August 8, 2024 • 32 mins
Is AI the future of recruitment, or just the latest trend? In this episode of Real Talk on Talent, Dina and Hilary promise to uncover how AI is transforming the recruitment landscape by making it more efficient and streamlined.
Learn how AI tools are automating administrative tasks like creating job descriptions and improving candidate communication, freeing up recruiters to focus on what truly matters—building relationships and honing their skills.
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Links & Mentions:
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➡︎ Hot Take | “A.K.A we will need less people to pay wages to”: Naughty Dog President Neil Druckmann’s Hot Take on AI’s Many Benefits Irks ‘The Last of Us’ Fandom
➡︎ Workday accused of facilitating widespread bias in novel AI lawsuit
➡︎ CGI in Hollywood | Why TRON Was Disqualified From Being A Visual Effects Oscar Nominee
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Connect with our Team of Huemans:
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➡︎ Website: https://www.hueman.com/
➡︎ Podcast: https://www.youtube.com/@huemanps/podcasts
➡︎ LI: https://www.linkedin.com/company/hueman-people-solutions
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#hueman #talentacquisition #recruiting #recruitmentprocess #rpo
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 2 (00:06):
Welcome to Real Talk on Talent, a human resources
podcast where we talk abouttalent acquisition, recruiting
and all things hiring.
Hey Dina, hi Hilary, welcomeback.
Thank you, I'm excited to behere today.
I'm always excited to be herewith you, I know.
Thank you, I'm excited to behere today.
I'm always excited to be herewith you.
Sometimes it takes me a minuteto get like my momentum, but I'm
(00:30):
always excited to sit down withyou.
Speaker 3 (00:31):
So I have my coffee right now.
So.
I'm hoping that can kickstartmy momentum.
Speaker 2 (00:35):
Also, I just realized that the human mug matches the
color of your dress by designNailed it.
Speaker 3 (00:40):
My coffee mug always matches what I'm wearing.
It's very on brand.
Speaker 2 (00:43):
Yeah Well, there we go.
As the marketing person here,I'm very proud of this.
Thank you, thank you you knowwe talked one time about getting
custom human scarves.
Speaker 3 (00:50):
Yes, we still need to make that.
Yeah, yeah, no, I would likethat, okay.
Speaker 2 (00:54):
Let's do it, I would like that.
Yeah, of course we're going tojump straight in to AI, ai,
because we keep referencing it.
Everybody's talking about it.
Literally as we were sittingdown, I got an alert from the
New York Times all about AI,like it's Killer robots.
(01:14):
Yes, yeah, can't get away fromit.
Yeah, not the robots that we'renot going to talk about.
Speaker 3 (01:19):
We're going to stay away from them.
We so we really can't, we'renot gonna talk about killer
robots?
Speaker 2 (01:23):
Okay, good, because this is the talent podcast Okay
Okay, good Helpful directionthere.
Speaker 3 (01:29):
Got it.
Okay, got it.
Speaker 2 (01:30):
So I would like for us to talk about AI, but
specifically thinking about howAI is being integrated into the
recruitment process, how you useit, and also thinking about
pros and cons and even just someinteresting elements that I'm
(01:53):
sure will come up as we talkabout AI and how leaders and
recruiters should can thinkabout it.
Maybe even candidates.
Oh yeah, Love it, Love it.
I do want to start this byadmitting that I have never used
chat GPT.
You love it, I do love it.
I feel like we're a goodrepresentation of the two sides
(02:13):
of.
Ai in the informal adoption.
Yes, for me.
I find so much pleasure in likecrafting words and like doing
analysis that I just haven'tever thought about where I would
want to integrate it into myday-to-day work life.
(02:34):
So let's start here.
You are a recruitmentoperations leader, you work in
sales, you lead people, youinterface with a lot of
different individuals.
How do you use ChatGPT, or Ishould say AI, ai.
Speaker 3 (02:50):
Yes, so you know what ?
That is actually something thatI want to say, I think, since
AI is relatively new and ChatGPTseems to be the product that
everybody knows, it is the thingthat brought AI to the masses
in a usable way.
One thing I often hear peoplesaying is well, how are you
going to use chat GPT inrecruitment?
So I want to be clear, likethat's not the right way to say
(03:10):
it, so, Hillary, don't say thatagain.
It's.
Speaker 2 (03:12):
AI.
You know what I am learningfrom you there we go.
Speaker 3 (03:17):
So, first of all, huge fan of AI.
For me, what I really like is,as I was explaining earlier,
sometimes my brain is like abowl of spaghetti and I don't
know where to start with it.
So for me, AI platforms such asChatGPT are a great place to
organize my thoughts, so I cantake a whole bunch of data, dump
(03:38):
it in there and it'll spit outsome high, you know.
Here are the highlights.
Kind of help you digest it andstart somewhere.
Exactly, exactly, but's a greatcall out, but from a
recruitment perspective, likethere are lots of different use
cases for it, I think where I'mstruggling right now to actually
see it applied is in a cohesivemanner within one platform.
Speaker 2 (03:59):
Yes, yes, and you kind of see this like race to AI
, where, as soon as it becameavailable to the mass market,
everybody started you know,snapchat's like we're going to
give you your AI best friend,and the job boards are putting
AI content, like recommendations, into their sourcing tools.
(04:20):
It is absolutely been this.
Here's this ability.
How can we commercialize it?
And I do think that, for on therecruiting side, there has been
a very tight focus on recruiterefficiency, which I think is
the number one place that AI isreally breaking into the
(04:41):
recruitment space, completelyagree.
Speaker 3 (04:42):
I think that's the best place for it to break in.
Speaker 2 (04:45):
Okay, tell me for you , because we actually talked
about efficiency last time, yeah, yeah, so, and we didn't even
touch on AI interestingly, wetried to save it for this topic.
We talked about AI.
So when you think about AI,there are a number of studies
that talk about pros and cons,how people play into it, all
that kind of stuff.
Give me your perspective on,very tactically, how you think
(05:09):
AI should and is most effectiveat the recruitment level.
Speaker 3 (05:13):
Yeah, so when I think of a recruiter, I want to think
of what is their highest andbest use of their time.
When you think of anybody intheir role, what is your highest
and best use?
As a recruiter, your highestand best use is not
administrative tasks, and thatis where I see AI helping out
quite a bit.
Speaker 2 (05:30):
Okay.
So when you say that, Iimmediately think of job
descriptions.
Speaker 3 (05:33):
Job descriptions, what else?
Yep?
So there is.
We actually demoed this ATS andI absolutely loved it, but for
some reason it's not going towork for our business needs.
But I'm going to tell you allthe bells and whistles that this
particular system had withoutsaying it.
So here's what I loved, and tome it outlined every opportunity
for recruiter efficiency.
(05:54):
So first, a recruiter needs tocreate a job built in AI to help
with that job description.
Okay, it does the candidatecommunication on the front end
to kind of screen out candidatesEmail text, chatbot, chatbot.
So chatbot and again these areoften very black and white
things that it is screeningcandidates out for so basic
(06:16):
qualification questions.
I don't want my AI makingdecisions, I want them following
kind of instructions that Igave it almost.
Speaker 2 (06:26):
So that's interesting , but that's not AI.
You're right, because ifthey're just following if-then
statements, then that's justnatural language processing or
automated processes.
But you do bring up a good pointwhere you said it does the
initial screening for black andwhite elements.
So, looking for certifications,If it were me I'd probably
stick to those types of veryformal.
(06:47):
There is no nuance to it.
You must have it to take thisrole.
But maybe you use AI to furtherdiscover skill abilities or
think about how you couldtranslate other experiences in.
So it's not kicking them out,but maybe it's helping like
digest that experience and bringit forward to the recruiter.
Speaker 3 (07:10):
Yeah, so I think that .
