1 00:00:00,200 --> 00:00:03,440 Speaker 1: Welcome the Money and Wealth with John Hobryant, a production 2 00:00:03,680 --> 00:00:15,880 Speaker 1: of the Black Effect Podcast Network and iHeartRadio. Yo, Yo, 3 00:00:16,040 --> 00:00:18,799 Speaker 1: this is John Hobryant and this is the Money in 4 00:00:18,840 --> 00:00:25,440 Speaker 1: Wealth podcast series on iHeartRadio on the Black Effect Network. 5 00:00:26,040 --> 00:00:32,720 Speaker 1: So here we go today's episode AI Artificial intelligence for 6 00:00:32,840 --> 00:00:37,800 Speaker 1: all of us navigating the pain and the opportunity of 7 00:00:37,840 --> 00:00:41,640 Speaker 1: a changing world. AI is sort of like the electricity 8 00:00:41,640 --> 00:00:47,440 Speaker 1: of our time, powering everything, transforming industries and altering how 9 00:00:47,479 --> 00:00:50,839 Speaker 1: we live and how we work. For communities already on 10 00:00:50,880 --> 00:00:54,960 Speaker 1: the edge, this change could feel like a tsunami unless 11 00:00:54,960 --> 00:00:59,120 Speaker 1: we act with intention. Now that sounded like me? Right? 12 00:00:59,440 --> 00:01:03,120 Speaker 1: That that sounded just like I said it and wrote it, right, Ashley, 13 00:01:03,880 --> 00:01:07,760 Speaker 1: That was AI acting like me. I asked, Hey, why 14 00:01:07,840 --> 00:01:10,800 Speaker 1: to give me an opening line that sounded like John 15 00:01:10,840 --> 00:01:15,160 Speaker 1: O'Brien And there you go. Uh, this world is about 16 00:01:15,200 --> 00:01:20,119 Speaker 1: to fundamentally change. Let me break this down of how 17 00:01:20,160 --> 00:01:22,880 Speaker 1: I got into this situation. My friend, my brother Van Jones, 18 00:01:22,920 --> 00:01:26,120 Speaker 1: said this might be the ultimate leveler. By the way, 19 00:01:26,640 --> 00:01:30,280 Speaker 1: he said, of black folks don't know a thing about 20 00:01:30,319 --> 00:01:36,600 Speaker 1: AI really pause, but nine percent of white folks don't 21 00:01:36,640 --> 00:01:41,840 Speaker 1: know a thing about AI either. Pause. That we are 22 00:01:41,920 --> 00:01:46,160 Speaker 1: all starting for the first time with a technology at 23 00:01:46,200 --> 00:01:51,320 Speaker 1: the same place, lost but convinced that everything is going 24 00:01:51,400 --> 00:01:56,640 Speaker 1: to change all at once, and they're completely right. By 25 00:01:56,720 --> 00:02:00,760 Speaker 1: twenty thirty, the world's in it as you know it. 26 00:02:01,200 --> 00:02:03,760 Speaker 1: You heard it here. I didn't say twenty fifty. I 27 00:02:03,760 --> 00:02:09,480 Speaker 1: didn't say twenty eighty. Within six years time, five years time. 28 00:02:09,520 --> 00:02:12,800 Speaker 1: Actually now twenty twenty five, the world as you know 29 00:02:12,840 --> 00:02:17,880 Speaker 1: it is going to fundamentally shift, and it's shifting underneath 30 00:02:17,919 --> 00:02:21,160 Speaker 1: your feet right now. And I'm gonna explain some of 31 00:02:21,200 --> 00:02:24,000 Speaker 1: that to you. How did I get into this because 32 00:02:24,040 --> 00:02:27,000 Speaker 1: my obsessions, you know, as I've been saying, the financial 33 00:02:27,000 --> 00:02:31,080 Speaker 1: literacy is the civil rights issue of this generation. I 34 00:02:31,080 --> 00:02:33,880 Speaker 1: think if Doctor King, God rest his soul, we just 35 00:02:33,880 --> 00:02:38,919 Speaker 1: celebrated his birthday. If God, if Doctor King was alive today, 36 00:02:39,080 --> 00:02:45,000 Speaker 1: he'd be passionate about things like financial literacy as a leveler. 37 00:02:45,040 --> 00:02:47,359 Speaker 1: It's as important, I believe it's the right to vote. 38 00:02:47,680 --> 00:02:50,640 Speaker 1: I've been on this mission at Operation Hope, with Operation 39 00:02:50,720 --> 00:02:53,720 Speaker 1: Hope and financial literacy and all that comes from it 40 00:02:53,760 --> 00:02:56,560 Speaker 1: and through it. I've been on this thing for thirty 41 00:02:56,720 --> 00:03:00,799 Speaker 1: two years. It was the largest financial literacy coaching organization 42 00:03:00,880 --> 00:03:06,519 Speaker 1: in America, four point five billion dollars invested in communities, 43 00:03:06,720 --> 00:03:12,399 Speaker 1: four million plus clients, fifteen hundred offices doing financial coaching. 44 00:03:12,960 --> 00:03:16,440 Speaker 1: You know, advised three US presidents from both parties, recognized 45 00:03:16,480 --> 00:03:19,920 Speaker 1: by five Know nine. You know, just leaning in on 46 00:03:20,000 --> 00:03:24,280 Speaker 1: everything from financial coaching on the workplace, to financial literacy 47 00:03:24,320 --> 00:03:27,280 Speaker 1: in schools, children bank accounts for kids with out Mayor 48 00:03:27,320 --> 00:03:30,440 Speaker 1: Andrea Dickens in the City of Atlanta City Council for 49 00:03:30,520 --> 00:03:35,240 Speaker 1: every kid in kindergarten, kids accounts in Atlanta, the work 50 00:03:35,480 --> 00:03:39,320 Speaker 1: we're doing with major employers like Delta Airlines and ups 51 00:03:39,960 --> 00:03:43,160 Speaker 1: and the Walmart co chairing of Financial Literacy for All, 52 00:03:43,200 --> 00:03:48,240 Speaker 1: the CEO dougcmillon, the book Financial Literacy for all our work. 53 00:03:48,240 --> 00:03:52,560 Speaker 1: And disaster We're going to California. Just my heart goes 54 00:03:52,560 --> 00:03:55,520 Speaker 1: out to everybody affected by the fires and particularly the 55 00:03:55,560 --> 00:03:59,520 Speaker 1: communities in Altadena where a lot of black wealth was lost. 56 00:04:00,840 --> 00:04:04,800 Speaker 1: I'm passionate about this issue. Hoping side disaster, I work 57 00:04:04,840 --> 00:04:07,200 Speaker 1: with FEMA of creating the Emergency Financial First Aid Kit. 58 00:04:07,400 --> 00:04:10,200 Speaker 1: It goes on and on. Freedman's Bank. You've all heard 59 00:04:10,240 --> 00:04:12,440 Speaker 1: me go on and on and on, and nothing gets 60 00:04:12,440 --> 00:04:16,839 Speaker 1: me unfocused, nothing gets me off message and I get 61 00:04:16,880 --> 00:04:22,960 Speaker 1: a call from a friend named Sam Aldman a few 62 00:04:23,040 --> 00:04:25,640 Speaker 1: years ago, a couple three years ago at this point, 63 00:04:25,960 --> 00:04:27,800 Speaker 1: and what I went to go see him in his 64 00:04:27,839 --> 00:04:29,560 Speaker 1: office in San Francisco on one of my trips there 65 00:04:29,600 --> 00:04:30,920 Speaker 1: because I'm just nosy. I don't want to see what 66 00:04:30,960 --> 00:04:33,520 Speaker 1: he was doing. And he opened up his laptop and 67 00:04:33,560 --> 00:04:37,080 Speaker 1: he showed me a prototype for something that really at 68 00:04:37,120 --> 00:04:39,599 Speaker 1: that point was not in the market in the marketplace, 69 00:04:39,600 --> 00:04:42,520 Speaker 1: I don't even think it was released, and it was 70 00:04:42,560 --> 00:04:46,560 Speaker 1: what we now call chat GPT, It's open AI. I 71 00:04:46,560 --> 00:04:49,240 Speaker 1: didn't really know what I was seeing at that moment. 72 00:04:49,240 --> 00:04:52,320 Speaker 1: I just knew it was transformational. He asked me my advice. 73 00:04:52,320 --> 00:04:55,520 Speaker 1: I said, you make sure that you introduced his technology. Well, 74 00:04:55,520 --> 00:04:58,040 Speaker 1: first of all, thanks for asking me for my advice. Sam, 75 00:04:58,400 --> 00:05:01,120 Speaker 1: Most people don't who are geniuses makes think they know everything. 76 00:05:01,680 --> 00:05:04,239 Speaker 1: But he knows that the smartest people in the world 77 00:05:04,279 --> 00:05:06,440 Speaker 1: can be so hyper focused. You can have a blind spot, 78 00:05:06,720 --> 00:05:08,479 Speaker 1: and a lot of tech leaders have a blind spot 79 00:05:08,520 --> 00:05:10,280 Speaker 1: called people. He didn't want to be one of those 80 00:05:10,320 --> 00:05:12,039 Speaker 1: people who had a blind spot. What should I do? 81 00:05:12,080 --> 00:05:13,960 Speaker 1: Make sure you're talking to underserved communities when you go 82 00:05:13,960 --> 00:05:17,200 Speaker 1: on tour to talk this into the country in the world. 83 00:05:17,320 --> 00:05:19,159 Speaker 1: Go make sure you go in the underserved communities, John, 84 00:05:19,200 --> 00:05:21,720 Speaker 1: when you do it with me, absolutely get a call 85 00:05:21,720 --> 00:05:23,440 Speaker 1: from his office. Sorry, Sam won't be to do the 86 00:05:23,520 --> 00:05:26,360 Speaker 1: underserved tour. He's international right now. I text Sam directly. 87 00:05:26,400 --> 00:05:29,360 Speaker 1: I'm like, uh no, brother, you're not doing it for me. 88 00:05:29,560 --> 00:05:31,880 Speaker 1: You do it for yourself. You need to make sure 89 00:05:31,960 --> 00:05:34,720 Speaker 1: you go to these communities. He said, Let me e right, 90 00:05:34,800 --> 00:05:37,560 Speaker 1: let me think about it. I know. Weeks passed by, 91 00:05:37,680 --> 00:05:39,440 Speaker 1: and then I get a call from him out of 92 00:05:39,480 --> 00:05:40,840 Speaker 1: the blue in the middle of the night, I think 93 00:05:40,880 --> 00:05:43,840 Speaker 1: it was. It was I think close to midnight. I 94 00:05:43,839 --> 00:05:46,120 Speaker 1: remember I made a call for that too the East 95 00:05:46,160 --> 00:05:48,960 Speaker 1: Coast to the president of Clarktland University, doctor George French, 96 00:05:49,000 --> 00:05:50,719 Speaker 1: and it was probably two in the morning there, so 97 00:05:50,920 --> 00:05:54,120 Speaker 1: it was eleven, maybe close to midnight. I get this call, 98 00:05:54,200 --> 00:05:57,320 Speaker 1: Hey man, I got to go to the White House 99 00:05:57,320 --> 00:06:00,320 Speaker 1: to meet with President Biden on my work, et cetera. 