EP 97: Combining AI + HR: How to do it responsibly

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If you want to get promoted or if you want to get hired, that's most of us. Right then today's episode is definitely for you because in the world of AI, everything is changing. So yeah, whether you're looking for the new job or trying to climb that corporate ladder, make sure to stay tuned to today's episode. Thank you for joining us. My name is Jordan Wilson. I'm the host of Everyday AI. Everyday AI is. It's for you all. This is for everyday people to help us all not just learn what's going on in the world of AI, but how we can actually leverage it in our careers in our companies. Extremely excited for our guest today. We have a senior leader from IBM joining us to talk all things AI and hr. I'm so excited. But before we do, you know how it goes, y'.

All.

We start with the AI news and some big pieces today. And if you are joining, please, on the live stream. Get, get your questions in now. Get your questions. What do you want to know about AI and HR and just the future of work? Because we're going to talk about it. All right, AI news, big pieces today. So Microsoft is offering to pay your legal bills if you get in trouble with using Copilot. All right, so Copilot365 is on its way out. I had an episode slash kind of rant about it about a week ago, so make sure to check that out. But Microsoft has pledged to assume some, some type of legal responsibility for any copyright infringement over materials generated by its Copilot365AI software. This is for, you know, kind of, I believe, larger, larger scale commercial customers who are sued for using AI tool. So lot of, lot of fine print, a lot of details. We're going to have it in the newsletter, but that's huge news. A company like Microsoft who is rolling out generative AI in its operating system to put that out there, that's, that's enormous. Enormous. All right, next, AI agents are coming in, raking in money. So research lab Imbu just raked in $200 million round of fundraising with big contributions coming in from Nvidia, the Astro Institute and the co founder of Notion. So Imbu is a San Francisco based startup that builds AI agents. We're not going to get into the details of what agents are, but essentially agents help connect other AI bots to each other. You Know, it's a lot of times we as humans kind of watch over, you know, a bot like ChatGPT agents kind of do that for us and help them complete a series of tasks. All right, last but not least, AI is taking away journalist jobs and it's kind of failing at it. So shout out to Leonard for sending this earlier in the week, but some updates to this story now. Gizmodo fired their Spanish speaking staff and replaced them with AI and it started making errors immediately. So go media. So the owner of Gizmodo, they recently replaced the Gizmodo and Espanol staff with an AI powered translation tool and it's not going well so far. All right, so much going on, Geez, in the world of AI news, but maybe you probably showed up to talk about AI and HR and to learn about the future of human resources in the workplace. So very excited to bring on our guest for today. Jen Kirkwood is a partner in talent in AI at IBM. Jen, thank you for joining the show.

Good morning. Thanks for having me here, Jordan. It's great to be here.

All right, well, let's, let's start there just, just a little bit. Just tell everyone briefly, just, just what are you doing in your role at IBM? Because it looks like you are a huge advocate for, you know, pushing, you know, responsible AI throughout the organization.

So. That's right. So first of all, I'm a huge advocate of diversity and that goes hand in glove with the push for ethical AI, responsible AI, and being really thoughtful of the use cases that we select in HR and the placement of AI and automation in hr. There has been a tremendous amount of AI and automation progress that's been made over the years, passionately, thoughtfully, and it's been an exciting time as we modernize HR and the world of work. It's exciting to see, and in my 28 years experience, not to date myself, it's been thrilling to see that evolution. But at the same time, especially in the evolution of generative AI that has been accelerating so quickly, you know, we need to be thoughtful about that. Not all AI is for all purposes. So. And it's really not only a hybrid type of strategy. You know, when we look to modernize the world of work and respond to things, we really need to be thoughtful because we're talking about people. And in hr, you gotta love people. You need to be a leader who loves people. And we need to be very thoughtful on the things that we do with our people and how we leverage these strategies. And so with ethics and hr and AI, it's really a trifecta of a dream job for me and working with people as we do. And so in IBM Consulting, which has just been named one of the largest consulting practices that I'm honored to be a part of, I get to work with some of the largest organizations that are really trying to be thoughtful on the strategies that they're looking at. And at the same time, I have the unique privilege of being on the AI Ethics board as a focal for talent and HR under the Chief Privacy Officer of Christina Montgomery.

