1 00:00:00,280 --> 00:00:02,840 Speaker 1: Brought to you by the reinvented two thousand twelve camera. 2 00:00:03,160 --> 00:00:06,320 Speaker 1: It's ready, are you hey there, Tech stuff listeners, This 3 00:00:06,440 --> 00:00:09,319 Speaker 1: is Jonathan Strickland, and I wanted to talk to you 4 00:00:09,440 --> 00:00:11,639 Speaker 1: a little bit about something cool going on at how 5 00:00:11,680 --> 00:00:14,040 Speaker 1: stuff works right now. I know all of you guys 6 00:00:14,040 --> 00:00:17,119 Speaker 1: are really creative and you love technology. Well, now you 7 00:00:17,160 --> 00:00:19,720 Speaker 1: can show us what you're made of, because Toyota is 8 00:00:19,720 --> 00:00:22,360 Speaker 1: sponsoring a new photo upload widget over at how stuff 9 00:00:22,360 --> 00:00:27,000 Speaker 1: works dot com. You can share your gadget ideas, modifications, hacks, 10 00:00:27,360 --> 00:00:30,120 Speaker 1: some great tech ideas. Show us what you're made of. 11 00:00:30,200 --> 00:00:32,640 Speaker 1: Let us know how creative you are. You can go 12 00:00:32,720 --> 00:00:37,120 Speaker 1: to www dot how stuff works dot com, slash upgrade 13 00:00:37,159 --> 00:00:39,960 Speaker 1: your tech and upload those photos. Now we want to 14 00:00:40,000 --> 00:00:45,479 Speaker 1: see what you got. Get in touch with technology with 15 00:00:45,640 --> 00:00:54,120 Speaker 1: tech stuff from how stuff works dot com. Hello everyone, 16 00:00:54,120 --> 00:00:56,320 Speaker 1: and welcome to tech stuff. My name is Chris Poulette 17 00:00:56,320 --> 00:00:58,480 Speaker 1: and I am an editor at how stuff works dot com. 18 00:00:58,480 --> 00:01:01,160 Speaker 1: Sitting across from me as usual, a senior writer, Jonathan 19 00:01:01,240 --> 00:01:05,560 Speaker 1: st Hey there, Yeah, today we're today we're gonna talk 20 00:01:05,600 --> 00:01:10,440 Speaker 1: about women in tech. Yeah, we wanted to really kind 21 00:01:10,440 --> 00:01:13,200 Speaker 1: of focus on this because it's an it's a topic 22 00:01:13,280 --> 00:01:16,800 Speaker 1: that I think bears a lot of discussion, and part 23 00:01:16,880 --> 00:01:20,040 Speaker 1: of that is just due to the fact that there 24 00:01:20,080 --> 00:01:24,320 Speaker 1: there are fewer by percentage women in technology roles than 25 00:01:24,319 --> 00:01:26,959 Speaker 1: there are men. And there are a lot of different 26 00:01:26,959 --> 00:01:29,280 Speaker 1: reasons for that. I think one of the big ones 27 00:01:29,440 --> 00:01:33,800 Speaker 1: is there's a there's a social pressure that it is 28 00:01:33,840 --> 00:01:38,520 Speaker 1: not necessarily even a conscious one that tends to guide 29 00:01:39,200 --> 00:01:42,880 Speaker 1: women away from those jobs or men towards those jobs. 30 00:01:43,240 --> 00:01:46,280 Speaker 1: And it's not, you know, it's it has nothing to 31 00:01:46,319 --> 00:01:49,720 Speaker 1: do with a person's ability to hold that job, certainly 32 00:01:49,760 --> 00:01:52,520 Speaker 1: not no matter what their gender is. It's just that 33 00:01:52,520 --> 00:01:55,040 Speaker 1: that's sort of it's almost like the social roles that 34 00:01:55,120 --> 00:01:59,040 Speaker 1: we have set out, and it's slowly breaking down where 35 00:01:59,320 --> 00:02:03,040 Speaker 1: you're seeing a lot of cross pollination across genders in 36 00:02:03,160 --> 00:02:07,040 Speaker 1: both sorts of what nothing. Cross pollination is what you're 37 00:02:07,120 --> 00:02:12,160 Speaker 1: laughing at. I'm talking about jobs here, buddy, jobs. Um, 38 00:02:12,200 --> 00:02:13,919 Speaker 1: but no, you're saying, Okay, So you're seeing a lot 39 00:02:13,960 --> 00:02:20,680 Speaker 1: of people working in roles that perhaps were originally thought 40 00:02:20,720 --> 00:02:24,080 Speaker 1: of as being gender specific or at least dominated by 41 00:02:24,080 --> 00:02:27,639 Speaker 1: a particular gender. Um Now in the field of technology, 42 00:02:27,720 --> 00:02:32,200 Speaker 1: that's still pretty much true for men. There was a 43 00:02:32,320 --> 00:02:35,480 Speaker 1: several articles about how many women hold jobs in in 44 00:02:35,600 --> 00:02:39,919 Speaker 1: the field of technology UH compared to men, And most 45 00:02:39,960 --> 00:02:44,920 Speaker 1: surveys put in that about of all jobs in the 46 00:02:45,000 --> 00:02:49,640 Speaker 1: US anyway revolving around technology, so just one quarter of 47 00:02:49,760 --> 00:02:53,880 Speaker 1: jobs UM, and that if you're looking at the executive level, 48 00:02:54,680 --> 00:02:57,560 Speaker 1: the numbers are even lower. The there's a British tech 49 00:02:57,720 --> 00:03:02,880 Speaker 1: recruitment group called Harvey Nash and their US division held 50 00:03:02,880 --> 00:03:07,560 Speaker 1: a survey and discovered that nine