Tim Sackett – HR Tech 2024 – How AI Eliminates Bias in Recruitment

Connect with Tim:

• 

Connect with David:

• • 

• david.turetsky@salary.com

Connect with Dwight:

• • 

• dwight.brown@salary.com

Podcast Manager, Karissa Harris:

• HRDataLabs@salary.com

 

Production by Affogato Media

Resources:

• Tim’s website
• Salary.com Consulting practice
• HR Data Labs Season 8 Episode 13
• HR Data Labs Season 8 Episode 11

• “We had this concept a year ago—maybe two years ago—where [we thought] ‘the technology is more biased than humans,’ and it was wrong . . . I truly believe the closest we’ll come to bias-free hiring is the use of AI in sourcing and screening.”

Announcer: 0:01

The world of business is more complex than ever. The world of human resources and compensation is also getting more complex. Welcome to the HR Data Labs podcast, your direct source for the latest trends from experts inside and outside the world of human resources. Listen as we explore the impact that compensation strategy, data and people analytics can have on your organization. This podcast is sponsored by Salary.com, your source for data technology and consulting for compensation and beyond. Now here are your hosts, David Turetsky and Dwight Brown,

 

David Turetsky: 0:38

Hello and welcome to the HR Data Labs podcast. I am your host, David Turetsky, we're recording live from the 2024 HR Technology Conference in beautiful Mandalay Bay, exposition center in Las Vegas, Nevada. And I'm here with my friend Tim Sackett. Tim, how are you?

 

Tim Sackett: 0:55

I'm great, David. How are you?

 

David Turetsky: 0:56

I'm tired.

 

Tim Sackett: 0:58

We've both got, like, the raspy voice going from two days of non stop conversations.

 

David Turetsky: 1:02

Oh my god, I can't shut the hell up. Eventually I will, especially when I'm getting food later!

 

Tim Sackett: 1:08

Yeah.

 

David Turetsky: 1:09

But we have the pleasure of talking to you, and there's so much really cool stuff that's happening all around us in the world of recruiting and applicant tracking systems, and there's a lot of buzz.

 

Tim Sackett: 1:20

Yeah.

 

David Turetsky: 1:21

You've heard the buzz.

 

Tim Sackett: 1:22

I've heard the buzz. AI.

 

David Turetsky: 1:25

Before we get the world of AI. What's one fun thing that's happened to my friend Tim in the last year?

 

Tim Sackett: 1:32

Oh, wow. I actually so we were before we got on air, I talked about I golf a lot. I had my first hole in one.

 

David Turetsky: 1:38

Dude no way! That's awesome!

 

Tim Sackett: 1:41

That was exciting. I actually had a good friend of mine and my one of my cousins golfing with me. So I had, like, a big crowd of people that saw it, like, we got to watch. It was a good shot, too. It wasn't one of those, like, off of tree bounces out onto the green.

 

David Turetsky: 1:56

It was a squirrel.

 

Tim Sackett: 1:57

It was like, yeah. It was like, I hit this perfect shot. And I'm like, I thought it was gonna be a little short. It bounced right in front of the hole, about six feet, and rolled in. And we watched the whole thing. It was pretty cool.

 

David Turetsky: 2:06

What was the yardage on that?

 

Tim Sackett: 2:08

140 yards into the wind with an eight iron.

 

David Turetsky: 2:11

Wow! Oh, my God, no way!

 

Tim Sackett: 2:13

Yeah.

 

David Turetsky: 2:14

That seems perfect.

 

Tim Sackett: 2:15

You know, yeah, like, at least. I mean,

 

David Turetsky: 2:17

I mean, you can't get better than a hole in one!

 

Tim Sackett: 2:19

I think that group in this I've actually, like. So my son has two holes in one. I actually was golfing with him in his first and like that time I was more excited than he was in my playing group was more excited than I was. Like, it's just a weird thing. Like, you're just like, Okay. Like, I just, you know, what do you do? Like, yeah,

 

David Turetsky: 2:38

Right, yeah. You just pick up the ball from the hole when everybody else is done!

 

Tim Sackett: 2:42

I know they're all excited, because I think you're like, you know, tradition is you go buy, you have to pay drinks in the clubhouse afterwards. So they're like, yes, free drinks!

 

David Turetsky: 2:50

Well, I mean, but you, this is a badge of honor for you for a while now. I mean, get to say I hit a real hole in one.

 

Tim Sackett: 2:57

Yeah.