100 00:06:01,040 --> 00:06:03,800 Speaker 1: You know, two three days I think it was can 101 00:06:03,839 --> 00:06:05,839 Speaker 1: I come to you? Think I can come to Atlanta 102 00:06:05,920 --> 00:06:09,320 Speaker 1: after that? And uh, have you host a meeting to 103 00:06:10,000 --> 00:06:13,159 Speaker 1: have this conversation. The only thing I had to say 104 00:06:13,240 --> 00:06:16,200 Speaker 1: was yes, with no time and no idea I was 105 00:06:16,240 --> 00:06:18,479 Speaker 1: going to do it. I hung the phone from him 106 00:06:18,520 --> 00:06:20,880 Speaker 1: and called doctor George French as clock Atlanta. H'm on 107 00:06:20,880 --> 00:06:25,559 Speaker 1: the board. Doctor French said absolutely, And three days later 108 00:06:25,640 --> 00:06:28,800 Speaker 1: we had Sam Autman from the White House to our 109 00:06:28,800 --> 00:06:32,200 Speaker 1: house in Atlanta for this conversation. The King Families in 110 00:06:32,240 --> 00:06:36,039 Speaker 1: the house. My friend, doctor Bernice King is actually on 111 00:06:36,080 --> 00:06:38,240 Speaker 1: the board of AI Ethics Council. Now I'll get to 112 00:06:38,240 --> 00:06:40,520 Speaker 1: that in a second. The King families in the house, 113 00:06:40,520 --> 00:06:44,279 Speaker 1: young families in the house, all the HBCU presidents, more House, Spelman, 114 00:06:44,880 --> 00:06:47,680 Speaker 1: uh doctor Thomas and then doctor Helen Gale, who was 115 00:06:47,720 --> 00:06:50,080 Speaker 1: president of Spelman at that time, and doctor Thomas more 116 00:06:50,120 --> 00:06:55,680 Speaker 1: House and heroes and she ros everywhere. And I was terrified, 117 00:06:56,680 --> 00:07:02,200 Speaker 1: absolutely terrified about what I was hearing. And Sam, are 118 00:07:02,240 --> 00:07:06,719 Speaker 1: there any unintended consequences that can come from this answer? Yes, 119 00:07:07,560 --> 00:07:09,920 Speaker 1: I know that we'll probably cure cancer within ten years, 120 00:07:10,920 --> 00:07:12,960 Speaker 1: but something bad may also happen, and I can't tell 121 00:07:12,960 --> 00:07:17,240 Speaker 1: you where that is. And I respected it as honesty, 122 00:07:17,280 --> 00:07:19,480 Speaker 1: and so I knew at that point that I had 123 00:07:19,520 --> 00:07:23,720 Speaker 1: to change my agenda to it wasn't replacing financial literacy. 124 00:07:23,720 --> 00:07:26,600 Speaker 1: I had to move it over to include what I 125 00:07:26,680 --> 00:07:30,760 Speaker 1: now call AI literacy literacy Artificial intelligence. Financial literacy is 126 00:07:30,760 --> 00:07:34,000 Speaker 1: a civil rights issue of this generation, and AI literacy 127 00:07:34,040 --> 00:07:38,480 Speaker 1: as a sylvi rights issue of this generation, moving us 128 00:07:38,480 --> 00:07:41,600 Speaker 1: from the streets to the suites. And so soon after 129 00:07:41,640 --> 00:07:45,600 Speaker 1: that Sam came to the Hope Lebal Forum. We announced 130 00:07:45,600 --> 00:07:49,360 Speaker 1: the Artificial AI Ethics Council on stage together, and within 131 00:07:49,360 --> 00:07:52,120 Speaker 1: a year we had a plan that we had a 132 00:07:52,160 --> 00:07:55,040 Speaker 1: board put together a lot of heroes and she roes 133 00:07:55,080 --> 00:07:57,800 Speaker 1: that you respect on that board. I don't want to 134 00:07:57,800 --> 00:08:00,440 Speaker 1: take up valuable time here going through a resume a list, 135 00:08:01,120 --> 00:08:03,600 Speaker 1: but it's a lot of incredible leaders on that board. 136 00:08:04,000 --> 00:08:07,080 Speaker 1: And then we just announced something powerful with Georgia State 137 00:08:07,200 --> 00:08:10,720 Speaker 1: University and the mayor here at Andrew Dickens, called the 138 00:08:10,800 --> 00:08:16,600 Speaker 1: AI l P three AI Literacy Project here in Atlanta. 139 00:08:17,120 --> 00:08:19,680 Speaker 1: Now all this you're saying, Okay, John, this is a 140 00:08:19,720 --> 00:08:21,760 Speaker 1: nice story, but you told me this is going to 141 00:08:21,880 --> 00:08:26,080 Speaker 1: change everything. I don't see it yet. Here you go 142 00:08:27,520 --> 00:08:33,520 Speaker 1: to lenses the anticipated pain, job losses and societal disruption. 143 00:08:36,120 --> 00:08:42,000 Speaker 1: Number two, the opportunity new industries and jobs emerging in 144 00:08:42,040 --> 00:08:44,960 Speaker 1: the AI driven economy. That's why, by the way, we've 145 00:08:44,960 --> 00:08:48,199 Speaker 1: done AI LP three with Georgia State University with Morehouse 146 00:08:48,520 --> 00:08:55,160 Speaker 1: with Clark Atlanta Spellman the Mayor's office here, because we're 147 00:08:55,160 --> 00:08:56,880 Speaker 1: going to train up a whole new generation of kids 148 00:08:56,920 --> 00:08:59,439 Speaker 1: from kindergarten with a bank account in kindergarten all the 149 00:08:59,440 --> 00:09:02,240 Speaker 1: way up through through high school, middle school, high school 150 00:09:02,280 --> 00:09:05,520 Speaker 1: and college in Atlanta as an ecosystem to create a 151 00:09:05,559 --> 00:09:08,080 Speaker 1: farm club for the future and create our own jobs 152 00:09:08,080 --> 00:09:09,880 Speaker 1: on wate sol to disrupt you out of a job, 153 00:09:09,960 --> 00:09:15,080 Speaker 1: destroy it. Let's create our own jobs and anticipate the 154 00:09:15,120 --> 00:09:19,200 Speaker 1: pain and replace it with promise. Now, let's now get 155 00:09:19,240 --> 00:09:22,120 Speaker 1: to the pain and why you have to listen to 156 00:09:22,160 --> 00:09:23,760 Speaker 1: this while you tell all your friends that listen to this. 157 00:09:23,920 --> 00:09:26,720 Speaker 1: You can go right to minute ten if you like, 158 00:09:26,920 --> 00:09:29,400 Speaker 1: and cut to the chase if that's if you have 159 00:09:29,520 --> 00:09:35,120 Speaker 1: limited time. Here are industries that will be absolutely disrupted Manufacturing. 160 00:09:36,440 --> 00:09:41,120 Speaker 1: AI driven robotics are going to replace roles on assembly lines, 161 00:09:41,840 --> 00:09:47,480 Speaker 1: including automobile production. An example of this is factories utilizing 162 00:09:47,600 --> 00:09:54,560 Speaker 1: robots for welding and quality control. Haven't you seen the 163 00:09:54,640 --> 00:10:01,280 Speaker 1: Amazon drones? Haven't you seen these delivery bots that have 164 00:10:01,360 --> 00:10:05,280 Speaker 1: wheels on it that robots that are delivering pizzas and 165 00:10:05,320 --> 00:10:09,000 Speaker 1: things like that. And packages. Haven't you seen, I mean, really, 166 00:10:10,440 --> 00:10:14,160 Speaker 1: drones are really preambles to this. By the way, this 167 00:10:14,200 --> 00:10:15,839 Speaker 1: is nothing sneaking up on you. By the way, right 168 00:10:15,840 --> 00:10:20,440 Speaker 1: in front of you, haven't you seen robots doing welding 169 00:10:21,040 --> 00:10:24,520 Speaker 1: in factory tours as you're looking as your TV set. 170 00:10:24,720 --> 00:10:29,080 Speaker 1: That used to be people, Those used to be manual jobs. 171 00:10:29,120 --> 00:10:33,679 Speaker 1: Now those jobs are automated. Okay, so manufacturing is going 172 00:10:33,720 --> 00:10:35,959 Speaker 1: to be completely disrupted. These by the way, these are 173 00:10:35,960 --> 00:10:39,439 Speaker 1: industries now where you need a high school education. Needed 174 00:10:39,480 --> 00:10:43,439 Speaker 1: a high school education, that's gone. Now if you have 175 00:10:43,480 --> 00:10:46,040 Speaker 1: a high school education and no hustle and no intention 176 00:10:46,200 --> 00:10:48,800 Speaker 1: in getting a better education or skills for the future, 177 00:10:48,880 --> 00:10:52,160 Speaker 1: you're toast. It's not lover hate anymore. It's radical indifference. 178 00:10:52,160 --> 00:10:53,760 Speaker 1: Nobody's going to care if about you, to hate you 179 00:10:54,720 --> 00:10:56,719 Speaker 1: or to care for you. And I don't care whether 180 00:10:56,760 --> 00:10:58,440 Speaker 1: your black, white, red, brown, or yellow. You're not going 181 00:10:58,480 --> 00:11:00,280 Speaker 1: to see any more green. So the color is not 182 00:11:00,400 --> 00:11:03,120 Speaker 1: again the color. This is not race based, right, This 183 00:11:03,240 --> 00:11:05,959 Speaker 1: is going to be talent based and opportunity based, and 184 00:11:06,040 --> 00:11:09,840 Speaker 1: understanding based and hustle based. And in some ways people 185 00:11:10,600 --> 00:11:12,640 Speaker 1: who are underserved are going to be better positions. We've 186 00:11:12,640 --> 00:11:14,280 Speaker 1: been doing so much with so little, so long, we 187 00:11:14,320 --> 00:11:16,600 Speaker 1: can almost do anything with nothing, and so we got 188 00:11:16,600 --> 00:11:19,160 Speaker 1: a hustle on ten when you know, if we wake 189 00:11:19,240 --> 00:11:21,920 Speaker 1: up paranoid, so we might be able to pivot here, 190 00:11:22,240 --> 00:11:24,360 Speaker 1: particularly in the creative spaces, and make it something out 191 00:11:24,360 --> 00:11:26,160 Speaker 1: of nothing, in a rainbow out of the storm, because 192 00:11:26,160 --> 00:11:28,640 Speaker 1: you cannot have a rainbow without a storm. First, Can 193 00:11:28,640 --> 00:11:31,720 Speaker 1: I get an a man? Yes, I'm preaching. Here's the 194 00:11:31,720 --> 00:11:37,040 Speaker 1: industry number two that will get disrupted, transportation and logistics, 195 00:11:38,400 --> 00:11:42,800 Speaker 1: Autonomous vehicles and AI optimize logistical systems. Let me get 196 00:11:42,800 --> 00:11:48,000 Speaker 1: an example of this, self driving trucks and automated warehouse 197 00:11:48,120 --> 00:11:54,360 Speaker 1: management systems. Now, you've already seen self driving cars being tested. 198 00:11:54,400 --> 00:11:59,880 Speaker 1: You've already seen self driving basically taxis in San Francisco. 