Nicholas Rhodes - How AI in the Workplace Can Improve Employee Experiences

[00:00:02] Here's an experiment for you. Take passionate experts in human resource technology. Invite cross-industry experts from inside and outside HR. Mix in what's happening in people analytics today. Give them the technology to connect, hit record, pour their discussions into a beaker.

[00:00:21] Mix thoroughly and voila! You get the HR Data Labs podcast where we explore the impact of data and analytics to your business. We may get passionate, and even irreverent, that count on each episode challenging and enhancing your understanding of the way people data can be

[00:00:39] used to solve real-world problems. Now here's your host, David Turetsky. Hello and welcome to the HR Data Labs podcast. I'm your host David Turetsky alongside my co-host, trusted friend, partner. I could come up with a couple other names. Dwight Brown from salary.com.

[00:00:57] I think a lot of people could come up with other names for me. Yeah, but this is a PG rated show so we can't go into this. Yeah, exactly. I gotta keep those secrets. Yes, yes, it is a secret.

[00:01:09] Maybe we'll cover that on the 25th episode. Today we have with us a pretty brilliant guy, and you'll hear why in just a minute. Nicholas Rhodes, he's the founder and creative director of OutSnap. Hello, Nicholas, how are you? Hello, hello. I am well. I'm coming to you from

[00:01:27] New York City. We have bright blue skies with big white fluffy clouds so I'm in a good mood today. There you go. In fact, I was just there yesterday dropping off some boxes for my kiddo

[00:01:39] to pack up their dorm at the School of Visual Arts on 24th Street. They'll be coming. I'll be picking them up maybe in two weeks. Oh my goodness, that's incredible. Yeah, this year has flown. It really has. But Nicholas, tell us a little bit about you.

[00:01:57] Yeah. Where do you want me to start? Well, you can start with birth, but that might be a little bit long for this 30-minute podcast. I don't remember much from that day.

[00:02:08] Cool. So I guess, well, I'll give you the short history. So I went to school in Boston, studied what they call New Media at the time, which was early 2000s, back in the time when

[00:02:20] the internet was black web pages with bread text and we thought it was super, super cool. So I did four years at Emerson learning what we called New Media like I said. And

[00:02:30] at the time I graduated, the incoming freshmen seemed to know more about New Media than I did. Also after four years of looking for missing semicolons and commas, I decided that I

[00:02:42] wanted to really focus on print design and not so much on the technical aspects of the internet anymore. So up to date, and we'll kind of jump back and forth in time, I've kept up just enough

[00:02:56] with technology encoding to what I call or I should say as my dev team calls to be very annoying because I know what's possible but can't do any of it myself anymore. Yeah, no enough to be dangerous.

[00:03:08] Yeah, exactly. I know enough to be a nuisance going into a weekend when I'm like, I don't know, it seems like you could have done that. So after school, I was a double major in new media and

[00:03:18] photography. After school, I decided that photography was going to always be my hobby and that I was going to really dive headfirst into editorial design. And so it was a really interesting time,

[00:03:31] especially I mean everywhere but in New York City, I came in as a 21 year old eager to work in print design while every other 21 year old and everyone was eager to work on the internet.

[00:03:42] And in my head, I was like that internet, I've been there done that. I remember literally a day where entire class was devoted to watching a movie buffer, like a one minute movie buffer

[00:03:54] and thinking to myself like how dumb this idea was. And now obviously we know the internet has come more than full circle on that moment. Oh yeah. And so that was a big learning lesson for me though that just because I couldn't see the

[00:04:08] promise in something at the moment, I saw they keep an eye on it and play with it and tinker with it. So I worked in print design. It was really, really cool. Like I said, because I got

[00:04:18] this opportunity to really jump ahead of where I should have been as a 21 year old because no one else was vying for these jobs and magazines. And so I had a really good run going from a production intern up to a art director within the first 10, 12 years.