 

David Turetsky: 2:57

It's not a mini golf hole! So is it because you've been playing so much that

 

Tim Sackett: 2:58

Six days later, I hit one within 12 inches. And, like, same thing, I was with one of the guys was with me again. He's like, I can't believe you just did it again. And we had four guys were standing on the like, waved us up on the green, and they were all cheering. They thought it was gonna go in and just stop short. this is getting to be where you're getting so good, or is it just luck? I don't think so. Like, you see, like, Tiger Woods, or somebody has, like, 18 or whatever, that dude has played millions of holes. Sometimes it's just like the amount, right, of golf. I still think there's also professional PGA golfers have never had one. Like, it's such a lucky thing, right? Like, you look at the stats of a hole in one and it really is, like, like a bolt of lightning kind of striking, right?

 

David Turetsky: 3:39

Well, everything has to be perfect. Like, you had to have the right stroke. You had to have the right club, yeah. The wind conditions had to be perfect. The grass on the green needs to be perfect every

 

Tim Sackett: 3:49

Yeah. So it is weird because, like, you like, I would rather shoot a 79 like, shoot under 80 then have a hole in one and shoot 89

 

David Turetsky: 3:59

Yeah, yeah. Well, wait, but it's nobody cares about your round. They care about that story.

 

Tim Sackett: 4:07

They do, yeah.

 

David Turetsky: 4:08

And that's why I say it's a badge of honor, because you're gonna be able to carry that with you forever.

 

Tim Sackett: 4:11

Yeah.

 

David Turetsky: 4:12

Well, congratulations.

 

Tim Sackett: 4:14

Yeah, thank you.

 

David Turetsky: 4:14

In the hockey world, you know, especially for a goaltender, we kind of think of, you know, what's the big deal? Like, maybe a shutout or something, but, but that's not just you. That's the entire team. Yeah, and I play, because I play hockey on Monday nights, really late, with a bunch of guys that I know really my badge of honor is, you know, they scored less than 10 goals on me. Yes, thank you for that cheer. That was a cheer from the crowd, but, but that's really great. So Tim, let's now get to the topic at hand. So let's talk about recruiting, and let's talk about recruiting technology. There's been a lot of evolution that's happened. And really, evolution has been happening for quite some time!

 

Tim Sackett: 5:05

Yeah.

 

David Turetsky: 5:06

But to you, what have you seen lately? What is like, really remarkable to you about the evolution of recruiting technology?

 

Tim Sackett: 5:12

You know, it's an interesting thing, because you see it here. I mean, you see it like a lot of the trend stuff, like you're here. When we were here last year at the pitch fest, which is a startup competition, right? We were because, like, that point, like, hiring maybe started to maybe slow down a little bit. You didn't really hear, it's still, like, hot as can be, right, right? And there was no recruiting tech and startup really, like, this is, like, it was odd. Like, you just, I mean, there was just none, really. And we just had gotten, like, you know, big chat, GPT stuff. And so we thought, okay, yeah, it's gonna happen. But, like, it just wasn't there in the startup world. And then this year we come and, like, every other one is a tech one. So yeah, there's this trailing thing where you go, great, you built it. But now, like, the market's changed again!

 

David Turetsky: 5:57

Yeah.

 

Tim Sackett: 5:57

So then next year we'll see, like, okay, what are people like wishing they had this year. That's not there. The other thing I've seen is because of, like, the generative AI stuff, everybody came out with, I could literally, like, it's like, the five same features, right? I can help you write a better job description. I can help you do better communication to, you know, like, personalized blah, blah, blah. And it didn't matter if you were a CRM, an ATS, a sourcing tech, or whatever, interview tech, they all have the same features, and then the buyer goes, so you guys all are the same, right? Like, well, no, but the marketing is so, so much so that it feels like everybody's turned into the same thing when they're really different, but they're all marketing the same features, right? Even though that's only like a tiny part of their feature set they want, everyone wants to get the new AI stuff out there.

 

David Turetsky: 6:44

So are they all competing against each other, or are they all cooperating?

 

Tim Sackett: 6:47

Well, that's the crazy thing, they're not really they, I mean, they shouldn't be competing against each other, but I think the buyer actually believes they're doing the same thing. So now the buyer may be putting them in a same bucket where they're actually in different verticals. So there's, I mean, again, it's we have this issue. It just becomes more confusing.

 

David Turetsky: 7:03

Right.

 

Tim Sackett: 7:03

And I think I don't know if this is really the technology that's confusing. It's more of the marking of the technology. It becomes very confusing, you know? I always like, especially like, we get this on the pitch fest, where someone comes in, they have three minutes tell you what they do. And after three minutes, my first question is, so what do you do? Like, you you have 11 words to tell me what you do. Can you just tell me what you do?

