1 00:00:00,160 --> 00:00:03,640 Speaker 1: This battle isn't going away, and it's a battle between nations, 2 00:00:03,640 --> 00:00:07,160 Speaker 1: a battle within nations, and it's going to be a 3 00:00:07,240 --> 00:00:15,400 Speaker 1: feature of the international economy for decades to come. From 4 00:00:15,440 --> 00:00:20,880 Speaker 1: Bloomberg News and iHeartRadio, it's the big day. I'm West 5 00:00:20,920 --> 00:00:25,960 Speaker 1: Cansova today. The war for workers is just getting started. 6 00:00:35,360 --> 00:00:38,519 Speaker 1: Historic unemployment in the US right now means there are 7 00:00:38,640 --> 00:00:42,160 Speaker 1: many more jobs available than workers willing to fill them, 8 00:00:42,200 --> 00:00:45,800 Speaker 1: and that means employers have to work harder to attract 9 00:00:45,840 --> 00:00:48,640 Speaker 1: new talent and hang on to the employees they have. 10 00:00:49,320 --> 00:00:51,360 Speaker 1: When this happened in the past, it was usually just 11 00:00:51,520 --> 00:00:54,840 Speaker 1: a matter of time before the economy cooled, the job 12 00:00:54,880 --> 00:00:59,240 Speaker 1: market tightened again, and companies seized back the advantage. That 13 00:00:59,360 --> 00:01:02,760 Speaker 1: might not be the case this time around. Me Sean 14 00:01:02,840 --> 00:01:06,440 Speaker 1: Donn and Bloomberg's senior economics writer and friend of the 15 00:01:06,480 --> 00:01:09,640 Speaker 1: Big Tag podcast, is back to tell us how even 16 00:01:09,720 --> 00:01:13,240 Speaker 1: some of the biggest, best known companies like Intel are 17 00:01:13,319 --> 00:01:16,200 Speaker 1: preparing for a future in which they have to compete 18 00:01:16,319 --> 00:01:21,160 Speaker 1: for every worker. Sean, glad to have you back, people wars. 19 00:01:21,240 --> 00:01:24,640 Speaker 1: That's how you've been describing the job market of the future. 20 00:01:24,800 --> 00:01:28,080 Speaker 1: Can you start by painting a picture of the current 21 00:01:28,080 --> 00:01:32,479 Speaker 1: mismatch between jobs and workers, and why you think it's 22 00:01:32,480 --> 00:01:35,479 Speaker 1: going to become even harder for companies to fill out 23 00:01:35,480 --> 00:01:38,800 Speaker 1: their ranks in the years ahead. So if you look 24 00:01:38,800 --> 00:01:43,080 Speaker 1: out at US economy today, everywhere you look, you see 25 00:01:43,120 --> 00:01:47,000 Speaker 1: shortages of workers, and there's a temptation that we have 26 00:01:47,400 --> 00:01:51,640 Speaker 1: to blame that on the pandemic. Right. Pandemic upended how 27 00:01:51,680 --> 00:01:54,480 Speaker 1: we think about work to put a lot of people 28 00:01:54,520 --> 00:01:56,840 Speaker 1: out of work and then back into work when the 29 00:01:57,320 --> 00:02:01,200 Speaker 1: economic response happened. It also is a story though, about 30 00:02:01,280 --> 00:02:05,559 Speaker 1: demographics in America and the moment that America finds itself at. 31 00:02:06,440 --> 00:02:10,960 Speaker 1: One of the great competitive advantages that the American economy 32 00:02:11,080 --> 00:02:16,120 Speaker 1: has had almost since its inception has been people. It 33 00:02:16,200 --> 00:02:19,280 Speaker 1: attracts a lot of people, and it has through its 34 00:02:19,320 --> 00:02:23,320 Speaker 1: history it has always been you know this idea, it's 35 00:02:23,320 --> 00:02:27,960 Speaker 1: this honey pot for talent around the world, and through immigration, 36 00:02:28,320 --> 00:02:31,959 Speaker 1: through birth rates and so on, the population has grown, 37 00:02:32,000 --> 00:02:36,280 Speaker 1: and as the population grows, the economy grows. It's this 38 00:02:36,360 --> 00:02:40,040 Speaker 1: amazing resource. Well, for the first time in its history, 39 00:02:40,520 --> 00:02:44,600 Speaker 1: America is confronting a problem now whereby its working age 40 00:02:44,639 --> 00:02:48,639 Speaker 1: population is growing at its slowest rate since at least 41 00:02:48,680 --> 00:02:51,120 Speaker 1: nineteen sixteen. Quite possibly since the end of World War 42 00:02:51,160 --> 00:02:55,600 Speaker 1: Two and is likely to shrink in the years to come. 43 00:02:56,120 --> 00:02:58,360 Speaker 1: Take that apart a little bit, what are the different 44 00:02:58,400 --> 00:03:02,600 Speaker 1: pieces of that pause. So the biggest piece of that 45 00:03:02,680 --> 00:03:06,560 Speaker 1: puzzle is this generation, the baby boomers, who were born 46 00:03:06,880 --> 00:03:10,200 Speaker 1: in the decade after World War Two and have been 47 00:03:10,520 --> 00:03:14,359 Speaker 1: the biggest presence in the American labor force ever since. 48 00:03:14,960 --> 00:03:18,399 Speaker 1: They're retiring. They're cycling out, and that is hitting all 49 00:03:18,440 --> 00:03:24,560 Speaker 1: sorts of professions, from construction workers to police men and 50 00:03:24,760 --> 00:03:30,360 Speaker 1: women to manufacturing. All these key parts of the economy 51 00:03:30,520 --> 00:03:34,160 Speaker 1: are losing this big cohort of people. The other end 52 00:03:34,200 --> 00:03:37,560 Speaker 1: of that is there's fewer babies being born, and there 53 00:03:37,560 --> 00:03:40,960 Speaker 1: were fewer babies born eighteen years ago, which means there's 54 00:03:40,960 --> 00:03:45,080 Speaker 1: fewer people young people coming into the workforce. And that's 55 00:03:45,160 --> 00:03:48,200 Speaker 1: not even the end of it. There are still more 56 00:03:48,320 --> 00:03:52,120 Speaker 1: cross currents, right, and then there's immigration. This goes back 57 00:03:52,160 --> 00:03:54,840 Speaker 1: to the nineteenth century. One of the ways the US 58 00:03:54,920 --> 00:03:59,320 Speaker 1: has built this incredible workforce has been through immigration. And 59 00:03:59,480 --> 00:04:04,160 Speaker 1: what we've seen since twenty sixteen and the election of 60 00:04:04,160 --> 00:04:07,760 Speaker 1: Donald Trump has been a slowdown in the number of 61 00:04:07,800 --> 00:04:13,120 Speaker 1: migrants coming into America, which means again, this is less 62 00:04:13,200 --> 00:04:16,560 Speaker 1: working age migrants coming into America, which means less workers 63 00:04:16,560 --> 00:04:19,400 Speaker 1: in America. You started out by saying that we think 64 00:04:19,400 --> 00:04:21,560 Speaker 1: of this as a COVID problem, but it's not. But 65 00:04:22,000 --> 00:04:24,919 Speaker 1: COVID does play a role in that, Is that right? Oh? Absolutely, Look, 66 00:04:24,960 --> 