percent of United States 51 00:03:07,680 --> 00:03:13,360 Speaker 1: chief information officers are female so or male UH, and 52 00:03:13,400 --> 00:03:19,399 Speaker 1: that that's actually a smaller percentage than previous year surveys 53 00:03:19,480 --> 00:03:23,919 Speaker 1: had revealed. Back in UH two thousand eleven it was 54 00:03:23,960 --> 00:03:27,160 Speaker 1: eleven percent, and then two thousand and ten it was 55 00:03:27,200 --> 00:03:31,600 Speaker 1: twelve percent. So from twelve to eleven, then from eleven 56 00:03:31,639 --> 00:03:34,240 Speaker 1: to nine, the number appears to be dropping, or at 57 00:03:34,280 --> 00:03:37,480 Speaker 1: least the percentage is dropping. Keep in mind that you know, 58 00:03:37,520 --> 00:03:39,600 Speaker 1: from one year to the next, the number of companies 59 00:03:39,640 --> 00:03:43,600 Speaker 1: could increase, but the number of of women in executive 60 00:03:43,680 --> 00:03:47,680 Speaker 1: roles hasn't increased, and so that way the percentage goes down. Right, 61 00:03:47,720 --> 00:03:49,920 Speaker 1: It's not just necessarily that women are getting out of 62 00:03:49,920 --> 00:03:52,560 Speaker 1: these positions. It may be that there are more positions, 63 00:03:52,600 --> 00:03:58,080 Speaker 1: but same number of women. Um, and that of the 64 00:03:58,280 --> 00:04:01,960 Speaker 1: four this was this was what was really troubling. Of 65 00:04:02,040 --> 00:04:07,040 Speaker 1: the fifty American tech executives polled in the survey said 66 00:04:07,080 --> 00:04:10,200 Speaker 1: they're I T groups have no women at all in 67 00:04:10,280 --> 00:04:16,240 Speaker 1: management positions. And when they were asking the same groups, 68 00:04:17,320 --> 00:04:22,400 Speaker 1: do you feel that women are underrepresented in your department? 69 00:04:23,480 --> 00:04:28,280 Speaker 1: Half of those people said no. So so you've got 70 00:04:28,320 --> 00:04:32,960 Speaker 1: this this of these executives saying there are no women 71 00:04:32,960 --> 00:04:35,480 Speaker 1: in our department. Out of that thirty percent and half 72 00:04:35,480 --> 00:04:38,800 Speaker 1: of those are saying women are not underrepresented, which is 73 00:04:39,200 --> 00:04:45,200 Speaker 1: that's a fairly telling philosophical and social outlook. I think, 74 00:04:45,680 --> 00:04:49,200 Speaker 1: you know, it essentially is saying that these people are saying, 75 00:04:49,240 --> 00:04:53,360 Speaker 1: These men are saying, uh, no, women don't really belong here. 76 00:04:54,279 --> 00:04:56,279 Speaker 1: I mean, it's an a nicer way of saying that, 77 00:04:56,320 --> 00:04:59,120 Speaker 1: but that's effectively what they are saying. Yeah. Well, and 78 00:04:59,120 --> 00:05:02,400 Speaker 1: and of course there could be people who are just uh, 79 00:05:02,560 --> 00:05:05,080 Speaker 1: there could be people in that group who are looking 80 00:05:05,080 --> 00:05:09,240 Speaker 1: around and going, well, of my department is made up 81 00:05:09,240 --> 00:05:12,200 Speaker 1: of women, or you know, or something that seems reasonable 82 00:05:12,240 --> 00:05:14,920 Speaker 1: to them. So you know that that that number might 83 00:05:14,960 --> 00:05:17,920 Speaker 1: be part of it, but probably not all of it. Yeah, 84 00:05:18,320 --> 00:05:20,240 Speaker 1: they're probably quite a few, and yeah, you know what, 85 00:05:20,320 --> 00:05:24,320 Speaker 1: I really don't care who's here, right, And you know, 86 00:05:24,680 --> 00:05:27,120 Speaker 1: ultimately the nice thing would be for us to not 87 00:05:27,400 --> 00:05:29,719 Speaker 1: care who is there as long as they are the 88 00:05:29,800 --> 00:05:34,279 Speaker 1: right person for the job, male or female. Um. But yeah, 89 00:05:34,320 --> 00:05:41,200 Speaker 1: that's so those statistics are a little troubling. But despite 90 00:05:41,240 --> 00:05:44,760 Speaker 1: those statistics, there are plenty of women we can talk 91 00:05:44,800 --> 00:05:50,040 Speaker 1: about who have really, uh made a name for themselves 92 00:05:50,040 --> 00:05:55,279 Speaker 1: in the field of technology and pushed technology forward. Yeah. Actually, 93 00:05:55,440 --> 00:05:58,800 Speaker 1: one of the reasons I wanted to talk about this 94 00:05:59,160 --> 00:06:03,040 Speaker 1: on our podcast was we started talking about Yahoo because 95 00:06:03,040 --> 00:06:04,680 Speaker 1: of a lot of the big changes that have been 96 00:06:04,680 --> 00:06:07,960 Speaker 1: going on over there, and we we did touch on that, um, 97 00:06:08,000 --> 00:06:11,279 Speaker 1: and it was it was the person who has taken 98 00:06:11,320 --> 00:06:16,040 Speaker 1: over the helm over there, Marissa Meyer, who I consider 99 00:06:16,279 --> 00:06:21,880 Speaker 1: one of the you know, really