 

David Turetsky: 7:24

Right!

 

Tim Sackett: 7:25

And like, Oh my God. Like, if you can't just, like, put that in one sentence, there's a problem, right? You know?

 

David Turetsky: 7:30

Well, that should be what the pitch fest is about, right?

 

Tim Sackett: 7:34

We actually, we actually, because, you know, George LaRocque, friend of mine, that is the MC there, and does like stuff with here in the Investor Summit, right? We, we actually changed the rubric and actually asked them. We gave them two sentences. I actually only wanted to give them 11 words. George like was nicer, and he said, like, give us two sentences of what you do. And again, it's two sentences of marketing speak to make them sound super sexy. And I want to go, Okay, I still don't know what you do.

 

David Turetsky: 7:58

Well, shouldn't that qualify them right away? I mean, I'm not trying to be offensive to people, but, like, if you can't be just freaking honest and just yeah, you can have some marketing words in there. Just stop the BS and get Isn't that like a say it, don't say it, prove right to the point!

 

Tim Sackett: 8:10

It does make you question if they are after real tech or is it vapor. You know, is it really a service, not a technology? It hurts them. I think the people that come and say here, this is exactly what we do, and they show it, and they talk about the real life HR use case for it, right, right? And they can give multiple examples of that, like, immediately they're going to be raised up higher, they're going it, kind of thing? Yeah, because, I mean, I'm in sales to get higher scores, right? and, you know, I get that all the time. Listen, I heard what you have to say. Show me the use cases. Show me the client stories. Show me the references that have done what you say. Yeah. And as a judge, you try to help them! Like I try to ask the question that says, look, look, I know what you do, because I'm in this space, and I look at a million things, and I like, but like, you have all these other people in the audience that are voting for you that they I can tell you right now, they have no idea what you do. I could go around with a mic and they'd be like, I don't know, right?

 

David Turetsky: 9:07

But it's a person who has the best presentation or the best style or the best gimmicky BS.

 

Tim Sackett: 9:12

And the marketing is way better on these startups, like they're spending money. I mean, the product looks really good. Yeah, it looks like professional product, right? So then you get, so sometimes you get like, you're like, oh gosh, it looks like, like a really good piece of stuff I want to use. But just because it looks great doesn't mean it necessarily does what it should be doing, but,

 

David Turetsky: 9:28

But is that market texture, or is that real product at that point?

 

Tim Sackett: 9:32

It could be both. Some have real products. Some are still, like, in the idea design phase, like, this is what it's going to look like, but that, but they can't show me a real product. Like,

 

David Turetsky: 9:40

Oh, so when they're in pitch fest, it's not a real product, yet.

 

Tim Sackett: 9:43

Could be! Some are pre revenue, some are post revenue. Some have already raised 3 million. Like, there's, there's some rules, but the rules are kind of, it allows for a big range to come in. So you do have people coming in going, like,

 

David Turetsky: 9:52

Okay. look, I'm looking for, you know,$500,000 to actually build out an MVP. And then you have some going. And we're already doing a million in ARR, right,you know? Yeah, well, yeah. I mean, pre revenue people, to me, that's brilliant, but I mean, if it were me, I'd wait until I actually had the money.

 

Tim Sackett: 10:12

That's where I'm like, yeah, if you can't, you know, kind of bootstrap together, an MVP, like, why even? Why are you coming? You know?

 

David Turetsky: 10:18

Right? Because you're competing against people who've already solved that problem. You probably already have clients and whatnot. Who are telling clients stories!

 

Tim Sackett: 10:26

yeah.

 

David Turetsky: 10:26

So that's just so hard.

 

Tim Sackett: 10:28

The other great thing about that, though, David, is, like, you when you see these entrepreneurs coming and building product, like, it's, there's a little bit of like, you have to disassociate yourself from reality a little bit to be an entrepreneur and think you're gonna do like, you know, because, again, it's the 99% of these things are gonna fail, right? But when you, like, listen to every single one of them, they all believe they're the one that's gonna make it. There's something really motivating and inspiring about

 

David Turetsky: 10:50

Right, right, right, but, but then again, that, right? That's the core of, like, what you do and come here, because you don't know. At some point, all these giant booths that are here were that glimmer of someone's eye that think I have an idea, right? And they, you know, so you can't say that it doesn't work, you know, right? there might be people on the floor that are actually solving the same problem. They just not as good of marketers, or they're not as good as pitch people, yeah, as those people?