[00:04:36] At the same time I started as my hobby photographing parties and nightlife and music, you know, the up and coming 20 something with not a lot of spare money. I was getting entry

[00:04:48] into concerts and parties by saying I would take photos in exchange for going to the event. So I was getting photo passes and media passes to things and that spiraled into what at the time

[00:04:58] they called a personal brand. That's where to now it's influencers. But I had a blog that was operating essentially in my off hours for my day job, I'd go out to parties and take photos and post

[00:05:10] them online starting like 2006 ish. And at the height of that website we were doing close to 150,000 pages a day from all the major like fashion centers in the world and other major market

[00:05:21] cities. So this was like now we think of kind of the most of the world as kind of being homogeneous in style and concept and music because all these things pass borders so quickly. But back then people

[00:05:34] were tuned in to see what was happening in New York from all around the world. So that was really awesome. So as a result of that I transitioned from my role as an art director

[00:05:45] at the magazine I was working with at the time radar, RIP and became the managing editor of the website which was once again a role that I was probably too young to be doing because I

[00:05:56] did not know how to manage anyone. But I didn't know how to run a website because while everybody else I was working with was sleeping I was getting 100 plus thousand page views a day.

[00:06:06] So I came in and was working with these folks and it was a really interesting time because we were in the process of moving from kind of a website for a magazine having a subscribe

[00:06:16] button on it essentially to subscribe to the official print magazine and then started running content on those sites themselves especially in sort of the gossip world that I was working on.

[00:06:26] Radar magazine was what I like to call a very smart people or us weekly and you could see who was reading it, who got the jokes like we would always joke in the focus groups who

[00:06:36] was very smart. So we would start the story essentially where us weekly and people left off and continue with the more interesting parts of from those things. So long story short that went

[00:06:48] out of business in 2008 magazines literally are still not hiring and I had to figure out how to make a living so I started working as a professional photographer with that website that

[00:06:58] I had met figured out how to monetize it. I did a lot of really amazing things and eventually realizing that in the world I was living as the only way I was going to be able to make rent was

[00:07:09] if I started throwing events myself. So so many of the things that I have learned I sort of in my head invented digital marketing because there was no one to teach at the time they learn

[00:07:21] to teach me at least at the time so I learned about A.B. testing and things like that and creating products to literally sell tickets to future events. That's cool. Yeah awesome. Fast forwarding

[00:07:32] to where we are right now. I could not expand on that particular project Niki Digital because I was one person. So I started figuring out ways to expand that brand which then spawned OutSnap which is the company that had all the learnings from starting a business and all

[00:07:52] of those other things that were part of it. So now OutSnap focuses primarily on marketing experiences internal events for companies. We used to be just an events business but now we do a lot of long-term marketing campaigns. We've had full two three year campaigns internally with companies

[00:08:09] like Cisco for their onboarding programs through HR where people can take selfies together and document their onboarding experiences and things like that. That's great. Cool. Well now that we know so much more about you Nicholas we need to ask

[00:08:23] what's one fun thing that no one knows about Nicholas Rhodes? So this is the thing that eventually usually slips out like a year two or three of a friendship with someone who will jump to it today. Well we're fast forwarding. Yeah as a kid I was a magician

[00:08:40] but like obsessively it was all I cared about like legitimately all I cared about and when we would travel around the first thing I would do when I went somewhere with my family was

[00:08:50] open the yellow pages to see if there was a magic shop and there were so few of them around the country that occasionally I would really really score big. There is an old New York Times article

[00:09:01] floating around so I can't say no one knows about it but I was lucky enough to be on Broadway for a little bit opening another magician show. Wow. Sort of like the kid

[00:09:12] opener to get the crowd warmed up which was an amazing experience and so much of what I have learned about interacting with people and public speaking really came from that as a child and having

[00:09:25] people take interest in me. That's a wonderful experience. Yeah that's awesome. Yeah it was really really cool luckily they have lost the photo it's no longer attached to the New York Times

[00:09:34] article so you have to wait until you really know me to see the photo of me in a top hat and tail. There you go we will probably hopefully one day ask you for that. Yeah.