So just from a pureproductivity perspective,
there's a lot of time to besaved by recruiters If there is
some type of technology having aconversation with candidates
saying, hey, this job is 40hours a week, you have to work
weekends and compensation is $12an hour.
(07:32):
Are you interested in movingforward?
Speaker 2 (07:34):
But you don't need AI for that, you don't need AI for
that, full stop.
Speaker 3 (07:42):
Actually, though, here you're going to bring me up
, I'm going to, I'm going to.
I think I need another cup ofcoffee.
No, put it down.
Pre-podcast, okay.
So when we first heard about AIin recruitment world, I think
there were some technologiesthat came out and they said this
is AI recruitment technology,because it sounded nice, but it
was not actually, but it wasn'tactually.
(08:03):
Because it sounded nice but itwas not actually, but it wasn't
actually.
It is what I'm describing rightnow.
It is where you go in and youprogram answers and it will
screen candidates according toyour answers.
That is helpful in somesituations.
Again, those are high-volumetype jobs where we are screening
people on very black and whitethings.
Fine, but you were talkingabout recruiter efficiencies and
how AI ties into it.
(08:24):
Here we go.
So recruiter efficienciesscheduling candidates that helps
.
Let's look at candidateavailability.
Recruiter availability when Ireally started to get excited
about some of the efficiencieswere some technologies that we
demoed actually had recruitersdoing phone screens.
Ai was listening on their phonescreens.
As a result of thatconversation, it would write up
(08:46):
the candidate summary for you.
Here's everything we heardabout the candidate.
Speaker 2 (08:50):
It could go ahead and distill that information In an
ideal world, love it.
It sounds amazing and I'mtotally bought into that.
I completely agree Get rid ofall of the administrative tasks
so that a recruiter could spendtheir time building
relationships, sourcing for hardto fill candidates, et cetera.
We didn't even talk about AIsourcing that.
We.
Maybe we'll tap it, not if wehave time.
(09:12):
What two things.
There have been some studiesconcerns that AI.
Because AI is completelyfounded on, like, the
information being fed to itright and like, for example,
google has been serving up morelike AI solutions, like.
(09:33):
I think it's specifically tiedto Reddit is the example I'm
thinking of and this may be acorrection section if I'm
getting the specifics wrong butthe AI is serving up answers
from Reddit, but, as you canimagine, some of the answers
from Reddit that are being shownon Google are not great and, in
fact, some are just straight upbad.
So, yeah, so what happens if AIis not actually getting better?
(10:01):
And how do you have a recruiter?
Make sure that they're notover-relying on the information
being served back to it, becausewe know it's not perfect.
Yeah, so how do you?
Speaker 3 (10:10):
navigate that.
So first don't ever blindlytrust anything.
Life lessons from Dina DiMarco.
Speaker 1 (10:16):
Life lessons.
Speaker 3 (10:17):
Don't put blind trust in something, except for me,
obviously, okay, obviously, inthis particular scenario where
AI is writing the candidatesummary, really what it's doing
in that case is it's saving therecruiter, it's allowing the
recruiter to spend more timelistening to the candidate,
really paying attention, payingattention, truly understanding.
I like that, I like that.
(10:37):
So when you get that summary,the recruiter is not going to
just send that summary rightover to the manager.
It's going to make a couple oftweaks and it's going to say I'm
going to add this, I'm going totake that down, but that saves
the recruiter then from havingto go ahead and write their own
summary, upload it into the ATS,wordsmith it for the client,
all of those type of things.
That's a really good point.
Speaker 2 (10:57):
I didn't even think about it that way, because I did
see I'm not going to call outwho it was.
It was a staffing company thatwas talking about benefits of AI
and one of the things they saidis to serve up a resume and
your job description and ask AIto basically talk about
compatibility.
Okay, interesting, which is aninteresting angle, because you
may not consider how certainbackgrounds are tie in.
(11:19):
Yeah, but two things One, Ifeel like that's your job as a
recruiter.
Yes, I feel like a summarycould be interesting, but if
you're basically saying what'sthe compatibility on this?
Like it was like a beige flagfor me, not beige, what is it?
An orange flag for me?
Speaker 3 (11:35):
OK, the other you do tend to be a neutral person, so
I could see how a beige flagwould work for you, I think
beige flag is like there is nogood or bad?
Speaker 1 (11:42):
There we go.
Speaker 2 (11:45):
The other thing is what if a candidate has written
their resume based off your jobdescription using AI?
Okay, so they take your jobdescription, they throw it in a
chat GPT say, here's myexperience.
Now make it sound great.
Essentially, you have chat GPTapplying to a job or AI applying
to a job and AI analyzing theapplication, so you don't
(12:08):
actually have any humanintersection there at all, yeah,
yeah.
Speaker 3 (12:12):
So again, is that wrong though?
So it is wrong.
Okay, it is wrong.
And this is where people needto be involved in the hiring
process.
You know there is always goingto be this discerning element,
so, in that need to me needs tobe involved in the hiring
process.
You know there is always goingto be this discerning element,
so, and that need to me needs tobe a human element of who is
going to actually make thedecision whether or not somebody
moves forward.
I think my biggest concern witha lot of the AI platforms is is
(12:33):
what is the data set that theyare learning from and what are,
what are the biases that existin there?
And then you know, to the pointyou just made, how, right now,
there's such an emphasis onskills-based hiring, where we
are looking for people.
You know you don't have to havethe exact experience, but do
you have relevant and adjacentskills?
(12:55):
You know the idea of comparinga resume to a job description
really kind of undermines thatconcept.
Speaker 2 (13:00):
That's interesting and you know you said that.
The whole idea of skills basedhiring, I think one.
What that makes me think of iswe often talk about integrating
AI for efficacy, to be able tomake recruiters move more
quickly, you know, to see morecandidates shorten your time to
fill all that kind of stuff.
(13:21):
But I would argue that when youadd in AI, you actually need to
rethink your process in general.
It's not a one-to-one switch.
You're not just saying, hey,you're not scheduling candidates
, therefore you should have morecandidates on your calendar.
That might be a byproduct butsaying, because you are no
longer doing this, theexpectation is you're no longer
(13:44):
taking notes in your interviewwith the candidates, so your
default may be to be like, ohgreat, now it took me half as
long to get my summary, I'm justgoing to send it over.
But what's the new step in theprocess that you can add in?
To be a better recruiter, tohave better relationships, to
learn about skills-based likethat creativity.
(14:05):
But I think it's a leader's jobto set the expectation of if
we're investing in this tool sothat you no longer have to spend
time here.
It's not just so that you cansee more people.
Yeah, it's so that you can see,so you can learn more people,
that's not right.
Speaker 3 (14:21):
Well, you know what I mean.
Yeah, we don't only want toimpact the quantity of work that
we're doing, we want to impactthe quality of work that we're
doing as well.
Quantity will be a byproduct ofthat.
I agree Quantity is going to bea byproduct, but you nailed it
on the head with what you justsaid, because people's default
(14:47):
is going to be oh, I'm so muchmore productive now more
quantity.
How do you take the efficiencyand the time back that you've
gained to enhance your skillsand to become a better recruiter
in general?
How are you now, when you're onthat phone screen, asking
really probing questions towardsthe candidate?
How do you spend more timeunderstanding which skills truly
are transferable, doing backendresearch, whatever it is?
Speaker 2 (15:01):
I think that is something that when you read
about AI and recruiting, it's sovery tactically based.
But that idea of like I'm kindof stuck on the skills
transference or I'm eventhinking about like second
chance candidates.
Okay, Like people from eitherthat you may just say, oh, you
don't meet the qualifications,like whatever.
(15:22):
If we can use AI efficiently,it actually opens up the door
for us to better not just findand engage, but even potentially
coach and help and help thebusiness rethink.