00:04:27,880 Speaker 1: we lost more than a million people in America as 67 00:04:27,880 --> 00:04:30,679 Speaker 1: a result of COVID. That clearly has had an impact 68 00:04:31,120 --> 00:04:34,000 Speaker 1: on the labor for us. Also, you know, there was 69 00:04:34,120 --> 00:04:37,800 Speaker 1: a pandemic slowdown in immigration the borders were closed. That 70 00:04:38,000 --> 00:04:42,000 Speaker 1: had an impact as well. But that impact is on 71 00:04:42,160 --> 00:04:46,880 Speaker 1: top of this bigger, broader demographic impact that we really 72 00:04:46,920 --> 00:04:48,960 Speaker 1: are just at the start of. We're at the start 73 00:04:48,960 --> 00:04:53,040 Speaker 1: of this chapter in American economic history. And so companies 74 00:04:53,160 --> 00:04:56,640 Speaker 1: of all kinds, employers of all kinds are looking at 75 00:04:56,680 --> 00:05:00,719 Speaker 1: their situation now and saying we need workers. They're looking 76 00:05:00,720 --> 00:05:04,240 Speaker 1: down the road and saying we're going to need workers. 77 00:05:04,520 --> 00:05:07,200 Speaker 1: And your story focuses on one of those companies is 78 00:05:07,200 --> 00:05:10,560 Speaker 1: one we all know, Intel, the computer chip makers, probably 79 00:05:10,560 --> 00:05:12,640 Speaker 1: got a chip in something in your pocket or something 80 00:05:12,680 --> 00:05:15,360 Speaker 1: on your desk, and they're building a big new plant 81 00:05:15,400 --> 00:05:18,200 Speaker 1: in Ohio and thinking, what are we going to do 82 00:05:18,320 --> 00:05:21,640 Speaker 1: for workers? What did you find? So this is one 83 00:05:21,680 --> 00:05:23,760 Speaker 1: of the great projects. It's not just that we know 84 00:05:23,880 --> 00:05:26,040 Speaker 1: Intel and that we have these chips in our pockets 85 00:05:26,080 --> 00:05:28,920 Speaker 1: and our phones and in our cars. It's also that 86 00:05:28,960 --> 00:05:32,479 Speaker 1: if you look at American economic policy right now and 87 00:05:32,800 --> 00:05:39,120 Speaker 1: America's economic ambitions, getting semiconductor production back in this land 88 00:05:39,520 --> 00:05:41,640 Speaker 1: is a huge priority for the Biden administration, in fact, 89 00:05:41,640 --> 00:05:46,400 Speaker 1: a bipartisan priority. And Intel this project in Licking County, Ohio, 90 00:05:46,600 --> 00:05:49,760 Speaker 1: a place called New Albany, in a farm field there 91 00:05:50,200 --> 00:05:54,279 Speaker 1: where they're going to build two enormous semiconductor chip plants 92 00:05:54,320 --> 00:05:57,839 Speaker 1: and eventually five times as many as well around there. 93 00:05:58,320 --> 00:06:01,760 Speaker 1: It's a huge twenty billion dollar project. But right now 94 00:06:01,800 --> 00:06:05,359 Speaker 1: they are scrambling to find not just the workers to 95 00:06:05,520 --> 00:06:08,279 Speaker 1: go into that plant there's about three thousand workers that 96 00:06:08,279 --> 00:06:10,880 Speaker 1: they'll need in that plant two or three years from 97 00:06:10,880 --> 00:06:14,240 Speaker 1: now when it opens, but also the seven thousand workers 98 00:06:14,279 --> 00:06:17,920 Speaker 1: that they need to build that plant. So this is 99 00:06:17,960 --> 00:06:21,159 Speaker 1: an interesting sort of puzzle because on the one hand, 100 00:06:21,240 --> 00:06:23,640 Speaker 1: they have a problem right now, you say they need 101 00:06:23,680 --> 00:06:25,520 Speaker 1: to build this thing, who is going to build it? 102 00:06:25,560 --> 00:06:29,200 Speaker 1: But then they're thinking who will do the highly skilled 103 00:06:29,279 --> 00:06:34,120 Speaker 1: jobs necessary to build these very complex components. Right, So, 104 00:06:34,160 --> 00:06:37,560 Speaker 1: if you break it down, there is Intel's problem two 105 00:06:37,640 --> 00:06:39,359 Speaker 1: or three years from now in terms of training the 106 00:06:39,400 --> 00:06:41,920 Speaker 1: people that needs those three thousand workers it needs initially. 107 00:06:42,160 --> 00:06:45,919 Speaker 1: And then there's the problem that it's big contractor, Bechtel has, 108 00:06:45,960 --> 00:06:50,640 Speaker 1: which is finding those seven thousand workers. Bechtel says it 109 00:06:50,720 --> 00:06:52,719 Speaker 1: is going to need to bring forty percent of those 110 00:06:52,760 --> 00:06:56,400 Speaker 1: workers from probably out of state, from other projects because 111 00:06:56,400 --> 00:07:01,159 Speaker 1: they're just not available locally. Another build to build the plant. 112 00:07:01,440 --> 00:07:07,080 Speaker 1: This is pipe fitters, electricians, welders, bulldozer drivers, all of 113 00:07:07,080 --> 00:07:09,080 Speaker 1: the things you need to build a high tech plant. 114 00:07:09,560 --> 00:07:11,160 Speaker 1: And if you look at all the jobs that they're 115 00:07:11,200 --> 00:07:13,960 Speaker 1: advertising for, they all are you know, we will pay 116 00:07:14,000 --> 00:07:17,520 Speaker 1: relocation expenses on there. So they've got to find these workers, 117 00:07:17,520 --> 00:07:19,560 Speaker 1: and they're looking all around the country because they're not 118 00:07:19,600 --> 00:07:23,680 Speaker 1: available there in the Columbus area in Ohio. Thirty percent 119 00:07:23,760 --> 00:07:26,520 Speaker 1: of the workers who build the plant are going to 120 00:07:26,560 --> 00:07:29,080 Speaker 1: be in premises that they have to. Lauren, you talk 121 00:07:29,120 --> 00:07:32,240 Speaker 1: to the local unions and they are reaching down into 122 00:07:32,320 --> 00:07:36,160 Speaker 1: middle schools to try and attract apprentices. And why do 123 00:07:36,200 --> 00:07:39,040 Speaker 1: they need those apprentices Publicas at the other end of 124 00:07:39,080 --> 00:07:42,360 Speaker 1: their membership, they have these baby boomer electricians and pipe 125 00:07:42,360 --> 00:07:44,880 Speaker 1: fitters and so on, who have been retiring over the 126 00:07:44,960 --> 00:07:48,200 Speaker 1: last few years, so that is a scramble on on 127 00:07:48,240 --> 00:07:51,560 Speaker 1: the construction side. On the side of Intel, they have 128 00:07:51,680 --> 00:07:56,680 Speaker 1: to create a whole educational infrastructure in order to find 129 00:07:56,680 --> 00:08:00,960 Speaker 1: these workers. There are no semiconductor engineers being trained at 130 00:08:01,000 --> 00:08:04,640 Speaker 1: Ohio State right now. It's not a program that exists 131 00:08:05,000 --> 00:08:07,880 Speaker 1: because a lot of the semiconductor industry, as we've been 132 00:08:07,920 --> 00:08:11,960 Speaker 1: reading about, is in Taiwan, it's in China, it's other places. 