[00:09:46] So our topic for today is one that will peak the interest of a lot of people inside and outside the world of HR and that is how AI in the workplace can improve employee experiences.

[00:10:05] So our first question for you Nicholas is you're a creative director you're a photographer you've been offering lots of experience to corporations and their employees for many years give us an overview of what you think general AI is and what it will really mean for an HR

[00:10:22] professional. Yeah well okay well I want to be clear I'm not an HR professional I'm one of the reasons why you don't play one on television right yeah right and one of the reasons I have to keep

[00:10:32] starting my own companies is because HR professionals google me and see photos of me dancing on top of things in between from polls with famous musicians but um so they see you as a risk is what you're

[00:10:44] saying yeah I don't get I don't get past HR's AI is essentially the issue right um so what is generative AI. Generative AI is so extraordinarily vast that it's hard to really even comprehend

[00:10:57] so one of the examples that I like to use about where generative or AI in general are going right now is we think of an operating system on our phones or our computers in this old fashion way

[00:11:09] right so when I used to pull up a calculator app on my computer I now just do that in chat gpt I'm already talking to chat gpt and I literally just say I have this event it starts on this day ends

[00:11:21] this day this many hours per day tell me how many hours total right so no longer am I utilizing the operating system of the computer I'm using literally a conversational operating system in

[00:11:32] which in the future I can do any number of things even right now I can say make me an illustration of xyz and that's how we're using it at my company mostly aside from interacting

[00:11:42] with our clients um we are using it as a product to make generative AI visually so that's kind of the broad scope of genii I'm happy to dive in on any of the smaller particles of it but that's like

[00:11:56] the broad scope is this thing is going to do everything that we do is you're going to get in your car and ask it to drive you somewhere but you have to learn how to ask it yes in order for

[00:12:07] it to be effective because if you say I want to go let's just because you're in New York City and I love my New York City if you're in New York City and you say hey I want you to take me to

[00:12:17] Jersey City and you don't say I'd like to use the Holland or Lincoln tunnels to do so is it going to try and find a route across the across the water go to LA first

[00:12:30] yeah I mean I wasn't gonna go that far well I was gonna say that that doesn't involve actually putting your car on the water so you know is you know you have to learn how to ask it the right

[00:12:42] question right 100% and I think this is also like a good point to pause and think about generative AI to everybody feels like this brand new thing but directions is a really great example

[00:12:54] of how we've been using it I don't know if map quest technically was AI but it was definitely figuring out how to get you some right to answer your question like ways anytime I try and out

[00:13:06] smart ways I regret it for the entire drive right sure so it's already doing things like that but yes it is about asking the questions and as the new interaction systems and as the AI gets

[00:13:17] smarter it'll be less so about asking the question because it can have enough smarts or reasoning to respond to you and say I don't understand what you mean do you mean acts or do you mean why

[00:13:28] we're already starting to see things like that with chat upt it will give you two answers and say which of these is what you want right yeah and it's learning from those interactions when

[00:13:37] you tell it which one you want yeah and I think the you know I've I've really started to integrate a lot of the AI the generative AI into even my work processes both life and work processes and

[00:13:51] it it has been interesting going through that learning process and to your point David the fact that you have to know how to ask the questions and sometimes it's peeling back the layers of

[00:14:02] the onion as you're trying to get it to do something it'll it'll kick something out and sometimes it just gets stuff completely wrong and you know the fear out there is that AI is going to

[00:14:14] take over the world and nobody will need human beings and that's just not correct I mean you need those human beings to interact with it to tell it what to do or ask it what to do and to recognize

[00:14:28] where it's wrong well I think one of the frustrations that I have Dwight is that even the you know Nicholas used the context of ways and I use Apple Maps right I find it very frustrating

[00:14:41] to ask Apple Maps hey listen I want to go home I am from going from New York City from the School of Visual Arts on 24th and 1st I want to go home but first I want to stop by a bagel store so I