Not just say, here's acandidate, how they're going to
fit in, or you have these skillsso you candidate can transfer
(15:45):
these skills into the role tobenefit us.
But you could even say thatit'll allow talent acquisition
to go back to the business andsay, look, there's an
opportunity here, whether it'swith someone who's a second
chance, or if we start thistraining program, we can help
them into this.
Like it could really help thebusiness do better by the
(16:05):
candidates that come in, notjust better screen out
candidates that don't fit.
Speaker 3 (16:10):
Yeah, yeah, there's.
There are a lot of doors thatit opens for you, and that's
what I think we're using itright.
If you use it right, I thinkthat's what we're just beginning
to open up is like okay, yes,we know AI is going to make you
more efficient.
There are lots of tactical ways, but as that door begins to
open wider, what are you doingwith that?
Yeah, you know, and to me,that's the exciting part.
Speaker 2 (16:31):
Do you know I, as a marketer, I've struggled with
job descriptions for a long timeEspecially.
You know they have to soundprofessional, you have to hit
all the important stuff You'replaying into.
You know the algorithms of thejob boards and their rules of
posting you kind of like.
Honestly, job descriptions havekind of been a struggle where
I'm like they're just not thatfun to write.
(16:53):
So what I would love to seetalk about the fun, creative
things we can do I want to see ajob description written in
limerick Okay Fullick, okay Fullstop Okay.
Speaker 1 (17:05):
Chat GPT could do that for you.
Speaker 2 (17:06):
That's what I'm saying that's what I'm saying.
So instead of just being like,oh yeah, yeah At Human, we're a
great place to work, Do you havethese seven skills?
Three of them are preferable.
You could start on Tuesday.
Speaker 3 (17:22):
Like instead like Tuesday.
Instead, use ChatGPT to turn itinto a limerick, Spice it up
and let's see.
Yes, so here we go there.
Once was a company in Nantucket, or whatever.
I am totally down to beta testthis.
Let's do it.
We'll go rogue, we'll post thejob on our own.
Not rogue, not rogue, not rogue.
We never go rogue.
We don't go rogue Ever.
No, nobody has approved thispodcast, but actually I actually
love that idea.
(17:42):
You know what I mean.
Speaker 2 (17:43):
Like have fun.
Think about the candidate isone.
What do they actually need toknow?
And I do agree, like I'm a bigbeliever in like to the point.
This is the role, like here'swhat you'd be doing, here's what
you need to know, here's whatwould be kind of helpful if you
knew.
But I'm also thinking aboutthat slog of going through,
especially right now, is likewe're shifting more to an
(18:04):
employer market.
I've seen more and more peopleon LinkedIn who are like I'm
looking for work I've applied toa bunch of jobs.
How nice would it be if you seethe same marketing specialist
job description 17 times andthen all of a sudden you get one
that's written in rhyme?
Speaker 3 (18:21):
Yeah, well, I think they're.
You know what?
We are totally going off therails here, but I'm into it.
Speaker 2 (18:26):
We're not, though, because we're talking about the
impact of AI.
Speaker 3 (18:28):
AI.
There we go, Okay.
So I do think it's a uniqueopportunity for companies to
tell a little bit more aboutthemselves in a more authentic
way.
Speaker 2 (18:37):
What do you think about AI in like an analysis
stand?
No, not analysis.
What I mean is like screening,so like you have your database
and you have AI layered on andthey're kind of analyzing all of
the candidates in there tosource up potentially qualified
individuals.
What do you think about AIsourcing?
Speaker 3 (19:00):
So you know, initially I'm all for it,
because here's what I'll tellyou I do feel like there's an
opportunity, there arecandidates within your database
that are good, and it's agoldmine, and databases are
often untouched.
What I worry about and what Ithink about is, like there was
that Workday lawsuit whereWorkday's AI you know they were
(19:23):
being sued because they weresaying the bias in the system.
So what I don't know enough ofis how is it serving up these
candidates and what is helpingit to make that decision?
What's its learning process?
Speaker 2 (19:36):
And I guess that is true for AI in general.
So what's the responsibility ofthe human?
Yeah, and is that sorry answer?
And then I've got somethingthat popped in my head yeah.
Speaker 3 (19:48):
So I think for me personally, until I can become
comfortable with the AI platformand understanding how it's
learning, what's its data set,what are the biases?
Where I want to use AI is noton decision making, but I want
to use it more on so you wouldnot use it for sourcing.
I'm not saying I wouldn't useit for sourcing, but I'd be
(20:12):
foolish not to use it forsourcing.
I mean, listen, if everybody'sadopting AI which they are you
will get left behind if you donot adopt it.
I am just recognizing thatthere is potential risk out
there with it.
Speaker 2 (20:25):
Yeah, I have seen more and more companies starting
kind of like companies havesecurity policies, having
specific statements aroundexpectations for AI use, so kind
of like there are expectedbehaviors of how you show up on
social media, of how you useyour work computer, that kind of
thing.
They're starting to have moreformal company positions on how
(20:46):
AI should be used and can beused in regards to work.
Speaker 3 (20:50):
Yeah, yeah.
So I'll tell you one kind ofinteresting use case here.
So my recruiters are oftenrequired to recruit for a
variety of job functions,sometimes which we've stopped
doing this because we found itdidn't work they were being
asked to recruit for a jobfunction that they have never
recruited for before and what Ifound they were doing was they
(21:11):
were going to chat GPT and theywere saying what are a list of
questions I can ask the hiringmanager to understand this
position and a list of questionsto ask the candidates?
It is, but not if you don'tactually take the time to
understand the position itself.
Sometimes it can be a shortcutto a detriment.
Speaker 2 (21:31):
Yeah, and if they serve up like incorrect
information or in a way that, ifyou said it, it's like a
trigger, you don't actually knowwhat you're talking about.
Exactly yeah, and so I do thinkthat's part of the risk as well
with AI, but I do think to yourpoint, like knowing where to
start to go in and say, hey,here's this new position.
Like Whitney, who did we justhire on?
The marketing team?
(21:51):
Emery, no.
The DevOps no.
Speaker 1 (21:57):
Oh, that's still in the works.
Speaker 2 (21:59):
No, but what's the role?
Oh See, it's a very specific.
You ladies need a cup of coffee, but so this is the exact See
the fact that we can't rememberthe exact title we just hired a
very or we just we have an openposition for a very specific
(22:19):
digital data analytics,specifically as it ties into the
revenue cycle and CRMmanagement, reporting, that kind
of thing.
So if you are a recruiter whohas no marketing experience, no
data analytics experience, andyou sit down to say, okay, I
have to go find someone, chadGBT could be like, okay, great,
(22:43):
let's give a little bit ofcontext about CRMs and like how
you look at revenue cycles andmaybe go look into this, and so
it could open up a door to startsaying here are the things that
are going to tie into this.
Speaker 3 (22:53):
Yeah, I think the important part is it's fine to
ask chat, gpt, what are goodscreening questions, but make
sure that the fundamentallearning is there too.
So, again, it's not justrelying on AI.
Speaker 2 (23:06):
What are you screening for, not what
questions are you asking?
Speaker 3 (23:09):
in the screening process and it's really making
sure that you're partnering AIwith the additional learnings
the foundational learnings of it, so it can accelerate people's
learning process.
It can make you come up tospeed on something much more
quickly, but it is importantthat you actually take the time
to absorb the information aswell.
I completely agree, okay.
Speaker 2 (23:29):
So reference back to our generational podcast Okay,
gen Zers are not going to Googleto find answers, they're going
to TikTok.
They're using TikTok as, like,the number one, like search
engine, okay, which we didn'ttouch on this, and I have a lot
of opinions about TikTok or chatGPT.