Wow. So, you know, one thing, one thing you said there, Jan, is the human piece, right? Which, which I love that you are, you know, really helping push AI forward in one of the largest companies in the world. But you have a focus on humans. But normally I don't bring on questions this early, but this just makes sense. So May Britt asking, super curious how, how AI even gets used in hr. So that's, that's a great question to start with, like it being used right now. Because yeah, I'm, I'm not. I mean I, I kind of think. I know, but I want to hear from you.

Okay, so first of all, if you're, as you said in your opening, if you're a candidate, if you're employed today, if you want to get promoted, you all are impacted by artificial intelligence and even those organizations. Because I work globally around the globe here. Even if you think in your organization, if you're an HR executive or leader, you're saying we don't use AI. I would beg to differ that in some fashion, unless people are hand keying resumes, everyone is using a form of AI. And I'll share with you why. First you know some of the statistics and I believe my point of view and all these opinions are my own, but I, I definitely believe that these are underreported statistics. In the United States, according to Society for Human Resources Management, it's reported that about 70%, 79% of organizations are using AI and HR in some capacity. And in the UK by the House of Lords and Parliament, it's about 59%. And again, it's underreported. And that is because it's HR that is self reporting. But that could come from a lack of understanding and knowledge because at a basic level there are things in the ecosystem of their technology that may not be understood of what is AI. And at a basic level, from what's called resume parsing, we have shown our HR executives and especially around this thing called New York 144, which we can talk about. I know you enjoy that, that law, and you've talked about it a couple times in your show. And HR has now found the bruising of that law, and there's been so many others that have sprouted we can talk about. But within that law, resume parsing is embedded in what we call applicant tracking systems. And all candidates go through some type of applicant tracking system or process. And applicant tracking systems and this resume parsing allow simply data to move from one system to another. Well, unless people are hand keying all the resumes, which is what they did in the 90s, and I don't think they're doing that anymore because you'd need large call centers to do these things anymore. And it's highly prone to errors. And so when the AI came out for this, it advanced and the machine learning advanced and the natural language processing within that advanced tremendously. And now they're using Pytorch and all the different types of machine learning and deep learning within that. And so it's a widely known fact in the data science community that it's a fact deep learning or machine learning, but it's not well known within the HR community. So within the HR ecosystem, they are in fact using AI, but it's not widely known until we bring up examples like this.

Yeah. And you know, Jen, I think that one of the things that, you know, I think the average person just heard your response and they were probably like, oh, I had no clue. And, you know, kind of. Yeah. And kind of where my mind goes to is, is bias. Right. Because when you start to use, you know, more and more AI in hr, I think you're going to run into that. And it's a big question. So even Cecilia here asking, you know, examples of how IBM is using AI to support DEI initiatives, but let's even make it a little more a broader and just talk about her second half there, about implicit biased and, and how AI can still deal with that, especially in an HR capacity.

Oh, good, because I can't see the questions right now. So thank you. So how can repeat the last part?

Yeah. So mainly Cecilia is asking how AR can be used effectively in HR without the implicit biases that usually come along with systemized AI.