[00:14:51] can feed my kids well even just the user experience of being able to go and do that is very frustrating because it asks oh you want a bagel place in New York City no no no

[00:15:02] do one in Yonkers or outside of Manhattan okay do you want one in the Bronx um yeah actually the Bronx bagels are good but no no I want one further it you we're still not at a place though

[00:15:13] yet where right it can read my mind right it knows kind of no I want to kind of escape the city first before I try and get a bagel I want to be able to park in a parking lot and not have to

[00:15:25] worry about parking on the street so what I'm talking about in terms of generative AI is almost like a smart tool learning you an assistant who learns you learns how you like to do things

[00:15:38] and then enables you to do them by asking them something very simple and they already know the context and all the assumptions behind it yeah so there's well I have to see if it still

[00:15:48] exists but there's a really good bagel place in top story which should be on your way for next time so remind me to look yeah please do yeah that would be great um and and I won't

[00:15:56] take a dig at Apple Maps either well right here but um it's all fair yeah the thing that I think is really interesting is since these are conversational operating systems to do what you're talking about

[00:16:11] is is already available within chat gpt or Gemini right chat gpt has something that I think it's a feature that I personally think they should have come up with a better name for

[00:16:22] those are called gpt's within chat gpt and you can conversationally program them to do things so for example our team we have conversationally programmed one of these through iteration to draft emails

[00:16:39] based on responses and things like that so a lot of the times we can plug in a bunch of information cut and paste or another really good example of this is I've created one that I put together

[00:16:50] before I hop on a meeting for people I scour the web for mentions of them and then I take their LinkedIn profile the email that we've had to date and drop it into this tool that I've created

[00:17:03] and anyone on my team can use it via the same link and it will put together a meeting briefing about the person based on what's on their LinkedIn it'll tell me if we have people in

[00:17:12] common all of those things so I can sit down and instead of doing the four hours of research before a meeting which no one has time to do anymore I can read a 10 minute thing that my gpt

[00:17:24] put together for me and then go and do the further research on those things that I want to do once again ai is not fully replacing me or an assistant because I still have to go through and do those

[00:17:35] things and my assistant is the person who's putting that information into the gpt and giving me the output right like what you hear so far make sure you never miss a show by clicking subscribe

[00:17:48] this podcast is made possible by salary.com now back to the show let's transition this though to well so what does it impact or how does it impact the world of hr because what we've been

[00:18:00] talking about is really kind of the how it can personally impact us sure in what normal stuff you know outside of the world of work and then well what you just mentioned would be really

[00:18:10] useful because it's a really cool tool for you to be prepared for your next meeting but how does it help hr yeah well I think I've joked about it earlier but I mean this is goes back to 2015

[00:18:21] 16 17 hr has already been using these sort of initial screeners that are ai based to determine whether or not they should even have a conversation with someone right so very similar kind of a tool that I just mentioned for different use case right so going through all these

[00:18:39] resumes and just determining whether or not it's worth talking to someone I think you know like I said and this goes back to why humans are still very relevant I think that I would have

[00:18:49] been a very valuable asset to a team but I couldn't get past those ai bots right to even talk to a human but another really cool way you could use these things is for you know imagination

[00:19:02] workshops too I think that these tools since they can do so many vast things it's a really great opportunity to lead workshops internally with your team sales kickoffs team building experiences

[00:19:15] the ability to imagine what you would look like as a better leader you know if you're working on a CEO workshop or something like that so there's a lot of opportunity and I think one of the things

[00:19:26] that makes these conversations so tricky is that I'm a creative so my imagination starts spinning and I'm not super data oriented where I know HR is or I shouldn't say I'm not data oriented

[00:19:37] I'm not looking at the same data metrics on a regular basis so one of the ways that I think it could work really well for HR in this use case for example if you're at a career fair

