1 00:00:00,040 --> 00:00:02,560 I've talked before about how essential into a QuickBooks 2 00:00:02,560 --> 00:00:05,440 Payroll is for small businesses, especially if you're juggling HR 3 00:00:05,440 --> 00:00:08,240 responsibilities. Having payroll, job codes, time 4 00:00:08,240 --> 00:00:10,760 tracking and accounting connected in one system saves 5 00:00:10,760 --> 00:00:13,160 time, reduces errors and makes it easier. 6 00:00:13,440 --> 00:00:15,280 To make smart. Decisions fast. 7 00:00:15,480 --> 00:00:17,920 It's easy to see why it's the number one payroll software for 8 00:00:18,000 --> 00:00:20,440 small businesses. In fact, I actually know someone 9 00:00:20,440 --> 00:00:23,080 who is a small business owner who uses into a QuickBooks 10 00:00:23,080 --> 00:00:26,440 payroll and gets all of these amazing benefits from it. 11 00:00:26,840 --> 00:00:28,480 And now it's getting even better. 12 00:00:28,640 --> 00:00:29,960 Starting this summer, QuickBooks. 13 00:00:30,040 --> 00:00:32,720 Payroll is evolving into something bigger, expanding 14 00:00:32,720 --> 00:00:35,360 beyond payroll to support the entire team life. 15 00:00:35,360 --> 00:00:38,480 Cycle. HR time, benefits and payroll 16 00:00:38,480 --> 00:00:41,880 will work together in one connected system, fully 17 00:00:41,880 --> 00:00:44,960 integrated with your books. And I love that because it's all 18 00:00:44,960 --> 00:00:47,120 symbiotic. And that means that soon 19 00:00:47,120 --> 00:00:49,800 businesses will be able to recruit and manage hiring from 20 00:00:49,800 --> 00:00:53,120 job posting to offer a letter right inside QuickBooks on board 21 00:00:53,120 --> 00:00:55,680 employees and one seamless flow that feeds directly into 22 00:00:55,680 --> 00:00:58,120 payroll. Manage digital documents with E 23 00:00:58,120 --> 00:01:00,880 signatures. Love that and acknowledgments 24 00:01:00,920 --> 00:01:04,599 all organized in one place. Configure automated HR workflows 25 00:01:04,599 --> 00:01:06,520 for things like promotions or off boarding. 26 00:01:06,840 --> 00:01:10,560 Track performance, time off and benefits alongside payroll. 27 00:01:10,800 --> 00:01:13,720 And everything lives where you already run your finances, 28 00:01:13,880 --> 00:01:17,440 giving you more visibility, consistency and confidence. 29 00:01:17,440 --> 00:01:18,520 And who? Doesn't love. 30 00:01:18,520 --> 00:01:21,320 That find me one person who doesn't love that you won't be 31 00:01:21,320 --> 00:01:23,440 able to. So start using QuickBooks 32 00:01:23,440 --> 00:01:26,200 Payroll today and see how it simplifies your workflow. 33 00:01:26,200 --> 00:01:29,120 And stay tuned for the evolution coming this summer. 34 00:01:29,440 --> 00:01:32,120 Learn more at quickbooks.com/workforce. 35 00:01:32,120 --> 00:01:38,880 That's quickbooks.com/workforce. Welcome back to the Bringing the 36 00:01:38,880 --> 00:01:42,160 Human Back to Human Resources podcast The Replay series. 37 00:01:42,480 --> 00:01:45,000 I'm your host, Tracy Chernoff, and I'm thrilled to have you 38 00:01:45,000 --> 00:01:48,240 join us once again as we journey through the episodes that have 39 00:01:48,240 --> 00:01:51,680 top charts around the world. In this podcast series, we're 40 00:01:51,680 --> 00:01:54,680 revisiting some of our most insightful, thought provoking, 41 00:01:54,680 --> 00:01:58,120 and transformative conversations with industry experts, thought 42 00:01:58,120 --> 00:02:01,720 leaders, and practitioners. These episodes have made waves, 43 00:02:01,720 --> 00:02:05,040 sparking meaningful conversation and inspiring positive change 44 00:02:05,040 --> 00:02:08,000 throughout human resources. Whether you're a dedicated 45 00:02:08,000 --> 00:02:10,919 listener who's been with us from the start or you're just tuning 46 00:02:10,919 --> 00:02:14,160 in for the first time, the Replay series offers a chance to 47 00:02:14,160 --> 00:02:16,680 dive deep into the core principles that guide our 48 00:02:16,680 --> 00:02:21,240 exploration into HR practices. So get ready to rediscover the 49 00:02:21,240 --> 00:02:23,920 discussions that continue to shape the future of HR. 50 00:02:24,400 --> 00:02:27,200 Without further ado, let's step back in time and immerse 51 00:02:27,200 --> 00:02:30,080 ourselves into the podcast's top charted episodes. 52 00:02:30,320 --> 00:02:33,120 Let the replay begin. Hello, everyone, and welcome 53 00:02:33,120 --> 00:02:35,280 back to the podcast. Thank you so much for being here 54 00:02:35,280 --> 00:02:37,280 for another week. I'm really, really excited 55 00:02:37,280 --> 00:02:42,520 because Joshua Berry returns to the podcast, and Joshua has been 56 00:02:42,520 --> 00:02:44,680 on the podcast before, as you can tell from what I've just 57 00:02:44,680 --> 00:02:50,160 said, but he was on the podcast June in 2024 and so not so long 58 00:02:50,160 --> 00:02:52,760 ago. But Joshua has some very 59 00:02:52,760 --> 00:02:56,000 exciting updates for us and we have a lot to cover. 60 00:02:56,240 --> 00:03:00,080 The last time he was on it was episode 183 and the episode was 61 00:03:00,080 --> 00:03:03,400 called Challenging Beliefs There to be Naive featuring Joshua 62 00:03:03,400 --> 00:03:06,680 Berry. So let me remind you who he is 63 00:03:06,920 --> 00:03:08,720 and then we'll jump right into the episode. 64 00:03:09,000 --> 00:03:11,760 Joshua Berry is a world class facilitator of change. 65 00:03:11,760 --> 00:03:14,240 As an author, speaker, entrepreneur, and director of 66 00:03:14,240 --> 00:03:17,400 Econic, Joshua has spent the last two decades evolving the 67 00:03:17,400 --> 00:03:21,000 what, who and why of Fortune 500 companies and venture backed 68 00:03:21,000 --> 00:03:23,120 startups. For employees and leaders 69 00:03:23,120 --> 00:03:25,320 looking to grow themselves and their organizations. 70 00:03:25,520 --> 00:03:29,120 Joshua speaks on overcoming limiting beliefs, adaptive 71 00:03:29,120 --> 00:03:32,160 leadership, and the innovation systems and mindsets that create 72 00:03:32,240 --> 00:03:35,840 create engines for growth. So of course, I'll link where 73 00:03:35,840 --> 00:03:40,320 you can find Joshua and iconic and all of that fabulous 74 00:03:40,320 --> 00:03:43,360 information that you might need in order to connect. 