Speaker 3 (23:54):
So, if I am correct, chat GPT's data is a couple of
years old, like they're notgetting the most recent stuff,
so I would actually pick TikTok,you would.
Speaker 2 (23:59):
Over chat GPT.
Speaker 3 (23:59):
Interesting.
That being said, I have neverbeen on TikTok before, so you
haven't.
No, oh no, I'm not a TikToker.
Speaker 2 (24:06):
So then that's a little bit of a I'm on MySpace.
I'm not a TikToker, so thenthat's a little bit of a I'm on
MySpace.
Speaker 3 (24:11):
That's a throwback.
Tom is my one friend.
I'm on Zynga, sorry.
Zynga is the real throwback.
Never even heard of that one.
Interesting because Actually, Imean no, I would do chat, tpt.
I mean I don't know, I guess itdepends what you want.
Speaker 2 (24:27):
If I want current information, it's just, it's an
interesting thing because youare still going to an
intermediary to analyze andprocess information and bring it
back to you.
Anyway, we went off on that onea little bit.
Any other thoughts on AI andrecruiting?
Speaker 3 (24:42):
Yeah, I think so.
No, you know, I think there is.
There's a lot of opportunitieswith it.
I think things to consider andthings to think about is how can
it easily integrate within yourworkflow, while there's a lot
of different technologies outthere, nobody wants to work in
20 different technologyplatforms.
So don't just buy the shinyobject and, with the capacity
(25:03):
that people have from it, figureout how you can better them in
their professional career andbring new skills into it.
Speaker 2 (25:11):
So I think it's a great way to wrap it.
Boom, boom.
Thank you, dina.
That's a wrap.
That's a wrap on AI for today.
We're definitely going to havea correction section next time,
because I'm going to avoid this.
Speaker 1 (25:22):
Okay, the job title is Revenue Operations Analyst.
Speaker 2 (25:26):
Oh, I should have remembered that.
Oh, revops Analyst.
Oh, I should have rememberedthat, oh, revops analyst.
See, I said I think it's adigital anyway.
Speaker 3 (25:31):
RevOps analyst.
Speaker 2 (25:32):
There we go, there we go.
Thank you, whitney.
We have no correction sectionfrom last time.
No, listen, we are nailing this.
I really hope we don't like ageout of correction section,
because I truly enjoy it.
Correction section.
Speaker 3 (25:48):
Just for fun, just for fun, just for fun.
For some reason I've takenTolkien at the camera going like
this lately.
Speaker 2 (25:55):
Why not?
You have a beautiful face.
Speaker 3 (25:56):
There we go.
Speaker 2 (25:58):
Whitney hot takes Hot topics.
Last time was hot, so we've gotsomething to live up to on this
one.
Speaker 1 (26:06):
This is actually a hot take from someone you may or
may not know.
Not on a personal level, if youmay or may not know.
Not on a personal level, if youdo let me know, uh, anyway, uh,
so this is from a comment thatNeil Druckmann made about AI.
Speaker 3 (26:27):
He is the creator of the last of us.
Speaker 1 (26:29):
Okay, good series.
So he said he voiced hissupport for AI, saying that you
know it's going to give them theability to do motion capture
right from home.
It reduces both costs andtechnical hurdles and opens the
door for them to take on moreadventurous projects and push
the boundaries of storytellingin games.
(26:50):
The problem is a lot of peopletook that as quote.
Oh then all you're saying is weneed less people to pay wages.
What's your take on it?
Speaker 3 (27:02):
Yeah, so maybe they need less people, which, if okay
, don't don't be mad at him.
He found he's using efficiencyto run his business better.
Speaker 1 (27:15):
Don't be mad, let me frame it a little better.
So what is, where's that fineline between reducing costs and
improving efficiency and keepingpeople on top of mind?
Speaker 3 (27:30):
Yeah, yeah, great question.
So I think this is reallysimilar to the conversation we
were having before, and it isthat, yes, ai may replace some
careers, but it may also giveother individuals the
opportunity to elevate the workthat they're doing.
So I don't know enough aboutgame making other than I game
(27:50):
making.
I played Hogwarts, legacy.
That's really kind of my gamingexperience.
But you know, to me this isagain the opportunity to how do
you get rid of the mundane andmaximize other people's skills.
Speaker 2 (28:01):
It's interesting because it made me think of and
I don't remember which movie itis was not qualified for the
Oscars, and this was back in theday because they used CGI.
Okay, and now all movies aremade with CGI.
We're going to have to look upthat, whitney, so we can put
that for next time and so thismay be something that becomes a
(28:26):
little bit of a non-issue.
Yeah, yeah, like.
So here's the other exampleI'll use is lucas films.
Okay, they have a fascinatingum, there's a fascinating uh
series I think it's on netflixof the entire history of the
special effects group that didall of the star wars stuff and
was critical in like cgidevelopment, like whatnot, and
(28:49):
through their evolution intocomputer graphics.
And now the way that they dolike the Mandalorian.
They don't even have sets.
They have these super high techlike TV screens that they can
project the background on.
So they don't even do setbuilding anymore for these.
That's why they're able toproduce these movie level like
(29:09):
experiences for tv series.
So if you think about that, allof these people who did all of
the puppetry, who did the clay,who just said they're no longer
being used, but there was anadaption of many people to say,
how do you take that knowledgeof the physical and bring it
into the digital space?
So bridging that gap.
(29:29):
So I think there is like askills transference.
But I also think that this issomething we've faced as a
society over and over again.
We don't have telephoneoperators anymore.
No one thinks about that.
You know, and so I do think it'sgoing to be a shakeup.
I think that we're going toneed to, as an education system,
think about what do skills looklike Like there?
(29:50):
I think that we're going toneed to, as an education system,
think about what do skills looklike Like there's kind of that
whole thing.
The other thing thank you forletting me run with my nerdy
side of the house.
I liked it Because the otherpiece is I referenced this
before, I think about the bookseries Dune.
Okay, new movie yes, great, butread the book, it's amazing.
Movie yes, great, but read thebook, it's amazing.
(30:12):
And the whole thing isessentially that they referenced
it in the past, that they thatlike technology.
They kind of like said screwyou technology, like we're
giving up on you.
So then they trained the humanmind to be able to process like
a computer.
So I sometimes I'm like are weheading on this path where
eventually we're going to get sodigitally driven that we're
going to say let's go back andlike be, use the human mind to
get us where we need to go?
(30:33):
It's not relevant.
I just had to bring it upbecause I love it.
Speaker 3 (30:36):
Listen, I'm, I'm, I'm for it.
Um, I actually just watchedDune one and two on the play and
now I'm starting the book nextweek, so good, there we go,
there you go.
Speaker 2 (30:44):
Okay, love it.
Speaker 3 (30:55):
Yeah, right in high school school.
Speaker 2 (30:56):
It's one I go back to all the time.
It's fabulous.
Um, I would totally put mybrain towards like a prototype,
um, you know, futuristic humancomputer power.
Yeah, we wouldn't, yeah like,so you have like super
processing, exactly, yeah,obviously.
Speaker 3 (31:01):
Random note, I do believe that telekinesis is a
possibility.
We just haven't figured it outyet.
Speaker 1 (31:05):
Dead serious so using ai to unlock the entire brain's
potential?
Speaker 2 (31:13):
maybe potentially uh-huh, uh-huh, well where I was
going.
Well, let's save that one, okay, because I I do believe that
there's more, that there's a lotwe don't understand.
I have never taken that to thetelekinesis side of the house,
but I'll follow you there.
I'll move this coffee mug assoon as we're off here, we can
do it.
Um, anything else on that, onai and jobs, and no, no, I will
(31:39):
say and I've said this beforeand I'm stealing this quote I
really need to find out who saidit originally or if it's just
one of those internet thingsthat pops around.