133 00:08:11,960 --> 00:08:15,560 Speaker 1: And that's this whole semiconductor war that we've been hearing about. 134 00:08:15,640 --> 00:08:17,840 Speaker 1: And as you say, it's a big priority of the 135 00:08:17,880 --> 00:08:21,800 Speaker 1: Biden administration to bring that back to the US. Right So, 136 00:08:21,960 --> 00:08:25,560 Speaker 1: Intel is having to spend one hundred million dollars fifty 137 00:08:25,600 --> 00:08:28,440 Speaker 1: million dollars of it in the kind of Ohio area 138 00:08:28,560 --> 00:08:34,120 Speaker 1: in the Midwest, just on education and training, and you know, 139 00:08:34,160 --> 00:08:37,720 Speaker 1: that's the semiconductor engineers. So at Ohio State they are 140 00:08:38,320 --> 00:08:42,120 Speaker 1: trying to create a program with Intel that will generate 141 00:08:42,160 --> 00:08:45,560 Speaker 1: those semiconductor engineers. But then there's also the bulk of 142 00:08:45,600 --> 00:08:48,439 Speaker 1: these jobs are actually jobs that you don't need a 143 00:08:48,480 --> 00:08:52,720 Speaker 1: college degree. For seventy twenty three hundred people who will 144 00:08:52,760 --> 00:08:56,080 Speaker 1: work in that factory will be there with an associate's 145 00:08:56,080 --> 00:08:59,120 Speaker 1: degree or some kind of certificate there, and so they're 146 00:08:59,120 --> 00:09:02,240 Speaker 1: working with community college is there. And we spent time 147 00:09:02,280 --> 00:09:06,120 Speaker 1: with Central Ohio Technical College, and what you find there 148 00:09:06,280 --> 00:09:10,839 Speaker 1: is amazing and that they have a program that trains 149 00:09:10,880 --> 00:09:14,920 Speaker 1: people in kind of electrical engineering technology. It's the basics 150 00:09:15,000 --> 00:09:19,040 Speaker 1: of understanding circuit boards and electricity works. And so they've 151 00:09:19,040 --> 00:09:21,319 Speaker 1: only got one hundred and fifty people in that program 152 00:09:21,440 --> 00:09:25,280 Speaker 1: right now, and it's a part time program to your program, 153 00:09:25,600 --> 00:09:31,679 Speaker 1: how many people do they eventually need until needs twenty three, Sean. 154 00:09:31,760 --> 00:09:34,520 Speaker 1: You spoke with John Barry, who's the president of the 155 00:09:34,600 --> 00:09:38,720 Speaker 1: Central Ohio Technical College, this place that is training up 156 00:09:39,000 --> 00:09:42,400 Speaker 1: workers who will eventually go to work for Intel. Here's 157 00:09:42,400 --> 00:09:45,480 Speaker 1: what he had to say. Intel literally being in my 158 00:09:45,559 --> 00:09:48,960 Speaker 1: backyard from that botascical campus, they are nine minutes and 159 00:09:48,960 --> 00:09:53,920 Speaker 1: twenty eight seconds this boom. This is significantly different than 160 00:09:53,960 --> 00:09:56,640 Speaker 1: I think any of us have ever experienced. And where 161 00:09:56,679 --> 00:09:59,719 Speaker 1: we see it continuing to go, it will be transformed. 162 00:10:00,360 --> 00:10:02,800 Speaker 1: Some of our communities are no longer going to be 163 00:10:02,920 --> 00:10:06,959 Speaker 1: what we'd known them to be. He seems pretty optimistic 164 00:10:07,000 --> 00:10:09,520 Speaker 1: about this. He's got to be optimistic, right, It's his 165 00:10:09,640 --> 00:10:11,920 Speaker 1: job to meet the challenge here and so on. But 166 00:10:11,960 --> 00:10:16,280 Speaker 1: at the same time, he knows that he isn't just 167 00:10:16,480 --> 00:10:20,080 Speaker 1: recruiting people to work in a chip plant. He also 168 00:10:20,080 --> 00:10:23,440 Speaker 1: has a big program training up EMTs and nurses and 169 00:10:23,640 --> 00:10:27,880 Speaker 1: radiology technicians and all of these other careers that are 170 00:10:27,880 --> 00:10:31,719 Speaker 1: in demand in central Ohio that are also facing their 171 00:10:31,760 --> 00:10:37,120 Speaker 1: demographic challenges. Is Intel approaching young people in saying go 172 00:10:37,200 --> 00:10:39,960 Speaker 1: to school, yet you're training and we're going to hire you, 173 00:10:40,120 --> 00:10:42,640 Speaker 1: or are they saying you're hired now, we're going to 174 00:10:42,679 --> 00:10:45,720 Speaker 1: send you to school for now? They are relying on 175 00:10:45,760 --> 00:10:50,000 Speaker 1: the institutions to recruit people, right, So they're helping the 176 00:10:50,080 --> 00:10:54,840 Speaker 1: institutions get people into their programs. Where we go eventually 177 00:10:55,600 --> 00:11:00,200 Speaker 1: is unclear, But you know, Intel is working really really 178 00:11:00,320 --> 00:11:04,480 Speaker 1: hard to build this network of educational institutions, not just 179 00:11:04,559 --> 00:11:06,760 Speaker 1: in the Midwest but around the country. They also have 180 00:11:06,800 --> 00:11:10,079 Speaker 1: a big plant out in Arizona to create these workers 181 00:11:10,080 --> 00:11:14,120 Speaker 1: because without those workers, it can't do what it needs 182 00:11:14,120 --> 00:11:17,199 Speaker 1: to do. And so are these classes that you can 183 00:11:17,240 --> 00:11:19,959 Speaker 1: take to get this technical training the sort of thing 184 00:11:20,000 --> 00:11:21,960 Speaker 1: that you would get and you can go anywhere if 185 00:11:22,000 --> 00:11:25,360 Speaker 1: people are competing, or is this very specifically aimed at 186 00:11:25,400 --> 00:11:28,120 Speaker 1: getting you a job at this plant in this state. 187 00:11:28,559 --> 00:11:32,360 Speaker 1: At the technical college level, these courses are pretty general. 