[00:19:49] you could have an interactive AI experience that asks perspective we do a lot of these for schools of prospective students but they could be first perspective employees as well ask a lot of questions about where they are in their educational career to see when they will be

[00:20:05] hireable what their how they see themselves as a leader what traits they want to learn and improve on and those answers to the mad live could actually give a visual output that's a takeaway

[00:20:15] for the individual but it also will give the HR person a list and a CSV of all the information that was collected which could tell you about your perspective hires as well and it's scouring the web

[00:20:28] yep yep it could which might be good or it might be really bad for that person if they've been a very frequent poster on tiktok and have drank a lot of alcohol and then posted those which

[00:20:41] we're really not supposed to look at in the world of hiring you know we're really not supposed to scour the web for those things and I guess the question is so where does HR have to draw

[00:20:49] the line on those things so that we know what we can do and what we can't do or is it really kind of I hate to use the term wild west right now but is it kind of like open yeah I think I think it is

[00:21:01] wild west and I you know I would love to say that HR would never do this but if you have two candidates and they're equal on paper except one of them there's a an explicit photo on the

[00:21:13] internet no you shouldn't be taking that into account but as a human there's no way not to right so in theory if you were to program that into AI you AI could not have the human

[00:21:26] emotion that's connected with that that we have so in theory it would do the reverse there where you're actually making a better educated decision because you have no human perspective on it to me that seems silly though because the human perspective is how you became the HR professional

[00:21:43] and therefore is you know what makes you good at your job but but as the HR professional we know the rules that we have to follow though sure and we need to tell the AI that there are

[00:21:52] certain rules like we have to have certain blinders on for certain things sure and then you know if a background check comes back and someone has a criminal history that they haven't disclosed well

[00:22:01] that's a bad thing and we need to you know we need to take specific actions on that based on what we're allowed to do not just on what we want to do or what we think is the right

[00:22:10] thing to do and one of the things to take into account with this is the error rate that's that's out there oh yeah and the you know I I googled myself for lack of a better term on chat GPT

[00:22:26] and it was interesting what it came up with apparently I'm a journalist over I don't know somewhere out east and there were a couple other facts that I I must have been in a total

[00:22:38] blackout for but it may be because you hit your head when you were doing some exactly a botch launch on extreme sports but but you know the HR professional has to has to be able to weed through that as

[00:22:54] well you need that human interaction there that and I don't know I don't even know how that works exactly but yeah there's there's an up-and-coming photographer somewhere in the UK with the

[00:23:06] same name as me which has been giving my Google it's a real run for their money and I keep getting alerts of these very cute photos of squirrels that are being published around the internet

[00:23:16] and like Nick so you sure those aren't you pretty sure I did take I took photo 101 in school right on the Boston Commons and there's actually a rule that you are not allowed to take photos

[00:23:27] of squirrels because there are so many squirrels there and apparently pre that rule just everyone would come back with this tons of photos of squirrels the squirrel sued we want lots of nuts

[00:23:39] right all in nuts got to be in nuts yeah but but if we think about this in the context of HR though other than you know other than recruiting you know is there other kind of data that

[00:23:54] gen AI can capture that would be useful or helpful in the AR world sorry in the HR world not the AR it'll be AR pretty soon augmented reality exactly we're all gonna be in our heads up

[00:24:07] dude Dwight has one not anymore he's got one not anymore you got rid of it I got rid of it dude you shizzled to me well I just returned it I didn't even sell it okay he had the apple one

[00:24:20] yeah gotcha did you see like a day two or three after that came out there was a guy driving the cyber truck yes amazing amazing and everyone looks at it's like what's wrong with the world today

[00:24:33] so I think yes data mining is going to be huge for a obviously it's it's a really obvious one I think one of the other ways that it can really work is activity or strengthening relationships on teams building and creating conversation amongst people and I think that

[00:24:54] for me the data side of it is really interesting because it can look at data over a long period of time and see things that we as humans can't see we work a lot with visual AI and we've had a