 

Tim Sackett: 11:15

Oh, for sure, yeah. There was a Japanese company that came in and, like, you could tell, I mean, obviously the founder, like CEO, first language, Japanese, second language, English. He actually brought, you know, one of his employees that was a native English speaker, and she led most of it. He, like she and then she would, you know, would help with some of the questioning. I think that's smart, because I've had other people that haven't, yeah, and again, there's no offense. Like, I mean, that's great that you come, that you're not, but it's hard in three minutes, right? If you're if you're struggling with English, to get that pitch across.

 

David Turetsky: 11:45

Absolutely, absolutely

 

Announcer: 11:49

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David Turetsky: 11:59

So the evolution of recruiting technology, it's ongoing. It's going to continue. What's the biggest thing you saw here that kind of wowed you?

 

Tim Sackett: 12:12

I think if we go back last year and take a look at I think everyone felt like got to be careful with AI, that technology can be biased, in the bias, you know, and it can, it can learn to do bad things, blah, blah, blah, I think we're starting to see the tipping point where people are going, Oh, wait, actually, a technology can't be biased. It could be learned biased, right? I can also control for that.

 

David Turetsky: 12:36

Right.

 

Tim Sackett: 12:36

Unlike a human right! And so we had this concept maybe a year ago, two years ago, where it was, like, the technology's more biased and humans and it was wrong, but, like, but if you went to a crowd of 100 HR leaders, they would all believe that, oh yeah, yeah, definitely right, because the media portrayed it as, like, the evil, like, technology, right? And I kept saying, like, no, like, I'm in a minority, but I truly believe the closest will come to bias free hiring is the use of AI in sourcing and screening. And so, you know, I, you know, now, like, I think the coolest thing is, is, like, Let's go traditional. And by the way, this is still most hiring. Recruiter puts out a job. They get 100 people apply. Recruiter goes in, they take a look at 20 25, they reach out to 10 or 15, three or four, call them back, they screen, they send those on to the hiring manager. Hey, here's the best of the who applied, right? 75 people didn't even get in the didn't even get a sniff. They didn't get part of the process, right? And you turn AI into that, and the AI starts to screen, or AI at least, starts to like show you who the best are. You for the first time in history, 100% of the people can be a part of the process, right? Which is going to make us more diverse, more inclusive, better talent, higher quality, all of that stuff is because of AI, because the humans just didn't have the capacity. Again, we could have had the capacity to do it, but we couldn't put that much resources to it. And like in the company, we lose, like, we lose money!

 

David Turetsky: 13:54

Yeah, at scale, it doesn't make any sense. Yeah. The thing that bothers me, and I think we've talked about this in the past about that process, though, is when they get rejected eight seconds after.

 

Tim Sackett: 14:05

Yeah, yes, yeah. Again. I still think like, again I can, you know, I've seen four, five different live voice screening AIs, and it's amazing. It's literally, like, if you think about who's the best recruiter I ever talk with the energy, the voice, the they were interested in me and they were they loved their company.

 

David Turetsky: 14:26

Passion, yeah.

 

Tim Sackett: 14:27

That's those AI screeners now, like it doesn't sound like some computer voice, this sounds like a real person. There's a little latency, right? But so I have a feeling that we can actually deliver really good feedback at scale with AI that actually is real feedback. And having that person even get that call is exciting, when, if you just turn them, if you just turn them over to the disposition pile, they're going to be pissed, and they're never going to come back to you again. They may be best, the best for the next job that comes available, but now you've destroyed your pipeline.

 

Tim Sackett: 15:02

Here's like, when we talk about and, like, I know Bersin did this in his keynote this morning, talking about the agent stuff, right? The AI agents, like, there's, there is a real use case here where you start to take all the data that somebody did, like, through, like, hey, we go and do this assessment. We go into this interview. And AI is going to be able to go and take a look at all of that and say, Hey, you didn't get chosen, but we appreciate everything you did. And here's like, where we saw your strengths, and here's what we like. We'd love to see you do like, because

 

David Turetsky: 15:28

That's a value add!

 

Tim Sackett: 15:29

It's a value add and like, it's going to be able to do it with the with all the bumpers in place to make sure they never say anything that's going to get you legally in trouble.

 

David Turetsky: 15:37

Wouldn't it be really cool to that point, if it would say, back, listen, you applied for this job, but here's a better job for you. And by the way, we put you in for that role because your resume was really strong in these areas, and we think you'd be a better fit there. Yeah, you're gonna get a call.