188 00:11:32,520 --> 00:11:37,200 Speaker 1: It's understanding how to use AutoCAD, the kind of design tools, 189 00:11:37,320 --> 00:11:41,280 Speaker 1: understanding how circuit boards are built, and so on. Understanding 190 00:11:41,640 --> 00:11:45,319 Speaker 1: the different technical and I guess I want to say mechanical, 191 00:11:45,360 --> 00:11:48,480 Speaker 1: although it's not mechanical, but you know how to operate robots, 192 00:11:48,480 --> 00:11:51,640 Speaker 1: how to operate machinery, and so on. One student at 193 00:11:51,640 --> 00:11:55,880 Speaker 1: the Central Ohio Technical College is Maddox Curless, and he 194 00:11:55,960 --> 00:11:59,400 Speaker 1: talked to us about all the opportunities he has. If 195 00:11:59,480 --> 00:12:02,240 Speaker 1: I look on the internet, you know, look up engineering 196 00:12:02,280 --> 00:12:07,160 Speaker 1: tech roles, there's a plethora of opportunities out there. And 197 00:12:07,559 --> 00:12:09,800 Speaker 1: you know, there's multiple times I've been over to my 198 00:12:09,840 --> 00:12:12,959 Speaker 1: friend's apartments and we'll just sit there for a couple 199 00:12:13,000 --> 00:12:15,520 Speaker 1: hours and we'll just talk what about this job? What 200 00:12:15,600 --> 00:12:17,760 Speaker 1: about this job? You know they got this you know 201 00:12:17,760 --> 00:12:21,000 Speaker 1: it's dangerous work, but they get paid good. I don't know, 202 00:12:21,160 --> 00:12:24,120 Speaker 1: you know, those conversations happen all the time. You know, 203 00:12:25,400 --> 00:12:27,800 Speaker 1: this is it. The Maddox Cross is twenty years old 204 00:12:28,000 --> 00:12:30,640 Speaker 1: and the world is his oyster. Right. He has all 205 00:12:30,760 --> 00:12:35,079 Speaker 1: of these amazing opportunities, and that's wonderful. And thematics croll list. 206 00:12:35,160 --> 00:12:37,800 Speaker 1: But it also gets at a problem for Intel. It's 207 00:12:37,960 --> 00:12:42,080 Speaker 1: not the only game in town. These young people who 208 00:12:42,160 --> 00:12:46,160 Speaker 1: are coming out of technical colleges like Central Ohio Technical 209 00:12:46,240 --> 00:12:50,000 Speaker 1: College with these skills are in huge demand. Intel is 210 00:12:50,040 --> 00:12:52,400 Speaker 1: going to have to fight for every last one of 211 00:12:52,440 --> 00:12:57,160 Speaker 1: these people. Sean, please stay with me. We'll keep talking 212 00:12:57,280 --> 00:13:08,199 Speaker 1: after the break. Sean, Earlier you talked about how Intel 213 00:13:08,360 --> 00:13:13,280 Speaker 1: is having to essentially steal all of these construction workers 214 00:13:13,320 --> 00:13:16,280 Speaker 1: from other US states. Imagine that's not so popular. There's 215 00:13:16,280 --> 00:13:19,040 Speaker 1: a long history of governors trying to poach industries from 216 00:13:19,080 --> 00:13:21,800 Speaker 1: other states. How are they actually doing it? What is 217 00:13:21,840 --> 00:13:25,240 Speaker 1: their pitch to people from other places? Right? So, I 218 00:13:25,280 --> 00:13:27,760 Speaker 1: mean it used to be that the war between states 219 00:13:28,000 --> 00:13:32,280 Speaker 1: was a war for investment, right and factories. Well, now 220 00:13:32,280 --> 00:13:34,400 Speaker 1: it's kind of a war for people. The people wars 221 00:13:34,400 --> 00:13:38,520 Speaker 1: are here and you can see it in Ohio where 222 00:13:38,880 --> 00:13:41,840 Speaker 1: during the pandemic they were putting up billboards in New 223 00:13:41,920 --> 00:13:46,400 Speaker 1: York City in Austin, Texas kind of making fun of 224 00:13:46,440 --> 00:13:48,360 Speaker 1: the local situation. In New York City. It was a 225 00:13:48,360 --> 00:13:51,240 Speaker 1: billboard that when I'm said, work from home, not a 226 00:13:51,280 --> 00:13:55,160 Speaker 1: tiny studio apartment. In Austin the billboard that went up 227 00:13:55,280 --> 00:13:59,240 Speaker 1: was like keep Austin weird, like weirdly high priced of living, right. 228 00:13:59,280 --> 00:14:05,000 Speaker 1: I mean, the whole idea is pitching an alternative lifestyle 229 00:14:05,520 --> 00:14:09,000 Speaker 1: that is a kind of healthy middle class lifestyle with 230 00:14:09,160 --> 00:14:13,280 Speaker 1: space and with opportunities and so on. But if you 231 00:14:13,280 --> 00:14:16,840 Speaker 1: don't attract those people, you're not going to attract the factories. 232 00:14:16,840 --> 00:14:19,720 Speaker 1: And that's where things have really turned around. Ohio was 233 00:14:19,760 --> 00:14:21,960 Speaker 1: a state that in the last couple of years has 234 00:14:22,000 --> 00:14:24,640 Speaker 1: actually lost population and it was one of twenty four 235 00:14:24,720 --> 00:14:29,440 Speaker 1: states where we saw that phenomenon, and that is really 236 00:14:29,480 --> 00:14:31,840 Speaker 1: going to change the balance of the economy in the 237 00:14:31,920 --> 00:14:35,080 Speaker 1: United States. And that is a kind of existential fight 238 00:14:35,200 --> 00:14:39,560 Speaker 1: between states. I imagine New York and Texas, which are 239 00:14:39,600 --> 00:14:42,640 Speaker 1: being raided by Ohio, are not too happy about it. 240 00:14:42,840 --> 00:14:46,640 Speaker 1: How are they essentially fighting back in the people war, right, Well, 241 00:14:46,640 --> 00:14:50,600 Speaker 1: they're fighting back with their own training programs. So up 242 00:14:50,760 --> 00:14:54,480 Speaker 1: near Syracuse, New York State, has a new semiconductor plant 243 00:14:54,520 --> 00:14:56,880 Speaker 1: coming in where they're facing a lot of the same 244 00:14:57,160 --> 00:15:01,600 Speaker 1: problems in terms of developing people in education and so on. 245 00:15:02,080 --> 00:15:05,080 Speaker 1: You can see in Texas clearly they have been attracting 246 00:15:05,120 --> 00:15:08,440 Speaker 1: a lot of people in recent years they are able 247 00:15:08,480 --> 00:15:12,520 Speaker 1: to offer a housing picture that is easier than the 248 00:15:12,560 --> 00:15:16,360 Speaker 1: suburbs of New York. The theme across the country, though, 249 00:15:16,920 --> 00:15:19,160 Speaker 1: is pretty clear. We have seen for a number of 250 00:15:19,240 --> 00:15:22,960 Speaker 1: years now people moving out of the Northeast and industrial 251 00:15:23,000 --> 00:15:26,840 Speaker 1: Midwest and moving south, and that is changing the balance 252 00:15:26,840 --> 00:15:29,480 Speaker 1: in the economy and that's going to be going on 253 00:15:29,600 --> 00:15:32,040 Speaker 1: for some time. But what we're starting to see now 254 00:15:32,200 --> 00:15:34,800 Speaker 1: is states like Ohio fightback kind of clawback some of 255 00:15:34,800 --> 00:15:38,360 Speaker 1: those people. And it's not just state versus state within 256 00:15:38,440 --> 00:15:42,080 Speaker 1: the US, but it's the US competing for talent, especially 257 00:15:42,680 --> 00:15:45,760 Speaker 1: very highly skilled talent, with other nations around the world. 