noticeable women in leadership 100 00:06:21,880 --> 00:06:24,880 Speaker 1: positions in technology. And I thought, well, you know, there 101 00:06:24,880 --> 00:06:27,080 Speaker 1: are so many others and we we really haven't done 102 00:06:27,120 --> 00:06:32,320 Speaker 1: a podcast on on them as a group. And many 103 00:06:32,360 --> 00:06:34,080 Speaker 1: of the people, as Jonathan was pointing out to me, 104 00:06:34,400 --> 00:06:37,320 Speaker 1: just in personnel or before we started the podcast, Uh, 105 00:06:37,400 --> 00:06:39,480 Speaker 1: you know, many of these people we could talk about 106 00:06:40,000 --> 00:06:42,839 Speaker 1: uh in their own podcasts do a full episode on 107 00:06:42,880 --> 00:06:45,160 Speaker 1: these women. So this is really kind of an overview, 108 00:06:45,200 --> 00:06:48,760 Speaker 1: but don't don't take away thinking that this is all 109 00:06:48,800 --> 00:06:50,800 Speaker 1: we have to say on the subject of these ladies 110 00:06:51,520 --> 00:06:56,080 Speaker 1: as they are. They're interesting people, and they are holding 111 00:06:56,120 --> 00:06:59,880 Speaker 1: some very important positions in technology, and they are making 112 00:07:00,080 --> 00:07:05,320 Speaker 1: some decisions that are really reflected through technology technological industry 113 00:07:05,320 --> 00:07:08,360 Speaker 1: as a whole, not just of their company. So there's 114 00:07:08,400 --> 00:07:11,480 Speaker 1: definitely the opportunity for us to do future podcasts on 115 00:07:11,600 --> 00:07:13,960 Speaker 1: many of these women. And I do have a secondary 116 00:07:13,960 --> 00:07:15,520 Speaker 1: reason for wanting to do this, and it's it's a 117 00:07:15,560 --> 00:07:19,040 Speaker 1: very personal reason. I have two daughters, both of whom 118 00:07:19,800 --> 00:07:22,800 Speaker 1: uh seem to like technology. They're they're still fairly young, 119 00:07:22,880 --> 00:07:26,680 Speaker 1: but you know, I'm thinking, well, it would be nice if, um, 120 00:07:27,040 --> 00:07:29,520 Speaker 1: they saw a lot of these women that we're going 121 00:07:29,560 --> 00:07:32,600 Speaker 1: to talk about today as role models. You know, maybe 122 00:07:32,600 --> 00:07:35,720 Speaker 1: they don't necessarily want to get into programming or or 123 00:07:35,800 --> 00:07:39,160 Speaker 1: into a technology position, but I want them to see 124 00:07:39,200 --> 00:07:42,160 Speaker 1: that they can, uh, you know, and they're there are 125 00:07:42,160 --> 00:07:46,480 Speaker 1: people who are really setting the bar very high as 126 00:07:46,520 --> 00:07:50,080 Speaker 1: women in technology positions. So you know, personally, I would 127 00:07:50,120 --> 00:07:52,520 Speaker 1: like to see them see this as an opportunity if 128 00:07:52,560 --> 00:07:54,640 Speaker 1: it's something they're interested in later in life. There are 129 00:07:54,640 --> 00:07:57,600 Speaker 1: many women on this list who achieved more by the 130 00:07:57,640 --> 00:08:00,520 Speaker 1: time they were in their mid twenties than I have 131 00:08:00,800 --> 00:08:07,760 Speaker 1: in my final year of my mid thirties. Nice. Well, 132 00:08:07,800 --> 00:08:09,280 Speaker 1: you know, I got to hold onto that as long 133 00:08:09,320 --> 00:08:11,360 Speaker 1: as I possibly can. This is it, this is it 134 00:08:11,440 --> 00:08:13,760 Speaker 1: after you know, next year I'm in my late thirties. 135 00:08:14,000 --> 00:08:16,640 Speaker 1: Well if if some of those people who said that 136 00:08:16,680 --> 00:08:22,280 Speaker 1: they don't see um any discrepancy in the numbers for 137 00:08:22,360 --> 00:08:24,720 Speaker 1: women in technology, I wonder if they know that the 138 00:08:24,840 --> 00:08:28,559 Speaker 1: very first programmer computer programmer was a woman. We actually 139 00:08:28,600 --> 00:08:32,600 Speaker 1: talked about her time ago. Yes, a Lovelace. Yes, we 140 00:08:32,640 --> 00:08:35,240 Speaker 1: had an entire podcast on her as well as I 141 00:08:35,280 --> 00:08:37,560 Speaker 1: think stuff you missed in history class did an episode 142 00:08:37,559 --> 00:08:42,400 Speaker 1: on her. Two fascinating historical figure and an incredibly smart 143 00:08:42,480 --> 00:08:45,800 Speaker 1: woman and uh, incredibly smart human being. I mean that's 144 00:08:45,840 --> 00:08:49,079 Speaker 1: really just a woman. Just sounds like I'm adding a 145 00:08:49,160 --> 00:08:51,760 Speaker 1: qualifier on her, and that's totally not what I mean. 146 00:08:51,880 --> 00:08:55,160 Speaker 1: She was wicked smart. Yeah. Well, I mean, when you're 147 00:08:55,200 --> 00:08:59,280 Speaker 1: writing software for a computer that doesn't actually physically exist, yeah, 148 00:09:00,000 --> 00:09:03,839 Speaker 1: is pretty impressive. Yeah