I want AI to do my laundry andmy chores, yeah, so I can spend
time making art.
Okay, I don't want AI to makeart.
Speaker 3 (31:58):
So I can spend time doing the- 100%.
Speaker 2 (32:02):
Yeah, so that is what I want.
Speaker 3 (32:04):
Yeah, I'm for it, cool yeah.
Speaker 2 (32:09):
Thanks, dina, don't meet again, hilary, I'll, I'm
for it, cool.
Yeah, thanks, dina, join meagain.
We'll see you next time.
Bye, bye.
Welcome to Real Talk on Talent, a human resources
podcast where we talk abouttalent acquisition, recruiting
and all things hiring.
Hey Dina, hi Hilary, welcomeback.
Thank you, I'm excited to behere today.
I'm always excited to be herewith you, I know.
Thank you, I'm excited to behere today.
I'm always excited to be herewith you.
Sometimes it takes me a minuteto get like my momentum, but I'm
(00:30):
always excited to sit down withyou.
Speaker 3 (00:31):
So I have my coffee right now.
So.
I'm hoping that can kickstartmy momentum.
Speaker 2 (00:35):
Also, I just realized that the human mug matches the
color of your dress by designNailed it.
Speaker 3 (00:40):
My coffee mug always matches what I'm wearing.
It's very on brand.
Speaker 2 (00:43):
Yeah Well, there we go.
As the marketing person here,I'm very proud of this.
Thank you, thank you you knowwe talked one time about getting
custom human scarves.
Speaker 3 (00:50):
Yes, we still need to make that.
Yeah, yeah, no, I would likethat, okay.
Speaker 2 (00:54):
Let's do it, I would like that.
Yeah, of course we're going tojump straight in to AI, ai,
because we keep referencing it.
Everybody's talking about it.
Literally as we were sittingdown, I got an alert from the
New York Times all about AI,like it's Killer robots.
(01:14):
Yes, yeah, can't get away fromit.
Yeah, not the robots that we'renot going to talk about.
Speaker 3 (01:19):
We're going to stay away from them.
We so we really can't, we'renot gonna talk about killer
robots?
Speaker 2 (01:23):
Okay, good, because this is the talent podcast Okay
Okay, good Helpful directionthere.
Speaker 3 (01:29):
Got it.
Okay, got it.
Speaker 2 (01:30):
So I would like for us to talk about AI, but
specifically thinking about howAI is being integrated into the
recruitment process, how you useit, and also thinking about
pros and cons and even just someinteresting elements that I'm
(01:53):
sure will come up as we talkabout AI and how leaders and
recruiters should can thinkabout it.
Maybe even candidates.
Oh yeah, Love it, Love it.
I do want to start this byadmitting that I have never used
chat GPT.
You love it, I do love it.
I feel like we're a goodrepresentation of the two sides
(02:13):
of.
Ai in the informal adoption.
Yes, for me.
I find so much pleasure in likecrafting words and like doing
analysis that I just haven'tever thought about where I would
want to integrate it into myday-to-day work life.
(02:34):
So let's start here.
You are a recruitmentoperations leader, you work in
sales, you lead people, youinterface with a lot of
different individuals.
How do you use ChatGPT, or Ishould say AI, ai.
Speaker 3 (02:50):
Yes, so you know what ?
That is actually something thatI want to say, I think, since
AI is relatively new and ChatGPTseems to be the product that
everybody knows, it is the thingthat brought AI to the masses
in a usable way.
One thing I often hear peoplesaying is well, how are you
going to use chat GPT inrecruitment?
So I want to be clear, likethat's not the right way to say
(03:10):
it, so, Hillary, don't say thatagain.
It's.
Speaker 2 (03:12):
AI.
You know what I am learningfrom you there we go.
Speaker 3 (03:17):
So, first of all, huge fan of AI.
For me, what I really like is,as I was explaining earlier,
sometimes my brain is like abowl of spaghetti and I don't
know where to start with it.
So for me, AI platforms such asChatGPT are a great place to
organize my thoughts, so I cantake a whole bunch of data, dump
(03:38):
it in there and it'll spit outsome high, you know.
Here are the highlights.
Kind of help you digest it andstart somewhere.
Exactly, exactly, but's a greatcall out, but from a
recruitment perspective, likethere are lots of different use
cases for it, I think where I'mstruggling right now to actually
see it applied is in a cohesivemanner within one platform.
Speaker 2 (03:59):
Yes, yes, and you kind of see this like race to AI
, where, as soon as it becameavailable to the mass market,
everybody started you know,snapchat's like we're going to
give you your AI best friend,and the job boards are putting
AI content, like recommendations, into their sourcing tools.
(04:20):
It is absolutely been this.
Here's this ability.
How can we commercialize it?
And I do think that, for on therecruiting side, there has been
a very tight focus on recruiterefficiency, which I think is
the number one place that AI isreally breaking into the
(04:41):
recruitment space, completelyagree.
Speaker 3 (04:42):
I think that's the best place for it to break in.
Speaker 2 (04:45):
Okay, tell me for you , because we actually talked
about efficiency last time, yeah, yeah, so, and we didn't even
touch on AI interestingly, wetried to save it for this topic.
We talked about AI.
So when you think about AI,there are a number of studies
that talk about pros and cons,how people play into it, all
that kind of stuff.
Give me your perspective on,very tactically, how you think
(05:09):
AI should and is most effectiveat the recruitment level.
Speaker 3 (05:13):
Yeah, so when I think of a recruiter, I want to think
of what is their highest andbest use of their time.
When you think of anybody intheir role, what is your highest
and best use?
As a recruiter, your highestand best use is not
administrative tasks, and thatis where I see AI helping out
quite a bit.
Speaker 2 (05:30):
Okay.
So when you say that, Iimmediately think of job
descriptions.
Speaker 3 (05:33):
Job descriptions, what else?
Yep?
So there is.
We actually demoed this ATS andI absolutely loved it, but for
some reason it's not going towork for our business needs.
But I'm going to tell you allthe bells and whistles that this
particular system had withoutsaying it.
So here's what I loved, and tome it outlined every opportunity
for recruiter efficiency.
(05:54):
So first, a recruiter needs tocreate a job built in AI to help
with that job description.
Okay, it does the candidatecommunication on the front end
to kind of screen out candidatesEmail text, chatbot, chatbot.
So chatbot and again these areoften very black and white
things that it is screeningcandidates out for so basic
(06:16):
qualification questions.
I don't want my AI makingdecisions, I want them following
kind of instructions that Igave it almost.
Speaker 2 (06:26):
So that's interesting , but that's not AI.
You're right, because ifthey're just following if-then
statements, then that's justnatural language processing or
automated processes.
But you do bring up a good pointwhere you said it does the
initial screening for black andwhite elements.
So, looking for certifications,If it were me I'd probably
stick to those types of veryformal.
(06:47):
There is no nuance to it.
You must have it to take thisrole.
But maybe you use AI to furtherdiscover skill abilities or
think about how you couldtranslate other experiences in.
So it's not kicking them out,but maybe it's helping like
digest that experience and bringit forward to the recruiter.
Speaker 3 (07:10):
Yeah, so I think that .
So just from a pureproductivity perspective,
there's a lot of time to besaved by recruiters If there is
some type of technology having aconversation with candidates
saying, hey, this job is 40hours a week, you have to work
weekends and compensation is $12an hour.
(07:32):
Are you interested in movingforward?
Speaker 2 (07:34):
But you don't need AI for that, you don't need AI for
that, full stop.
Speaker 3 (07:42):
Actually, though, here you're going to bring me up
, I'm going to, I'm going to.
I think I need another cup ofcoffee.
No, put it down.
Pre-podcast, okay.