75 00:03:43,360 --> 00:03:45,400 But in the meantime, Joshua, welcome back. 76 00:03:45,400 --> 00:03:48,520 Thanks so much for for being able to join and being open to 77 00:03:48,520 --> 00:03:50,000 rejoin. So glad to have you back. 78 00:03:50,240 --> 00:03:52,880 Happy new year Tracy, excited to be back with you too. 79 00:03:53,720 --> 00:03:56,240 Amazing. Well, I don't want to. 80 00:03:56,320 --> 00:03:59,160 I don't want to share the big news, but you do have some big 81 00:03:59,160 --> 00:04:02,000 news for the listeners. Absolutely. 82 00:04:02,000 --> 00:04:06,440 So the last time I was with you, Tracy, you helped poke some 83 00:04:06,440 --> 00:04:10,760 ideas and we got into thinking about words and the meaning of 84 00:04:10,760 --> 00:04:13,440 words, and we could talk about those later. 85 00:04:13,440 --> 00:04:19,640 But that kind of snowballed into a Ted Talk that I was hoping to 86 00:04:19,640 --> 00:04:22,560 get chosen for eventually got chosen for that. 87 00:04:22,560 --> 00:04:28,680 And I delivered that Ted Talk to a full audience in Omaha, NE in 88 00:04:28,680 --> 00:04:32,480 November of 2024. And in that talk should be 89 00:04:32,480 --> 00:04:36,120 released soon. But it has big implications for 90 00:04:36,120 --> 00:04:40,240 truly bringing the human back into human resources and 91 00:04:40,240 --> 00:04:42,560 artificial intelligence and a bunch of other things we can get 92 00:04:42,560 --> 00:04:44,160 into. But I really just wanted to come 93 00:04:44,160 --> 00:04:47,840 back to say thank you, Tracy, for poking and dislodging 94 00:04:47,840 --> 00:04:52,560 something in my brain, in my heart that turned into what what 95 00:04:52,560 --> 00:04:55,720 hopefully people will see as a provocative idea that's worth 96 00:04:55,720 --> 00:04:58,800 spreading. Oh my gosh, First of all, you 97 00:04:58,960 --> 00:05:01,600 owe me no thanks. But I will say you're welcome 98 00:05:01,600 --> 00:05:03,880 because I was raised not to be rude. 99 00:05:04,600 --> 00:05:06,840 When someone says thank you, you say you're welcome. 100 00:05:07,040 --> 00:05:11,040 No, I, you really, you know, I make joke make I'm making light 101 00:05:11,040 --> 00:05:12,840 of this, but you really don't owe me anything. 102 00:05:12,840 --> 00:05:14,520 It was such a pleasure having you on. 103 00:05:14,520 --> 00:05:18,960 It's why I'm so excited that you're back and I'm really 104 00:05:18,960 --> 00:05:21,560 excited for you. I mean, a Ted Talk is kind of 105 00:05:21,560 --> 00:05:25,360 like, that's the thing. Like that's if, you know, if 106 00:05:25,400 --> 00:05:29,160 we're not doing anything else, like we should probably want to 107 00:05:29,160 --> 00:05:30,720 have a Ted Talk at some point in our lives. 108 00:05:30,720 --> 00:05:32,480 And you've done it. That's so amazing. 109 00:05:32,480 --> 00:05:35,000 I can't wait for it to come out. Thank you. 110 00:05:35,160 --> 00:05:40,000 It definitely was on the bucket list and it was something that 111 00:05:40,640 --> 00:05:43,480 at the beginning of the year, I, I truly set forward a couple of 112 00:05:43,480 --> 00:05:46,400 ideas and goals. And so the fact that that was 113 00:05:46,400 --> 00:05:48,800 able to happen, I'm excited and we'll see how it's received 114 00:05:48,880 --> 00:05:50,320 right. That's, that's always the thing. 115 00:05:50,560 --> 00:05:51,280 So. Totally. 116 00:05:51,280 --> 00:05:55,480 Well, knowing you now for the better part of what is that 117 00:05:55,480 --> 00:05:58,360 about Cigna? 8 months now, no more than that, 118 00:05:58,360 --> 00:06:02,160 maybe nine months, considering we spoke before we recorded, I 119 00:06:02,160 --> 00:06:04,120 think that it will be received very well. 120 00:06:04,400 --> 00:06:07,440 And you know, something that I really appreciate about what you 121 00:06:07,440 --> 00:06:12,560 do and what you bring also to to this audience is that you 122 00:06:12,640 --> 00:06:15,440 emphasize the importance of things that matter. 123 00:06:15,520 --> 00:06:17,840 Like we're talking like words, for example. 124 00:06:18,120 --> 00:06:25,040 And sometimes people, I think undervalue the value of words or 125 00:06:25,280 --> 00:06:28,760 you know what, what we can do with the things that we say or 126 00:06:28,760 --> 00:06:31,720 how we say them. I mean, I'm asked, for example, 127 00:06:31,720 --> 00:06:34,080 all the time about bringing the human back to human resources 128 00:06:34,080 --> 00:06:37,320 where that came from. And it's like, well, it, it's 129 00:06:37,360 --> 00:06:40,600 in, it's in the name, right? So when we think about the power 130 00:06:40,600 --> 00:06:45,600 of words and, you know, coming back to also just what you stand 131 00:06:45,600 --> 00:06:49,080 for and what you've done, I mean, can you take us through or 132 00:06:49,080 --> 00:06:52,440 like, can you give us a slight preview into the Ted talk of 133 00:06:52,560 --> 00:06:54,360 what that was about? Yeah. 134 00:06:54,440 --> 00:06:59,080 Yeah, yeah. My pleasure, you know it, it 135 00:06:59,080 --> 00:07:04,080 came from the realization that, as you said, we use a lot of 136 00:07:04,080 --> 00:07:07,960 words without even thinking about them or more importantly, 137 00:07:07,960 --> 00:07:10,680 truly understanding the implications that they have. 138 00:07:11,120 --> 00:07:14,600 You know, I earlier in my career, I LED sales and 139 00:07:14,600 --> 00:07:19,200 marketing teams and we would constantly be talking about our 140 00:07:19,280 --> 00:07:22,840 prospects and our leads and how to put people in a better 141 00:07:22,840 --> 00:07:25,520 funnel. And often times we're talking 142 00:07:25,520 --> 00:07:29,840 about listeners like those to your podcast, right? 143 00:07:29,840 --> 00:07:33,120 Like who actually wants to be put into a funnel or to be 144 00:07:33,120 --> 00:07:36,360 prospected or targeted or any of those things. 