258 00:15:46,000 --> 00:15:48,640 Speaker 1: Absolutely so, one of the great advantages that the United 259 00:15:48,680 --> 00:15:51,720 Speaker 1: States has had for many decades has been its university 260 00:15:51,720 --> 00:15:56,560 Speaker 1: system and its ability to attract foreign students, particularly in 261 00:15:56,600 --> 00:15:59,560 Speaker 1: science programs and so on. Well, the answer is that 262 00:16:00,200 --> 00:16:04,400 Speaker 1: China and Taiwan and South Korea and Japan have all 263 00:16:04,480 --> 00:16:07,280 Speaker 1: developed their own universities and they're able to keep more 264 00:16:07,280 --> 00:16:10,080 Speaker 1: of their students at home now, which means fewer students 265 00:16:10,080 --> 00:16:12,280 Speaker 1: coming over here. And there is a real war for 266 00:16:12,440 --> 00:16:15,720 Speaker 1: talent going on now. The US may be in a 267 00:16:15,760 --> 00:16:20,480 Speaker 1: better position than some other countries. It's population isn't as 268 00:16:20,560 --> 00:16:24,480 Speaker 1: old as Germany's. Per se we actually saw China lose 269 00:16:24,600 --> 00:16:28,840 Speaker 1: population last year for the first time since the nineteen sixties, 270 00:16:28,880 --> 00:16:32,520 Speaker 1: and that is a much more dramatic picture. But this 271 00:16:32,520 --> 00:16:36,000 Speaker 1: battle isn't going away, and it's a battle between nations, 272 00:16:36,000 --> 00:16:39,560 Speaker 1: a battle within nations, and it's going to be a 273 00:16:39,600 --> 00:16:45,080 Speaker 1: feature of the international economy for decades to come. So, Sean, 274 00:16:45,440 --> 00:16:49,760 Speaker 1: we started out with you describing this demographic problem. There 275 00:16:49,800 --> 00:16:53,360 Speaker 1: are simply fewer people working now and because of all 276 00:16:53,400 --> 00:16:55,360 Speaker 1: of the things you described, there are going to be 277 00:16:55,400 --> 00:16:59,840 Speaker 1: fewer people of working age in the future. So people 278 00:17:00,040 --> 00:17:03,640 Speaker 1: and move around from state to state to fill immediate needs, 279 00:17:03,680 --> 00:17:06,879 Speaker 1: but ultimately there won't be enough people to fill the 280 00:17:06,960 --> 00:17:10,600 Speaker 1: jobs to drive the economy. So what are the solutions here? 281 00:17:11,160 --> 00:17:13,480 Speaker 1: This is where it gets difficult, and this is where 282 00:17:13,480 --> 00:17:17,080 Speaker 1: politics intrude, and this is where the political divisions in 283 00:17:17,119 --> 00:17:24,200 Speaker 1: America intrude on the ability to find solutions. The central problem, 284 00:17:24,440 --> 00:17:26,920 Speaker 1: as we said, is not enough people. There were five 285 00:17:27,040 --> 00:17:31,359 Speaker 1: hundred thousand fewer babies born last year than there were 286 00:17:31,480 --> 00:17:34,879 Speaker 1: eighteen years ago. That means that eighteen years from now 287 00:17:34,960 --> 00:17:37,359 Speaker 1: there will be five hundred thousand fewer eighteen year olds 288 00:17:37,520 --> 00:17:42,080 Speaker 1: unless you add to them via immigration, and that is 289 00:17:42,119 --> 00:17:46,200 Speaker 1: the obvious solution, and we see other countries like Canada 290 00:17:46,320 --> 00:17:51,480 Speaker 1: and Australia going very aggressively after skilled migrants to try 291 00:17:51,480 --> 00:17:54,239 Speaker 1: and welcome them there. In Australia, for example, they have 292 00:17:54,520 --> 00:17:57,760 Speaker 1: a program now whereby if you have a nursing or 293 00:17:57,800 --> 00:18:00,840 Speaker 1: an education job, you can get your visa within three days. 294 00:18:01,560 --> 00:18:06,080 Speaker 1: In Canada, the population last year grew at its fastest 295 00:18:06,160 --> 00:18:09,040 Speaker 1: rate since in the nineteen fifties because of immigration, because 296 00:18:09,040 --> 00:18:11,960 Speaker 1: they welcome the immigration, because they recognize this problem. That 297 00:18:12,119 --> 00:18:14,280 Speaker 1: is not happening in the United States right now. There 298 00:18:14,400 --> 00:18:20,080 Speaker 1: is no constructive debate happening on Capitol Hill about immigration 299 00:18:20,080 --> 00:18:22,600 Speaker 1: reform and how you attract more skilled migrants, how you 300 00:18:22,720 --> 00:18:27,879 Speaker 1: retain PhD students in key areas. In other countries they 301 00:18:27,920 --> 00:18:30,199 Speaker 1: given the equivalent of green cards when they graduate. That 302 00:18:30,280 --> 00:18:32,359 Speaker 1: just does not happen in the United States yet kick 303 00:18:32,440 --> 00:18:35,480 Speaker 1: them out. So that is a fundamental problem. The other 304 00:18:35,520 --> 00:18:39,000 Speaker 1: solutions are even harder in some ways, and that is 305 00:18:39,760 --> 00:18:43,800 Speaker 1: delaying access to social security, making people work longer, which 306 00:18:43,880 --> 00:18:47,760 Speaker 1: is politically unpalatable. We've actually seen that in France, where 307 00:18:47,760 --> 00:18:50,520 Speaker 1: they've tried to extend a retirement age, and people have 308 00:18:50,600 --> 00:18:54,600 Speaker 1: taken to the streets. There are some other ways you 309 00:18:54,640 --> 00:18:57,600 Speaker 1: can try and draw more people into the workforce, like 310 00:18:57,960 --> 00:19:00,760 Speaker 1: offering affordable childcare to try and get more women into 311 00:19:01,160 --> 00:19:04,000 Speaker 1: the workforce, and but again that's something that we haven't 312 00:19:04,040 --> 00:19:08,560 Speaker 1: seen much movement on Capitol Hill. The problem America faces 313 00:19:08,960 --> 00:19:13,480 Speaker 1: is it's got this enormous demographic challenge and it's got 314 00:19:13,520 --> 00:19:20,159 Speaker 1: a political situation right now where it can't actually engage 315 00:19:20,240 --> 00:19:24,480 Speaker 1: with the solutions because they are too toxic for the moment. 