Okay, so AI can be used in so many great ways, but now we're seeing tremendous acceleration because of generative AI. Of course, to let you know, 80% of CEOs are looking to use generative AI this year, and 40% claim they're already using generative AI in some way. Shape or form. And HR is one of the top three areas that they're looking at because of productivity compliance and employee experience. So let's talk about some of the AI use cases that we're seeing. First of all, hiring. Hiring is a perfect area. And we talked about kind of just the basic resume parsing, but there's also tremendous AI. In fact, I really started its pioneering in the hiring process. And when you think about hiring, this includes sourcing, where are my candidates coming from? In a variety of different vendors, processes, targeting, sourcing, sourcing, screening, selection, onboarding. And all of these different processes are included in that, just that hiring word until you get to the day one of actually they're an employee. There's so many different processes, vendors, technologies, and that's for many different employee groups because you could have hourly salary, business units. So it's really complex. So from an hiring perspective, imagine I want to see, maybe I'm using a LinkedIn analytic. I want to see as a recruiter, who are the people that match my job. I just want to see who's matched my job. Well, that's already been pre sorted for me. In all likelihood it's already been pre sorted. Well what was that algorithm built on that was already pre sorted? Aha. That's a function of AI. And when you add on automations around it that says maybe in your company that hey, I want a built analytic that says pre sort based on this criteria. Kick off this analytic, send it to this person and it continues. Now you've got what New York calls an automated employment decision making tool, an AEDT. And now New York City and their local law 144 has taken this to say you cannot employ any AEDT. And they've defined it as a computational process, an analytic, an algorithm. They have an assortment of different things. I am not a lawyer, full disclosure or an attorney. And they have an assortment of different things. And you really need to look at the entire process with that to say, well wait, an automation could be an AEDT and an analytic. Well, it's already pre sorted, it's pre matched who my candidates are. For my recruiter, that decision process was already taken away from my recruiter. So when a decision is already taken away from someone within your process, it just needs to be evaluated. Well, these tools have to be evaluated and for New York it's within a year before you use the tool now. And the results have to be with impact analysis or 4 fist ratio and different statistical analysis and published on the website. And it goes on and on from an audit and regulation standpoint. But that's just one example. Right. The other examples are I want to see predictive analysis. Who is likely to leave my company. That's another idea.

Huge.

Yeah. It's not my favorite one because it's a likelihood, it's a probability. I think there's far better ones that are more of those artificial intelligent ones that say where are my skills today in my organization? Because every CEO wants to know right now, what is my future workforce need to look like in the future? You know, we think about and everyone's very worried and fearful of AI taking our jobs. It's going to take our jobs and the adage right now is be skilled in AI because those who aren't will lose their jobs to those who are. Take it as you will, but the World Economic Forum reports that by 2030 we will have lost. We have a gap of 85 million jobs. So by 2030 we have a skills gap and jobs of, of 85 million jobs and then we'll have a job loss. They've also reported. Well, the other part of the story is 90 million jobs. 90 million jobs will be created. We just don't know what the jobs are yet by AI and we're already seeing them in ethics roles, in new data science roles, in the genitive roles and in regulation.

Are you still running in circles trying to figure out how to actually grow your business with AI? Maybe your company has been tinkering with large language models for a year or more, but can't really get traction to find ROI on gen AI. Hey, this is Jordan Wilson, host of this very podcast. Companies like Adobe, Microsoft and Nvidia have partnered with us because they trust our expertise in educating the masses around generative AI to get ahead of and some of the most innovative companies in the country hire us to help with their AI strategy and to train hundreds of their employees on how to use Genai. So whether you're looking for ChatGPT training for thousands or just need help building your front end AI strategy, you can partner with us too. Just like some of the biggest companies in the world do. Go to your everydayai.com partner to get in contact with our team or you can just click on the partner section of our website will help you stop running in those AI circles and help get your team ahead and build a straight path to ROI on Gen AI. You know Jen, you brought up so many, gosh, so many good points here. I'm jotting down follow up questions and now it just looks like I'm writing A book, you know, so you talked about this, you know, the job skill gap. And then earlier on in your response, you talked about the survey that said, you know, 80, I believe it was 80% of CEOs want to be using generative AI soon in the workplace. So what's, I guess what's the gap there? Or are you seeing hesitancy? Not saying at IBM, but just across the board for enterprise companies to really embrace and to use generative AI? Is it ambiguity on governance? What are you seeing from your vantage point? The roadblocks to, you know, jumping from that 40% to 80% actually using it.

So we're seeing tremendous, tremendous, full, both feet jumping in on the generative AI in HR from executive leaderships, from the chief strategy officers and CEOs. And this is not just IBM across the market, across all of the big tech players and consulting market, we're seeing all of the organizations jumping in with tremendous velocity. We are seeing trepidation. And it's not necessarily fear. It's needing to get educated by the HR executives. It's on a multitude of levels on how do I understand the generative AI for my organization very appropriately, do we have the skills in HR to understand it? Then there is some fear on, you know, I understand there's privacy or intellectual property issues. How do I work these use cases for my workplace? And generative AI, very thoughtful and appropriate. And then truthfully, you know, we need to be bringing up privacy ethics and the appropriateness of where is the opportunity well thought out and well placed in HR and talented. And where are the risks and how do we mitigate the risks? Because there are risks with generative AI in hr, no question. And generative AI is not right for all use cases. It has a place, classical or traditional AI has a place and automation has a place. And so when you look at, and then the people in the loop, the human in the loop need to be appropriately inserted in any type of modernization strategy from a design perspective. So go ahead.