[00:25:06] few kind of sticky moments where some things come back and you know it's kind of a minefield because AI is based on society right so it has all the inherent biases that we as a society have for

[00:25:19] better or worse and we've had photos come back where people look of a different race perhaps and they you would perceive them to be and the person in this case happened to be Native American and we

[00:25:32] didn't see that in them but they were very surprised that they were like no one ever knows it but I'm like 70% Cherokee something like that and it was really interesting because AI saw whatever

[00:25:43] was in her face structure and was like oh I know that this what this person is or who this person is but their you know their identity is and that's a really interesting kind of interesting whole

[00:25:54] thing to flip flop on too yeah well from an HR perspective it's really kind of scary as well because it kind of outs people I was using air quotes everyone yeah out as to what their

[00:26:09] background is and that's not necessarily a good thing in the world of HR. No no it's not and I mean I think it's an interesting thing because in this case it was

[00:26:18] actually a moment that I was like oh no but the person actually felt very seen in a way that they had never really been seen by their peers before so it does go both ways but yes I

[00:26:29] understand what you're saying from that perspective for sure I mean it's there's so many parts of AI that are going to be perceived as landlines until we figure out how to use them right and

[00:26:40] I think it's like any tool like the wrong person using a backhoe can do a lot of damage and with AI you're the operator right and you get to use it in a responsible way.

[00:26:51] But the problem with the AI versus a backhoe is the data is really important in the world of AI whereas data for a backhoe is kind of what which lever you pushing right. Sure.

[00:27:04] Whereas the and this has been one of the issues with how some AI have been trained especially when it comes to different ethnicities and different races and so the data we have has been unbelievably biased from against or for one particular type of group and therefore

[00:27:24] when we talk gen AI in the context of HR we always get you know I hate to use the word defensive in this case but we get defensive about it because Dwight and I both share this because Dwight's a data

[00:27:36] guy and I'm an HR data guy and we share this kind of thought process that HR data sucks or kind of does suck and therefore how do you really get the most benefit out of it unless you go through

[00:27:47] the exercise of cleaning up the stuff you're going to leverage first. You could use AI in that cleaning process. But then you kind of Naran Pai has potentially built into the data. Exactly so it's no longer clean. Well I mean it is clean. It is further dirty.

[00:28:03] Well it's clean but what is it clean too? What's the standard use? What are the assumptions you're using and what are we doing to that or are we getting to a layer of abstraction that doesn't matter anymore? Right.

[00:28:14] Well I think it does matter I think whether or not we'll be able to fix it is the question right. I think there's so many questions that are still remaining to be seen. It is for the lack of better term the wild wild west.

[00:28:26] You're right it's so nascent and if you look at what we've seen change in literally it's been a year and two months three months since ChatGPT was publicly available and what it's done between

[00:28:36] now and then these things are going to be wildly different and I do think you know there are people who are talking about it the the government I think should be doing a little

[00:28:46] bit more than they are right now but I think we're about to see a sea change with that with starting with the tiktok ban and hopefully it starts and continues the conversation around

[00:28:56] privacy in general and that's going to go into AI as well versus just singling out a single app because I think as much as I'd like to point fingers around our American companies

[00:29:07] are doing very similar things right and that's where a lot of the data that we're talking about right now is actually coming from from those social networks. Hey are you listening to this and thinking to yourself man I wish I could talk to David about

[00:29:21] 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

[00:29:32] on your mind go to salary.com forward slash hrdl consulting to schedule your free 30 minute call today. So let's talk in our third question about what can HR professional do to get started

[00:29:48] in this world you know do they put their toe in and get Gemini or Bard or whatever the name is to download or just you know wait until the their particular flavor of AI comes about what

[00:30:02] where should they go? Yeah I think it's really interesting I had a really interesting conversation with a good friend of mine who works at a company which will not be disclosed for the sake of this but

[00:30:14] they as an entire company have been given the tasks of exploring AI right so everyone is sort of being challenged to figure out how AI can work in their workplace and interestingly their workplace