199 00:11:59,880 --> 00:12:03,880 Speaker 1: You've seen these things on television. This stuff's real. I 200 00:12:04,040 --> 00:12:07,120 Speaker 1: was just at CES conference in Las Vegas as a 201 00:12:07,160 --> 00:12:09,440 Speaker 1: guest of Delta Airlines, my friend ed Bastian, and the 202 00:12:09,480 --> 00:12:13,000 Speaker 1: stuff that they have right now is mind blowing and 203 00:12:13,120 --> 00:12:19,720 Speaker 1: mind bending around automation of automobiles and the transportation industry. 204 00:12:19,840 --> 00:12:25,920 Speaker 1: Truckers and Uber drivers and Uber you know, all the 205 00:12:27,720 --> 00:12:33,439 Speaker 1: driving services, the delivery services, the transit, the major transportation services. 206 00:12:33,760 --> 00:12:37,040 Speaker 1: That's one of the top ten employment sectors in the country. 207 00:12:37,240 --> 00:12:40,280 Speaker 1: Poof gone once again, you can do with a high 208 00:12:40,320 --> 00:12:43,760 Speaker 1: school education and a minor certification. Now that job is 209 00:12:43,800 --> 00:12:45,760 Speaker 1: not going to just completely go away, but it's going 210 00:12:45,800 --> 00:12:48,200 Speaker 1: to change how that it's not gonna You're not gonna 211 00:12:48,200 --> 00:12:50,599 Speaker 1: be driving the car. You're going to be maybe overseeing 212 00:12:50,800 --> 00:12:54,160 Speaker 1: a car being driven, the overseeing the technology. Getting ahead 213 00:12:54,160 --> 00:12:58,320 Speaker 1: of myself and write the stuff down. Here's a big one. 214 00:12:58,480 --> 00:13:00,360 Speaker 1: If you're black and brown, I want you to look 215 00:13:00,400 --> 00:13:01,800 Speaker 1: to the left and looking to the right of you 216 00:13:01,960 --> 00:13:05,120 Speaker 1: and see somebody who will not have a job, because 217 00:13:05,120 --> 00:13:08,440 Speaker 1: the likelihood that somebody that we know is employed in 218 00:13:08,440 --> 00:13:12,720 Speaker 1: this sector that I'm about to mention is everything retail 219 00:13:13,720 --> 00:13:20,000 Speaker 1: and customer service. So AI managing inventory, self checkout systems, 220 00:13:20,040 --> 00:13:26,560 Speaker 1: and customer interactions is going to be absolutely complete. The 221 00:13:26,600 --> 00:13:29,440 Speaker 1: takeover is going to be complete. Think about an Amazon 222 00:13:29,480 --> 00:13:31,640 Speaker 1: ghost store eliminating the need for a cashier. You know 223 00:13:31,640 --> 00:13:34,320 Speaker 1: what an Amazon ghost story is? Okay, I did a 224 00:13:34,400 --> 00:13:38,000 Speaker 1: video on this. Go on my look on my Instagram 225 00:13:38,040 --> 00:13:41,600 Speaker 1: page and look at the video I did about five 226 00:13:41,640 --> 00:13:45,240 Speaker 1: months six months ago going through airports and there was 227 00:13:45,280 --> 00:13:48,040 Speaker 1: an Amazon ghost shop that I featured, but you need 228 00:13:48,080 --> 00:13:50,200 Speaker 1: to go that far. I want you to think about 229 00:13:50,240 --> 00:13:53,120 Speaker 1: when you went to CBS recently or you went to 230 00:13:53,200 --> 00:14:00,800 Speaker 1: Walgreens recently. In the video version of this podcast, I'm 231 00:14:00,800 --> 00:14:04,719 Speaker 1: going to drop in some photos during the video presentation 232 00:14:05,360 --> 00:14:08,040 Speaker 1: of me in different places, most recently in Las Vegas, 233 00:14:08,240 --> 00:14:13,360 Speaker 1: where it used to be one soul checkout self checkout 234 00:14:13,400 --> 00:14:17,400 Speaker 1: situation where you scanned yourself. This last place I went 235 00:14:17,440 --> 00:14:21,880 Speaker 1: to in Las Vegas two weeks ago, one hundred percent 236 00:14:21,920 --> 00:14:26,040 Speaker 1: of the checkout was it was ten checkout stations or 237 00:14:26,200 --> 00:14:31,160 Speaker 1: self checkouts, with one guy overseeing the ten to make 238 00:14:31,200 --> 00:14:34,520 Speaker 1: sure the systems didn't break down, and nobody stole anything. 239 00:14:36,120 --> 00:14:38,320 Speaker 1: That store had a total of I believe I saw 240 00:14:38,360 --> 00:14:40,760 Speaker 1: two or three employees. This was a complete store of 241 00:14:40,800 --> 00:14:44,040 Speaker 1: Walgreens or CVS. Can remember which one that store used 242 00:14:44,040 --> 00:14:46,920 Speaker 1: to have. I don't know eight people. Okay on the 243 00:14:46,960 --> 00:14:52,880 Speaker 1: shift gone poof right, go to a grocery store and well, 244 00:14:52,920 --> 00:14:56,480 Speaker 1: I was in McDonald's. Mean, I walked past McDonald's in 245 00:14:57,360 --> 00:15:01,960 Speaker 1: where was I? I was in Seattle Layover and I 246 00:15:02,040 --> 00:15:05,080 Speaker 1: walked past a McDonald's. I'm not picking at McDonald's. This 247 00:15:05,120 --> 00:15:08,480 Speaker 1: is everybody and there literally was twelve. You got gonna 248 00:15:08,480 --> 00:15:12,600 Speaker 1: show a picture of this. Twelve checkouts, self checkouts, and 249 00:15:12,680 --> 00:15:15,640 Speaker 1: there was a place where you picked up your food 250 00:15:15,200 --> 00:15:18,680 Speaker 1: and there were robots on the other side of the 251 00:15:19,200 --> 00:15:21,720 Speaker 1: of the customer service person talking to you at the 252 00:15:21,760 --> 00:15:24,680 Speaker 1: counter handing you your food. That was happening to helping 253 00:15:24,720 --> 00:15:28,360 Speaker 1: us prepare the food. How many jobs do you think 254 00:15:28,360 --> 00:15:31,760 Speaker 1: that represented at McDonald's before they automated it. There's a 255 00:15:32,160 --> 00:15:35,480 Speaker 1: there's a restaurant in I believe it's San Francisco or 256 00:15:35,480 --> 00:15:40,720 Speaker 1: Oakland that's one hundred percent robotic, one hundred percent no employees, 257 00:15:41,360 --> 00:15:44,600 Speaker 1: and I'm told the food's pretty good. It's making hamburgers 258 00:15:44,600 --> 00:15:49,840 Speaker 1: an American hamburger shop. Check that out on my Instagram 259 00:15:49,880 --> 00:15:54,320 Speaker 1: page as well. Grocery store. Used to go to a 260 00:15:54,360 --> 00:15:58,520 Speaker 1: grocery store and there were twelve checkout counters and they're 261 00:15:58,680 --> 00:16:00,760 Speaker 1: the nice person was talking to you and it was 262 00:16:00,760 --> 00:16:03,400 Speaker 1: a line and all the stuff and you know, she 263 00:16:03,480 --> 00:16:05,600 Speaker 1: bagged it for you or he bagged it for you. 264 00:16:05,600 --> 00:16:07,920 Speaker 1: You go to a grocery store, now, just just watch 265 00:16:08,000 --> 00:16:10,040 Speaker 1: this now and listen to this and think about this. 266 00:16:10,720 --> 00:16:14,080 Speaker 1: There's twelve checkout counters. All of them are closed except 267 00:16:14,080 --> 00:16:18,440 Speaker 1: one maybe two and where's the line now? In self checkout? 268 00:16:18,760 --> 00:16:23,320 Speaker 1: They just it's almost like positive hurting. You know, you 269 00:16:23,840 --> 00:16:26,480 Speaker 1: put a frog in you drop a frog in the 270 00:16:26,720 --> 00:16:29,400 Speaker 1: pot of hot water, it jumps out. But if you 271 00:16:29,440 --> 00:16:33,760 Speaker 1: put that frog in some water and slowly just increase 272 00:16:33,800 --> 00:16:39,080 Speaker 1: the temperature, frog never realizes that it's cooking. I don't 273 00:16:39,120 --> 00:16:41,960 Speaker 1: want you to cook. I want you to learn how 274 00:16:42,040 --> 00:16:47,440 Speaker 1: to cook. And that means that before somebody's zeros, nobody 275 00:16:47,480 --> 00:16:50,320 Speaker 1: wants to deal with the girl with the attitude right 276 00:16:50,480 --> 00:16:53,680 Speaker 1: the counter? What you want? I want my food? What 277 00:16:54,400 --> 00:16:56,560 Speaker 1: can I do for you? I'm busy, I'm on the 278 00:16:56,560 --> 00:17:02,720 Speaker 1: phone with my boyfriend. Was it a do it? The attitude? Right? Nobody, 279 00:17:03,720 --> 00:17:07,119 Speaker 1: robots and AI don't complain, don't ask for breaks, they 280 00:17:07,119 --> 00:17:09,840 Speaker 1: don't ask for time off, don't ask for raises. Right, 281 00:17:10,480 --> 00:17:13,520 Speaker 1: they don't get tired, they don't get attitude right. It's 282 00:17:13,560 --> 00:17:29,360 Speaker 1: consistent and I'm joking, but I'm serious. This is completely serious. 283 00:17:29,720 --> 00:17:33,040 Speaker 1: All those jobs poof gone. That's a high school education 284 00:17:33,760 --> 00:17:37,960 Speaker 1: and no soft skill requirements and very little hard skill requirements. 285 00:17:38,119 --> 00:17:41,479 Speaker 1: Right is in You know you don't need a degree 286 00:17:41,640 --> 00:17:46,879 Speaker 1: or a certification to do it? Okay? That job gone? 287 00:17:48,880 --> 00:17:53,399 Speaker 1: Number four Food service and hospitality. I've touched on this 288 00:17:53,400 --> 00:17:55,440 Speaker 1: a little bit, but let me be very specific. Robotic 289 00:17:55,520 --> 00:18:01,359 Speaker 1: kitchens and self service chaos. Think about Flippy the burger 290 00:18:01,400 --> 00:18:07,000 Speaker 1: flipping robot. The AI driven reservation system right you may 291 00:18:07,040 --> 00:18:09,359 Speaker 1: be calling a reservation system right now and thinking you're 292 00:18:09,359 --> 00:18:15,720 Speaker 1: talking to a human. It might be artificial intelligence. This 293 00:18:15,800 --> 00:18:18,159 Speaker 1: is just mind blowing, how transformating to think about this 294 00:18:18,240 --> 00:18:20,520 Speaker 1: AILP Three we're gonna be doing here in Atlanta. We're 295 00:18:20,520 --> 00:18:23,399 Speaker 1: going to literally go through air every industry. We have 296 00:18:23,520 --> 00:18:26,840 Speaker 1: these kids AI in sports, not just sports, AI in football, 297 00:18:26,920 --> 00:18:31,639 Speaker 1: AI in basketball, AI in baseball, AI and soccer music, 298 00:18:31,720 --> 00:18:36,440 Speaker 1: AI in rock music. So I mean AI and engineering, 299 00:18:36,600 --> 00:18:41,320 Speaker 1: mechanical engineering, AI and automotive, AI in healthcare, AI and 300 00:18:41,359 --> 00:18:44,959 Speaker 1: beauty A Why because every sector is going to get 301 00:18:44,960 --> 00:18:50,480 Speaker 1: disrupted AI and medical care, healthcare, elder care. And have 302 00:18:50,600 --> 00:18:53,879 Speaker 1: these kids basically help us imagine jobs in the future 303 00:18:53,960 --> 00:18:56,320 Speaker 1: which are going to replace the jobs being produced being 304 00:18:56,600 --> 00:19:01,320 Speaker 1: decimated right now. Let me give you again, I'm not sorry. 