145 00:07:36,840 --> 00:07:39,280 And yet those are words we just, we just throw out. 146 00:07:39,280 --> 00:07:44,000 And what I explore in the talk is that unfortunately, just 147 00:07:44,000 --> 00:07:48,040 copying and pasting those words that were used before us, we 148 00:07:48,040 --> 00:07:52,200 sometimes start to rationalize behavior that we wouldn't 149 00:07:52,200 --> 00:07:56,200 normally take if the person was sitting right on the other side 150 00:07:56,200 --> 00:07:58,560 of the screen like you are to me, Tracy, right? 151 00:07:59,080 --> 00:08:01,960 And that extends into human resources, right? 152 00:08:01,960 --> 00:08:07,440 When we start to think about head count as just a number or 153 00:08:07,560 --> 00:08:11,120 people as an expense to be controlled or others, we start 154 00:08:11,120 --> 00:08:15,840 to dehumanize. And truly, dehumanization is one 155 00:08:15,840 --> 00:08:20,800 of the first steps towards even worse actions that that can come 156 00:08:20,800 --> 00:08:22,360 from that. So I get into all of that in my 157 00:08:22,360 --> 00:08:27,280 Ted talk in a nice little bite sized 10 minute entertaining. 158 00:08:28,600 --> 00:08:31,040 Wow. Well, my next question would be, 159 00:08:31,120 --> 00:08:32,960 how do you do that in 10 minutes? 160 00:08:32,960 --> 00:08:34,880 I mean, but it's the power of words. 161 00:08:35,159 --> 00:08:39,559 I mean, that's so amazing and it's really powerful. 162 00:08:39,559 --> 00:08:42,520 You're right. When when like I'm thinking 163 00:08:42,520 --> 00:08:45,520 about, first of all, let me take a step back because I could. 164 00:08:45,520 --> 00:08:50,320 I'm about to ramble if I don't. When I think about one of the 165 00:08:50,320 --> 00:08:53,520 main functions within HR, especially when you're starting 166 00:08:53,520 --> 00:08:58,080 to work on strategy and things like you are analyzing people. 167 00:08:58,560 --> 00:09:01,600 And when you're analyzing people, you eventually get to a 168 00:09:01,600 --> 00:09:04,480 place where you're analyzing people as numbers, to your 169 00:09:04,480 --> 00:09:07,880 point. And the bigger the company, the 170 00:09:07,880 --> 00:09:12,160 easier it is to remove yourself from what that number 171 00:09:12,160 --> 00:09:16,600 represents, who that number represents and who that person 172 00:09:16,600 --> 00:09:19,240 actually is. And so when you talk about 173 00:09:19,240 --> 00:09:22,920 dehumanizing, it is it is so real. 174 00:09:22,920 --> 00:09:26,320 And you know, The thing is, it's so beyond just business, like 175 00:09:26,880 --> 00:09:30,920 when anyone or anything is dehumanized, I mean, that's, 176 00:09:31,120 --> 00:09:34,200 it's kind of like the breakdown for everything, right? 177 00:09:34,200 --> 00:09:39,760 So when we keep the focus on the human and we do our, because of 178 00:09:39,760 --> 00:09:42,360 course it's unrealistic to think, Oh, well, we're going to 179 00:09:42,360 --> 00:09:46,000 look at every single person as a human when we're analyzing big 180 00:09:46,000 --> 00:09:49,920 things, sure, fine, no problem. But it's like when you're, I 181 00:09:49,920 --> 00:09:54,440 think the most important point in all of that when, when a 182 00:09:54,440 --> 00:09:59,680 company is analyzing people is once you come to the point where 183 00:09:59,680 --> 00:10:02,800 you're making a decision about those people that you reframe 184 00:10:02,800 --> 00:10:07,240 it, it's like, OK, you have 10,000 people that you are going 185 00:10:07,240 --> 00:10:10,080 to lay off. Well, who are those 10,000 186 00:10:10,080 --> 00:10:12,200 people? Who are they made-up of? 187 00:10:12,320 --> 00:10:15,040 You know, like what, what comprises that group of people? 188 00:10:15,040 --> 00:10:17,000 Do they have children? Are they on the benefits? 189 00:10:17,000 --> 00:10:19,320 Like what kind of resources are they going to need, you know, 190 00:10:19,840 --> 00:10:23,280 so. What you're hitting on is, is 191 00:10:23,280 --> 00:10:26,080 I'm not saying like remove all of that language. 192 00:10:27,120 --> 00:10:30,800 What I, what I advocate for is just being more intentional 193 00:10:30,840 --> 00:10:36,320 about the language that we're using and, and not just using 194 00:10:36,400 --> 00:10:44,440 unconscious words because a mentor of mine, Ari once told me 195 00:10:44,440 --> 00:10:48,640 that that words are just a symptom of our conscious or 196 00:10:48,640 --> 00:10:52,400 unconscious beliefs, right. And, and often times when we, 197 00:10:52,400 --> 00:10:54,840 when we throw out those words like you said, what we got a 198 00:10:54,840 --> 00:10:58,080 layout, we got a right size, we got to stream the line. 199 00:10:58,200 --> 00:11:01,000 The buzzwords. Any of those sorts of things 200 00:11:01,960 --> 00:11:06,080 that may be true and it may actually be necessary for a 201 00:11:06,320 --> 00:11:08,680 healthy organization going forward, let's say. 202 00:11:10,240 --> 00:11:16,880 And yet maybe those words are actually representative of some 203 00:11:16,880 --> 00:11:20,680 underlying unconscious or unspoken belief about the 204 00:11:20,880 --> 00:11:24,640 replaceability of people within a system that you're working in. 205 00:11:24,640 --> 00:11:28,360 OK, I at least want people to be cognizant of that. 206 00:11:28,920 --> 00:11:31,520 It'll even be intentional that. OK, that's what I think. 207 00:11:31,560 --> 00:11:36,240 And then back to what we talked about in episode 183, there are 208 00:11:36,240 --> 00:11:38,760 things you gain and there are things you lose by holding that 209 00:11:38,760 --> 00:11:41,720 particular belief. And so I just want people to 210 00:11:41,720 --> 00:11:45,200 wake up a little bit more to the consciousness of that, 211 00:11:45,760 --> 00:11:50,160 especially in today's day and age with artificial intelligence 212 00:11:50,960 --> 00:11:55,920 and, and the power that our words have on shaping our future 213 00:11:55,920 --> 00:11:59,720 through AI. Oh my gosh, yes. 214 00:12:00,200 --> 00:12:05,480 And actually, when I think about AI and words, my initial 215 00:12:05,480 --> 00:12:09,240 thought, and this is probably just because I just bought a 216 00:12:09,240 --> 00:12:12,200 minivan and it came up and I, I promise you I'm going to make 217 00:12:12,200 --> 00:12:13,840 the connection. I'm really excited about the 218 00:12:13,840 --> 00:12:17,240 minivan, by the way, even though I'm so much cooler than what a 219 00:12:17,240 --> 00:12:20,160 minivan necessarily like portrays. 