocracy, excellence and intelligence. And I don’t want dei, that is very dismissive, that is degrading, that is demoralizing for some individuals that come from marginalized and underrepresented audiences and communities. You don’t need that type of language to suggest. And so here’s what I say to people. You know, I often say it and, and I Don’t care how it makes people feel. I ask a very direct question. How is it that you have associated the DEI with everyone except for white men when all of the work that I’ve done has made sure that white men have been included in DNI conversations? From the very first training that we dropped on social talents platform back in 2018, it was covering C O V E R I N G. I made sure that Johnny and Holly and team made sure. We made sure that we captured content that said to all people, you are included. And so here’s what I asked them. Does DEI apply to white men? Have we ever hired mediocre, unexperienced, less than experienced, lowered the bar? Have we ever done that for white men? And I just wait for their response. And given that response, then I either know that I’m dealing with someone who’s an authentic and genuine individual, or I’m dealing with someone who is operating with a less than authentic frequency. And then I have to decide whether or not I really want to further engage.
Matt Alder [00:21:51]:
Of course, of course. So as a final question, tell us what you think the future looks like. What does the future look like? Where are we kind of heading in the workplace? And what role could AI play in shaping that?
Torin Ellis [00:22:06]:
Yeah, well, it’s not even what role, it’s what role will AI not play. I think that that’s really what it comes down to. You got folks that are hard at work, Matt, you know, trying to develop solutions and doing everything that they can to add efficiency and shortcut and nuance to the way that we work. Listen, my honest answer is I don’t know exactly what the future will hold. You know, five years ago, people were talking about the future of work when Covid set in. It changed everything in a 45 day period. I don’t want to be one of those individuals trying to predict what the future will look like. But I am, as I said earlier in the conversation, I am concerned with the amount of people that potentially will be displaced through the presence of artificial intelligence. I can’t underscore that enough. I can’t walk away from not thinking about how people are going to struggle to care for family, health, well being, be a part of community. I don’t want to see that unfold in that particular way. And so my hope is that some of the positive reports around artificial intelligence creating tens of millions of brand new jobs and categories that are not present today is what actually happens. That when we look at full employment, we consider full employment here in the US 150 million people or keeping our unemployment somewhere between 4 and 5.6%. I hope that we do create tens of millions of new categories and responsibilities and roles that people can transition into so that five years from now we do have full employment that when agentic AI really sets in. Read an article earlier in the month that said 25% of Fortune 500 CEOs are going to deploy an Agentic AI solution in 2025. Yeah, so you know many more are going to do it next year. Five years from now I want to see that we are still looking at unemployment somewhere around 4, 5, 6% and not 20 25%.
Matt Alder [00:24:27]:
100%. Torin thank you so much for talking to me.
Torin Ellis [00:24:33]:
I appreciate you. Thank you for sharing my voice. Thank you for trusting such thank you for amplifying the report that we did with Plum. Thank you, thank you, thank you.
Matt Alder [00:24:43]:
My thanks to Torin. You can follow this podcast on Apple Podcasts on Spotify or wherever you get your podcasts. You can search all the past episodes at recruitingfuture.com on that site. You can also sign up for our weekly newsletter, Recruiting Future Feast and get the inside track on everything that’s coming up on the show. Thanks very much for listening. I’ll be back next time and I hope you’ll join me.