305 00:19:01,359 --> 00:19:03,840 Speaker 1: I apologized for not completing this list yet. I'll get 306 00:19:03,880 --> 00:19:05,919 Speaker 1: back to it, but this context is more important than 307 00:19:05,960 --> 00:19:08,120 Speaker 1: the list. I need you to focus on the list. 308 00:19:08,160 --> 00:19:10,239 Speaker 1: I'm gonna give you good context. So it's scared you. 309 00:19:10,280 --> 00:19:12,800 Speaker 1: I scared you straight. Remember other kids went there. We 310 00:19:12,840 --> 00:19:16,040 Speaker 1: sent the services. We used to send kids to prison 311 00:19:16,080 --> 00:19:18,760 Speaker 1: on like a day visit to scare them straight straight, 312 00:19:18,800 --> 00:19:20,800 Speaker 1: so they never ended up in prison. Those kids were 313 00:19:20,840 --> 00:19:23,199 Speaker 1: like I do. I remember I got scared straight. I 314 00:19:23,200 --> 00:19:25,000 Speaker 1: stole I saw some crayons or something when I was 315 00:19:25,080 --> 00:19:27,400 Speaker 1: nine or ten years old, eight nine, ten years old 316 00:19:27,400 --> 00:19:30,440 Speaker 1: and Compton and the guys it was thrifty drug store 317 00:19:30,480 --> 00:19:33,040 Speaker 1: back then. The guys were looking from above. Pulled me 318 00:19:33,119 --> 00:19:37,560 Speaker 1: upstairs and closed the door and showed me some cuff links, 319 00:19:37,600 --> 00:19:41,439 Speaker 1: some cufflinks, showed me some handcuffs and said they're going 320 00:19:41,480 --> 00:19:42,639 Speaker 1: to call the police. And I was gonna get it. 321 00:19:42,680 --> 00:19:44,920 Speaker 1: I was going to jail. I mean, scared the jeebers 322 00:19:44,960 --> 00:19:48,600 Speaker 1: out of me. If if if I'm be truthful them, 323 00:19:48,640 --> 00:19:50,960 Speaker 1: I'd have wet my pants. They let me out of there, 324 00:19:51,000 --> 00:19:53,120 Speaker 1: and I swore I was never gonna steal anything again 325 00:19:53,160 --> 00:19:55,480 Speaker 1: in my life. And I never did. And those guys 326 00:19:55,520 --> 00:19:58,760 Speaker 1: were scared. But gi me saved me from you know, uh, 327 00:19:59,400 --> 00:20:01,800 Speaker 1: from messing up my whole world. Well, I'm trying to 328 00:20:01,840 --> 00:20:05,119 Speaker 1: scare you straight, so you create a new world. So 329 00:20:06,080 --> 00:20:10,880 Speaker 1: from eighteen fifty to nineteen ten, the most valuable thing 330 00:20:11,119 --> 00:20:14,760 Speaker 1: in the United States was a horse. Horses where everything 331 00:20:14,880 --> 00:20:23,240 Speaker 1: and everywhere, transportation, agriculture, automobile, that version of an automobile, horsepower, 332 00:20:23,280 --> 00:20:32,240 Speaker 1: that's where that came from. Wealth, class structure, machinery, harrises, 333 00:20:32,240 --> 00:20:33,679 Speaker 1: where everything and what we were one out of ten 334 00:20:33,840 --> 00:20:37,360 Speaker 1: jobs in America back then a faeririre. Who's somebody who 335 00:20:37,400 --> 00:20:43,399 Speaker 1: did the change the hoofs on a horse? So I 336 00:20:43,400 --> 00:20:45,120 Speaker 1: don't know, forty to fifty per cent of the entire 337 00:20:45,200 --> 00:20:50,760 Speaker 1: economy was horse based from eighteen fifty. Why does Atlanta 338 00:20:50,840 --> 00:20:52,760 Speaker 1: look the way it does? Well, you can't get out 339 00:20:52,800 --> 00:20:56,879 Speaker 1: the freeway and take a detour because everything turns left right. 340 00:20:56,960 --> 00:20:59,879 Speaker 1: You can't take a straight detour. Not a criticism like 341 00:21:00,000 --> 00:21:02,040 Speaker 1: New York City. Why is it like that? Because there 342 00:21:02,119 --> 00:21:05,359 Speaker 1: was based on horse paths. The horses used to to 343 00:21:06,080 --> 00:21:08,840 Speaker 1: you know, you took a horse, not over a hill, 344 00:21:08,880 --> 00:21:11,520 Speaker 1: around a hill. Well, what happens in Atlanta now you 345 00:21:11,640 --> 00:21:13,520 Speaker 1: drive around a hill on a road because they just 346 00:21:13,640 --> 00:21:16,240 Speaker 1: pave the roads that or you didn't know that you 347 00:21:16,520 --> 00:21:20,080 Speaker 1: were originally horse paths. But anyway, horses were everywhere everything. 348 00:21:21,560 --> 00:21:24,080 Speaker 1: Then the automobile hit in nineteen oh one, and there 349 00:21:24,160 --> 00:21:26,399 Speaker 1: was one hundred automobile manufacturers. Most of them went out 350 00:21:26,400 --> 00:21:28,600 Speaker 1: of business. Henry Ford and a few others survived. Henry 351 00:21:28,640 --> 00:21:31,880 Speaker 1: Ford created the modern middle class by paying workers enough 352 00:21:31,920 --> 00:21:34,800 Speaker 1: to build the automobiles to buy the automobiles that they 353 00:21:34,840 --> 00:21:37,440 Speaker 1: were building. Boom would create in the middle class, and 354 00:21:37,560 --> 00:21:40,840 Speaker 1: within ten years horses were no more valuable than glue. 355 00:21:43,359 --> 00:21:46,399 Speaker 1: Went from the most valuable thing on the planet to invisible, 356 00:21:46,680 --> 00:21:48,800 Speaker 1: gone poof and the most valuable thing you could do 357 00:21:48,880 --> 00:21:51,359 Speaker 1: with horses. And I apologize for horse lovers. I'm not 358 00:21:52,040 --> 00:21:54,840 Speaker 1: I didn't do this, I'm just reporting this. By nineteen ten, 359 00:21:55,119 --> 00:21:56,879 Speaker 1: the most valuable thing you could do an industry and 360 00:21:56,960 --> 00:22:01,159 Speaker 1: business other than just having a horse as a hobby 361 00:22:01,320 --> 00:22:04,240 Speaker 1: hobby horse, and the pun intendant was glue. So it 362 00:22:04,320 --> 00:22:08,320 Speaker 1: went from everything to nothing. Think about Seers being taken 363 00:22:08,359 --> 00:22:11,080 Speaker 1: out by Amazon, but just times one hundred. Think about 364 00:22:11,840 --> 00:22:16,000 Speaker 1: Blockbuster being taken out by Netflix, but just time one hundred. Right, Well, 365 00:22:16,280 --> 00:22:18,880 Speaker 1: we're going to go from that took sixty years, from 366 00:22:18,960 --> 00:22:23,200 Speaker 1: eighteen fifty to nineteen ten. We're talking about from two 367 00:22:23,280 --> 00:22:28,399 Speaker 1: thousand and four to twenty thirty six years, not sixty 368 00:22:28,480 --> 00:22:33,320 Speaker 1: years poof everything's going to change top to bottom. And 369 00:22:33,400 --> 00:22:35,080 Speaker 1: if you're on at the table, you're on the menu. 370 00:22:36,359 --> 00:22:39,720 Speaker 1: I want you at the table. Here's sector number five, 371 00:22:40,520 --> 00:22:42,920 Speaker 1: Finance and Banking, one of the sectors that I'm in. 372 00:22:43,600 --> 00:22:49,240 Speaker 1: Underwriting loans will be done by artificial intelligence. Managing portfolios 373 00:22:49,359 --> 00:22:54,280 Speaker 1: and detecting fraud will be done by artificial intelligence. All 374 00:22:54,359 --> 00:22:57,359 Speaker 1: the documentation and all these papers that get pushed around 375 00:22:57,440 --> 00:22:59,240 Speaker 1: and we sign here and do this and do that, 376 00:22:59,359 --> 00:23:01,520 Speaker 1: which is can be messed up with human error, and 377 00:23:01,880 --> 00:23:07,080 Speaker 1: determine risk and assets for a generation and or liability 378 00:23:07,119 --> 00:23:09,840 Speaker 1: for the bank or the or the lawyer doing the paperwork, whatever, 379 00:23:10,160 --> 00:23:12,200 Speaker 1: All that's going to be all that risk is gonna 380 00:23:12,200 --> 00:23:16,320 Speaker 1: be be squeezed out of the system. An example of 381 00:23:16,359 --> 00:23:20,880 Speaker 1: this is robo advisors like wealth Front and Betterment. These 382 00:23:20,920 --> 00:23:25,840 Speaker 1: are these are robo advisors AI assisted advisors in the 383 00:23:25,960 --> 00:23:30,600 Speaker 1: Wealth and Financial UH planning space Wealth managed and Financial 384 00:23:30,640 --> 00:23:35,760 Speaker 1: Planning space. Number six Legal services. So I'm not just 385 00:23:35,800 --> 00:23:39,320 Speaker 1: talking about poor people's jobs. These people with advanced education, right, 386 00:23:39,400 --> 00:23:42,000 Speaker 1: These jobs are going to go away or be transformed. 387 00:23:42,320 --> 00:23:47,960 Speaker 1: Finance and banking, UH, legal services, AI drafting contracts, conducting research, 388 00:23:48,480 --> 00:23:53,200 Speaker 1: and reviewing documents, think about UH tools like do not 389 00:23:53,560 --> 00:24:00,640 Speaker 1: pay in UH in loggings. It's a complete game changer accounting. 390 00:24:00,680 --> 00:24:02,520 Speaker 1: This is a bonus for you on this one, accounting. 