220 00:12:20,920 --> 00:12:22,920 I'm so. Redefining the minivan, Tracy, 221 00:12:23,120 --> 00:12:26,800 you're going to redefine. I really am like I am really 222 00:12:26,800 --> 00:12:29,800 changing the game for minivans. I'm just saying if Toyota wants 223 00:12:29,840 --> 00:12:31,640 the spots for me, I got the Sienna. 224 00:12:32,840 --> 00:12:34,720 I'm so excited. I'm going to make the connection 225 00:12:34,720 --> 00:12:38,720 here in a moment when when I think about AI, my first thought 226 00:12:38,720 --> 00:12:43,840 because of my experience buying the minivan is the what we ask 227 00:12:44,120 --> 00:12:49,600 AI if we're using generative like, you know, language with 228 00:12:49,640 --> 00:12:50,880 like let's say Chachi. PT. 229 00:12:51,160 --> 00:12:56,400 And I think about that because it's kind of a perfect example 230 00:12:56,400 --> 00:13:02,000 of like what you give to AI can sometimes be what you receive. 231 00:13:02,000 --> 00:13:05,040 It's not necessarily thinking beyond the scope of what you 232 00:13:05,040 --> 00:13:07,080 might mean, what your context might be, right? 233 00:13:07,440 --> 00:13:12,200 And so I share the minivan anecdote because when my husband 234 00:13:12,200 --> 00:13:15,560 and I were going to buy it, they were like, and you know, 235 00:13:15,560 --> 00:13:20,680 according to Google, this is like the percent above MSRP that 236 00:13:20,680 --> 00:13:25,080 it should be like above MSRP for I'm any that and no offense, 237 00:13:25,080 --> 00:13:30,960 minivans, but I love you. And the question was how much of 238 00:13:31,240 --> 00:13:36,320 what percentage above MSRP is the Toyota Sienna or the 239 00:13:36,320 --> 00:13:38,080 minivan? I'm like, well, of course that's 240 00:13:38,080 --> 00:13:41,400 going to tell you a percent above MSRP because you're asking 241 00:13:41,400 --> 00:13:46,800 it to tell you the percent if you ask what the average price 242 00:13:47,400 --> 00:13:50,720 of of a Toyota like that might not be above MSRP. 243 00:13:50,920 --> 00:13:55,720 So this is a very, very nuanced example, but that's the way I 244 00:13:55,720 --> 00:13:59,920 take kind of what you're saying in terms of like how we think 245 00:13:59,920 --> 00:14:03,920 about nuance and language when it is related to AI and that 246 00:14:03,920 --> 00:14:07,160 might not be your intention. But no, no, no, it's exactly a 247 00:14:07,160 --> 00:14:12,720 flavor of my intention in that as you said, large language 248 00:14:12,720 --> 00:14:17,040 models that power tools like ChatGPT or Anthropics Clock or 249 00:14:17,680 --> 00:14:25,160 Microsoft Copilot, etcetera, are all built on studying and 250 00:14:25,160 --> 00:14:31,680 ingesting and training on immense amounts of data and text 251 00:14:31,680 --> 00:14:35,240 and images and music and everything that can go into it. 252 00:14:35,960 --> 00:14:41,080 And in a response to your prompt, which you very much have 253 00:14:41,080 --> 00:14:49,920 control over, the agent will do its best to be able to predict 254 00:14:49,920 --> 00:14:52,080 what the right response should be to what you're saying. 255 00:14:52,080 --> 00:14:56,520 But it's all based upon previous patterns that it's seen in the 256 00:14:56,520 --> 00:14:59,400 training data. And so you're right, if they've 257 00:14:59,400 --> 00:15:05,360 asked 1000 times, what percent above MSRP is this van the 258 00:15:05,360 --> 00:15:09,120 thousandth and first time is likely going to give that back. 259 00:15:09,800 --> 00:15:14,240 And that's my intent of marrying this being conscious about your 260 00:15:14,240 --> 00:15:19,640 words, especially in human resources and AI, because as 261 00:15:19,640 --> 00:15:23,120 publicly available sources of training data are exhausted, 262 00:15:23,120 --> 00:15:29,480 companies are routinely turning more and more towards private or 263 00:15:29,480 --> 00:15:32,680 at least once in gated sources of information for for training 264 00:15:32,680 --> 00:15:35,720 their models. And so when you start to think 265 00:15:35,720 --> 00:15:43,680 about the last ways that you described people in your emails 266 00:15:43,680 --> 00:15:47,960 or Microsoft Teams messages or blog posts or other things, and 267 00:15:47,960 --> 00:15:52,600 there's a million examples of treating people like a resource 268 00:15:53,360 --> 00:15:58,680 in, in those previous ones, like what do we expect AI is going to 269 00:15:58,680 --> 00:16:01,720 predict the value of people is beyond that. 270 00:16:01,880 --> 00:16:05,160 And so I, I think we're, we're at a, we're at a very 271 00:16:05,160 --> 00:16:10,280 interesting inflection point where we can start to shift the 272 00:16:10,280 --> 00:16:14,840 narrative even of what generative AI thinks about 273 00:16:14,840 --> 00:16:19,000 people, right, and their value based upon the conscious word 274 00:16:19,000 --> 00:16:23,040 choice that we have. Yeah, Oh, this is really 275 00:16:23,040 --> 00:16:27,560 important because everyone, of course, rightfully so, is 276 00:16:27,560 --> 00:16:32,320 talking about AI. And AI will continue to be a 277 00:16:32,320 --> 00:16:37,000 part of the conversation naturally, because it's our 278 00:16:37,000 --> 00:16:40,480 future, it's our present. It's just, you know, what is 279 00:16:40,520 --> 00:16:44,440 important in today's day and age, but how we use it and 280 00:16:44,440 --> 00:16:49,440 having a better understanding of, I guess just generally like 281 00:16:49,440 --> 00:16:53,160 how we can best use it, what the best use case is, makes a lot of 282 00:16:53,160 --> 00:16:56,200 sense. Yes, absolutely. 283 00:16:56,280 --> 00:17:01,000 And I'm very much a pro AI and, and being intentional in its use 284 00:17:01,000 --> 00:17:06,880 case and just being, as I said, even before, whether we had AI 285 00:17:06,920 --> 00:17:10,920 or not, being a little bit more aware of the types of word 286 00:17:10,920 --> 00:17:13,440 choices that we're using and the implications that they have and 287 00:17:13,440 --> 00:17:17,040 how those choices impact our actions and behaviors. 