[00:30:28] blocks access to both Gemini and chat GBT. Wow really figure it out except yeah exactly so they're being asked to do this on their own time all as well which is really interesting so their argument is that they don't want any company information going into chat GBT

[00:30:46] for those places because once again once that data goes in it doesn't really ever come back out no may not spit it out exactly the same but the learnings from it never come out but I think

[00:30:57] what I suggest people doing is AI is really scary right now to a lot of folks and when you jump in and use Bard or sorry Gemini which is another funny name choice considering there's so many

[00:31:12] other Gemini's out there right now but anyhow you hop into Gemini it's free right now and these tools are not going to be free forever chat GBT you can use not the latest model but a pretty great

[00:31:22] model to play with it that's free currently too and these companies are losing oodles of money so that you can play with these tools for free right now too the compute power is not cheap on

[00:31:32] these and you can go in and literally just have a conversation with it ask it to tell you jokes ask it to write new lyrics to songs just to see the power of the tool and then innately you're

[00:31:43] going to start asking questions like you know that the touring test for those who aren't familiar is just the uh to pass the test the machine has to be able to fool you that it's a human right

[00:31:53] and with chat GBT it can get pretty close but one of the things that you'll probably do if you've never played with this is you as a human will not be able to help yourself quizzing this AI

[00:32:05] on how human it really is right and you'll hit barriers and you'll hit walls and it can be kind of a choose your own adventure game with this conversation right sure but I think

[00:32:15] what I would really suggest that someone can do is since these tools are free you can take any one of your tests the math example that I used earlier or um help me figure out the best schedule

[00:32:25] for this or I have these ingredients at home what are some good recipes and you can start to see how the how it responds to you and you can literally say if this isn't clear ask me more questions to get

[00:32:37] clarification you can also google around and find pre-existing prompts that help you build future prompts so before I got very comfortable in chat GBT myself there was a prompt that was

[00:32:48] a prompt builder so you'd put it in as your first step and then I would ask you a series of questions that help narrow down the question you were actually asking chat gp to sure there are

[00:33:00] million things racing through my mind right now of things I could ask chat gp to to help me with but in the world of hr that has to be more limited because we need to be able to focus on

[00:33:14] the human element of it not just the data element of it and because I can't bring in to your point before I can't bring in proprietary data nor data about the people that I work with

[00:33:26] then I still need to come up with this myself or at least that's my bias right now yes and no I mean I think I think that the data element like we said is really interesting but

[00:33:37] I I keep coming back to the activity concept of it so there's so many hr activities that happen once someone's already a member of the team whether it's team building those sales kickoffs we do

[00:33:49] a ton of sales kickoffs there's a lot of ways to utilize these tools to help people imagine a different future or imagine the future that they're already aiming for we did this really really cool event

[00:34:01] with Axios out in San Francisco where people were asked a series of questions to imagine what they wanted the future of San Francisco to be and it created a completely new San Francisco and you saw the Golden Gate Bridge in its modifications in the background right

[00:34:16] and so myself I'm not a painter for example but I can as a creative director I can describe a style of painting an artist that I really wanted to be inspired by were three artists that I want

[00:34:26] to be the combination of and you can create these things so it's not just about aesthetic but it could also I could take a photo of myself and say what would I look like as a CEO of

[00:34:37] 500 person company and based on the data that's in these tools already they'll find these CEOs that have 500 person companies and change me to look more like them right and those are once again going

[00:34:51] back to what's the data you know exactly but you can imagine these things in a way that are I should say you can see the things that you have in your imagination and a lot of the

[00:35:02] times when we're dealing with our clients they really know what they want until they see it and they're like oh that's not what I want at all right so using it as a visualization tool

[00:35:13] even with drafting an email you get them like oh I thought that's what I wanted to say but the sentiments are that I really need to be front and center aren't there so let me go back and

[00:35:23] rework it and there there are ways to anonymize data too that you're feeding into chat gpt and still be able to achieve what you're looking for with it yeah kind of like the the imagine San