391 00:24:02,560 --> 00:24:04,359 Speaker 1: I think you know, half of all accountants are going 392 00:24:04,440 --> 00:24:10,320 Speaker 1: to be, you know, challenged to adapt what they do. 393 00:24:10,520 --> 00:24:15,440 Speaker 1: Either they adapt with by taking by empowering themselves to 394 00:24:15,520 --> 00:24:18,600 Speaker 1: control AI, although be replaced by AI because too much 395 00:24:18,600 --> 00:24:22,080 Speaker 1: of that can be hello automated. Anything can be automated 396 00:24:22,560 --> 00:24:25,040 Speaker 1: is completely at risk. Again, this is a great level 397 00:24:25,080 --> 00:24:28,200 Speaker 1: of whether you're whether you're black and black or white 398 00:24:28,240 --> 00:24:32,040 Speaker 1: or rich or poorie, this doesn't care. Nine black folks 399 00:24:32,040 --> 00:24:33,800 Speaker 1: don't know thinking about AI, and nine percent of white 400 00:24:33,840 --> 00:24:36,400 Speaker 1: folks don't know think about AI either. It's like AI 401 00:24:36,560 --> 00:24:38,600 Speaker 1: or dummies. And I was the first dummy. And I'm 402 00:24:38,640 --> 00:24:40,879 Speaker 1: not calling you a name. It's what we don't know 403 00:24:40,960 --> 00:24:42,480 Speaker 1: that we don't know. This killing is what we think 404 00:24:42,520 --> 00:24:45,120 Speaker 1: we know. It's time to learn, baby. I'm Quincy Jones 405 00:24:45,160 --> 00:24:47,080 Speaker 1: Scott Risus. So how'd you get so smart? I'm just 406 00:24:47,320 --> 00:24:49,719 Speaker 1: nosy as hell, John. I want to know everything about everything. 407 00:24:49,720 --> 00:24:55,480 Speaker 1: I want you to be nosy about AI. Number seven Healthcare, Administration, 408 00:24:56,240 --> 00:25:02,000 Speaker 1: Automation and billing, scheduling, and diagnosing. Hello, what do you 409 00:25:02,119 --> 00:25:05,359 Speaker 1: see black and brown people? Hello? And women do? What 410 00:25:05,560 --> 00:25:09,120 Speaker 1: jobs do you think we're doing in healthcare administration? Right? 411 00:25:09,320 --> 00:25:15,040 Speaker 1: Think about AI powered diagnostics systems like IBM Watson computer. 412 00:25:15,359 --> 00:25:21,680 Speaker 1: We'll do the whole job. Number eight agriculture autonomous tractors 413 00:25:22,400 --> 00:25:25,639 Speaker 1: and drones monitoring crops you don't need. Doesn't take a 414 00:25:25,680 --> 00:25:28,840 Speaker 1: lot of imagination even to think about what I'm talking about. 415 00:25:28,880 --> 00:25:31,560 Speaker 1: You can see it in your mind's eye, by the 416 00:25:31,600 --> 00:25:33,800 Speaker 1: way you want to. I don't get all distracted. But 417 00:25:33,840 --> 00:25:36,960 Speaker 1: there's a documentary on the next is there gonna be 418 00:25:37,040 --> 00:25:39,040 Speaker 1: wars in the world. There may be worries about food 419 00:25:39,119 --> 00:25:44,600 Speaker 1: and water, and there's a great documentary on that. But 420 00:25:44,920 --> 00:25:47,840 Speaker 1: I'll save that that feature for another day. But it 421 00:25:47,920 --> 00:25:55,120 Speaker 1: deals with agriculture and this autonomous takeover of running a farm. 422 00:25:56,359 --> 00:25:59,639 Speaker 1: Some platforms like Jasper and d A L L. E 423 00:26:00,200 --> 00:26:04,440 Speaker 1: Y are are going to transform our system and agriculture. 424 00:26:06,520 --> 00:26:10,400 Speaker 1: I'm sorry that John Deere's AI enabling farming tool. Sorry 425 00:26:10,400 --> 00:26:15,439 Speaker 1: about that. Jasper and dollar E is my next example, 426 00:26:15,440 --> 00:26:21,399 Speaker 1: which is media and entertainment AI generating content and editing media. 427 00:26:24,440 --> 00:26:29,600 Speaker 1: I was drafting a document and needed help, and my 428 00:26:29,920 --> 00:26:33,000 Speaker 1: editing team weren't available and it was late at night, 429 00:26:33,359 --> 00:26:36,119 Speaker 1: and my friend Fisher TDJS was like, John, you're a 430 00:26:36,200 --> 00:26:38,280 Speaker 1: dummy like I thought you were smart, Like you know, 431 00:26:38,320 --> 00:26:40,959 Speaker 1: you're a public figure, right, so AI knows who you are, 432 00:26:41,400 --> 00:26:43,920 Speaker 1: So ask AI to help you because you're a public figure, 433 00:26:43,960 --> 00:26:45,840 Speaker 1: and say, you know, this is John O'Brien and can 434 00:26:45,880 --> 00:26:48,240 Speaker 1: you help me. You know this is the way I think, 435 00:26:48,320 --> 00:26:50,760 Speaker 1: and those ways knows how I think. I'm a public figure. 436 00:26:50,800 --> 00:26:56,479 Speaker 1: Can you help me frame out the answer or how 437 00:26:56,560 --> 00:26:59,159 Speaker 1: to answer this question or how to get me the 438 00:26:59,280 --> 00:27:02,680 Speaker 1: background for this question I'm trying to answer so I 439 00:27:02,760 --> 00:27:06,680 Speaker 1: can then, you know, basically finish writing this piece. And 440 00:27:06,760 --> 00:27:09,320 Speaker 1: so I asked a number of questions and it was 441 00:27:09,440 --> 00:27:11,959 Speaker 1: in it answered me back the way John Hope Bryant 442 00:27:12,840 --> 00:27:15,320 Speaker 1: would answer. It was scary. It's like it sounded just 443 00:27:15,600 --> 00:27:19,680 Speaker 1: like me because it is me. It's not plagiarism. It 444 00:27:19,800 --> 00:27:22,480 Speaker 1: is me. Is me asking me about me. That's crazy. Okay. 445 00:27:22,680 --> 00:27:26,240 Speaker 1: So another thing, do you know there's a book The 446 00:27:26,440 --> 00:27:28,720 Speaker 1: Future Is Faster Than You Think, which my friend Van 447 00:27:28,800 --> 00:27:31,159 Speaker 1: Jones had me read recently. You should read it and 448 00:27:32,600 --> 00:27:36,680 Speaker 1: it talked about how the you know it took two 449 00:27:36,760 --> 00:27:39,399 Speaker 1: hundred thousand years to get cognitive ability, in two hundred 450 00:27:39,480 --> 00:27:44,600 Speaker 1: years to really get this incredible leaps in society. And 451 00:27:44,680 --> 00:27:48,400 Speaker 1: within twenty years it's going to do more than AI 452 00:27:48,520 --> 00:27:51,240 Speaker 1: is going to do more. It could cause more change 453 00:27:51,240 --> 00:27:54,600 Speaker 1: in disruption and I think mostly positive change. And all 454 00:27:54,680 --> 00:27:58,359 Speaker 1: that those years in history combined it ended up practical 455 00:27:58,359 --> 00:28:00,480 Speaker 1: example of this is the best chess players in the 456 00:28:00,560 --> 00:28:05,440 Speaker 1: world were beaten by an AI in a very short 457 00:28:05,480 --> 00:28:08,040 Speaker 1: period of time. And then the computer that beat the 458 00:28:08,200 --> 00:28:13,400 Speaker 1: chess player in AI had another computer learning from that computer. 459 00:28:14,880 --> 00:28:17,520 Speaker 1: There was another AI learning from the AI that beat 460 00:28:17,640 --> 00:28:20,760 Speaker 1: the best chess player in the world, and within a 461 00:28:20,880 --> 00:28:26,119 Speaker 1: short period of time, the the new AI beat the 462 00:28:26,320 --> 00:28:29,320 Speaker 1: first AI in a fraction of the time. See, it's 463 00:28:29,400 --> 00:28:33,520 Speaker 1: just compounding, compound and compounding. It's building on itself. And 464 00:28:33,560 --> 00:28:35,440 Speaker 1: don't let's get to the point where we're talking about 465 00:28:35,720 --> 00:28:37,720 Speaker 1: what happens when AI starts thinking for itself. Well, let's 466 00:28:37,800 --> 00:28:42,720 Speaker 1: let's leave that movie and that question for another You 467 00:28:43,320 --> 00:28:44,760 Speaker 1: want me to do another episode, und there, you let 468 00:28:44,800 --> 00:28:46,640 Speaker 1: me know and I'll go to part two. But let 469 00:28:46,680 --> 00:28:48,240 Speaker 1: me just get to the let me get to the 470 00:28:48,280 --> 00:28:50,040 Speaker 1: sweet spot for you, which is the opportunity in which 471 00:28:50,080 --> 00:28:52,920 Speaker 1: the number you know, I've already dealt with UH media 472 00:28:52,920 --> 00:28:57,080 Speaker 1: and entertainment. Now there will be opportunities to because creativity 473 00:28:57,760 --> 00:28:59,600 Speaker 1: UH will be I think one of these unique things 474 00:28:59,680 --> 00:29:05,240 Speaker 1: that that might actually be preserved and reimagined by a 475 00:29:05,320 --> 00:29:09,600 Speaker 1: young generation. But it won't be lazy creativity. It'll be 476 00:29:09,720 --> 00:29:14,520 Speaker 1: very thoughtful creativity and multi media possibly too. Number ten 477 00:29:14,800 --> 00:29:18,280 Speaker 1: real estate and property management is another business that I'm 478 00:29:18,320 --> 00:29:23,760 Speaker 1: in AI for pricing, virtual tours and tenant management. This 479 00:29:23,960 --> 00:29:26,960 Speaker 1: is like Zilo's AI pricing tools is a real estate 480 00:29:27,040 --> 00:29:30,239 Speaker 1: platform that I use and virtual tours. Again, you can 481 00:29:30,320 --> 00:29:32,800 Speaker 1: imagine this kind of stuff. You don't you know AI? 482 00:29:33,000 --> 00:29:35,760 Speaker 1: You know, you go to a door and AI confirms 483 00:29:35,800 --> 00:29:44,880 Speaker 1: through eye technology, through site or your fingerprints. You know, 484 00:29:45,400 --> 00:29:48,239 Speaker 1: you've got the only fingerprints in the world. Yours are 485 00:29:48,320 --> 00:29:50,880 Speaker 1: only in the world. So when I go to the airport, now, 486 00:29:51,200 --> 00:29:54,080 Speaker 1: it used to take twenty thirty minutes to get through 487 00:29:54,360 --> 00:29:59,040 Speaker 1: international passport control, and then I got a global entry 488 00:29:59,080 --> 00:30:03,440 Speaker 1: and it took five minutes, eight minutes get through passport control. 