So when we first heard about AIin recruitment world, I think
there were some technologiesthat came out and they said this
is AI recruitment technology,because it sounded nice, but it
was not actually, but it wasn'tactually.
(08:03):
Because it sounded nice but itwas not actually, but it wasn't
actually.
It is what I'm describing rightnow.
It is where you go in and youprogram answers and it will
screen candidates according toyour answers.
That is helpful in somesituations.
Again, those are high-volumetype jobs where we are screening
people on very black and whitethings.
Fine, but you were talkingabout recruiter efficiencies and
how AI ties into it.
(08:24):
Here we go.
So recruiter efficienciesscheduling candidates that helps
.
Let's look at candidateavailability.
Recruiter availability when Ireally started to get excited
about some of the efficiencieswere some technologies that we
demoed actually had recruitersdoing phone screens.
Ai was listening on their phonescreens.
As a result of thatconversation, it would write up
(08:46):
the candidate summary for you.
Here's everything we heardabout the candidate.
Speaker 2 (08:50):
It could go ahead and distill that information In an
ideal world, love it.
It sounds amazing and I'mtotally bought into that.
I completely agree Get rid ofall of the administrative tasks
so that a recruiter could spendtheir time building
relationships, sourcing for hardto fill candidates, et cetera.
We didn't even talk about AIsourcing that.
We.
Maybe we'll tap it, not if wehave time.
(09:12):
What two things.
There have been some studiesconcerns that AI.
Because AI is completelyfounded on, like, the
information being fed to itright and like, for example,
google has been serving up morelike AI solutions, like.
(09:33):
I think it's specifically tiedto Reddit is the example I'm
thinking of and this may be acorrection section if I'm
getting the specifics wrong butthe AI is serving up answers
from Reddit, but, as you canimagine, some of the answers
from Reddit that are being shownon Google are not great and, in
fact, some are just straight upbad.
So, yeah, so what happens if AIis not actually getting better?
(10:01):
And how do you have a recruiter?
Make sure that they're notover-relying on the information
being served back to it, becausewe know it's not perfect.
Yeah, so how do you?
Speaker 3 (10:10):
navigate that.
So first don't ever blindlytrust anything.
Life lessons from Dina DiMarco.
Speaker 1 (10:16):
Life lessons.
Speaker 3 (10:17):
Don't put blind trust in something, except for me,
obviously, okay, obviously, inthis particular scenario where
AI is writing the candidatesummary, really what it's doing
in that case is it's saving therecruiter, it's allowing the
recruiter to spend more timelistening to the candidate,
really paying attention, payingattention, truly understanding.
I like that, I like that.
(10:37):
So when you get that summary,the recruiter is not going to
just send that summary rightover to the manager.
It's going to make a couple oftweaks and it's going to say I'm
going to add this, I'm going totake that down, but that saves
the recruiter then from havingto go ahead and write their own
summary, upload it into the ATS,wordsmith it for the client,
all of those type of things.
That's a really good point.
Speaker 2 (10:57):
I didn't even think about it that way, because I did
see I'm not going to call outwho it was.
It was a staffing company thatwas talking about benefits of AI
and one of the things they saidis to serve up a resume and
your job description and ask AIto basically talk about
compatibility.
Okay, interesting, which is aninteresting angle, because you
may not consider how certainbackgrounds are tie in.
(11:19):
Yeah, but two things One, Ifeel like that's your job as a
recruiter.
Yes, I feel like a summarycould be interesting, but if
you're basically saying what'sthe compatibility on this?
Like it was like a beige flagfor me, not beige, what is it?
An orange flag for me?
Speaker 3 (11:35):
OK, the other you do tend to be a neutral person, so
I could see how a beige flagwould work for you, I think
beige flag is like there is nogood or bad?
Speaker 1 (11:42):
There we go.
Speaker 2 (11:45):
The other thing is what if a candidate has written
their resume based off your jobdescription using AI?
Okay, so they take your jobdescription, they throw it in a
chat GPT say, here's myexperience.
Now make it sound great.
Essentially, you have chat GPTapplying to a job or AI applying
to a job and AI analyzing theapplication, so you don't
(12:08):
actually have any humanintersection there at all, yeah,
yeah.
Speaker 3 (12:12):
So again, is that wrong though?
So it is wrong.
Okay, it is wrong.
And this is where people needto be involved in the hiring
process.
You know there is always goingto be this discerning element,
so, in that need to me needs tobe involved in the hiring
process.
You know there is always goingto be this discerning element,
so, and that need to me needs tobe a human element of who is
going to actually make thedecision whether or not somebody
moves forward.
I think my biggest concern witha lot of the AI platforms is is
(12:33):
what is the data set that theyare learning from and what are,
what are the biases that existin there?
And then you know, to the pointyou just made, how, right now,
there's such an emphasis onskills-based hiring, where we
are looking for people.
You know you don't have to havethe exact experience, but do
you have relevant and adjacentskills?
(12:55):
You know the idea of comparinga resume to a job description
really kind of undermines thatconcept.
Speaker 2 (13:00):
That's interesting and you know you said that.
The whole idea of skills basedhiring, I think one.
What that makes me think of iswe often talk about integrating
AI for efficacy, to be able tomake recruiters move more
quickly, you know, to see morecandidates shorten your time to
fill all that kind of stuff.
(13:21):
But I would argue that when youadd in AI, you actually need to
rethink your process in general.
It's not a one-to-one switch.
You're not just saying, hey,you're not scheduling candidates
, therefore you should have morecandidates on your calendar.
That might be a byproduct butsaying, because you are no
longer doing this, theexpectation is you're no longer
(13:44):
taking notes in your interviewwith the candidates, so your
default may be to be like, ohgreat, now it took me half as
long to get my summary, I'm justgoing to send it over.
But what's the new step in theprocess that you can add in?
To be a better recruiter, tohave better relationships, to
learn about skills-based likethat creativity.
(14:05):
But I think it's a leader's jobto set the expectation of if
we're investing in this tool sothat you no longer have to spend
time here.
It's not just so that you cansee more people.
Yeah, it's so that you can see,so you can learn more people,
that's not right.
Speaker 3 (14:21):
Well, you know what I mean.
Yeah, we don't only want toimpact the quantity of work that
we're doing, we want to impactthe quality of work that we're
doing as well.
Quantity will be a byproduct ofthat.
I agree Quantity is going to bea byproduct, but you nailed it
on the head with what you justsaid, because people's default
(14:47):
is going to be oh, I'm so muchmore productive now more
quantity.
How do you take the efficiencyand the time back that you've
gained to enhance your skillsand to become a better recruiter
in general?
How are you now, when you're onthat phone screen, asking
really probing questions towardsthe candidate?
How do you spend more timeunderstanding which skills truly
are transferable, doing backendresearch, whatever it is?
Speaker 2 (15:01):
I think that is something that when you read
about AI and recruiting, it's sovery tactically based.
But that idea of like I'm kindof stuck on the skills
transference or I'm eventhinking about like second
chance candidates.
Okay, Like people from eitherthat you may just say, oh, you
don't meet the qualifications,like whatever.
(15:22):
If we can use AI efficiently,it actually opens up the door
for us to better not just findand engage, but even potentially
coach and help and help thebusiness rethink.
Not just say, here's acandidate, how they're going to
fit in, or you have these skillsso you candidate can transfer
(15:45):
these skills into the role tobenefit us.
But you could even say thatit'll allow talent acquisition
to go back to the business andsay, look, there's an
opportunity here, whether it'swith someone who's a second
chance, or if we start thistraining program, we can help
them into this.
Like it could really help thebusiness do better by the
(16:05):
candidates that come in, notjust better screen out
candidates that don't fit.
Speaker 3 (16:10):
Yeah, yeah, there's.