 

Tim Sackett: 15:54

You know, the one, one of the companies that you know had me do it. They, they said, Hey, go ahead and tell them. Tell us whatever job you want. We don't care. Just give us any job. Be as crazy as you want. And I said, I want to be the head coach of the Los Angeles Lakers. So the AI agent called me right and immediately started digging into my coaching experience, my career. What I do in these situations? Of course, I'm not a I'm not a pro basketball coach. I never played pro basketball. It got rid of me so fast, in the nicest way. And they in the technology called back, and they go on a scale, like they have a scale of, like, one to five, one being the worst, five being the best, in terms of, like, you're rating for a candidate. They go all of the testing we've done, the worst we've ever gotten anybody was a two. You got a one. It knew right away.

 

David Turetsky: 16:34

Wow.

 

Tim Sackett: 16:34

And by the way, it got rid of me very quickly. I'm like that to me, that's actually a great recruiting! To know that. Hey, we have somebody here that's

 

David Turetsky: 16:38

Sure. just, I mean, come on, like, this is a joke, right? There's no they didn't treat me that way, right? It treated me well, but immediately, after like, three or four questions knew. It was really gracious, you know, asked me if I had anything, we'll be in touch. Blah, blah, blah, you know. And now they treated you like a freaking human. It was a bot that treated you like that!

 

Tim Sackett: 16:58

yes, yes.

 

David Turetsky: 17:01

But that to me, that's next generation stuff. It's next generation thinking, because now I feel appreciated.

 

Tim Sackett: 17:07

Yeah, we had one of them in the pitch fest that actually did a live demo of it. And that's very dangerous here, because you know how it is, like, with, like, Wi Fi and everything else. And so we were like, Oh, he's gonna try it. And he did it live, and it was really good. And he said, like, there was like, maybe because it's only a three minute pitch, like, a minute into the interview, he's like, I have to go, sorry. And it was like, Oh, no problem. We'll connect back. Let us know.

 

David Turetsky: 17:29

Really?

 

Tim Sackett: 17:30

Like, immediately it could, like, respond to that! And you're just like, Oh my gosh.

 

David Turetsky: 17:34

Well, to me, that's the promise of artificial intelligence, where it's giving HR a reason for its existence. It's helping provide those ways in which HR can't freaking scale to do all those things, to call back the 100 people, to make sure that they felt but also now what it's also going to do is it's going to provide feedback, as you said, not only to the person who got the interview, but also to the hiring manager to say, Listen, we interviewed 100 people out of 100 you know, here are the best 10, the rest of the 90. We're going to disposition them this way. Don't worry about it, we got that.

 

Tim Sackett: 18:15

I like to think like I so often I like I'm sure you do, you talk to, like, with CEOs, and they'll just go, Oh my gosh, if you just, if I could just find people that want to work for me, they want to work for our company, like, I would teach them everything they need to know. Like, I just need, like, passionate people that want to be a part of us! And like, again, I think when you take a look at all the people that apply that maybe didn't have the stuff, so they never got a sniff, they never got an interview, but all of a sudden you could turn that, you could go into the algorithm and say, You know what, if something comes across where they're super passionate about working for us, right? And it comes across in the interview, we know we might not, like level them up to the to that job, but we want to make sure we star them and put them in a pile where somebody, like, in person is communicating with them, right? Because we're going to find something for those people, right? And like, all of a sudden now you're building on culture with the people who really want to work for you, and like, turns into like, great stuff. Like, you just never know. But before those people would literally, they would be, they would be a black hole. They never heard from you, and they got this crappy disposition email, yeah. And all of a sudden you turn, like, maybe one of your biggest fans to your brand into a negative or one of your biggest customers, right? Like, hey, I'm a top five. I buy more purses from you than anybody.

 

David Turetsky: 19:23

Well, now they become a detractor, and social media is what it is. So they're going to tell their experience to the entire world, and everybody's going to know about it. Yeah, and nobody wants to be treated like that. Hey, are you listening to this and thinking to yourself, Man, I wish I could talk to David about this. Well, you're in luck. We have a special offer for listeners of the HR Data Labs podcast, a free half hour call with me about any of the topics we cover on the podcast or whatever is on your mind. Go to salary.com/HRDLconsulting to schedule your free 30 minute call today. If only our world was that perfect, where all companies could do that. Now, you mentioned something before, about it's not about the technology. Is it about the configuration of the technology? Is about the data and the training of the technology, I mean. And the reason I'm going there is because of the Workday example, and you know how it was seen as being biased, and there's the lawsuits about it and, and I don't, I will tell you, I don't know the exact details, but to me, that speaks of that's a technology that wasn't configured correctly. That's just my

 