yeah, and it would have worked. Yeah, 149 00:09:03,840 --> 00:09:08,120 Speaker 1: it's kind of crazy. So yeah, these are all amazing 150 00:09:08,160 --> 00:09:09,920 Speaker 1: people that we're gonna be talking about, And now I 151 00:09:09,920 --> 00:09:12,480 Speaker 1: think we should probably start with Marissa Meyer. Even though 152 00:09:12,520 --> 00:09:15,000 Speaker 1: we covered her in the Yahoo podcast, I think it's 153 00:09:15,000 --> 00:09:17,920 Speaker 1: good to remind people who she is and what she's 154 00:09:17,920 --> 00:09:20,920 Speaker 1: accomplished already. And she's one of the things she's accomplished 155 00:09:20,920 --> 00:09:24,080 Speaker 1: that she became the youngest CEO of a fortune company 156 00:09:24,080 --> 00:09:26,679 Speaker 1: once she took over the reins over at Yahoo YEA, 157 00:09:26,800 --> 00:09:30,360 Speaker 1: and she she took over at Will not exactly directly, 158 00:09:30,440 --> 00:09:36,600 Speaker 1: but the Yahoo had had a female CEO UH shortly, 159 00:09:36,640 --> 00:09:41,320 Speaker 1: only maybe months before that, so Carol Carol Bartz, who 160 00:09:41,559 --> 00:09:45,439 Speaker 1: built Autodesk into a very very strong company to um 161 00:09:45,480 --> 00:09:50,280 Speaker 1: and UM. Meyer came from Stanford University where she graduated. 162 00:09:50,320 --> 00:09:52,880 Speaker 1: She had a degree in symbolic systems and a master's 163 00:09:52,920 --> 00:09:56,880 Speaker 1: in computer science, UH, specializing in artificial intelligence. And she 164 00:09:57,240 --> 00:10:00,960 Speaker 1: really made a name for herself over at Goal. You know, 165 00:10:01,080 --> 00:10:03,520 Speaker 1: she became the twentieth employee at Google. She was the 166 00:10:03,559 --> 00:10:06,800 Speaker 1: first female engineer at Google, not the first female employee, 167 00:10:06,800 --> 00:10:11,840 Speaker 1: but the first female engineer, and she ended up heading 168 00:10:11,920 --> 00:10:17,600 Speaker 1: up various parts of their search departments. And UH was 169 00:10:18,120 --> 00:10:21,599 Speaker 1: really well known for doing an excellent job over there. 170 00:10:21,640 --> 00:10:24,920 Speaker 1: Before she ended up leaving Google to become the CEO 171 00:10:25,000 --> 00:10:27,839 Speaker 1: of Yahoo. And it was kind of a remarkable thing, 172 00:10:27,920 --> 00:10:33,480 Speaker 1: really because people who had been very pessimistic about Yahoo's 173 00:10:33,559 --> 00:10:39,480 Speaker 1: chances sort of changed their tune or at least switched 174 00:10:39,520 --> 00:10:43,200 Speaker 1: over to cautious optimism when Meyer came over, because I 175 00:10:43,240 --> 00:10:47,560 Speaker 1: think that she sort of projects this this aura of uh, 176 00:10:47,679 --> 00:10:52,840 Speaker 1: you know, she's got determination, she's got technical skill, She's 177 00:10:53,960 --> 00:10:57,920 Speaker 1: known as a very good public speaker, although there are 178 00:10:58,000 --> 00:11:01,000 Speaker 1: some reports saying that she can be challenging to work with, 179 00:11:01,080 --> 00:11:05,240 Speaker 1: depending upon whom you ask. So there's there's some optimism 180 00:11:05,280 --> 00:11:09,040 Speaker 1: that was not really there for Yahoo among certain people. 181 00:11:09,080 --> 00:11:11,160 Speaker 1: There are plenty of others who are still like, you know, 182 00:11:12,720 --> 00:11:15,000 Speaker 1: Yahoo is is such a mess that it's going to 183 00:11:15,160 --> 00:11:18,080 Speaker 1: take more than just a change in leadership to really 184 00:11:18,120 --> 00:11:20,320 Speaker 1: turn things around. And really, time is the only thing 185 00:11:20,360 --> 00:11:23,480 Speaker 1: that's going to tell us who's right in that case. Yeah, 186 00:11:23,559 --> 00:11:26,640 Speaker 1: Yahoo has been suffering, at least as far as pundits 187 00:11:26,640 --> 00:11:31,440 Speaker 1: are concerned with a UM A lack of compelling product recently. 188 00:11:31,520 --> 00:11:35,040 Speaker 1: I would say, um, based on on what I've read, uh, 189 00:11:35,080 --> 00:11:38,120 Speaker 1: you know, they've they've built themselves into a content powerhouse. 190 00:11:38,800 --> 00:11:43,640 Speaker 1: UM really bring them sort of reinforcing their image as 191 00:11:43,679 --> 00:11:46,960 Speaker 1: a portal as an Internet destination when you're looking for information. 