[00:35:38] Francisco there's there's inputs that go with that and and I mean probably not a whole lot of privacy issues with that particular piece of things but at the same time to the to the point that

[00:35:52] you're making with that that there really is this creativity that goes with it and you can apply that in many different arenas especially in the HR arena as long as you're careful about the privacy piece of things anonymizing your data that you feed in there

[00:36:09] and and being able to arrive at you know arrive at good points for what you're looking for but Dwight the more data you put in and the more specific data you put in

[00:36:21] the better the model should be but that then goes against the privacy and the simplicity or what you're talking about the masking depending depending what you're looking for if you're looking for something on a specific candidate for example that is an issue if you're looking

[00:36:40] for something let's say you want to chat gpt to help you with an HR process that's something totally different and you know you that's one where you you could run into issues with internal processes with the company you don't necessarily want to send out into cyberspace

[00:37:00] but you can do some anonymization of the of the data to still be able to arrive at the same point so your point is spot on yes privacy and there are elements where you can't you know

[00:37:15] you just have to be very very careful but there are also elements that you know things you can build with it but let me ask I guess let me ask a question around that

[00:37:25] though and Nicholas I'm asking this to you unless Dwight you can answer this too the question I'd ask is is there any way to have a private chat gpt server where you can do these things

[00:37:37] in a box and not worry about it getting outside of that box and having that data leaked to the world air gap your data and yeah exactly I think well so currently in the world that

[00:37:48] I work in we can for generative AI for visuals there's a tool called stable diffusion which if you use the public version then it goes into the same big pool if you install it it's open source you

[00:37:59] can install it on your own server and then bring in existing libraries so you could in theory erase that server and everything is wiped my assumption is that as we see chat gpt and gemini

[00:38:13] go into enterprise mode they're definitely are going to be siloed out scenarios I mean Gemini right now they sent me an email via google saying like you know for a limited time only I

[00:38:24] can get seats for $25 a head to use Gemini so I don't know you know it's going to be a very expensive tool these but they will silo it out so you will not have to worry about your data

[00:38:35] being mixed with data outside of your scenario or I well I think but then you kind of lose some of the magic so I think exactly yeah it's about finding the happy spot where you have access to

[00:38:47] anonymized data that you could insert your data into and then reflect on how it fits in those scenarios and I think as we grow as a people people dealing with this new technology whether it's the practices that we use or the regulations that we're getting from the government

[00:39:09] will enforce on us whether it's from the EU which have already kind of put some regulations on privacy and data sharing about employees or you know our world in the US

[00:39:21] that's kind of going to be taken out of our hands a little bit but we have to have good hygiene into practices until that time sure I think we could talk about this for another year Nicholas

[00:39:38] yeah this is fun stuff this is really fun stuff yeah this is I mean what I want to do now and I'm kind of energized to do this is to kind of open up a sandbox and chat GPT and start playing

[00:39:50] and asking it some real-world questions about whether work or personal stuff yeah and seeing what kind of answers I get I tried early on and I wasn't good enough with prompts to be able to

[00:40:01] get anywhere so I think I might actually have to learn a little bit yeah there I will say if you're if you want to play there is a pro version I think it's $20 a month it is worth the extra 20 bucks

[00:40:14] to play with because chat GPT 4 I think 4 2 is what it's up to now is significantly better than the free one I know because I've run out of credits on the pro one and have to use the

[00:40:26] they have to wait an hour or use the old one but it's really it is wild and I do encourage you also to check out those GPTs you can search in them for HR tools I'm sure someone built them already

[00:40:37] and and dig it dig into those as well yeah all right cool well now our next conversation with you will be much smarter about chat GPT and our use of it sounds good thank you very much for

[00:40:49] being here Dwight thank you thank you thanks for being with us thank you for having me I could talk about this for hours thank you all for listening take care and stay safe that was the HR data labs

[00:41:00] 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