Tim Sackett: 20:34

Yeah. I mean, part of it is understanding what AI is and what AI isn't right. Like, everyone wants to say the AI is biased, but like, a like, AI, at its core is a young toddler being trained by something. And you go, Wait a minute. Like, we were all, we shouldn't have been shocked when open AI did, or Gemini, or any of these giant open, like, you know, language models, like, did really bad stuff, yeah, because you're like, it was being trained by the Internet exactly, you know, the bad stuff on an internet. Like, would you ever let a toddler loose on the like, you just wouldn't, right? Well, so we shouldn't have been like, so I think like, people figured out. And I think the like, the best companies in our space are building private language models, right? And we think, well, well, so it still could just come and do something? No, no. This is a software program. It can't do whatever it wants.

 

David Turetsky: 21:17

Right.

 

Tim Sackett: 21:17

If it is designed specifically to do one thing it can do only that thing. It can't just make up its own rules and do whatever it want. I think people don't understand that. And so we had some early examples of some bad things happening because people were testing probably, like public language models where they shouldn't have been right, right? Or they let you know the training in terms of machine learning go too far before being checked, yeah. And so it learned to be biased based on what your behaviors were, not itself, right? Yeah. And so again, I think no company wants to be on the front page of The New York Times on biased technology. And so I think we see now that they're being very

 

David Turetsky: 21:51

No. cautious, very careful. A lot of it is like, hey, it doesn't actually respond by itself. It will respond, but it still forces you as a person to actually send, right? And so you're the double checker, right? There's a lot of that going on again. I think eventually, two years down the road, that won't be the case. We'll be we'll understand that, oh, this is a private model. The best ones I've seen are, like, they built a private model to do something specific. They actually build a separate model that says, hey, whatever this model says, if there's anything that could be considered offensive, we're gonna go right into a pre approved response loop, right where it says, like, hey, you know what? That's a great question. We're gonna have a human reach out to you, right? You know? right, exactly, yeah.

 

Tim Sackett: 22:35

And so it's incapable of actually being offensive, yeah? And like, I think that's all we really care about, right? For our brands

 

David Turetsky: 22:41

In the in the old days, we used to call that QA. We just call it unit tests, yeah, I think. And we used to try and test for all those negative things from happening. In fact, it Workscape I had built a legal language dictionary, I called it, but it had nothing to do with legal language. It was all the bad words you couldn't say.

 

Tim Sackett: 22:57

Like, I demo so many things. And like, you know, work with so many of these companies, and I've tested a couple where they said, couple of where they said, like, try to break it, right? Try to get it to do something, try to get it to write code, try to get it to do anything. Try to get it to be mad at you. Yeah, it's just, it's impossible. Like, it just, you know, and again, those are the ones that are building private, right? I have some that I'll go and I'll ask them, like, well, what are you using for your backbone? And they'll go open AI, and I'm like, oh. And they're like, oh, but it's enterprise. I'm like, still, it's a public language model,

 

David Turetsky: 23:27

Exactly.

 

Tim Sackett: 23:27

You can't control that. You can bumper it. But again, I can also then create rules in my querying that, you know, that can, like, change the bumpers, you know. So it's like, if I'm smart enough, you know. And again, we're the software companies are getting smarter and smarter smarter, and how to stop people trying to change it, right, right? So it becomes more difficult every single day, but like, again, it's still risky when you're using public models.

 

David Turetsky: 23:51

And that's what a lot of the people that are in these enterprises today that aren't there are no guard rails on them, being able to use Open AI, Gemini, Copilot or whatever, and some of the others that I don't know, and be able to do that from a consumer perspective, and type in whatever query they want, that may actually be giving out intellectual property that they don't realize.

 

Tim Sackett: 24:14

Yeah.

 

David Turetsky: 24:15

So where do you think that the companies need to stand? Is this an IT locking this stuff down, or?

 

Tim Sackett: 24:21

I don't think so. I mean, here's, here's the ironic part is, like, we have job postings out there saying, hey, we want you to come in and use AI and develop AI and do all this stuff, but we're not going to allow you in the recruiting process to use AI, or we're not going to, you know, do all these things. I think we have to know, like, right now, we let people just do whatever they want and like, and we're like, Well, isn't there a lot of risk at that? I always take it as like, hey, if I'm working with somebody that I think is a poor performer, and I asked them to do some work for me, and they send me something, I'm double, triple checking. I'm not gonna let that go without me saying, wait a minute. I don't trust what Tim's putting out. I'm gonna check it. I'm doing the same thing with my AI.

 

David Turetsky: 25:04

Yeah.