489 00:30:03,480 --> 00:30:06,400 Speaker 1: Everybody else is standing in line, and now I get 490 00:30:06,440 --> 00:30:10,960 Speaker 1: through passport control in about two minutes. Because it looks 491 00:30:11,120 --> 00:30:14,240 Speaker 1: at my eyes. Nothing else doesn't. I used to scan 492 00:30:14,360 --> 00:30:17,240 Speaker 1: my passport and all that stuff and wait and somebody 493 00:30:17,240 --> 00:30:19,120 Speaker 1: would ask me a question. Now it scans my eyes 494 00:30:19,280 --> 00:30:23,040 Speaker 1: and it can tell within five seconds or less that 495 00:30:23,160 --> 00:30:25,160 Speaker 1: I'm one of eight billion people in the world that's 496 00:30:25,240 --> 00:30:28,320 Speaker 1: just me and gives me my approval, confirms it's me. Yes, 497 00:30:28,400 --> 00:30:29,960 Speaker 1: that's me, and I walk out the door and wait 498 00:30:30,800 --> 00:30:33,520 Speaker 1: at the police officer security officer on the way out. 499 00:30:33,560 --> 00:30:37,160 Speaker 1: It's unbelievably accurate. So think about this at the door 500 00:30:37,960 --> 00:30:41,880 Speaker 1: of a real estate property you want to see. So 501 00:30:42,240 --> 00:30:44,960 Speaker 1: it confirms it's you through fingerprints or through eyes, It 502 00:30:45,080 --> 00:30:47,560 Speaker 1: gives you access, It talks to you through a tour. 503 00:30:47,680 --> 00:30:49,600 Speaker 1: I mean, it goes on and goes on and goes on. 504 00:30:51,840 --> 00:30:57,160 Speaker 1: So let's talk about societal disruptions, the education gaps, lack 505 00:30:57,200 --> 00:31:01,360 Speaker 1: of AI literacy in schools, leaving communities unprepared, and of 506 00:31:01,440 --> 00:31:03,760 Speaker 1: course he's going to be underserved schools. That's why the 507 00:31:03,880 --> 00:31:06,720 Speaker 1: AILP three that we're doing with Georgia DA University in 508 00:31:06,800 --> 00:31:08,400 Speaker 1: the Mayor's office here in Atlanta is going to be 509 00:31:08,440 --> 00:31:10,440 Speaker 1: a national model in my opinion. So if you guys 510 00:31:10,440 --> 00:31:12,640 Speaker 1: are interested in your city's interested in that you can 511 00:31:12,680 --> 00:31:14,160 Speaker 1: get a hold of my office, or get a hold 512 00:31:14,200 --> 00:31:17,000 Speaker 1: of the mayor's office or Georgia State University School of Business, 513 00:31:17,800 --> 00:31:22,240 Speaker 1: Dean Phillips office. And we will try to include other 514 00:31:22,320 --> 00:31:25,280 Speaker 1: cities as we expand the model. We got to make 515 00:31:25,280 --> 00:31:28,400 Speaker 1: it work in Atlanta first, I believe we will. By 516 00:31:28,440 --> 00:31:30,160 Speaker 1: the way, every kid in Atlanta gets Atlanta Hope and 517 00:31:30,200 --> 00:31:32,040 Speaker 1: it gets a Hope Child Savors account they're going to 518 00:31:32,080 --> 00:31:34,959 Speaker 1: get can get financial literacy from that account. In AI literacy, 519 00:31:35,080 --> 00:31:36,800 Speaker 1: seventy five percent of any kid that has money in 520 00:31:36,840 --> 00:31:40,400 Speaker 1: account at kindergarten is seventy five percent more likely to 521 00:31:40,480 --> 00:31:43,280 Speaker 1: graduate from college. Hello, and City Group is domiciling those 522 00:31:43,320 --> 00:31:55,960 Speaker 1: accounts for us. By the way, so you're going to 523 00:31:56,000 --> 00:31:59,760 Speaker 1: have mental health in social strain, psychological effects of job 524 00:32:00,960 --> 00:32:03,640 Speaker 1: and societal instability. I mean, I think half people are 525 00:32:03,720 --> 00:32:07,440 Speaker 1: depressed right now. I think the vast majority majority of minorities, 526 00:32:07,520 --> 00:32:10,760 Speaker 1: particularly after Americans, are depressed right now. Can you imagine 527 00:32:10,840 --> 00:32:13,360 Speaker 1: what happens in poor whites are depressed right now? I 528 00:32:13,400 --> 00:32:16,840 Speaker 1: think that you know, it's another conversation, uh because you know, 529 00:32:16,960 --> 00:32:19,000 Speaker 1: but in how people are acting out on that. But 530 00:32:19,200 --> 00:32:22,560 Speaker 1: I think they're gonna You're gonna just imagine that on steroids, 531 00:32:23,080 --> 00:32:26,720 Speaker 1: that depression, that that sense of not being valued or valuable. 532 00:32:27,440 --> 00:32:29,320 Speaker 1: Economic de you got people lying in them. By the way, 533 00:32:29,440 --> 00:32:33,560 Speaker 1: it's giving them solutions now economic disparities, AI adoption, uh, 534 00:32:33,800 --> 00:32:37,280 Speaker 1: potentially winding the gap between the halves and the have nots. Again, 535 00:32:37,400 --> 00:32:40,760 Speaker 1: not somebody hates you, They just don't care about you. Now, 536 00:32:41,240 --> 00:32:44,520 Speaker 1: I'm just gonna give you a positiveness. Just trying to 537 00:32:44,720 --> 00:32:46,600 Speaker 1: want you, guys to jump off of once the first 538 00:32:46,600 --> 00:32:49,400 Speaker 1: four over one story building listening to this podcast. If 539 00:32:49,440 --> 00:32:51,720 Speaker 1: you're if you're a doctor in a small village in 540 00:32:52,240 --> 00:32:56,240 Speaker 1: rural Africa, a rural Latin America somewhere, a rural Asia, 541 00:32:56,400 --> 00:33:00,959 Speaker 1: rural somewhere, and you've got you've got no know, no sophistication, 542 00:33:01,160 --> 00:33:03,360 Speaker 1: no staff. You're going to have within a couple of 543 00:33:03,440 --> 00:33:11,080 Speaker 1: years the same solutions mental brain power as Emory University, 544 00:33:11,240 --> 00:33:13,520 Speaker 1: because you're going to have artificial intelligence and you'll be 545 00:33:13,600 --> 00:33:17,040 Speaker 1: to help the help patients and a small village and 546 00:33:17,440 --> 00:33:21,240 Speaker 1: remote and disconnected from the world to solve problems, extend life. 547 00:33:23,800 --> 00:33:26,960 Speaker 1: We create wellness at the same level that an Emery 548 00:33:27,040 --> 00:33:30,200 Speaker 1: University would. Isn't that magical? And then you'll have robotics 549 00:33:30,680 --> 00:33:33,320 Speaker 1: at a fraction of the cost of what early robotics 550 00:33:33,320 --> 00:33:35,280 Speaker 1: will cost. You'll have a box getting down little costs 551 00:33:35,320 --> 00:33:40,640 Speaker 1: where you can do dental surgery and and simple surgeries 552 00:33:40,680 --> 00:33:43,720 Speaker 1: and laser based surgeries at a little to no costs. 553 00:33:45,280 --> 00:33:48,080 Speaker 1: Uh in these rural communities. Okay, you can tell I'm 554 00:33:48,080 --> 00:33:52,719 Speaker 1: really excited about this topic. So you're gonna have uh 555 00:33:54,160 --> 00:33:58,520 Speaker 1: every examples of disruption, I mean the obvious changes automated 556 00:33:58,640 --> 00:34:01,800 Speaker 1: checkouts AI and customers service drivers vehicle has talked about 557 00:34:01,840 --> 00:34:06,280 Speaker 1: that less obvious changes. AI replacing middle management task like 558 00:34:06,360 --> 00:34:10,319 Speaker 1: scheduling and analysis. So if you don't like your boss, 559 00:34:10,600 --> 00:34:12,319 Speaker 1: no problem, they may not be there very long. Okay, 560 00:34:12,360 --> 00:34:14,919 Speaker 1: that was not a that it was not nice. Number 561 00:34:14,960 --> 00:34:20,160 Speaker 1: three the opportunity, new job creation and emerging industries again 562 00:34:20,280 --> 00:34:23,279 Speaker 1: or run through this because his podcast is longer than 563 00:34:23,320 --> 00:34:26,000 Speaker 1: I thought. I hope you're enjoying this because I am 564 00:34:27,520 --> 00:34:31,080 Speaker 1: industries and growth potential. Write this down. Now is where 565 00:34:31,080 --> 00:34:32,279 Speaker 1: we want to get your degrees. This is where we 566 00:34:32,320 --> 00:34:33,880 Speaker 1: get your certifications. This is where you want to get 567 00:34:33,880 --> 00:34:41,000 Speaker 1: your hustle focused healthcare, AI powered diagnostics, telemedicine. My wife 568 00:34:41,120 --> 00:34:42,920 Speaker 1: used a pad of telemedicine right now, by the way, 569 00:34:44,280 --> 00:34:46,360 Speaker 1: and her dad, doctor Dalton, he's right now, and her 570 00:34:46,440 --> 00:34:50,640 Speaker 1: mother Penny Mom. We hard met Amy Dalton and personalized 571 00:34:50,680 --> 00:34:55,160 Speaker 1: treatment plans. So think about startups creating AI driven cancer 572 00:34:55,239 --> 00:34:58,959 Speaker 1: detection tools right. This stuff's happening right now. Think about 573 00:34:58,960 --> 00:35:01,439 Speaker 1: the watch that you've had from Apple or whatever watch 574 00:35:01,480 --> 00:35:04,080 Speaker 1: you're wearing, that is that's digitized and it's taking your 575 00:35:04,080 --> 00:35:05,799 Speaker 1: blood pressure and all that kind of stuff where blood 576 00:35:05,800 --> 00:35:09,800 Speaker 1: pressure is coming, but is your posts and all that 577 00:35:09,920 --> 00:35:13,879 Speaker 1: stuff that's in sending messages back through your health app 578 00:35:13,960 --> 00:35:15,640 Speaker 1: on your phone. I mean that's not a phone, it's 579 00:35:15,640 --> 00:35:18,800 Speaker 1: a mini computer in your hands. That's it's a smart 580 00:35:18,960 --> 00:35:23,200 Speaker 1: literally a smartphone. So healthcare the same thing that's that's 581 00:35:23,239 --> 00:35:25,879 Speaker 1: going to potentially for job losses in many cases, there's 582 00:35:25,960 --> 00:35:30,479 Speaker 1: opportunity for reimagining job growth green technology AI optimizing energy 583 00:35:30,560 --> 00:35:34,439 Speaker 1: usage and advancing sustainability initiatives. This is thinking about smart 584 00:35:34,480 --> 00:35:39,240 Speaker 1: grids and renewable energy projects, cybersecurity, protecting systems from AI 585 00:35:39,440 --> 00:35:42,360 Speaker 1: driven attacks. This is going to be a huge business. 586 00:35:42,640 --> 00:35:45,719 Speaker 1: Right It's no longer somebody trying to shoot you. Is 587 00:35:45,760 --> 00:35:49,760 Speaker 1: somebody trying to steal your identity, steal your money, electronically. 