316 00:19:25,200 --> 00:19:27,280 Speaker 1: The good news is we are starting to see some 317 00:19:27,480 --> 00:19:31,160 Speaker 1: changes in politics. We're starting to see governors in red 318 00:19:31,280 --> 00:19:35,359 Speaker 1: states like Ohio talk about the need for more sensible 319 00:19:35,400 --> 00:19:39,919 Speaker 1: immigration policy. We're starting to see mayors talk about it. 320 00:19:39,920 --> 00:19:42,680 Speaker 1: I was in a place called Hamilton County, Indiana last 321 00:19:42,760 --> 00:19:46,880 Speaker 1: year where a very Republican mayor was telling me that 322 00:19:46,920 --> 00:19:49,760 Speaker 1: he needs more immigrants in town to fill the gap. 323 00:19:50,680 --> 00:19:54,560 Speaker 1: So the conversation may be changing and that may lead 324 00:19:54,640 --> 00:19:59,040 Speaker 1: us to some solutions. Sean, always great talking to you. 325 00:19:59,119 --> 00:20:01,439 Speaker 1: Thanks so much for coming the show. It's always wonderful 326 00:20:01,480 --> 00:20:04,399 Speaker 1: to be here. Thank you when we come back. The 327 00:20:04,560 --> 00:20:18,040 Speaker 1: Hunt for Tomorrow's workers today. So we've heard how Intel 328 00:20:18,119 --> 00:20:20,800 Speaker 1: needs a lot of workers for the plant it's building 329 00:20:20,880 --> 00:20:24,880 Speaker 1: in Ohio, But where will they come from. Gabriella CRUs 330 00:20:24,920 --> 00:20:28,080 Speaker 1: Thompson is in charge of answering that question. She's the 331 00:20:28,119 --> 00:20:33,200 Speaker 1: company's director of University Research Collaboration, and she joins me, Now, 332 00:20:34,400 --> 00:20:38,760 Speaker 1: so Intel is building this very big chip manufacturing plan 333 00:20:39,320 --> 00:20:43,440 Speaker 1: and you need to fill I believe it's three thousand jobs. 334 00:20:43,920 --> 00:20:47,160 Speaker 1: That is correct. Yes, how are you going about doing that? 335 00:20:47,160 --> 00:20:51,600 Speaker 1: That seems like a really big task. We most importantly 336 00:20:51,800 --> 00:20:56,920 Speaker 1: are working on building up the education pipeline that will 337 00:20:57,040 --> 00:21:01,359 Speaker 1: provide new people to our factor in Ohio. Tell me 338 00:21:01,400 --> 00:21:03,600 Speaker 1: about that. How is that going to work? How do 339 00:21:03,640 --> 00:21:06,600 Speaker 1: you reach out to the community to say, hey, we've 340 00:21:06,600 --> 00:21:10,480 Speaker 1: got really good jobs here. Yeah. Well, as we thought 341 00:21:10,520 --> 00:21:13,920 Speaker 1: about how we build a new factory in the United States, 342 00:21:13,960 --> 00:21:17,639 Speaker 1: which we haven't done in decades, the first thing that 343 00:21:17,720 --> 00:21:20,240 Speaker 1: we realized we needed to do was to reach out 344 00:21:20,280 --> 00:21:25,080 Speaker 1: to the higher education community in Ohio. So even before 345 00:21:25,119 --> 00:21:27,960 Speaker 1: the announcement of the selection of the site, we were 346 00:21:28,040 --> 00:21:32,760 Speaker 1: already having conversations with the universities, with the community colleges, 347 00:21:33,080 --> 00:21:36,640 Speaker 1: even with the K through twelve system, just to make 348 00:21:36,680 --> 00:21:40,240 Speaker 1: sure that the education system as a whole is ready 349 00:21:40,320 --> 00:21:43,960 Speaker 1: to welcome us as a new employer in Ohio. What 350 00:21:44,080 --> 00:21:45,480 Speaker 1: did you tell them You went to them and say, 351 00:21:45,520 --> 00:21:48,199 Speaker 1: we're building this big plant. What was your sort of 352 00:21:48,240 --> 00:21:52,600 Speaker 1: pitch to them, Well, that's it, We're building this big plant. 353 00:21:52,800 --> 00:21:58,360 Speaker 1: We acquire this large amount of land, and for the 354 00:21:58,400 --> 00:22:02,120 Speaker 1: first phase of the project, we expect two factories, two 355 00:22:02,200 --> 00:22:06,400 Speaker 1: buildings will become an existence in then the next three 356 00:22:06,440 --> 00:22:09,840 Speaker 1: to five years. And those two buildings that we committed to, 357 00:22:09,880 --> 00:22:12,639 Speaker 1: those two factories that we were committing to build in 358 00:22:12,680 --> 00:22:19,399 Speaker 1: Ohio will need three thousand employees, full time Intel employees. Gabby, 359 00:22:19,480 --> 00:22:22,439 Speaker 1: when you went to the schools and told them a 360 00:22:22,480 --> 00:22:25,440 Speaker 1: few years, we're going to need employees, but really into 361 00:22:25,480 --> 00:22:29,119 Speaker 1: the future, we're going to need employees. What did you 362 00:22:29,320 --> 00:22:31,960 Speaker 1: ask the schools? What did you want of them to 363 00:22:32,119 --> 00:22:38,040 Speaker 1: prepare their students to potentially become Intel employees. We typically 364 00:22:38,520 --> 00:22:42,639 Speaker 1: discussed us with educators in two cents, we need technical 365 00:22:42,720 --> 00:22:48,480 Speaker 1: skills education in engineering. Most of the engineering disciplines. For example, 366 00:22:48,560 --> 00:22:52,000 Speaker 1: we need electrical engineers, we need chemical engineers, we need 367 00:22:52,040 --> 00:22:55,840 Speaker 1: mechanical engineers. We need even a few computer scientists. We 368 00:22:55,880 --> 00:23:00,640 Speaker 1: need materials engineers. So it's almost the entire breath of 369 00:23:01,280 --> 00:23:06,000 Speaker 1: education in the engineering disciplines. But we also need two 370 00:23:06,119 --> 00:23:10,480 Speaker 1: year associate degrees graduates because most of the people that 371 00:23:10,560 --> 00:23:13,119 Speaker 1: we're going to hire are going to be technicians that 372 00:23:13,160 --> 00:23:16,320 Speaker 1: are in the production floor, and we need them to 373 00:23:16,400 --> 00:23:22,160 Speaker 1: have either two year associates degrees or equivalent experience from 374 00:23:22,200 --> 00:23:26,480 Speaker 1: an existing industry, and we need to give them skills 375 00:23:26,560 --> 00:23:30,440 Speaker 1: so that they can transition into semiconductors. They can transition 376 00:23:30,600 --> 00:23:34,679 Speaker 1: from a factory, a more traditional manufacturing place that exists 377 00:23:34,720 --> 00:23:37,840 Speaker 1: in Ohio today, to working in a clean room in 378 00:23:37,920 --> 00:23:42,280 Speaker 1: a fab creating silicon chips, which is a very advanced 379 00:23:42,280 --> 00:23:48,159 Speaker 1: type of manufacturing. Are you providing resources or money to 380 00:23:48,680 --> 00:23:52,800 Speaker 1: schools to train these students to do this kind of work. 381 00:23:53,280 --> 00:23:57,080 Speaker 1: That is definitely what we decided at the very beginning 382 00:23:57,119 --> 00:24:00,480 Speaker 1: of this program that we needed to do the big 383 00:24:00,520 --> 00:24:03,600 Speaker 1: scheme of things and the long term. We committed to 384 00:24:03,640 --> 00:24:08,000 Speaker 1: invest at least fifty million dollars in Ohio for education. 