288 00:17:17,280 --> 00:17:22,240 Yeah, no, it makes sense. I was just talking to someone in 289 00:17:22,280 --> 00:17:29,480 HR who I kind of said like, Hey, what do you, what do you think 290 00:17:29,480 --> 00:17:34,280 about this fear that people have with like AI taking their jobs, 291 00:17:34,600 --> 00:17:35,880 basically? And this was not in the 292 00:17:35,880 --> 00:17:37,720 recording. It was like an intro call 293 00:17:37,720 --> 00:17:40,640 because I'd like to, you know, see what I can get out of 294 00:17:40,640 --> 00:17:42,640 people, you know, because these are some, these are the 295 00:17:42,640 --> 00:17:47,080 questions that people have. And she was like, oh, well, it's 296 00:17:47,080 --> 00:17:50,200 totally true. AI is going to replace jobs. 297 00:17:50,520 --> 00:17:52,560 And this is like, you know, ahead of people. 298 00:17:53,000 --> 00:17:56,920 And I was like, oh, like I was kind of taken aback because part 299 00:17:56,920 --> 00:18:01,680 of me like, you know, I get it. Of course there are jobs that 300 00:18:01,680 --> 00:18:05,000 are at risk. And then the other part of me is 301 00:18:05,000 --> 00:18:11,960 like, well, how do we see AI as a resource to better fulfill our 302 00:18:11,960 --> 00:18:14,840 jobs so that we're not as much at risk? 303 00:18:15,960 --> 00:18:18,200 But that is not something that you can cover in a 10 minute 304 00:18:18,200 --> 00:18:20,960 conversation. And so I wonder like, you know, 305 00:18:20,960 --> 00:18:25,040 from your perspective and how, you know, I guess really 306 00:18:25,040 --> 00:18:28,040 relating it to being very cognizant of what we say and how 307 00:18:28,040 --> 00:18:31,960 we say it, especially in HR. How would you answer? 308 00:18:31,960 --> 00:18:33,000 I'm putting you in the hot seat here. 309 00:18:33,000 --> 00:18:36,120 I'm so sorry, but how would you like answer that? 310 00:18:36,120 --> 00:18:38,880 If someone's like, you know, I'm really worried that AI is going 311 00:18:38,880 --> 00:18:42,480 to take my job. I'm an HR admin, I'm an HR 312 00:18:42,480 --> 00:18:46,200 manager, I'm an HR whatever. And I'm really worried that AI 313 00:18:46,200 --> 00:18:48,040 is going to take over my job. Maybe it's someone in 314 00:18:48,040 --> 00:18:52,920 recruiting. What do I do to how do I, how do 315 00:18:52,920 --> 00:18:57,640 I navigate using AI without putting myself in a position 316 00:18:57,640 --> 00:19:02,000 where it's doing my job instead of me doing my job with AI? 317 00:19:02,000 --> 00:19:04,880 You know, like, is there a way that we answer that? 318 00:19:04,880 --> 00:19:07,880 Or maybe it's on the other side of things where like, how do 319 00:19:07,880 --> 00:19:12,080 you, what would you say to an HR person who's like an HR leader 320 00:19:12,080 --> 00:19:15,240 who is confronted with that and has to navigate answering that 321 00:19:15,240 --> 00:19:17,200 question? Like either perspective, I'd 322 00:19:17,240 --> 00:19:21,320 love to hear. So the first thing that comes to 323 00:19:21,320 --> 00:19:25,720 mind is is I believe you called out and some of your 2025 HR 324 00:19:25,720 --> 00:19:30,080 trends, the need for adaptability, for evolving, for 325 00:19:30,080 --> 00:19:34,680 continuous skill development. I think that all very much 326 00:19:34,680 --> 00:19:40,880 applies here because the the individual or the leader who's 327 00:19:40,880 --> 00:19:45,160 thinking about application of HR and their workflows or or job 328 00:19:45,160 --> 00:19:49,920 tasks for their people, just like digging in your heels and 329 00:19:49,920 --> 00:19:52,880 resisting likely isn't going to work. 330 00:19:54,600 --> 00:19:58,440 The better approach is to start to understand, OK, what are some 331 00:19:58,440 --> 00:20:03,920 of the ways that if I had, this is I think the best descriptor. 332 00:20:03,920 --> 00:20:10,160 Somebody said if I had infinite interns at my disposal, what 333 00:20:10,160 --> 00:20:14,520 would I be able to do? And and and, and because at 334 00:20:14,520 --> 00:20:18,360 least for now, at least some of the abilities are around to that 335 00:20:18,360 --> 00:20:21,520 level and, and so you, you need to think about that's a. 336 00:20:21,560 --> 00:20:23,680 Fabulous. Example things on a different 337 00:20:23,680 --> 00:20:27,520 level of scale. And so if you were basing let's 338 00:20:27,520 --> 00:20:32,120 you to your HR admin role, like if you were basing your job 339 00:20:32,120 --> 00:20:36,520 value on the ability to know all of the policies and how to 340 00:20:36,520 --> 00:20:41,360 implement them and how to adjudicate them and and being a 341 00:20:41,480 --> 00:20:46,640 resource, know how person that that is something that could 342 00:20:46,640 --> 00:20:51,400 probably be replaced eventually, probably not the relational side 343 00:20:51,400 --> 00:20:54,720 of things. But even there, I'll start to 344 00:20:54,720 --> 00:20:57,120 challenge that some younger generations would actually 345 00:20:57,120 --> 00:21:00,920 probably prefer to interface with a non person for some of 346 00:21:00,920 --> 00:21:03,560 that information. And so you, you are left with 347 00:21:03,560 --> 00:21:06,640 thinking what what are the additional skills or other 348 00:21:06,640 --> 00:21:09,400 things that could continue to add value around that? 349 00:21:09,400 --> 00:21:13,840 Because if it's just information retrieval or analysis, that may 350 00:21:13,840 --> 00:21:16,920 not be as as helpful going forward. 351 00:21:17,080 --> 00:21:21,560 And so a simple way to also answer this is just start 352 00:21:21,560 --> 00:21:26,480 experimenting, find ways that are either corporately 353 00:21:26,480 --> 00:21:31,080 responsible, if you, if you can, or off on the side on your own 354 00:21:31,080 --> 00:21:34,920 personal things to at least start to practice with some of 355 00:21:34,920 --> 00:21:38,440 these tools so that you can have a better understanding of what 356 00:21:38,440 --> 00:21:41,800 they're capable of and, and practice that curiosity. 