So, no, just, just so much, so much to tackle there. You know, Jen, I, as you're talking, I keep thinking of the progress and just, just really the timeline of how HR companies or HR departments have been and will continue to be using AI. But, but I'm also curious, what is, what are you seeing this look like in the future? You know, because someone from your vantage point probably has a lot more exposure to this than, than the average listener out there. But what do you see kind of the future of AI in hr? Not asking you to look in Your crystal ball. But where, where are we headed? Because it seems like things are developing rapidly. And then what does that, what does the future of AI and HR mean for both people in hr? And then what does it mean for the rest of us?

Okay, you might have to remind me of all those segments. I think the first three things that I would suggest because some of the future, we talk about the future of work, but let's talk about the future is now. Because futuristic pieces need to be realized right now. And there's three things. The modernizing of HR includes the modernization and the upskilling of HR right now. And that includes from upskilling HR in data science or data engineering skills from a basic level. It includes explainability in ethics and understanding regulations, that those pieces cannot be relegated to IT or legal, that the compliance and the pieces of regulation and the IT pieces have to exist and be understood in hr, that there are too many pieces going on, that the workforce needs to build trust, that the brand needs to be protected and that sits squarely in hr. And don't mistake, IT has to be triangulated and used within their partners of enterprise IT strategy and with their legal business partners. But HR is the center of educating the organization and their workforce because their entire workforce needs to be digitally skilled. But HR needs to be modernized both from technology and education. The second thing is, you know, they need to understand the new regulations. OFCCP with the. The Office of Federal Compliance for federal contractors literally just rolled out a new law that on August 23, this is how fast everything is coming. California rolled out a new law on defining the employers under the Fair Housing Act. These things are changing the way we're onboarding or we're screening applicants. The OFCCP is now changing the way you can screen an applicant with gamification software. So if you're trying to scroll screen for a packaging worker and you're having them try out simulation, which is very fair, or any other type of gamification software that you use in pre selection or with an applicant. You need to now review this because if it has AI in it, which it likely does, it can, it can actually have bias in it. And it needs to be reviewed in terms of race, ethnicity, gender, etc. And then the third piece is experience, understanding that the quest in the holy grail for creating the perfect employee experience has to dramatically transform and we don't have a choice in HR now employees, if you have a policy, it says you can't use ChatGPT in your workforce. Understand the employees are now pushing the organization because they are going to bring it to work and understanding that these black box models that do not have the transparency, the explainability and put the company at risk for loss of intellectual property. Samsung tried to finish a code and when they tried to finish the line of code, they lost valuable IP because it was now consumed in property of that model. And that is often the same with Llama and Bard or other types of models that are out there. And HR needs to understand that and write policies, but also understand that employees now expect these digital tools at work. So experience has to change because if you don't serve up these type of experiences, they will bring their experience to work. So now what the future looks like is it's ethics. It's ethics and privacy because all of these regulations are coming globally. Greece, Latin America, the EU that it's now passed or, and it's coming fast and furiously. The Senate, the states, the cities, all of this is coming fast and furiously. And I'm hopeful that they will lean on precision regulation versus licensing, big tech for carte blanche type of licensing versus competitive pieces and let everybody play and regulate use case by use case. But you know, this is ethics and privacy and understanding these models has to be the future, not just really as HR leaders and executives, but truly as digital citizens. Because you know, this is, this is not the Elon Musk here of doom and gloom. But if we don't get educated on this and squarely in hr, we will have, you know, extreme risk for organization and ourselves.