 

Tim Sackett: 25:05

Like, I'm not gonna just go, oh, it's AI did it? It must be perfect! You know, and just send it, and all of a sudden realize, Oh my gosh, it said something not true or wrong or whatever.

 

David Turetsky: 25:13

Right? Well, there's a warning there. There's a there's a tale of people using these models, yeah, and just saying, Oh, well, it's good enough.

 

Tim Sackett: 25:22

But there's also really great use cases for this stuff that actually work really well. Like, it's amazing. You know, you can go in there and be like, hey, I want, like, 1800 a day calorie diet with 150 grams of protein and this many carbs. And I want to buy everything at Trader Joe's, and immediately it gives you this list. You're like, holy crap. This is amazing!

 

David Turetsky: 25:43

And I'm gluten free, or shellfish intollerant Really?

 

Tim Sackett: 25:46

There's so many cool things you can do. So I or whatever. think, like, first you have to get out there, play with it, understand, like, what it can do, be comfortable with what you know, what you're gonna. And the hallucinations. Like, I think I told you, like, when I first started doing it, I was like, you know, what's the most controversial quote Tim Sackett's ever said on, you know, And, yeah, and so I came back that don't, don't hire ugly people, it will, it will decrease the value of your company. And I'm like, wow, that is controversial. I never said that. It completely so it took a quote that I said was, I said, only hire pretty people, it increases the value of your company. And it turned it around to a negative and made it more controversial with ugly.

 

David Turetsky: 26:23

Wow! No way!

 

Tim Sackett: 26:24

It completely hallucinated it. Because I said, I'm like, That's a great quote. Where did you get it from? And it took me to the blog post where I wrote it, and it was completely and I said, Well, find me that quote on this, you know, I go, and it can't find it, it's not, you know. So did you make this up? You know?

 

David Turetsky: 26:39

Well, and in that case, was the AI lying?

 

Tim Sackett: 26:42

Well, they call it a hallucination. It's a fancy way to say it lied. Yeah,

 

David Turetsky: 26:46

Really?

 

Tim Sackett: 26:47

So there's, it gets less and less. There's less less hallucination that happens within the AI. Again, that's a public model, you know.

 

David Turetsky: 26:54

But is that the AI going rogue? Or is that the AI trying to give you back what you what it thought you wanted?

 

Tim Sackett: 26:59

Exactly. That's a lot of that's what it is, right? Because I said, like, controversial, right, you know. So it knew to go and, like, you know, of the millions of words I've written online, it was going to go out and, like, see all of those, and then make something controversial, you know.

 

David Turetsky: 27:14

Dude! And you said it on the HR Data Labs podcast. Wow. But that's so fascinating, because that does get to the dystopian concerns that people have about, you know, you know, is the AI gonna start doing things that we

 

Tim Sackett: 27:32

You see this on social all the time, especially aren't telling it. with the image generation stuff, right? Where you can basically tell it to don't do anything, and for the most part, it'll give it to you, and then all of a sudden it gets out there and someone says, oh my god, did you see this picture? And you're like, it's AI, it's not real. Well, it looks so real.

 

David Turetsky: 27:46

I know. Well, I've used Adobe Illustrator, yeah, AI, which, that's the initials for Adobe Illustrator. And it can do some fascinating things, but you have to know how to prompt it. You have to know how to write it the right way.

 

Tim Sackett: 28:02

Yeah.

 

David Turetsky: 28:03

And it could take you eight hours, and then after the eight hours, you go, Oh, shit, I could have just drawn this myself.

 

Tim Sackett: 28:08

You know, the I think, though, like, another trend we're seeing like, is that, because it used to be what we thought, everyone's going to become a prompt engineer in HR, you gotta learn how to prompt. They're building this stuff now where you can just natural language ask what you want. You don't have to learn how to prompt. And it will prompt. And it will prompt, it'll write the prompts for you, right? And you can just kind of keep going back and reiterating based on real language. And I think that's ultimately, I mean, eventually, you'll just be talking to your computer, right? You know, hey, I need this data. Like we, I actually talked with some data science people today, and they're like, you know, the prior part of that is, if you're not really good at data anyways, you ask for something and it just gives it to you, great. But, like, right? Maybe what you got is not what you think you got. What they're trying to recreate is really teaching you how to do BI, where you go, right? Hey, I need this data. And it would go, why are you looking? What do you need about that data? You know?

 

David Turetsky: 28:53

Right.