357 00:21:41,800 --> 00:21:45,320 And, and yeah, consider the, the thought exercise. 358 00:21:45,320 --> 00:21:48,760 If I had infinite interns, what might I be capable of? 359 00:21:49,240 --> 00:21:51,680 I love that so much and it's really true. 360 00:21:51,720 --> 00:21:57,240 As a former intern myself, that is exactly where Chachi like AI 361 00:21:57,240 --> 00:21:58,960 is. I shouldn't just say Chachi BTU. 362 00:21:58,960 --> 00:22:02,960 It's really any AI tool that we're using because I guess 363 00:22:02,960 --> 00:22:05,880 depending I think of these, what is the phrase? 364 00:22:05,880 --> 00:22:09,280 It's not generative. I guess it is generative AI, 365 00:22:09,280 --> 00:22:10,400 right. With that's what I'm thinking 366 00:22:10,440 --> 00:22:10,720 of. Yeah. 367 00:22:11,120 --> 00:22:15,160 So with any generative AI tool that I have used, and I've used 368 00:22:15,160 --> 00:22:19,920 a few, anything that I kind of put in it is kind of, you know, 369 00:22:19,920 --> 00:22:22,840 it's a little sophomoric. It's it's coming, it's 370 00:22:23,120 --> 00:22:27,360 delivering information based on, you know, a limited or certain 371 00:22:27,360 --> 00:22:30,480 amount of data. And with limited experience so 372 00:22:30,480 --> 00:22:32,840 far. And I can only imagine once 373 00:22:32,960 --> 00:22:37,920 generative AI turns 30, you know, how how much more or maybe 374 00:22:37,920 --> 00:22:42,080 even 40 or 50 or 60, like how much more it will be able to do. 375 00:22:42,440 --> 00:22:46,680 And then when you were sharing about, you know, not resisting 376 00:22:46,680 --> 00:22:50,120 so much, I'm really basically embracing this technology. 377 00:22:50,360 --> 00:22:53,240 It makes me think about the phrase keep your, keep your 378 00:22:53,240 --> 00:22:54,800 friends close, keep your enemies closer. 379 00:22:55,040 --> 00:22:58,160 Because even though I don't believe that AI is the enemy at 380 00:22:58,160 --> 00:23:00,600 all, I really don't. I say that to be very tongue in 381 00:23:00,600 --> 00:23:02,480 cheek. It's kind of like this, this 382 00:23:02,480 --> 00:23:07,600 idea that you, you could find yourself in a position where 383 00:23:07,800 --> 00:23:13,520 technology could do the a certain job. 384 00:23:13,680 --> 00:23:16,400 I don't think that it's going to be able to do like at least with 385 00:23:16,400 --> 00:23:19,360 an HR, especially from the relationship side. 386 00:23:19,360 --> 00:23:22,640 That's still a very important part of what we do is build and 387 00:23:22,640 --> 00:23:26,720 maintain those relationships. And so it's like, well, if it's 388 00:23:26,720 --> 00:23:29,680 doing all these other things that actually help us to 389 00:23:30,360 --> 00:23:34,200 repurpose our time that was once spent doing heavily 390 00:23:34,200 --> 00:23:36,760 administrative things. It's kind of like you're keeping 391 00:23:36,760 --> 00:23:39,600 it closer. Once you embrace it, it's not 392 00:23:39,600 --> 00:23:41,920 this thing that you have to work against anymore. 393 00:23:41,920 --> 00:23:44,440 It's this thing that you're working with and that's 394 00:23:44,440 --> 00:23:47,360 empowering you, enabling you hopefully and your job to do 395 00:23:47,760 --> 00:23:50,720 more, to upskill, to adapt. I appreciate that you reference 396 00:23:50,720 --> 00:23:55,160 the 2025 HR Trends episode because that's kind of what I'm 397 00:23:55,160 --> 00:23:58,480 hoping to invoke throughout the rest of this year is that like 398 00:23:58,600 --> 00:24:02,400 AI doesn't have to be the enemy. It's something that we really 399 00:24:02,400 --> 00:24:05,920 can kind of leverage. It's, you know, it's a tool at 400 00:24:05,920 --> 00:24:07,360 the end of the day. Yeah. 401 00:24:07,960 --> 00:24:12,600 You know, we so our core business is custom training and 402 00:24:12,600 --> 00:24:17,040 development programming, whether it's leadership development 403 00:24:17,040 --> 00:24:21,200 programming to certain specific skills or behaviors. 404 00:24:22,200 --> 00:24:28,040 We use it quite often to help make us better facilitators and 405 00:24:28,400 --> 00:24:31,160 curriculum designers and and experienced people. 406 00:24:32,360 --> 00:24:36,520 So if you start to think about it as a tool of not just go find 407 00:24:36,520 --> 00:24:41,000 this for me or research this for me, but instead, here's here's 408 00:24:41,000 --> 00:24:45,960 an outline for an experience. Why won't this work right? 409 00:24:46,000 --> 00:24:49,360 Or you start using it in a coaching challenging make me 410 00:24:49,360 --> 00:24:53,160 better sort of way. I think you can unlock then a 411 00:24:53,160 --> 00:24:57,440 whole nother level of potential value out of a tool like that. 412 00:24:59,280 --> 00:25:02,960 Here's here's even a, a silly, maybe it's a meta example of 413 00:25:02,960 --> 00:25:07,120 this is if you're the HR admin and you had your job 414 00:25:07,120 --> 00:25:09,960 description, you could put it into one of these tools and say 415 00:25:10,280 --> 00:25:15,200 which of these tasks are most likely to be taken over by AI in 416 00:25:15,200 --> 00:25:18,320 the future and why? And then teach me why. 417 00:25:18,320 --> 00:25:19,600 And then what are some things I could do? 418 00:25:19,600 --> 00:25:22,280 Like use the tool for itself, right? 419 00:25:22,720 --> 00:25:27,240 Yes, I think that's great advice and I really like what you 420 00:25:27,240 --> 00:25:31,800 shared in terms of this idea around brainstorming like you 421 00:25:31,800 --> 00:25:34,640 don't need to tap the shoulder of your Co worker when you've 422 00:25:34,640 --> 00:25:38,400 got an AI brain readily available to you, you know, and 423 00:25:38,680 --> 00:25:42,640 to think about like asking it, well, what wouldn't work about 424 00:25:42,640 --> 00:25:44,280 this? What am I missing? 