588 00:35:50,120 --> 00:35:53,960 Speaker 1: Think about the risk of cryptocurrency. If somebody gets a 589 00:35:54,040 --> 00:35:56,440 Speaker 1: hold of your You got your physical cash in your pocket, 590 00:35:56,520 --> 00:35:59,359 Speaker 1: you got your your credit cards in your pocket, right, 591 00:36:00,160 --> 00:36:03,560 Speaker 1: somebody still in the key, the digital key. You got 592 00:36:03,640 --> 00:36:06,000 Speaker 1: drunk one night and you mentioned your key to somebody 593 00:36:06,160 --> 00:36:08,560 Speaker 1: or somebody you wrote it down, somebody took what you 594 00:36:08,600 --> 00:36:10,440 Speaker 1: wrote down. You don't remember what you wrote down. Whatever, 595 00:36:11,080 --> 00:36:14,280 Speaker 1: You can't access the digital currency that you have. Somebody 596 00:36:14,360 --> 00:36:16,439 Speaker 1: else can. They can lock you out of it. My brother, 597 00:36:17,760 --> 00:36:21,560 Speaker 1: Howard Hewitt has had a Facebook account that he got 598 00:36:21,640 --> 00:36:24,279 Speaker 1: locked out of for six months because he didn't do 599 00:36:25,400 --> 00:36:29,400 Speaker 1: dual security on his situation at least then he doesn't now, 600 00:36:29,840 --> 00:36:33,359 Speaker 1: and somebody hacked his system. Not his fault. They hacked 601 00:36:33,400 --> 00:36:36,279 Speaker 1: his system and was literally talking to his fans. It's 602 00:36:36,360 --> 00:36:37,960 Speaker 1: hundreds of thousands of fans like it was him. He 603 00:36:37,960 --> 00:36:39,640 Speaker 1: could do nothing about it. They were asking He's asking 604 00:36:39,680 --> 00:36:42,520 Speaker 1: for the asking for money as if he's Howard Hewitt. 605 00:36:42,520 --> 00:36:44,480 Speaker 1: It wasn't Howard. Howardodn't ask you for any money. It 606 00:36:44,640 --> 00:36:47,200 Speaker 1: was maddening to him, but he could do nothing about it. 607 00:36:47,600 --> 00:36:49,439 Speaker 1: This is just a very small We got to finally 608 00:36:49,440 --> 00:36:52,359 Speaker 1: help him get his identity back. I'll get his page back. 609 00:36:52,800 --> 00:36:56,000 Speaker 1: Took almost six months and he was at it every day. 610 00:36:56,120 --> 00:36:59,040 Speaker 1: And this is this is a Grammy Award winning superstar imagining. 611 00:36:59,080 --> 00:37:01,279 Speaker 1: This is an average a person, every day person who 612 00:37:01,360 --> 00:37:05,279 Speaker 1: somebody steals your identity. All right, Uh, so cybersecurity is 613 00:37:05,320 --> 00:37:07,200 Speaker 1: going to be huge and it's a business for people 614 00:37:07,400 --> 00:37:09,360 Speaker 1: that he can start. Is a career as a business, 615 00:37:09,480 --> 00:37:13,160 Speaker 1: it's not just negative as a positive. So ethical hackers 616 00:37:13,280 --> 00:37:17,280 Speaker 1: and cybersecurity analysis analysts are going to be a big business. 617 00:37:18,280 --> 00:37:20,239 Speaker 1: Uh again, you want to pull down the report from 618 00:37:20,239 --> 00:37:22,120 Speaker 1: the AI Ethics Council. It will be on our website 619 00:37:22,160 --> 00:37:24,759 Speaker 1: this week. Uh, where we do a whole report on 620 00:37:25,120 --> 00:37:31,320 Speaker 1: on on ethical issues tied tied to AIU, what you 621 00:37:31,360 --> 00:37:32,759 Speaker 1: should do about it, which you should look out for 622 00:37:32,960 --> 00:37:35,319 Speaker 1: and and so we cover this ground, but we don't 623 00:37:35,400 --> 00:37:37,600 Speaker 1: we don't cover the opportunity as much as why I'm 624 00:37:37,640 --> 00:37:40,799 Speaker 1: doing this podcast. But download the report on the AI 625 00:37:40,840 --> 00:37:46,960 Speaker 1: Ethics Council website, number number four. AI Ethics and Regulation, 626 00:37:47,400 --> 00:37:51,800 Speaker 1: ensuring Fairness and transparency and AI Systems creating ethical frameworks 627 00:37:51,800 --> 00:37:55,840 Speaker 1: for automated decision making. So again you want to download 628 00:37:55,840 --> 00:37:58,600 Speaker 1: our report of the AI Ethics Council is but one example. 629 00:37:59,719 --> 00:38:04,600 Speaker 1: Number five AI operations and maintenance, supporting and maintaining AI systems, 630 00:38:05,440 --> 00:38:08,880 Speaker 1: robotic technicians, and AI trainers. So there's gonna be seventy 631 00:38:08,960 --> 00:38:11,160 Speaker 1: five million jobs proofs that were gonna go away because 632 00:38:11,200 --> 00:38:14,640 Speaker 1: of AI. But they've gone probably pretty eighty five million jobs, 633 00:38:14,680 --> 00:38:16,680 Speaker 1: eighty eight million jobs. I think as a number member, 634 00:38:16,800 --> 00:38:21,040 Speaker 1: it's going to be created by AI. See what I'm saying. So, 635 00:38:21,480 --> 00:38:23,799 Speaker 1: but the but is not a one for one. It's 636 00:38:23,800 --> 00:38:25,400 Speaker 1: not like you've got you lost a job. Now you 637 00:38:25,440 --> 00:38:27,839 Speaker 1: get a job. Somebody's gonna lose a job. Somebody else 638 00:38:27,960 --> 00:38:30,080 Speaker 1: may get a job. It may not be you unless 639 00:38:30,080 --> 00:38:34,520 Speaker 1: you get these skills. I'm talking about creative industries. Number six, 640 00:38:35,360 --> 00:38:38,239 Speaker 1: enhancing human creativity through AI. I talked to member. I 641 00:38:38,320 --> 00:38:42,080 Speaker 1: talked about the losses in entertainment and creative spaces and 642 00:38:42,160 --> 00:38:46,960 Speaker 1: also talked about the gains personalized content creating creation platforms. 643 00:38:49,080 --> 00:38:53,160 Speaker 1: Networks are communications. Networks are going to change. You have 644 00:38:53,480 --> 00:38:57,240 Speaker 1: increasingly people like me and Shannon Sharp and Van Jones 645 00:38:57,280 --> 00:38:59,440 Speaker 1: and Steven A. Smith. These are friends of mine and Charlemagne, 646 00:38:59,520 --> 00:39:02,480 Speaker 1: that god who run who runs the Black Network that 647 00:39:02,480 --> 00:39:04,680 Speaker 1: I'm on the board of. This I'm on his platform 648 00:39:04,760 --> 00:39:07,319 Speaker 1: right now. You know, all these podcasters, they're creating their 649 00:39:07,360 --> 00:39:11,080 Speaker 1: own following, their own subscribers, their own products, their own 650 00:39:11,320 --> 00:39:15,120 Speaker 1: you know networks, if you will. Right, these are and 651 00:39:15,200 --> 00:39:19,000 Speaker 1: we're using technology, and we're using robotics and you know, 652 00:39:19,239 --> 00:39:21,760 Speaker 1: so on and so forth and AI tools, et cetera. 653 00:39:22,520 --> 00:39:25,160 Speaker 1: So if you're not part of the solution, if you're 654 00:39:25,200 --> 00:39:27,400 Speaker 1: not part of the future, you're going to be run 655 00:39:27,480 --> 00:39:31,200 Speaker 1: over it by it. Okay, So skills for the future, 656 00:39:31,560 --> 00:39:36,640 Speaker 1: hard skills. Okay, kids, listen to me now, coding, AI development, 657 00:39:37,120 --> 00:39:46,600 Speaker 1: data analysis, cybersecurity, solve skills, creativity, adaptability, emotional intelligence, like 658 00:39:47,000 --> 00:39:50,400 Speaker 1: vocational training for AI to specific roles like you know, 659 00:39:52,400 --> 00:39:55,480 Speaker 1: you know, anything tied to engineering, Like you want to 660 00:39:55,520 --> 00:39:57,359 Speaker 1: not to go broke. Be an engineer or any kind 661 00:39:57,360 --> 00:40:00,760 Speaker 1: of engineer, mechanical engineer, computer engineer, any kind of engineer. 662 00:40:00,800 --> 00:40:02,640 Speaker 1: You will not get broken go broke. I think like 663 00:40:02,680 --> 00:40:06,120 Speaker 1: six percent of all engineers are black. Oh no, sorry, 664 00:40:06,160 --> 00:40:09,120 Speaker 1: six percent of white, six or seven women, six or 665 00:40:09,120 --> 00:40:11,160 Speaker 1: seven percent of women, and I think three to four 666 00:40:11,200 --> 00:40:13,360 Speaker 1: percent are black. So there's a huge opportunity to be 667 00:40:13,400 --> 00:40:17,400 Speaker 1: an engineer. And again you'll you'll make six figures for 668 00:40:17,400 --> 00:40:24,200 Speaker 1: the rest of your life and like hidden opportunities, AI 669 00:40:24,440 --> 00:40:30,799 Speaker 1: powered farming, specialized logistics, AI assistant creative projects, not they're 670 00:40:30,840 --> 00:40:33,400 Speaker 1: not so obvious. But whoever finds that and master that, 671 00:40:33,680 --> 00:40:37,160 Speaker 1: you can corner the market. Here's a call to action. 672 00:40:37,800 --> 00:40:40,680 Speaker 1: What we must do now. We have got to obsess 673 00:40:41,040 --> 00:40:46,040 Speaker 1: about AI literacy. Encourage everyone to understand AI basics. Listen 674 00:40:46,120 --> 00:40:49,279 Speaker 1: to this podcast as a as a starting step. One, 675 00:40:49,400 --> 00:40:51,360 Speaker 1: listen to what Van Jones has a video where we 676 00:40:51,400 --> 00:40:53,879 Speaker 1: talked about the five AI apps that he uses. Listen 677 00:40:53,920 --> 00:40:56,279 Speaker 1: to what he's saying, mostly for creatives, but listen to 678 00:40:56,360 --> 00:40:58,440 Speaker 1: what he's saying, and listen to people like him and 679 00:40:58,480 --> 00:41:01,719 Speaker 1: stop listening to dummies like you know we made We 680 00:41:01,840 --> 00:41:03,680 Speaker 1: tell you gonna be have a real problem with artificial 681 00:41:03,719 --> 00:41:06,440 Speaker 1: intelligence and robotics criminals. If you're a crook, this is 682 00:41:06,560 --> 00:41:08,160 Speaker 1: this isould be one of the industries that's going away. 683 00:41:09,000 --> 00:41:10,960 Speaker 1: You know, I got a mask. You know it's it's 684 00:41:11,120 --> 00:41:13,359 Speaker 1: it's COVID. I can just wear a mask. Somebody's gonna 685 00:41:13,440 --> 00:41:17,560 Speaker 1: nobody can see my face. AI can and it can 686 00:41:17,640 --> 00:41:19,600 Speaker 1: see right to the pupils, it can go, it can 687 00:41:19,680 --> 00:41:22,040 Speaker 1: look you know you still your eyes is still visible. 