192 00:11:47,600 --> 00:11:51,480 Speaker 1: Um And, uh, you know, as far as as technical 193 00:11:51,520 --> 00:11:56,520 Speaker 1: products have UH been concerned, I would say that that 194 00:11:56,600 --> 00:12:00,319 Speaker 1: Yahoo is sort of uh dated itself and that way 195 00:12:00,360 --> 00:12:03,199 Speaker 1: because a while ago, you know, they were known for 196 00:12:03,200 --> 00:12:07,319 Speaker 1: for their web mail program, for their for their chat. 197 00:12:07,760 --> 00:12:11,920 Speaker 1: But those those things were, you know, long ago. They're 198 00:12:12,280 --> 00:12:14,480 Speaker 1: very very commonplace. Now they haven't done a lot of 199 00:12:14,480 --> 00:12:18,679 Speaker 1: innovation in that sphere. And um and Meyer has led 200 00:12:19,000 --> 00:12:24,160 Speaker 1: Google to launch several products, some of which are admittedly 201 00:12:24,160 --> 00:12:27,160 Speaker 1: no longer with us. But um, you know, she's known 202 00:12:27,200 --> 00:12:30,360 Speaker 1: as someone who can who has the technical background, as 203 00:12:30,360 --> 00:12:33,280 Speaker 1: you said, and can lead in that regard. And I 204 00:12:33,320 --> 00:12:35,480 Speaker 1: think that's that has a lot to do with what 205 00:12:35,559 --> 00:12:40,680 Speaker 1: they feel about Yahoo's rejuvenation. Um And let's let's face it, 206 00:12:40,720 --> 00:12:43,640 Speaker 1: not all of Yahoo's recent uh C e O s 207 00:12:43,720 --> 00:12:49,280 Speaker 1: have been media friendly over the past while. So I 208 00:12:49,280 --> 00:12:54,160 Speaker 1: think she adds she adds that multidimensional up Um, as 209 00:12:54,200 --> 00:12:58,800 Speaker 1: you were saying, sticking with early employees of Google, Yes, 210 00:12:58,880 --> 00:13:04,200 Speaker 1: there's also Susan Wajiski. Yes, and Wajiski is the senior 211 00:13:04,280 --> 00:13:08,040 Speaker 1: vice president of Advertising at Google. Now, folks, that's how 212 00:13:08,120 --> 00:13:11,160 Speaker 1: Google makes the majority of its money, and we're talking 213 00:13:11,280 --> 00:13:17,200 Speaker 1: billions of dollars. It's all in ads. And so Susan 214 00:13:17,360 --> 00:13:22,000 Speaker 1: heads up this, this entire department that is all about, 215 00:13:22,240 --> 00:13:24,719 Speaker 1: you know, generating revenue through advertising. Being a senior vice 216 00:13:24,760 --> 00:13:28,400 Speaker 1: president and that's that's a huge job. And she she 217 00:13:28,559 --> 00:13:33,920 Speaker 1: was the sixteenth employee or sixteenth person hired by Google now. 218 00:13:34,400 --> 00:13:39,800 Speaker 1: Wiki also holds another interesting um title or I guess 219 00:13:39,840 --> 00:13:42,400 Speaker 1: you can't really call it. I guess garage owner isn't 220 00:13:42,440 --> 00:13:46,480 Speaker 1: such a title, huh, but no, wiski is. She's the 221 00:13:46,640 --> 00:13:50,800 Speaker 1: person who owned the garage that Larry Page and Serge 222 00:13:50,960 --> 00:13:55,360 Speaker 1: Brend rented when they first had Google as just a 223 00:13:55,360 --> 00:14:00,600 Speaker 1: couple of computers running their algorithms. So she gave them 224 00:14:00,679 --> 00:14:04,480 Speaker 1: the physical space they needed to house the earliest version 225 00:14:04,480 --> 00:14:08,880 Speaker 1: of Google. So um, without her, Google would have been 226 00:14:08,920 --> 00:14:13,560 Speaker 1: homeless or at least garage less. Yeah. Her, her mom 227 00:14:13,880 --> 00:14:18,320 Speaker 1: esther is an educator, and uh, I actually have been 228 00:14:18,400 --> 00:14:21,520 Speaker 1: sort of following. She's a She's very active in social 229 00:14:21,520 --> 00:14:24,280 Speaker 1: media circles and and posts a lot. And I actually 230 00:14:24,320 --> 00:14:28,240 Speaker 1: sort of came across her through Uh. Susan's sister Anne 231 00:14:28,720 --> 00:14:30,840 Speaker 1: who was one of the founders of twenty three and Me, 232 00:14:30,920 --> 00:14:37,080 Speaker 1: the genetics organization that has popularized uh spitting a cup 233 00:14:37,080 --> 00:14:38,720 Speaker 1: and send it to us and will tell you about 234 00:14:38,760 --> 00:14:41,960 Speaker 1: your genome. Yeah, we'll tell you know, where you descend 235 00:14:42,120 --> 00:14:45,880 Speaker 1: from and whether you have certain genetic markers or not. Yeah, 236 00:14:45,880 --> 00:14:48,560 Speaker 1: it's which I which I think is absolutely fascinating stuff. 237 00:14:48,560 --> 00:14:51,680 Speaker 1: So it's obvious that, uh, the women in that family 238 00:14:51,840 --> 00:14:58,160 Speaker 1: are very interested in science and technology. Um. Also interesting 239 00:14:58,320 --> 00:15:02,680 Speaker 1: is that that and uh it's also married to Sara 240 00:15:02,720 --> 00:15:05,960 Speaker 1: gay Brand. Yeah. So there there's a tight Google connection 241 00:15:06,000 --> 00:15:09,480 Speaker 1: there is, which actually explains why when I was reading 242 00:15:09,520 --> 00:15:12,320 Speaker 1: first reading about twenty three and Me, it was because 243 00:15:12,680 --> 00:15:15,000 Speaker 1: they were interested in you know, he was going, I 244 00:15:15,000 --> 00:15:17,800 Speaker 1: want to know more about my geno. So it's a 245 00:15:18,480 --> 00:15:23,320 Speaker 1: very very tight just that connection to that family and uh, 246 00:15:23,360 --> 00:15:28,960 Speaker 1: you know, just the whole curiosity idea there. So who 247 00:15:29,040 --> 00:15:32,200 Speaker 1: who did you want to talk about next? Well, um, 248 00:15:32,680 --> 00:15:38,360 Speaker 1: let's see, there's a there's a CEO of a president 249 00:15:38,440 --> 00:15:44,600 Speaker 1: CEO of a certain company called HP. Oh, yes, Meg Whitman. Uh. 250 00:15:44,760 --> 00:15:49,520 Speaker 1: Now she has led more than one mega mega size 251 00:15:49,760 --> 00:15:55,240 Speaker 1: tech organization. Yeah. Now she's got a really tough job ahead. 