There are a lot of doors thatit opens for you, and that's
what I think we're using itright.
If you use it right, I thinkthat's what we're just beginning
to open up is like okay, yes,we know AI is going to make you
more efficient.
There are lots of tactical ways, but as that door begins to
open wider, what are you doingwith that?
Yeah, you know, and to me,that's the exciting part.
Speaker 2 (16:31):
Do you know I, as a marketer, I've struggled with
job descriptions for a long timeEspecially.
You know they have to soundprofessional, you have to hit
all the important stuff You'replaying into.
You know the algorithms of thejob boards and their rules of
posting you kind of like.
Honestly, job descriptions havekind of been a struggle where
I'm like they're just not thatfun to write.
(16:53):
So what I would love to seetalk about the fun, creative
things we can do I want to see ajob description written in
limerick Okay Fullick, okay Fullstop Okay.
Speaker 1 (17:05):
Chat GPT could do that for you.
Speaker 2 (17:06):
That's what I'm saying that's what I'm saying.
So instead of just being like,oh yeah, yeah At Human, we're a
great place to work, Do you havethese seven skills?
Three of them are preferable.
You could start on Tuesday.
Speaker 3 (17:22):
Like instead like Tuesday.
Instead, use ChatGPT to turn itinto a limerick, Spice it up
and let's see.
Yes, so here we go there.
Once was a company in Nantucket, or whatever.
I am totally down to beta testthis.
Let's do it.
We'll go rogue, we'll post thejob on our own.
Not rogue, not rogue, not rogue.
We never go rogue.
We don't go rogue Ever.
No, nobody has approved thispodcast, but actually I actually
love that idea.
(17:42):
You know what I mean.
Speaker 2 (17:43):
Like have fun.
Think about the candidate isone.
What do they actually need toknow?
And I do agree, like I'm a bigbeliever in like to the point.
This is the role, like here'swhat you'd be doing, here's what
you need to know, here's whatwould be kind of helpful if you
knew.
But I'm also thinking aboutthat slog of going through,
especially right now, is likewe're shifting more to an
(18:04):
employer market.
I've seen more and more peopleon LinkedIn who are like I'm
looking for work I've applied toa bunch of jobs.
How nice would it be if you seethe same marketing specialist
job description 17 times andthen all of a sudden you get one
that's written in rhyme?
Speaker 3 (18:21):
Yeah, well, I think they're.
You know what?
We are totally going off therails here, but I'm into it.
Speaker 2 (18:26):
We're not, though, because we're talking about the
impact of AI.
Speaker 3 (18:28):
AI.
There we go, Okay.
So I do think it's a uniqueopportunity for companies to
tell a little bit more aboutthemselves in a more authentic
way.
Speaker 2 (18:37):
What do you think about AI in like an analysis
stand?
No, not analysis.
What I mean is like screening,so like you have your database
and you have AI layered on andthey're kind of analyzing all of
the candidates in there tosource up potentially qualified
individuals.
What do you think about AIsourcing?
Speaker 3 (19:00):
So you know, initially I'm all for it,
because here's what I'll tellyou I do feel like there's an
opportunity, there arecandidates within your database
that are good, and it's agoldmine, and databases are
often untouched.
What I worry about and what Ithink about is, like there was
that Workday lawsuit whereWorkday's AI you know they were
(19:23):
being sued because they weresaying the bias in the system.
So what I don't know enough ofis how is it serving up these
candidates and what is helpingit to make that decision?
What's its learning process?
Speaker 2 (19:36):
And I guess that is true for AI in general.
So what's the responsibility ofthe human?
Yeah, and is that sorry answer?
And then I've got somethingthat popped in my head yeah.
Speaker 3 (19:48):
So I think for me personally, until I can become
comfortable with the AI platformand understanding how it's
learning, what's its data set,what are the biases?
Where I want to use AI is noton decision making, but I want
to use it more on so you wouldnot use it for sourcing.
I'm not saying I wouldn't useit for sourcing, but I'd be
(20:12):
foolish not to use it forsourcing.
I mean, listen, if everybody'sadopting AI which they are you
will get left behind if you donot adopt it.
I am just recognizing thatthere is potential risk out
there with it.
Speaker 2 (20:25):
Yeah, I have seen more and more companies starting
kind of like companies havesecurity policies, having
specific statements aroundexpectations for AI use, so kind
of like there are expectedbehaviors of how you show up on
social media, of how you useyour work computer, that kind of
thing.
They're starting to have moreformal company positions on how
(20:46):
AI should be used and can beused in regards to work.
Speaker 3 (20:50):
Yeah, yeah.
So I'll tell you one kind ofinteresting use case here.
So my recruiters are oftenrequired to recruit for a
variety of job functions,sometimes which we've stopped
doing this because we found itdidn't work they were being
asked to recruit for a jobfunction that they have never
recruited for before and what Ifound they were doing was they
(21:11):
were going to chat GPT and theywere saying what are a list of
questions I can ask the hiringmanager to understand this
position and a list of questionsto ask the candidates?
It is, but not if you don'tactually take the time to
understand the position itself.
Sometimes it can be a shortcutto a detriment.
Speaker 2 (21:31):
Yeah, and if they serve up like incorrect
information or in a way that, ifyou said it, it's like a
trigger, you don't actually knowwhat you're talking about.
Exactly yeah, and so I do thinkthat's part of the risk as well
with AI, but I do think to yourpoint, like knowing where to
start to go in and say, hey,here's this new position.
Like Whitney, who did we justhire on?
The marketing team?
(21:51):
Emery, no.
The DevOps no.
Speaker 1 (21:57):
Oh, that's still in the works.
Speaker 2 (21:59):
No, but what's the role?
Oh See, it's a very specific.
You ladies need a cup of coffee, but so this is the exact See
the fact that we can't rememberthe exact title we just hired a
very or we just we have an openposition for a very specific
(22:19):
digital data analytics,specifically as it ties into the
revenue cycle and CRMmanagement, reporting, that kind
of thing.
So if you are a recruiter whohas no marketing experience, no
data analytics experience, andyou sit down to say, okay, I
have to go find someone, chadGBT could be like, okay, great,
(22:43):
let's give a little bit ofcontext about CRMs and like how
you look at revenue cycles andmaybe go look into this, and so
it could open up a door to startsaying here are the things that
are going to tie into this.
Speaker 3 (22:53):
Yeah, I think the important part is it's fine to
ask chat, gpt, what are goodscreening questions, but make
sure that the fundamentallearning is there too.
So, again, it's not justrelying on AI.
Speaker 2 (23:06):
What are you screening for, not what
questions are you asking?
Speaker 3 (23:09):
in the screening process and it's really making
sure that you're partnering AIwith the additional learnings
the foundational learnings of it, so it can accelerate people's
learning process.
It can make you come up tospeed on something much more
quickly, but it is importantthat you actually take the time
to absorb the information aswell.
I completely agree, okay.
Speaker 2 (23:29):
So reference back to our generational podcast Okay,
gen Zers are not going to Googleto find answers, they're going
to TikTok.
They're using TikTok as, like,the number one, like search
engine, okay, which we didn'ttouch on this, and I have a lot
of opinions about TikTok or chatGPT.
Speaker 3 (23:54):
So, if I am correct, chat GPT's data is a couple of
years old, like they're notgetting the most recent stuff,
so I would actually pick TikTok,you would.
Speaker 2 (23:59):
Over chat GPT.
Speaker 3 (23:59):
Interesting.
That being said, I have neverbeen on TikTok before, so you
haven't.
No, oh no, I'm not a TikToker.
Speaker 2 (24:06):
So then that's a little bit of a I'm on MySpace.
I'm not a TikToker, so thenthat's a little bit of a I'm on
MySpace.
Speaker 3 (24:11):
That's a throwback.