688 00:41:22,440 --> 00:41:24,399 Speaker 1: Your whole face might be might be covered. In fact, 689 00:41:24,440 --> 00:41:27,440 Speaker 1: AI can now identify you with a mask on. Look 690 00:41:27,480 --> 00:41:30,719 Speaker 1: at your iPhone. Now we can now identify you for 691 00:41:31,040 --> 00:41:34,520 Speaker 1: face ID with your mask on. Think about that. And 692 00:41:34,600 --> 00:41:39,800 Speaker 1: there's and there's cameras increasingly everywhere. Old school criminals. I 693 00:41:39,800 --> 00:41:41,400 Speaker 1: don't even know what a new school criminal looks like. 694 00:41:41,400 --> 00:41:44,319 Speaker 1: I guess it's cybersecurity. But old school criminals are uh, 695 00:41:45,200 --> 00:41:48,160 Speaker 1: rob and mug and grab and and and running in 696 00:41:48,560 --> 00:41:51,560 Speaker 1: stores and grabbing stuff and knocking somebody over the head 697 00:41:51,680 --> 00:41:54,440 Speaker 1: and running into the cars and doing you know stuff 698 00:41:54,520 --> 00:41:58,040 Speaker 1: you know, and doing road rage. All that stuff's gone 699 00:41:58,200 --> 00:42:01,400 Speaker 1: because a camera's got you on and they're coming to 700 00:42:01,560 --> 00:42:06,239 Speaker 1: get you. They're coming to get you. That's actually a 701 00:42:06,320 --> 00:42:08,760 Speaker 1: good thing. But anyway, just if you, if your criminal, 702 00:42:08,880 --> 00:42:11,279 Speaker 1: just stop it right now. Like it's just that, that's 703 00:42:11,280 --> 00:42:15,280 Speaker 1: an industry that will get completely disrupted. It's old school 704 00:42:15,520 --> 00:42:18,960 Speaker 1: gangsters and criminals and whatever. So you've got to become 705 00:42:19,040 --> 00:42:24,400 Speaker 1: a life a lifetime learner and and focused on reskilling 706 00:42:25,200 --> 00:42:30,040 Speaker 1: at every age. Community level action introducing AI literacy in 707 00:42:30,080 --> 00:42:33,560 Speaker 1: schools and vocational programs again, AI Ethics Council and AI 708 00:42:33,719 --> 00:42:35,200 Speaker 1: l P three. This is what we're doing here in 709 00:42:35,239 --> 00:42:40,480 Speaker 1: Atlanta to follow our model civil rights public private partnerships, 710 00:42:40,520 --> 00:42:45,840 Speaker 1: collaborating with tech companies for accessible training programs. Again follow 711 00:42:45,920 --> 00:42:53,480 Speaker 1: our model, uh, national action policy advocacy, upskilling programs, universal 712 00:42:53,560 --> 00:42:58,520 Speaker 1: basic income pilots. Even though I'm you know, not really 713 00:42:58,600 --> 00:43:02,120 Speaker 1: crazy about the concept of universal basic income. I like 714 00:43:02,600 --> 00:43:05,680 Speaker 1: minimum wage, I like living wages. I don't want to 715 00:43:06,120 --> 00:43:09,320 Speaker 1: guarantee somebody an income, and I think that it strips 716 00:43:09,360 --> 00:43:14,000 Speaker 1: people of their dignity and without financial literacy, you know, 717 00:43:14,040 --> 00:43:17,640 Speaker 1: basic income just means you'll spend to that level and 718 00:43:17,640 --> 00:43:21,080 Speaker 1: then you'll need more. But uh, the tech companies do, 719 00:43:21,280 --> 00:43:24,120 Speaker 1: like some of the tech tech leaders, when they think 720 00:43:24,160 --> 00:43:26,480 Speaker 1: that jobs are going to go away, they will give 721 00:43:26,520 --> 00:43:30,040 Speaker 1: you a grant or a program in the city or 722 00:43:30,080 --> 00:43:31,920 Speaker 1: state to pilot some of this stuff. And they're going 723 00:43:31,960 --> 00:43:33,839 Speaker 1: to at least the're gonna do it. I guess they're 724 00:43:34,280 --> 00:43:36,600 Speaker 1: do it. You should, the money's there, you should take it. 725 00:43:36,640 --> 00:43:39,520 Speaker 1: I just don't think that has a long future ahead 726 00:43:39,560 --> 00:43:44,160 Speaker 1: of it. Ethical rewriting, ethical AI regulations is going to 727 00:43:44,200 --> 00:43:46,960 Speaker 1: be done in the city, state, federal, international level. Again, 728 00:43:47,000 --> 00:43:48,200 Speaker 1: that's what some of the things we're doing. The AI 729 00:43:48,200 --> 00:43:50,719 Speaker 1: ethics Council, follow a little bit of what we're doing 730 00:43:50,760 --> 00:43:53,200 Speaker 1: and download our report and read every inch of it. 731 00:43:54,280 --> 00:43:59,720 Speaker 1: Expanding broadband access and digital inclusion programs nonprofits and community 732 00:43:59,760 --> 00:44:02,840 Speaker 1: based organizations. You may need to rewrite a little bit 733 00:44:02,880 --> 00:44:05,480 Speaker 1: of your future history about what you're going to focus on. 734 00:44:05,640 --> 00:44:07,280 Speaker 1: Maybe you should be focusing on some of this stuff. 735 00:44:07,960 --> 00:44:11,239 Speaker 1: The greatest wealth building opportunity of this era will come 736 00:44:11,320 --> 00:44:16,320 Speaker 1: from embracing technology, not fearing it. Together, we can ensure 737 00:44:16,360 --> 00:44:19,719 Speaker 1: that AI isn't just for some of us, it's for 738 00:44:20,160 --> 00:44:24,319 Speaker 1: all of us. The pain of disruption and the opportunities 739 00:44:24,360 --> 00:44:29,399 Speaker 1: and new industries in ROWS is unfortunately right in front 740 00:44:29,440 --> 00:44:32,680 Speaker 1: of us. The future is in something we Inherit is 741 00:44:32,760 --> 00:44:35,799 Speaker 1: something we build. And so if you wait and wait 742 00:44:36,280 --> 00:44:39,560 Speaker 1: and wait, you're going to get hit by the weight again. 743 00:44:39,640 --> 00:44:42,120 Speaker 1: If you're not out of the table, you're on the menu. 744 00:44:42,719 --> 00:44:45,840 Speaker 1: But you can make a change. Rainbows only follow storms. 745 00:44:45,880 --> 00:44:48,400 Speaker 1: You cannot have a rainbow without a storm first. So 746 00:44:48,520 --> 00:44:51,680 Speaker 1: let's make this a call to action. Share this podcast, 747 00:44:52,200 --> 00:44:55,680 Speaker 1: start a conversation, explore resources from Operation Hope and the 748 00:44:55,760 --> 00:44:59,920 Speaker 1: AI Ethics Council and AILP three and other innovative heroes 749 00:45:00,040 --> 00:45:02,279 Speaker 1: and she rows and doers from the streets of the 750 00:45:02,320 --> 00:45:05,080 Speaker 1: suites and backs that are trying to create opportunity for 751 00:45:05,160 --> 00:45:08,040 Speaker 1: people at scale and planning for the future that we 752 00:45:08,120 --> 00:45:11,440 Speaker 1: will all have together. Uh AI is for all of us. 753 00:45:11,520 --> 00:45:16,120 Speaker 1: Let's make sure that no one gets left behind. This 754 00:45:16,320 --> 00:45:20,240 Speaker 1: is John O'Bryant. This was AI for Dummies, which started 755 00:45:20,280 --> 00:45:23,520 Speaker 1: with me. I was a dummy and I am trying 756 00:45:23,520 --> 00:45:25,200 Speaker 1: to learn as fast as I can. And what I 757 00:45:25,360 --> 00:45:29,400 Speaker 1: know is nobody else knows anything either, So that just 758 00:45:29,480 --> 00:45:33,960 Speaker 1: makes me comfortable. But if you hustle, and you understand 759 00:45:34,200 --> 00:45:36,680 Speaker 1: what I say on my this T shirt here, nobody 760 00:45:36,800 --> 00:45:40,680 Speaker 1: cares work harder. If you've got these these these concepts 761 00:45:40,760 --> 00:45:43,239 Speaker 1: in your in your your spirit, you work hard. You've 762 00:45:43,280 --> 00:45:45,319 Speaker 1: got hustle. You understand that only in the dictionary does 763 00:45:45,360 --> 00:45:47,920 Speaker 1: the word success coming for the word work, because it's alphabetical. 764 00:45:48,239 --> 00:45:50,800 Speaker 1: And you understand we're all starting at the same uneven place, 765 00:45:51,440 --> 00:45:53,680 Speaker 1: and that you have a chance to go become the 766 00:45:53,760 --> 00:45:57,560 Speaker 1: next Edison or uh the next Steve Jobs or the 767 00:45:57,640 --> 00:46:01,000 Speaker 1: next uh Oprah Winfrey and the new creative space or 768 00:46:01,480 --> 00:46:05,960 Speaker 1: you know, the next hero or Shero. All these industries 769 00:46:06,000 --> 00:46:08,759 Speaker 1: are going to get disrupted. Everything is I can't under 770 00:46:08,920 --> 00:46:14,440 Speaker 1: I can't explain this, underscore this more that I'm saying 771 00:46:14,560 --> 00:46:16,719 Speaker 1: this simply, but I can't. I'd want to say it 772 00:46:16,840 --> 00:46:21,040 Speaker 1: ten times. I just know that maybe you just need 773 00:46:21,080 --> 00:46:27,200 Speaker 1: to hear it one slowly. Every industry in the world 774 00:46:29,080 --> 00:46:33,160 Speaker 1: is going to get disrupted. Pick one. When you're getting 775 00:46:33,239 --> 00:46:35,760 Speaker 1: run out of town, get in front of the crowd 776 00:46:35,920 --> 00:46:40,200 Speaker 1: and make like a parade. Turn your problem or somebody 777 00:46:40,239 --> 00:46:42,759 Speaker 1: else's into an opportunity. By the way, that's what capitalism is. 778 00:46:42,880 --> 00:46:46,479 Speaker 1: Capitalism is solving problems with people. Had nappy here, somebody 779 00:46:46,520 --> 00:46:49,239 Speaker 1: created a comb Can you create an AI digital com 780 00:46:49,280 --> 00:46:51,759 Speaker 1: for the future. Okay, I'm stopping John O'Briant. This is 781 00:46:51,840 --> 00:46:54,960 Speaker 1: Money and Wealth on the Black Effect Network and this 782 00:46:55,080 --> 00:46:58,799 Speaker 1: is my podcast series for twenty twenty five. iHeartRadio. Let's 783 00:46:58,840 --> 00:47:15,760 Speaker 1: Go Money and Wealth with John O'Brien is a production 784 00:47:15,960 --> 00:47:19,279 Speaker 1: of the Black Effect Podcast Network. For more podcasts from 785 00:47:19,320 --> 00:47:23,680 Speaker 1: the Black Effect Podcast Network, visit the iHeartRadio app, Apple Podcasts, 786 00:47:24,160 --> 00:47:26,600 Speaker 1: or wherever you listen to your favorite shows.