Yeah. And you know, if people are listening to this on the podcast, when Jen just mentioned, you know, the kind of this not power struggle but you know, employees wanting to use generative AI tools and then HR having to be the one to set the policies, my face lit up because to me it's so intriguing and I'd say that's where probably so many companies, Jen, now are, especially those small and medium sized businesses. So that brings me up and I know this conversation has drug on for a very long time, but I do want to get this question in. So Dr. Harvey Castro asking, saying hey, can you please give simple and advanced ways to use AI and hr? But I'm going to put a slight spin on that and say for the smaller or medium sized businesses, I think Jen, what, what you just referenced is probably what's going on a lot. You know, maybe HR isn't able or maybe they don't have the expertise yet to set that kind of AI governance that's, that's required. Yet you have the employees wanting to use it, and probably rightfully so, you know, as you're seeing it rolled out even into operating systems. So what's some advice from your vantage point on how to deal with that? And then kind of simple ways that companies of all shapes and sizes can use AI in their hr.

Okay, great questions, wonderful questions. Let me go simple here. The use cases that we're seeing, the predominant need for besides experience, right. Is employees, and notably managers find that employee transfers are some of the hardest activities. And even within our own company, that was feedback that we got before we put AI and generative AI and different pieces in place. So we got it from our own managers. If you can look within any size company and ask how am I doing employee transfers, how are my managers? What kind of time are they spending on that versus spending with the customer, their employees, their products, that is a huge transactional effort. And AI can really improve that process and so can generative AI. So that is a huge opportunity and area the recruiter process. Recruiters are spending heavy transactional time and we have found in hard documentation and in research that happy to share afterwards that there is huge transactional savings. Recruiters would rather be using strategy and coaching and helping in developmental areas versus the mundane, sending emails, doing those type of activities. And AI can be used heavily with the recruiters to get them out of their transactional activities and trying to not only source the employee, the candidates, but also move the candidates through the process, such as the scheduling activities, the manager activities and what was the second part of your question?

Just kind of how that kind of balance, balance of power. But just how can the employees still take advantage of all these great generative AI tools without a huge HR team that has experience in AI governance?

Yes. So leveraging tools that for HR without making them data scientists. There are tools out there that can be leveraged, that are private. And I would look for large language models, AKA generative tools that have catalogs, skills that are already pre built. And IBM does have those with our Watson. But if they're pre built, HR technology experts within HR can leverage these pieces and actually pull these in. Very simply, those are a real win for companies because you can leverage those pieces. Now governance, you cannot skip governance. There has to be governance and understanding privacy and understanding the ethics around it so that when an employee says how is my data being used? If you're tracking productivity and keystrokes in companies, then you need to reevaluate that and say have I shared with employees how their data is used, how the data is shared and consult on those types of pieces.

Wow, Jen, thank you. Wow. I mean we literally went from the history to the future ethics practical examples. We went top to bottom here. Thank you so much for coming on the show and sharing your expertise. I really appreciate it.

I really appreciate the invite and thank you to the audience. Any follow up questions. I would say the center for Inclusive Change.org is a phenomenal resource with Dr. Carrie Miller. I would also say littler with Naloy Ray. Awesome. A great resource. Your radio show has had some fantastic privacy and ethics speakers on here that I would reference and going back and listening to for anyone who's interested in and leaning in and finding more as well.

All right, well hey, thank you for that. Well, let me go ahead and add a couple more things in here. So just as a reminder, Jen covered a lot so you know, we didn't even get in. She's written some great in depth articles on just AI and hr so we'll be sharing those in our newsletter. So if you're not signed up, just as a reminder, please go to your everydayai.com Sign up for the daily newsletter. We're going to have a recap of everything Jen talked about and more and some of the things that we didn't get time. So make sure to go sign up for that and also as a thank you. Thank you Jen. It's almost like you're my assistant here but make sure to check, check the show notes because some of those other great episodes and great guests that had on that are related to topic, this topic, we're going to be throwing those in there as well. So Jen, thank you again. Thank you everyone for tuning in and we hope to see you back for another edition of Everyday AI. Thanks y'.

All. Thank you. And that's a wrap for today's edition of Everyday AI. Thanks for joining us. If you enjoyed this episode, please subscribe and leave us a rating. It helps keep us going for a little more AI magic. Visit your everydayai. Com and sign up to our daily newsletter so you don't get left behind. Go break some barriers and we'll see you next time.