425 00:25:44,320 --> 00:25:48,560 What it what are my blind spots? I mean, I think of so many use 426 00:25:48,560 --> 00:25:52,640 cases for that. And as I always share on the 427 00:25:52,640 --> 00:25:55,480 podcast that, you know, I'm the first to admit that I move 428 00:25:55,480 --> 00:25:58,000 really fast, most of the time too fast. 429 00:25:58,000 --> 00:26:01,440 I like don't always like notice like the fine details because 430 00:26:01,440 --> 00:26:04,320 I'm moving so fast and like, you know, execution, execution, 431 00:26:04,320 --> 00:26:09,480 execution. And I find like IAI generative 432 00:26:09,600 --> 00:26:11,640 AI and I tend to use Chachi PT the most. 433 00:26:11,920 --> 00:26:15,880 I find it to be extremely helpful to be aware of my blind 434 00:26:15,880 --> 00:26:18,120 spots. Like what, what question am I 435 00:26:18,120 --> 00:26:22,160 not asking? What, what am I missing about 436 00:26:22,160 --> 00:26:25,760 this like really important topic and whether it's for my podcast 437 00:26:25,760 --> 00:26:28,400 or for work. I mean, it's, it just tends to 438 00:26:28,400 --> 00:26:33,840 be to me like an additional brain, something that will allow 439 00:26:33,840 --> 00:26:37,480 me to think more deeply about something that I otherwise would 440 00:26:37,480 --> 00:26:40,280 probably miss unless I ask someone else and hopefully they 441 00:26:40,280 --> 00:26:42,240 wouldn't miss it. Yeah, yeah. 442 00:26:42,760 --> 00:26:47,120 Yes, great, great topic. We can keep digging into this 443 00:26:47,720 --> 00:26:52,080 and again how it all ties back to that Ted talk. 444 00:26:52,080 --> 00:26:59,040 I think that we can use and leverage the power of AI to also 445 00:26:59,040 --> 00:27:04,040 bring more human back into human resources in the workplace 446 00:27:04,240 --> 00:27:10,920 because our intentional usage each time, hopefully, each time, 447 00:27:10,920 --> 00:27:14,320 hopefully a transcript from your podcast is getting put in the 448 00:27:14,320 --> 00:27:17,360 training data. I hope it's getting smarter and 449 00:27:17,360 --> 00:27:21,440 more more pro human. I hope all the thoughts. 450 00:27:21,440 --> 00:27:22,800 That would be kind of cool, yeah. 451 00:27:23,080 --> 00:27:24,720 I hope. And actually it makes me think 452 00:27:24,720 --> 00:27:27,440 of another question for you here, which is, you know, when 453 00:27:27,440 --> 00:27:33,000 you think about AI and the human, you know, let's say 454 00:27:33,000 --> 00:27:38,080 humanizing work more, humanizing the workplace more, are there 455 00:27:38,520 --> 00:27:42,880 strategies that maybe people who struggle with this, like people 456 00:27:42,880 --> 00:27:47,400 who really tend to lose sight of the human element, are there 457 00:27:47,400 --> 00:27:50,520 strategies that you would advise they take or follow when it 458 00:27:50,520 --> 00:27:53,200 comes to using AI in order to ensure that they're not 459 00:27:53,640 --> 00:27:57,000 inadvertently dehumanizing? Yeah, I, I. 460 00:27:57,400 --> 00:28:07,720 Think that one can be more how you are using it for coaching, 461 00:28:07,920 --> 00:28:09,680 right? Just being conscious about the 462 00:28:09,680 --> 00:28:12,960 questions that you're asking and, and why, right? 463 00:28:12,960 --> 00:28:16,720 And then so back to the idea of not putting in anything that you 464 00:28:16,720 --> 00:28:19,280 wouldn't want to see on the front page of the newspaper. 465 00:28:20,120 --> 00:28:24,080 Just being cognizant of, of that and how a lot of that data is 466 00:28:24,080 --> 00:28:26,560 being used. We, we were, we were doing a 467 00:28:26,560 --> 00:28:31,480 workshop on adaptive leadership at one of the big companies out 468 00:28:31,480 --> 00:28:36,840 there that also has an AI product that may sit by your 469 00:28:36,840 --> 00:28:38,600 side. We'll just call it that. 470 00:28:39,320 --> 00:28:44,960 And they too were thinking about and saying, like, we, we believe 471 00:28:44,960 --> 00:28:47,400 that Big Brother is always watching our stuff that we're 472 00:28:47,400 --> 00:28:50,800 putting into here because we, we are the makers of this, of this 473 00:28:50,800 --> 00:28:53,360 tool. And so I think just being 474 00:28:53,360 --> 00:28:57,400 conscious about that can maybe keep some of it into check, 475 00:28:57,400 --> 00:29:01,200 especially because you have a, you have another lens that your 476 00:29:01,200 --> 00:29:04,640 words might actually be perpetuating a different world 477 00:29:04,640 --> 00:29:08,080 in the future that could have ramifications beyond what you 478 00:29:08,080 --> 00:29:11,720 thought. And then the other is maybe a 479 00:29:11,720 --> 00:29:15,720 very practical use of how you can start to humanize your work 480 00:29:15,720 --> 00:29:21,920 a little bit more is to ask whatever AI tool you're using, 481 00:29:22,840 --> 00:29:25,880 things like here's the e-mail I'm about to send. 482 00:29:26,040 --> 00:29:32,040 How might this be received by someone or ask empathy driven 483 00:29:32,040 --> 00:29:35,120 questions to give you feedback, right. 484 00:29:35,120 --> 00:29:40,000 And and I've this has helped me, I'm sure, send out some emails 485 00:29:40,000 --> 00:29:42,600 that were landed a lot better than than the ones. 486 00:29:42,600 --> 00:29:44,920 So you know, you know the old thing in the past of like write 487 00:29:44,920 --> 00:29:47,720 your e-mail if you're mad and then delete it or write your 488 00:29:47,720 --> 00:29:50,400 e-mail if you're mad and then leave it in your drafts for 24 489 00:29:50,400 --> 00:29:51,880 hours or exactly. Yep. 490 00:29:52,560 --> 00:29:55,360 You could potentially also. Do that here and say like this 491 00:29:55,360 --> 00:29:57,440 is what I'm going to send. How might this be received? 