Everyday AI Podcast – An AI and ChatGPT Podcast - EP 97: Combining AI + HR: How to do it responsibly
Episode Date: September 8, 2023Everything is changing because of AI, including the HR and the hiring process. So what does responsible AI look like in HR? Will it be your next interviewer or even your next employer? Jen Kirkwood, P...artner, Ethical HR & AI at IBM, joins us to discuss how AI is transforming HR and ways to use it responsibly. Newsletter: Sign up for our free daily newsletterMore on this: Episode PageJoin the discussion: Ask Jen and Jordan questions about AI in HRUpcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTimestamps:[00:01:17] Daily AI news[00:04:00] About Jen and IBM[00:06:20] How AI is used in HR[00:10:14] Avoiding bias when using AI in HR[00:16:34] Are enterprise companies using AI?[00:19:20] What's the future of AI in HR?[00:25:30] How small to medium businesses can use AI in HRTopics Covered in This Episode:I. IntroductionII. Discussion on AI and HR with Jen KirkwoodIV. AI in Specific HR FunctionsV. AI in HR for Small and Medium-Sized BusinessesKeywords:AI agents, AI bots, tasks, journalism, translation tool errors, human resources, productivity, compliance, employee experience, hiring process, resume parsing, sourcing, screening, selection, onboarding, LinkedIn analytics, automation, employment decision-making tool, promotion, hiring, Microsoft, copyright infringement, research lab, Embu, show notes, diversity, ethical AI, hybrid strategy, skills in HR, privacy, intellectual property, appropriate use of AI in the workplace, humans in the loop.Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Start Here ▶️Not sure where to start when it comes to AI? Start with our Start Here Series. You can listen to the first drop -- Episode 691 -- or get free access to our Inner Cricle community and all episodes: StartHereSeries.com Also, here's a link to the entire series on a Spotify playlist.
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This is the Everyday AI Show, the everyday podcast where we simplify AI and bring its power to your fingertips.
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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.
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My name's Jordan Wilson.
and 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 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 copilot 365 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 type of legal response.
for any copyright infringement over materials generated by its co-pilot 365 AI software.
This is for, you know, kind of, I believe, larger scale commercial customers who are sued for using AI tools.
So a 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 enormous, enormous.
All right, next, AI agents are coming and raking in money.
So, Research Lab, Imbu, just raked in $200 million round of fundraising,
with big contributions coming in from Nvidia,
the Astor Institute, and the co-founder of Notion.
So, Inbu 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 chat
GPT.
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 GEO Media, so the owner of Gizmodo,
they recently replaced the Gizmodo in Español 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 and 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 start there.
Just a little bit.
Just tell everyone briefly, 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 far,
quickly, you know, we need to be thoughtful about that. Not all AI is for all purposes. 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 got to 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 in 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 in HR under the Chief Privacy Officer of Christina
Montgomery. Wow. So, you know, one thing, one thing you said there, Jen, 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 I'm,
Normally I don't bring on questions this early, but this just makes sense.
So May Britt asking super curious how AI even gets used in HR.
So that's a great question to start with.
Like, how is it being used right now?
Because, yeah, I'm not, I mean, 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 impassed.
by artificial intelligence.
And even those organizations,
because we're 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 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 8%.
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 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 allowed simply data to move from one system to another.
Well, unless people are handkeying 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 pie torch and all the different types of machine learning
and deep learning within that. And so it's a widely known fact in the daily 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 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 little broader and just talk about her second half there about implicit biased 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 I 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, AI 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?
Uh-huh.
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 automator.
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 for-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.
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 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.
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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 is there, are you seeing hesitancy,
not saying at IBM, but just across the board for enterprise companies to, you know,
really embrace and to use generative AI? Is it, is it a, you know, an ambiguity on governance? Like,
what are you seeing, you know, 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 in 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 talent?
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 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 I'm also curious, 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 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 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. OFCP with the
Office of Federal Compliance for Federal Contractors literally just rolled out a new law that on
August 23rd, 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 OFCP is now changing the way you can screen an applicant with gamification
software. So if you're trying to 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 actually
have bias in it and it needs to be reviewed in terms of race, ethnicity, gender, et cetera.
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 chat GPT 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 try to finish the line of code, they lost
valuable IP because it was now consumed and property of that model.
And that is often the same with Lama and Bard or other types of models that are out there.
And HR needs to understand that in right 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 types 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.
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. It 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 nothing.
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 policy.
my face lit up because to me that's 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 I know we're uh you know this conversation as has drug on for a very long time but I
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
these smaller or medium-sized businesses, I think, Jen, what you just referenced is probably
what's going on a lot. Maybe HR isn't able or maybe they don't have the expertise yet to set
that kind of AI governance 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
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've 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.
an area, the recruiter process. Recruiters are spending heavy transactional time, and we have found
in hard documentation and in research that I'm 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 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 of power, not, yeah, but just how can, you know,
the employees still take advantage of all these.
great generative AI tools without, you know, a huge HR team that has experience in AI governance.
Yeah. 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 and 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. 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 everyday AI.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, thank you, thank you, Jen.
It's almost like you're my assistant here.
But make sure to check the show notes because some of those other great episodes and great
guests that we've 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.
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