252 00:15:55,240 --> 00:15:58,560 Speaker 1: Of her too, just like Marissa Meyer in that HP 253 00:15:58,800 --> 00:16:04,280 Speaker 1: has had a rough couple of of quarters, really rough 254 00:16:04,320 --> 00:16:08,880 Speaker 1: couple of years through some tough acquisitions that didn't work out. 255 00:16:09,120 --> 00:16:13,080 Speaker 1: I mean Palm being a great example where HP acquired 256 00:16:13,160 --> 00:16:17,240 Speaker 1: Palm and the web Os operating system and then it 257 00:16:17,440 --> 00:16:20,320 Speaker 1: just sort of languished for a while, although there has 258 00:16:20,400 --> 00:16:24,760 Speaker 1: been some recent news about web Os kind of coming 259 00:16:24,760 --> 00:16:28,880 Speaker 1: alive again in a limited capacity. HP is spinning off 260 00:16:29,120 --> 00:16:32,600 Speaker 1: another company that's going to be sent me Independent that 261 00:16:32,720 --> 00:16:36,800 Speaker 1: the web Os will live under. But yes, um, uh, 262 00:16:37,560 --> 00:16:41,360 Speaker 1: she's leading that company. I mean that's a and I 263 00:16:41,360 --> 00:16:45,400 Speaker 1: mean that's one of the big historic companies in technology 264 00:16:45,400 --> 00:16:48,360 Speaker 1: in the United States. M of course we've done an 265 00:16:48,400 --> 00:16:51,280 Speaker 1: episode about it. So yeah, now now she uh, she 266 00:16:51,760 --> 00:16:55,040 Speaker 1: is more of a business person, uh and didn't really 267 00:16:55,080 --> 00:16:58,760 Speaker 1: start in tech. She she has a degree from from 268 00:16:58,800 --> 00:17:03,600 Speaker 1: Princeton You Adversity and an NBA from Harvard Business School. Um. 269 00:17:03,680 --> 00:17:06,480 Speaker 1: And she actually had been working at Procter and Gamble, which, 270 00:17:06,640 --> 00:17:10,280 Speaker 1: if you're not familiar, is a a company that makes 271 00:17:10,320 --> 00:17:13,879 Speaker 1: all kinds of products for the home. That's probably what 272 00:17:13,920 --> 00:17:18,840 Speaker 1: they're best known for, detergent, soaps, um and other kinds 273 00:17:18,840 --> 00:17:21,040 Speaker 1: of and they make tons and tons of different kinds 274 00:17:21,040 --> 00:17:25,040 Speaker 1: of products and they're sold all over the world. She did, however, 275 00:17:25,160 --> 00:17:27,439 Speaker 1: work with that. That that was where she had an 276 00:17:27,440 --> 00:17:29,760 Speaker 1: opportunity to work with someone very famous in tech. And 277 00:17:29,920 --> 00:17:33,760 Speaker 1: do you know about this, the uh somebody else who 278 00:17:33,760 --> 00:17:36,320 Speaker 1: worked at Procter and Gamble before he ran off in 279 00:17:36,440 --> 00:17:41,800 Speaker 1: eight three different detergent brands future Microsoft CEO Steve Balmer, 280 00:17:42,600 --> 00:17:44,440 Speaker 1: which may explain why he was foaming at the mouth. 281 00:17:45,480 --> 00:17:50,000 Speaker 1: But we pick on Steve, but we like Steve anyhow. Yeah, uh, 282 00:17:50,240 --> 00:17:53,199 Speaker 1: Meg Whitman was working at at Procter and Gamble and 283 00:17:53,240 --> 00:17:57,280 Speaker 1: then spent ten years at at eBay, which is how 284 00:17:57,560 --> 00:18:01,119 Speaker 1: I came to know who she was, um and and 285 00:18:01,200 --> 00:18:03,879 Speaker 1: she led it for a long time and uh you know, 286 00:18:04,240 --> 00:18:07,760 Speaker 1: then she got she sort of nurtured a political ambition. 287 00:18:07,960 --> 00:18:12,720 Speaker 1: She uh um decided to uh um run for governor 288 00:18:12,760 --> 00:18:16,080 Speaker 1: of California, which is a small state on the West 289 00:18:16,080 --> 00:18:19,640 Speaker 1: coast of the United States. Yeah, it's um uh. It's 290 00:18:19,720 --> 00:18:24,600 Speaker 1: separated by a northern part that uh is very different 291 00:18:24,600 --> 00:18:27,479 Speaker 1: from the southern part. And boy will they tell you 292 00:18:27,520 --> 00:18:31,840 Speaker 1: about it. Um. But then yeah, after you know, she 293 00:18:31,920 --> 00:18:35,800 Speaker 1: did not get elected, but that did make her available 294 00:18:35,840 --> 00:18:38,960 Speaker 1: to run Hewlett Packard when that job became available. So 295 00:18:39,240 --> 00:18:43,600 Speaker 1: she certainly knows technology and she knows business, so she 296 00:18:43,680 --> 00:18:49,000 Speaker 1: came in to replace Leo uh Appetaker. Yeah. I I 297 00:18:49,080 --> 00:18:51,680 Speaker 1: never can pronounce his name. I've heard his name pronounced 298 00:18:51,720 --> 00:18:53,800 Speaker 1: about a hundred times, and I don't think it was 299 00:18:53,840 --> 00:18:59,320 Speaker 1: pronounced the same way twice Leo A yeah, yes, apothecar. 