492 00:29:57,440 --> 00:30:01,680 Help me come up with a more empathetic way to share this 493 00:30:01,680 --> 00:30:04,640 through AB or C Should I even send this e-mail? 494 00:30:04,640 --> 00:30:06,560 Right. Like there's different ways that 495 00:30:06,560 --> 00:30:09,240 you can, if you think about it from a coaching standpoint, 496 00:30:10,120 --> 00:30:13,320 yeah, makes a lot. Of sense the other piece, I 497 00:30:13,320 --> 00:30:15,760 don't know. If you use this but there is the 498 00:30:15,760 --> 00:30:20,360 setting for instance, I also use ChatGPT as as my primary one. 499 00:30:21,200 --> 00:30:23,280 There's a setting where you can have almost like the master 500 00:30:23,280 --> 00:30:29,080 prompts in your settings and you can put in specific things like 501 00:30:29,360 --> 00:30:33,920 you could actually say if I am referring to people in a 502 00:30:33,920 --> 00:30:37,840 dehumanizing way, call me out on it and you can put some of those 503 00:30:37,840 --> 00:30:41,560 master prompts in there. You. 504 00:30:42,480 --> 00:30:44,680 You're. Not maybe you're not using this. 505 00:30:44,960 --> 00:30:47,280 Hey, we need to we need to teach you. 506 00:30:47,720 --> 00:30:50,080 I know, I feel. Like, I know what you're talking 507 00:30:50,080 --> 00:30:51,920 about and I've probably ignored it. 508 00:30:53,360 --> 00:30:55,880 That's OK. If you go into, tell me. 509 00:30:57,440 --> 00:30:59,920 If you go into, I probably can't screen share, can I? 510 00:30:59,920 --> 00:31:01,800 But when I'm in Chad, actually, can I? 511 00:31:01,800 --> 00:31:02,600 Can I? Let's see. 512 00:31:02,680 --> 00:31:05,560 Yeah, I think you can. Do you see share and then screen 513 00:31:05,560 --> 00:31:07,360 do but now oh, we're. In the. 514 00:31:07,880 --> 00:31:09,960 All we're in. The thick of it and you're gonna 515 00:31:10,000 --> 00:31:11,360 see we're in it all. Of. 516 00:31:11,440 --> 00:31:12,880 For those who are watching a video. 517 00:31:12,880 --> 00:31:14,800 They're gonna really be in for it now. 518 00:31:14,800 --> 00:31:16,480 And now you're gonna see all my search. 519 00:31:16,480 --> 00:31:18,160 Terms. I don't even see what I have. 520 00:31:18,280 --> 00:31:20,640 That's really funny. When? 521 00:31:20,640 --> 00:31:26,200 I am over in the right here and I go into customize ChatGPT. 522 00:31:26,800 --> 00:31:32,000 I can start to see things like what what should it call me? 523 00:31:32,160 --> 00:31:36,840 What traits so I put treat me as an expert, consider new 524 00:31:36,840 --> 00:31:42,160 technologies, no moral lectures like list URLs at the end of 525 00:31:42,160 --> 00:31:45,440 your response. You can add a number of these 526 00:31:45,440 --> 00:31:50,120 things in here to help you have it. 527 00:31:50,120 --> 00:31:54,160 And so in there you could put something like, if ever I am 528 00:31:54,240 --> 00:31:56,680 sounding dehumanizing, like call me out on it. 529 00:31:57,240 --> 00:32:01,160 Oh my gosh. Well, listen, I first of all, I 530 00:32:01,160 --> 00:32:02,680 learned something new today. Thank you. 531 00:32:03,240 --> 00:32:04,960 I can officially go home. The day is over. 532 00:32:06,160 --> 00:32:07,600 Funny. Yeah. 533 00:32:08,000 --> 00:32:09,560 I'm home. I'm home, I can just close my 534 00:32:09,560 --> 00:32:11,680 laptop and be done. Thank you for that. 535 00:32:11,920 --> 00:32:15,760 Secondly, I think you probably taught a lot of people something 536 00:32:15,760 --> 00:32:17,280 new today. So thank you for that. 537 00:32:17,800 --> 00:32:20,160 That's, I mean, first of all, everyone learned hopefully 538 00:32:20,160 --> 00:32:23,880 something new before you shared your screen, but now after 539 00:32:24,200 --> 00:32:29,880 really being able to see how we can make this technology work 540 00:32:29,880 --> 00:32:34,720 for us in the best possible humanly possible way. 541 00:32:34,840 --> 00:32:37,800 I mean, that's really cool. Thank you for sharing that. 542 00:32:38,120 --> 00:32:39,640 You're welcome. Amazing. 543 00:32:39,640 --> 00:32:43,720 Well, I don't know any better way to leave this episode and 544 00:32:43,720 --> 00:32:47,240 conclude, but I all I know is that I want to congratulate you 545 00:32:47,240 --> 00:32:50,760 again on your Ted talk. I can't wait for it to come out. 546 00:32:51,000 --> 00:32:53,880 Hopefully it'll be out by the time this episode is otherwise 547 00:32:53,880 --> 00:32:55,960 we will you. We will keep all of the 548 00:32:55,960 --> 00:33:00,640 listeners totally, totally informed and we'll get it shared 549 00:33:00,640 --> 00:33:03,240 in the newsletter once it's out. I'm just so excited for you. 550 00:33:03,640 --> 00:33:07,080 I can't think of anyone better to do a Ted Talk and any better 551 00:33:07,080 --> 00:33:08,240 topic. I think it's awesome. 552 00:33:08,840 --> 00:33:11,520 That's sweet and thank you so. Much, Tracy, I appreciate your 553 00:33:11,520 --> 00:33:16,000 curiosity and obviously for showing up every week and 554 00:33:16,000 --> 00:33:19,440 putting out great content like this to keep bringing even more 555 00:33:19,440 --> 00:33:20,960 humanity back into the workplace. 556 00:33:21,000 --> 00:33:22,880 So thank you for your work. Oh my gosh. 557 00:33:22,920 --> 00:33:24,920 Thank you so much. It is truly my pleasure. 558 00:33:24,920 --> 00:33:28,800 And with that, I will remind everyone that Joshua's links and 559 00:33:28,800 --> 00:33:32,360 everything that you might need in order to connect or learn 560 00:33:32,360 --> 00:33:35,480 more about Iconic or Joshua in general are in the show notes. 561 00:33:35,480 --> 00:33:38,280 So please click along and don't forget to rate, review, and 562 00:33:38,280 --> 00:33:40,480 subscribe. Joshua, thank you so much again. 563 00:33:40,480 --> 00:33:42,560 Second episode in the books, that just means you have to come 564 00:33:42,560 --> 00:33:45,720 back #3 there's. A special jacket? 565 00:33:45,720 --> 00:33:46,800 Some swag? Exactly. 566 00:33:47,920 --> 00:33:50,160 Ooh, that would. Be fine, don't tell me with a 567 00:33:50,160 --> 00:33:51,520 good time. I love swag. 568 00:33:52,320 --> 00:33:53,840 Amazing. Thank you so much. 569 00:33:54,520 --> 00:33:55,280 Thanks, Tracy. Hey. 570 00:33:55,360 --> 00:33:57,760 Just before you go. Don't forget to subscribe to 571 00:33:57,760 --> 00:33:59,920 this show so that you are the first to hear when. 572 00:33:59,920 --> 00:34:02,680 An episode. Drops each week and maybe leave 573 00:34:02,680 --> 00:34:05,360 a five star review and a comment about how much you loved this 574 00:34:05,360 --> 00:34:07,360 episode. Plus, if you have someone in 575 00:34:07,360 --> 00:34:09,840 mind who would really enjoy this episode, make sure you share it 576 00:34:09,840 --> 00:34:11,840 with them. Thank you so much for tuning in 577 00:34:11,840 --> 00:34:13,199 and I'll see you next week.