385 00:24:08,680 --> 00:24:12,320 Speaker 1: So instead of investing the entire fifty million right away, 386 00:24:12,480 --> 00:24:15,640 Speaker 1: we know this as a long term activity, we are 387 00:24:15,760 --> 00:24:19,840 Speaker 1: dividing that fifty million in three phases. Yeah, I mean, 388 00:24:19,840 --> 00:24:22,840 Speaker 1: when you say education, fifty million dollars is a lot 389 00:24:22,880 --> 00:24:24,919 Speaker 1: of money, but how is it divided what does actually 390 00:24:25,040 --> 00:24:29,280 Speaker 1: go for? So we encourage the institutions to work together 391 00:24:29,920 --> 00:24:35,560 Speaker 1: to leverage other programs that exist federal government grants, local 392 00:24:35,680 --> 00:24:41,000 Speaker 1: state government grants, and that they put together groups to 393 00:24:41,080 --> 00:24:44,280 Speaker 1: achieve the different things that we want to achieve. First, 394 00:24:44,359 --> 00:24:50,440 Speaker 1: we are funding opportunities for experiential opportunities for students hands 395 00:24:50,520 --> 00:24:55,800 Speaker 1: on lab activities. So we wanted the institutions to propose 396 00:24:55,880 --> 00:24:59,560 Speaker 1: to us what kind of on hands lab, maybe lab 397 00:24:59,560 --> 00:25:03,280 Speaker 1: equitment and maybe lab experiences they could provide two students. 398 00:25:04,160 --> 00:25:08,280 Speaker 1: We also are providing funding for creating or upgrading curriculum. 399 00:25:08,440 --> 00:25:11,480 Speaker 1: We know that Ohio institutions have not been focused on 400 00:25:11,520 --> 00:25:15,680 Speaker 1: semiconductor manufacturing per se because that didn't exist in Ohio. 401 00:25:16,000 --> 00:25:19,199 Speaker 1: So building up a curriculum that supports the type of 402 00:25:19,320 --> 00:25:22,720 Speaker 1: education we need is part of the grants. The other 403 00:25:22,760 --> 00:25:24,920 Speaker 1: thing that we want to make sure is that we 404 00:25:24,960 --> 00:25:29,840 Speaker 1: provide funding for educating the educators. Right, many professors that 405 00:25:29,880 --> 00:25:33,800 Speaker 1: are in the institutions today they were not delivering content 406 00:25:33,880 --> 00:25:38,440 Speaker 1: on semiconductor manufacturing. So we are providing some financial incentives 407 00:25:38,560 --> 00:25:43,280 Speaker 1: for the professors educations themselves. The institutions came together beautifully. 408 00:25:43,440 --> 00:25:45,840 Speaker 1: I tell you it is so exciting to see. We 409 00:25:45,880 --> 00:25:50,400 Speaker 1: announced in March March seventeenth last year, these grants we're 410 00:25:50,400 --> 00:25:53,280 Speaker 1: going to be released, and I can tell you almost 411 00:25:53,280 --> 00:25:58,040 Speaker 1: a year later, it's so beautiful to see eighty institutions 412 00:25:58,040 --> 00:26:02,000 Speaker 1: working together, Gabby. Earlier, we heard from a young man 413 00:26:02,160 --> 00:26:05,199 Speaker 1: studying at Central Ohio Technical College. That's one of the 414 00:26:05,240 --> 00:26:08,200 Speaker 1: schools where you aim to find employees, and he said 415 00:26:08,400 --> 00:26:12,359 Speaker 1: he and his classmates have many choices of employers, and 416 00:26:12,400 --> 00:26:14,280 Speaker 1: that means, of course that you're going to have competition 417 00:26:14,400 --> 00:26:18,439 Speaker 1: for his talents. What's your pitch to him? Our pitch 418 00:26:18,560 --> 00:26:22,439 Speaker 1: is that we have great benefits, We are a really 419 00:26:22,480 --> 00:26:28,000 Speaker 1: good employer, and it's absolutely fun place to work at Intel. 420 00:26:28,320 --> 00:26:31,359 Speaker 1: The salary of today, the salary that we're going to 421 00:26:31,400 --> 00:26:35,320 Speaker 1: be given to the average employee that we're going to hire, 422 00:26:35,840 --> 00:26:38,520 Speaker 1: is a pretty good salary. One hundred and thirty five 423 00:26:38,600 --> 00:26:41,560 Speaker 1: thousand dollars a year. And that's a starting salary for 424 00:26:41,640 --> 00:26:45,240 Speaker 1: somebody doing what sort of work. That is an average 425 00:26:45,280 --> 00:26:49,760 Speaker 1: starting salary for technicians in our production line. And what 426 00:26:49,960 --> 00:26:53,720 Speaker 1: is a technician? What does a technician do? So technicians 427 00:26:53,800 --> 00:26:55,960 Speaker 1: are the people in charge of making sure that the 428 00:26:56,040 --> 00:27:00,800 Speaker 1: production moves along without any issues and when there are issues, 429 00:27:00,840 --> 00:27:05,400 Speaker 1: because there's production plants always have issues. That they are 430 00:27:05,440 --> 00:27:08,159 Speaker 1: the first line of defense and the first line of 431 00:27:08,280 --> 00:27:12,800 Speaker 1: problems solving in the production. If you see, and there's 432 00:27:12,960 --> 00:27:16,879 Speaker 1: many videos out there of how this production lines are, 433 00:27:17,119 --> 00:27:21,159 Speaker 1: they're mostly fully automated. The materials run between machines in 434 00:27:21,200 --> 00:27:24,240 Speaker 1: an automated fashion, so people are not pushing or doing 435 00:27:24,280 --> 00:27:28,440 Speaker 1: hard work necessarily pushing the material, but people, the technicians 436 00:27:28,480 --> 00:27:32,680 Speaker 1: are fixing the tools that fall out of specifications, if 437 00:27:32,720 --> 00:27:35,919 Speaker 1: you will. So that's the main job of technicians, and 438 00:27:36,040 --> 00:27:39,000 Speaker 1: it's about three quarters of the workforce that we're going 439 00:27:39,040 --> 00:27:41,720 Speaker 1: to be hiring in Ohio. So three quarters of the 440 00:27:41,720 --> 00:27:44,040 Speaker 1: people of the three thousand we talked about will have 441 00:27:44,160 --> 00:27:47,400 Speaker 1: a starting salary of one hundred and thirty five thousand dollars, 442 00:27:47,720 --> 00:27:51,679 Speaker 1: that is correct. And then great benefits, right, great medical benefits, 443 00:27:52,080 --> 00:27:56,480 Speaker 1: great childcare benefits. There's also tuition benefits. So you come 444 00:27:56,520 --> 00:27:59,359 Speaker 1: to ININTIL with a two year degree, we have a 445 00:27:59,400 --> 00:28:02,720 Speaker 1: tuition imbursement program so that you can continue studying if 446 00:28:02,720 --> 00:28:04,920 Speaker 1: you want to become an engineer or if you want 447 00:28:04,960 --> 00:28:09,040 Speaker 1: to learn more about management and become a manager. We've 448 00:28:09,040 --> 00:28:12,159 Speaker 1: been talking a lot about how Intel is trying to 449 00:28:12,160 --> 00:28:15,280 Speaker 1: create this pipeline in Ohio for this plan. But if 450 00:28:15,320 --> 00:28:17,720 Speaker 1: we're just looking at a numbers game, three thousand is 451 00:28:17,760 --> 00:28:21,560 Speaker 1: a lot for that community to create even over time. 452 00:28:22,000 --> 00:28:24,080 