300 00:18:59,520 --> 00:19:02,280 Speaker 1: If you want to be just terrible about it, Um, 301 00:19:02,480 --> 00:19:04,560 Speaker 1: that's way it looks. Yeah, that's the way. That's the 302 00:19:04,560 --> 00:19:07,280 Speaker 1: way it's spelled. But I believe epic taker is the 303 00:19:07,320 --> 00:19:11,000 Speaker 1: one I've heard the most frequently, so he uh. He 304 00:19:11,200 --> 00:19:14,040 Speaker 1: was the person who was in charge through many of 305 00:19:14,200 --> 00:19:22,120 Speaker 1: the somewhat rocky decisions HP acted upon UH in its 306 00:19:22,160 --> 00:19:26,160 Speaker 1: recent past. But when Whitman took over, she said, this 307 00:19:26,280 --> 00:19:30,159 Speaker 1: is not an indication or an implication that we are 308 00:19:30,160 --> 00:19:34,480 Speaker 1: going to change strategy mid stride. It's a change in leadership, 309 00:19:34,520 --> 00:19:38,119 Speaker 1: but not necessarily of approach. So and that takes a 310 00:19:38,119 --> 00:19:40,280 Speaker 1: lot of guts to do too. I mean it's because 311 00:19:40,320 --> 00:19:43,720 Speaker 1: you know, you've got shareholders to answer for. They say, 312 00:19:43,880 --> 00:19:45,960 Speaker 1: what are you going to do about these decisions? And 313 00:19:46,040 --> 00:19:49,280 Speaker 1: you know, sometimes the answer isn't to just reverse everything 314 00:19:49,280 --> 00:19:51,880 Speaker 1: you're doing, because I can cause even more damage, even 315 00:19:51,920 --> 00:19:55,320 Speaker 1: though that might not make shareholders happy. So, like we said, 316 00:19:55,480 --> 00:19:59,600 Speaker 1: you know, UH Whitman has a really really tough job. 317 00:20:00,200 --> 00:20:02,960 Speaker 1: You know, when you're when you're running a business that 318 00:20:03,080 --> 00:20:06,920 Speaker 1: has as many complexities as HP. How many episodes do 319 00:20:06,960 --> 00:20:10,040 Speaker 1: we do on HP? It was at least two, might 320 00:20:10,119 --> 00:20:13,880 Speaker 1: have been three. Um, you have to I think when 321 00:20:13,880 --> 00:20:16,359 Speaker 1: you're you're being charged with turning the company around, I 322 00:20:16,359 --> 00:20:19,280 Speaker 1: think you have to take your time just simply because uh, 323 00:20:19,960 --> 00:20:22,639 Speaker 1: there's a lot of momentum you've built up behind you. Yeah, 324 00:20:22,720 --> 00:20:26,120 Speaker 1: so you know, she's she's taking her time and going 325 00:20:26,160 --> 00:20:29,000 Speaker 1: piece by piece, and I think that's why people seem 326 00:20:29,119 --> 00:20:32,440 Speaker 1: to feel somewhat confident that that she has a good 327 00:20:32,480 --> 00:20:35,680 Speaker 1: chance of helping out now. Of course, she wasn't the 328 00:20:36,119 --> 00:20:41,360 Speaker 1: only UH woman to lead HP in the past, UH 329 00:20:41,480 --> 00:20:46,439 Speaker 1: Carl Fierina. Actually she she dropped out of law school 330 00:20:46,920 --> 00:20:50,720 Speaker 1: and then joined A T and T um and and 331 00:20:50,720 --> 00:20:55,120 Speaker 1: and she led uh HP for for quite some time too. Um. 332 00:20:55,119 --> 00:20:57,480 Speaker 1: But it's funny because she she started as a sales 333 00:20:57,520 --> 00:20:59,399 Speaker 1: representative at a T and T when she was twenty 334 00:20:59,400 --> 00:21:03,320 Speaker 1: five years old, and UH basically moved on up I 335 00:21:03,320 --> 00:21:06,639 Speaker 1: mean she she was noticed because she knew she seemed 336 00:21:06,640 --> 00:21:09,840 Speaker 1: to know what she was doing. Um, and got generally 337 00:21:09,840 --> 00:21:11,520 Speaker 1: promoted up through the ranks at A T and T 338 00:21:11,760 --> 00:21:15,880 Speaker 1: and at Lucent, which um you know is the technology arm, 339 00:21:16,119 --> 00:21:21,600 Speaker 1: got spun off um over there, and then join HP 340 00:21:21,760 --> 00:21:26,160 Speaker 1: in UM. She was the first woman to start at 341 00:21:26,200 --> 00:21:29,920 Speaker 1: a for fortune company as as the CEO as a 342 00:21:30,000 --> 00:21:34,760 Speaker 1: matter of fact, um and was also a board member 343 00:21:34,800 --> 00:21:38,560 Speaker 1: of Kellogg and Merken company. UM. So she you know, 344 00:21:38,800 --> 00:21:44,439 Speaker 1: had her had a diverse background, not