 

Tim Sackett: 28:54

Oh, because I, my CEO's upset because we can't open things, because they think it's this and like, oh, well, maybe we should deliver this data story, around all these aspects of what's causing the problem, and, like, teaching them, like, really what that's all about. And I think again, all of a sudden, now, as an HR leader, you're like, I'm a now a data professional, like, I'm like, really good at this. Like, I'm going to be an expert based on, I have this agent that's great at BI.

 

David Turetsky: 29:16

And that, to me, is scary and beautiful at the same time, because now it's it's trying to train you on the better way of asking it the right thing. Yeah, and that's beautiful.

 

Tim Sackett: 29:30

Have you seen the very, the most late, like the latest model out. That's a paid model for chatGPT will actually show you how it's thinking, and it actually says words like, hmm. It will type it out as it

 

David Turetsky: 29:43

really

 

Tim Sackett: 29:43

and it will show you the process. And it's they call, I can't remember what they actually call it, but they, what they're trying to show you is like, this is how it actually is coming up to the answer it gets you

 

David Turetsky: 29:52

Wow

 

Tim Sackett: 29:52

Because you can challenge it often. Like, I'll go back and say, Are you sure the these are the top five things, you know, blah, blah, blah, and it'll come back and go, you know, you're right. I, you know, there's two other ones. I think I would add and replace this one, like, but like, if it just gives you the answer, it doesn't, you don't see where, like, oh well, this is where I got that. But then I found this one over here. And like, and so like, now you can start to dig into the black box and like, it will show you it thinking. And that's fascinating.

 

David Turetsky: 30:17

It is! I mean, if you ask somebody if you're sitting there with like, if I'm sitting there with you, and I'm asking you, well, how did you come up with that?

 

Tim Sackett: 30:25

Yeah.

 

David Turetsky: 30:26

First of all, you're gonna get really annoyed that I'm

 

Tim Sackett: 30:28

Yeah, but we could, if we did the exercise to brainstorm it out, right? I want to know everything you're thinking. We're gonna write it down. That again, that's how we formulate the answer as well.

 

David Turetsky: 30:36

Absolutely. But then again, it's also the secret sauce that makes Tim Sackett, who he is, right?

 

Tim Sackett: 30:41

For sure, yeah.

 

David Turetsky: 30:42

And I don't want to replicate that. I'd love to know your thinking, but that's the reason why I'm talking to you, is because your brilliant mind. I'm not going to become you. But it's really cool to understand how you came up with that.

 

Tim Sackett: 30:55

Yeah,

 

David Turetsky: 30:55

I just want to know what you think, dude.

 

Tim Sackett: 30:57

I know. Yeah, I do that. I still think, like to me, that all this comes back to is, where do you stick the human back in the loop, right? Where do you come? Where is it? Where do we need uniquely human experiences, whether that's in recruiting, in HR, in employee development, and wherever we do stuff, right? I think what you know to me, if the AI gives you a capacity to deliver a more human experience, and like, I always go back and like, people are like, Oh, eventually you'll have like, these AI friends and AI co workers and all this other stuff. And I'm like, I still believe, like, the unique human thing we have is we don't want to be alone.

 

David Turetsky: 31:30

And that's not dystopian. Yeah.

 

Tim Sackett: 31:30

We want to be with other humans. And so like, how No, no, that's a hopeful part of it, right? Like, that's the best thing, yeah.

 

David Turetsky: 31:32

But it becomes dystopian in like, a couple are we? Can AI help create those experiences where I feel like, degrees difference, right? Where you know that person does start Hey, I'm engaging with people like that. I've never, like, talked with before, but the AI knew we would have we were talking to the computer instead of start, start talking to thinking the same way about something, and we could come up with a great solution for it, right? people, or stop talking to people, start, stop relating. And I think this is a movie we've all seen, but hopefully that's not anytime soon.

 

Tim Sackett: 32:16

Yeah.

 

David Turetsky: 32:25

You've just gone through 30 minutes in one question!

 

Tim Sackett: 32:28

Like it was nothing, right?

 

David Turetsky: 32:29

Like exactly, and we could keep doing this like all afternoon, but I want to be respectful of your time. Thank you so much.

 

Tim Sackett: 32:36

Thank you for having me.

 

David Turetsky: 32:37

You know, I look forward to the HR technology show to talk to you and to have these conversations.

 

Tim Sackett: 32:43

I always enjoy it.

 

David Turetsky: 32:44

Thank you so much. Take care and stay safe.

 

Announcer: 32:48

That was the HR Data Labs podcast. If you liked the episode, please subscribe. And if you know anyone that might like to hear it, please send it their way. Thank you for joining us this week, and stay tuned for our next episode, stay safe.