Tom is my one friend.
I'm on Zynga, sorry.
Zynga is the real throwback.
Never even heard of that one.
Interesting because Actually, Imean no, I would do chat, tpt.
I mean I don't know, I guess itdepends what you want.
Speaker 2 (24:27):
If I want current information, it's just, it's an
interesting thing because youare still going to an
intermediary to analyze andprocess information and bring it
back to you.
Anyway, we went off on that onea little bit.
Any other thoughts on AI andrecruiting?
Speaker 3 (24:42):
Yeah, I think so.
No, you know, I think there is.
There's a lot of opportunitieswith it.
I think things to consider andthings to think about is how can
it easily integrate within yourworkflow, while there's a lot
of different technologies outthere, nobody wants to work in
20 different technologyplatforms.
So don't just buy the shinyobject and, with the capacity
(25:03):
that people have from it, figureout how you can better them in
their professional career andbring new skills into it.
Speaker 2 (25:11):
So I think it's a great way to wrap it.
Boom, boom.
Thank you, dina.
That's a wrap.
That's a wrap on AI for today.
We're definitely going to havea correction section next time,
because I'm going to avoid this.
Speaker 1 (25:22):
Okay, the job title is Revenue Operations Analyst.
Speaker 2 (25:26):
Oh, I should have remembered that.
Oh, revops Analyst.
Oh, I should have rememberedthat, oh, revops analyst.
See, I said I think it's adigital anyway.
Speaker 3 (25:31):
RevOps analyst.
Speaker 2 (25:32):
There we go, there we go.
Thank you, whitney.
We have no correction sectionfrom last time.
No, listen, we are nailing this.
I really hope we don't like ageout of correction section,
because I truly enjoy it.
Correction section.
Speaker 3 (25:48):
Just for fun, just for fun, just for fun.
For some reason I've takenTolkien at the camera going like
this lately.
Speaker 2 (25:55):
Why not?
You have a beautiful face.
Speaker 3 (25:56):
There we go.
Speaker 2 (25:58):
Whitney hot takes Hot topics.
Last time was hot, so we've gotsomething to live up to on this
one.
Speaker 1 (26:06):
This is actually a hot take from someone you may or
may not know.
Not on a personal level, if youmay or may not know.
Not on a personal level, if youdo let me know, uh, anyway, uh,
so this is from a comment thatNeil Druckmann made about AI.
Speaker 3 (26:27):
He is the creator of the last of us.
Speaker 1 (26:29):
Okay, good series.
So he said he voiced hissupport for AI, saying that you
know it's going to give them theability to do motion capture
right from home.
It reduces both costs andtechnical hurdles and opens the
door for them to take on moreadventurous projects and push
the boundaries of storytellingin games.
(26:50):
The problem is a lot of peopletook that as quote.
Oh then all you're saying is weneed less people to pay wages.
What's your take on it?
Speaker 3 (27:02):
Yeah, so maybe they need less people, which, if okay
, don't don't be mad at him.
He found he's using efficiencyto run his business better.
Speaker 1 (27:15):
Don't be mad, let me frame it a little better.
So what is, where's that fineline between reducing costs and
improving efficiency and keepingpeople on top of mind?
Speaker 3 (27:30):
Yeah, yeah, great question.
So I think this is reallysimilar to the conversation we
were having before, and it isthat, yes, ai may replace some
careers, but it may also giveother individuals the
opportunity to elevate the workthat they're doing.
So I don't know enough aboutgame making other than I game
(27:50):
making.
I played Hogwarts, legacy.
That's really kind of my gamingexperience.
But you know, to me this isagain the opportunity to how do
you get rid of the mundane andmaximize other people's skills.
Speaker 2 (28:01):
It's interesting because it made me think of and
I don't remember which movie itis was not qualified for the
Oscars, and this was back in theday because they used CGI.
Okay, and now all movies aremade with CGI.
We're going to have to look upthat, whitney, so we can put
that for next time and so thismay be something that becomes a
(28:26):
little bit of a non-issue.
Yeah, yeah, like.
So here's the other exampleI'll use is lucas films.
Okay, they have a fascinatingum, there's a fascinating uh
series I think it's on netflixof the entire history of the
special effects group that didall of the star wars stuff and
was critical in like cgidevelopment, like whatnot, and
(28:49):
through their evolution intocomputer graphics.
And now the way that they dolike the Mandalorian.
They don't even have sets.
They have these super high techlike TV screens that they can
project the background on.
So they don't even do setbuilding anymore for these.
That's why they're able toproduce these movie level like
(29:09):
experiences for tv series.
So if you think about that, allof these people who did all of
the puppetry, who did the clay,who just said they're no longer
being used, but there was anadaption of many people to say,
how do you take that knowledgeof the physical and bring it
into the digital space?
So bridging that gap.
(29:29):
So I think there is like askills transference.
But I also think that this issomething we've faced as a
society over and over again.
We don't have telephoneoperators anymore.
No one thinks about that.
You know, and so I do think it'sgoing to be a shakeup.
I think that we're going toneed to, as an education system,
think about what do skills looklike Like there?
(29:50):
I think that we're going toneed to, as an education system,
think about what do skills looklike Like there's kind of that
whole thing.
The other thing thank you forletting me run with my nerdy
side of the house.
I liked it Because the otherpiece is I referenced this
before, I think about the bookseries Dune.
Okay, new movie yes, great, butread the book, it's amazing.
Movie yes, great, but read thebook, it's amazing.
(30:12):
And the whole thing isessentially that they referenced
it in the past, that they thatlike technology.
They kind of like said screwyou technology, like we're
giving up on you.
So then they trained the humanmind to be able to process like
a computer.
So I sometimes I'm like are weheading on this path where
eventually we're going to get sodigitally driven that we're
going to say let's go back andlike be, use the human mind to
get us where we need to go?
(30:33):
It's not relevant.
I just had to bring it upbecause I love it.
Speaker 3 (30:36):
Listen, I'm, I'm, I'm for it.
Um, I actually just watchedDune one and two on the play and
now I'm starting the book nextweek, so good, there we go,
there you go.
Speaker 2 (30:44):
Okay, love it.
Speaker 3 (30:55):
Yeah, right in high school school.
Speaker 2 (30:56):
It's one I go back to all the time.
It's fabulous.
Um, I would totally put mybrain towards like a prototype,
um, you know, futuristic humancomputer power.
Yeah, we wouldn't, yeah like,so you have like super
processing, exactly, yeah,obviously.
Speaker 3 (31:01):
Random note, I do believe that telekinesis is a
possibility.
We just haven't figured it outyet.
Speaker 1 (31:05):
Dead serious so using ai to unlock the entire brain's
potential?
Speaker 2 (31:13):
maybe potentially uh-huh, uh-huh, well where I was
going.
Well, let's save that one, okay, because I I do believe that
there's more, that there's a lotwe don't understand.
I have never taken that to thetelekinesis side of the house,
but I'll follow you there.
I'll move this coffee mug assoon as we're off here, we can
do it.
Um, anything else on that, onai and jobs, and no, no, I will
(31:39):
say and I've said this beforeand I'm stealing this quote I
really need to find out who saidit originally or if it's just
one of those internet thingsthat pops around.
I want AI to do my laundry andmy chores, yeah, so I can spend
time making art.
Okay, I don't want AI to makeart.
Speaker 3 (31:58):
So I can spend time doing the- 100%.
Speaker 2 (32:02):
Yeah, so that is what I want.
Speaker 3 (32:04):
Yeah, I'm for it, cool yeah.
Speaker 2 (32:09):
Thanks, dina, don't meet again, hilary, I'll, I'm
for it, cool.
Yeah, thanks, dina, join meagain.
We'll see you next time.
Bye, bye.
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