Speaker 1: Do you anticipate that you're going to have to lure 453 00:28:24,119 --> 00:28:27,480 Speaker 1: in a lot of employees from other states? We think 454 00:28:27,520 --> 00:28:30,760 Speaker 1: we will need to move, you help people move from 455 00:28:30,760 --> 00:28:32,600 Speaker 1: other states, But I don't think it's going to be 456 00:28:32,640 --> 00:28:34,840 Speaker 1: a lot of people. I think the majority of people 457 00:28:34,960 --> 00:28:38,960 Speaker 1: are going to come from the institutions in Ohio or 458 00:28:39,080 --> 00:28:43,000 Speaker 1: from experienced people that are already in the workforce in Ohio. 459 00:28:43,440 --> 00:28:46,240 Speaker 1: And why do I say that? Back to your question 460 00:28:46,280 --> 00:28:50,160 Speaker 1: about the grants that we gave the institutions, the institutions 461 00:28:50,240 --> 00:28:53,400 Speaker 1: that we provided the funds and that are working and 462 00:28:53,440 --> 00:28:57,800 Speaker 1: then building this workforce pipeline, they are estimating that they 463 00:28:57,840 --> 00:29:01,360 Speaker 1: are going to be educating about nine and people. So 464 00:29:01,600 --> 00:29:04,920 Speaker 1: simple math tells you that we are educating enough people 465 00:29:05,000 --> 00:29:08,760 Speaker 1: for the people that we need to hire in our facilities. However, 466 00:29:09,040 --> 00:29:13,280 Speaker 1: we are very much aware of the needs of our suppliers, 467 00:29:13,400 --> 00:29:16,760 Speaker 1: so not just us Intel as a company, but our 468 00:29:16,800 --> 00:29:20,400 Speaker 1: supply base that all the companies that support our factories. 469 00:29:21,520 --> 00:29:27,800 Speaker 1: How does Intel look at hiring and training today versus say, 470 00:29:27,920 --> 00:29:31,680 Speaker 1: twenty thirty years ago when Intel was building chips in 471 00:29:31,720 --> 00:29:35,520 Speaker 1: the US. Is there a lot that's different. Well, this 472 00:29:36,360 --> 00:29:40,160 Speaker 1: is a very interesting question. Is it different? Yes, there 473 00:29:40,160 --> 00:29:43,160 Speaker 1: are aspects that are very different today than thirty years 474 00:29:43,200 --> 00:29:47,239 Speaker 1: ago or twenty years ago, but there is a fundamental 475 00:29:47,440 --> 00:29:52,600 Speaker 1: similarity which Intel's DNA has always been to work very 476 00:29:52,640 --> 00:29:59,400 Speaker 1: closely with the educators near our operations, our funding executives. 477 00:29:59,680 --> 00:30:04,320 Speaker 1: They we're very close working with University of California at 478 00:30:04,320 --> 00:30:07,840 Speaker 1: Berkeley and Stanford. A lot of the innovation and ideas 479 00:30:07,920 --> 00:30:12,400 Speaker 1: come from working with and talking to academics. That's where 480 00:30:12,440 --> 00:30:15,200 Speaker 1: Until started, you know, more than fifty years ago in 481 00:30:15,240 --> 00:30:18,400 Speaker 1: Silicon Valley, and that's been part of our DNA. So 482 00:30:18,480 --> 00:30:21,440 Speaker 1: twenty years ago or thirty years ago, when we needed 483 00:30:21,520 --> 00:30:24,680 Speaker 1: to hire people, the first place we always go is 484 00:30:24,680 --> 00:30:28,840 Speaker 1: the community colleges and the universities. So in that sense, 485 00:30:29,000 --> 00:30:32,800 Speaker 1: we are using that same playbook in Ohio. However, what 486 00:30:33,000 --> 00:30:36,640 Speaker 1: is different today compared to twenty years ago is that 487 00:30:36,720 --> 00:30:38,680 Speaker 1: we see that there's going to be a huge build 488 00:30:38,760 --> 00:30:44,240 Speaker 1: up of semiconductor manufacturing in the US. Many different companies 489 00:30:44,280 --> 00:30:48,880 Speaker 1: are trying to attract this talent in engineering disciplines. It's 490 00:30:49,000 --> 00:30:53,720 Speaker 1: a broad stroke of all the engineering disciplines, not one 491 00:30:53,840 --> 00:30:57,600 Speaker 1: or two, but basically all. We're also competing for scientists, 492 00:30:58,200 --> 00:31:00,920 Speaker 1: and we realize that we are competing, and we also 493 00:31:01,000 --> 00:31:05,560 Speaker 1: realize that the US needs to produce more scientists, more engineers, 494 00:31:05,760 --> 00:31:09,800 Speaker 1: more technologist. So yes, there is an aspect of competing 495 00:31:09,840 --> 00:31:13,560 Speaker 1: for the person that is graduating today. But there's recognition 496 00:31:13,600 --> 00:31:16,040 Speaker 1: not just at Intel, but at the industry that we 497 00:31:16,160 --> 00:31:19,640 Speaker 1: need to work together to build up that pipeline of 498 00:31:19,760 --> 00:31:23,719 Speaker 1: STEM workers right science and technology and engineering. And we 499 00:31:23,880 --> 00:31:26,800 Speaker 1: need to reach out to high schools and explain to 500 00:31:26,920 --> 00:31:29,840 Speaker 1: high school students what kind of a career you can 501 00:31:29,920 --> 00:31:34,480 Speaker 1: have either being a semiconductor manufacturing person, or being a 502 00:31:34,600 --> 00:31:38,640 Speaker 1: quoder for AI or doing cybersecurity. I mean, all of 503 00:31:38,640 --> 00:31:42,920 Speaker 1: these three topics are major importance to an industry that 504 00:31:43,000 --> 00:31:45,520 Speaker 1: needs to grow in the US, that needs to have 505 00:31:45,720 --> 00:31:49,840 Speaker 1: a very secure footh hall in the US. Gabriella Cruz Thompson, 506 00:31:50,160 --> 00:31:54,960 Speaker 1: thanks so much for talking with me. Thank you thanks 507 00:31:54,960 --> 00:31:56,920 Speaker 1: for listening to us here at the Big Take. It's 508 00:31:56,960 --> 00:32:00,640 Speaker 1: a daily podcast from Bloomberg and iHeartRadio. Shows from my 509 00:32:00,760 --> 00:32:04,880 Speaker 1: Heart Radio, visit the iHeartRadio app, Apple podcast, or wherever 510 00:32:04,960 --> 00:32:07,640 Speaker 1: you listen, and we'd love to hear from you. Email 511 00:32:07,720 --> 00:32:11,120 Speaker 1: us questions or comments to Big Take at bloomberg dot net. 512 00:32:11,720 --> 00:32:15,200 Speaker 1: The supervising producer of The Big Take is Vicky Bergolina. 513 00:32:15,320 --> 00:32:19,040 Speaker 1: Our senior producer is Katherine Fink. Our producers are Michael 514 00:32:19,080 --> 00:32:24,040 Speaker 1: Falerro and Mobarrow. Hilde Garcia is our engineer. Our original 515 00:32:24,120 --> 00:32:27,920 Speaker 1: music was composed by Leo Sidrin. I'm West Kasova. We'll 516 00:32:27,960 --> 00:32:30,040 Speaker 1: be back tomorrow with another Big Take