just in technology, um, 345 00:21:44,760 --> 00:21:49,040 Speaker 1: but you know, they she's she's definitely somebody of note 346 00:21:49,080 --> 00:21:52,280 Speaker 1: in tech. Well, speaking of someone else who's of note intech, 347 00:21:52,359 --> 00:21:56,879 Speaker 1: there's Virginia Romady. Oh yes, the first female president and 348 00:21:56,960 --> 00:22:03,719 Speaker 1: CEO of Big Blue IBM how itself. Um, that's just 349 00:22:03,800 --> 00:22:08,440 Speaker 1: a joke. How how even though even though the name 350 00:22:08,520 --> 00:22:12,600 Speaker 1: how is in fact one letter off each from IBM, 351 00:22:12,640 --> 00:22:17,119 Speaker 1: supposedly there's no connection. Uh. So she worked for General 352 00:22:17,160 --> 00:22:21,160 Speaker 1: Motors before she came over to IBM, but is now 353 00:22:21,320 --> 00:22:26,080 Speaker 1: leading that company, and she's credited with, you know, you know, 354 00:22:26,400 --> 00:22:28,840 Speaker 1: at her time at IBM, she's credited with pushing IBM 355 00:22:28,920 --> 00:22:33,320 Speaker 1: into the cloud computing business. And you know that was 356 00:22:33,600 --> 00:22:38,200 Speaker 1: that was a pretty risky maneuver for a company that 357 00:22:38,320 --> 00:22:43,480 Speaker 1: was very much entrenched in just enterprise solutions for companies, 358 00:22:44,080 --> 00:22:48,480 Speaker 1: UM and designing stuff that other manufacturers can by, you know, 359 00:22:48,520 --> 00:22:52,040 Speaker 1: going into the cloud computing business back before it became 360 00:22:52,640 --> 00:22:55,560 Speaker 1: essentially a household term, at least if you're living in 361 00:22:55,560 --> 00:22:57,960 Speaker 1: a geeky household, it was. You know, it was a 362 00:22:57,960 --> 00:23:01,960 Speaker 1: pretty big move. And she was also instrumental in maneuvering 363 00:23:02,480 --> 00:23:10,000 Speaker 1: IBMS Watson, which is the Jeopardy playing computer, into other 364 00:23:10,200 --> 00:23:15,159 Speaker 1: uses like she helped push to have Watson developed for 365 00:23:16,640 --> 00:23:20,000 Speaker 1: things like the medical field, which that was the intention 366 00:23:20,240 --> 00:23:24,000 Speaker 1: from the beginning for Watson, but she helped create those 367 00:23:24,040 --> 00:23:29,119 Speaker 1: those relationships and leverage that so that what it was 368 00:23:29,160 --> 00:23:32,280 Speaker 1: designed for and what it does is the same thing 369 00:23:32,720 --> 00:23:36,919 Speaker 1: that doesn't always happen. And technology, you'll often see companies 370 00:23:36,960 --> 00:23:41,040 Speaker 1: develop something with the with a with a very specific purpose, 371 00:23:41,440 --> 00:23:44,280 Speaker 1: and yet because it's a technology company and that purpose 372 00:23:44,320 --> 00:23:48,480 Speaker 1: may actually lie outside the realm of just whatever it 373 00:23:48,520 --> 00:23:52,080 Speaker 1: is that company generally does, it never goes anywhere. And 374 00:23:52,200 --> 00:23:54,280 Speaker 1: you have to be able to create these relationships and 375 00:23:54,400 --> 00:23:58,040 Speaker 1: leverage them so that you can get this product where 376 00:23:58,080 --> 00:23:59,720 Speaker 1: it needs to go. So it can do what it 377 00:23:59,760 --> 00:24:03,040 Speaker 1: was signed to do and UH and from what I've read, 378 00:24:03,760 --> 00:24:07,920 Speaker 1: she was very much instrumental in making that happen. UM. 379 00:24:07,960 --> 00:24:13,480 Speaker 1: Also also of notice Ursula Burns, the chairman and CEO 380 00:24:13,640 --> 00:24:18,520 Speaker 1: of Xerox. Yes, yes, another big big name and technology 381 00:24:18,560 --> 00:24:24,040 Speaker 1: absolutely UM. Yeah. In in in addition to UH being notable 382 00:24:24,119 --> 00:24:27,040 Speaker 1: for being a female CEO of a tech company, she 383 00:24:27,119 --> 00:24:30,639 Speaker 1: is also the first African American woman to run a 384 00:24:30,720 --> 00:24:35,160 Speaker 1: major public corporation in the United States. UM. And she 385 00:24:35,440 --> 00:24:37,480 Speaker 1: had had a big job in front of her too, 386 00:24:37,520 --> 00:24:42,520 Speaker 1: because of course, with computer technology changing the way we 387 00:24:42,520 --> 00:24:48,040 Speaker 1: we all work. UM. Xerox, which that heavily on its 388 00:24:48,119 --> 00:24:53,840 Speaker 1: duplication systems, UM had to compete with not only other people, 389 00:24:53,880 --> 00:24:57,679 Speaker 1: but they had to compete with UH organizations that they 390 00:24:57,720 --> 00:25:00,520 Speaker 1: didn't necessarily have to compete with in prior decades, So 391 00:25:00,560 --> 00:25:04,000 Speaker 1: they had to do a lot of shifting and UM 392 00:25:04,080 --> 00:25:08,920 Speaker 1: basically she's absolutely you know, she's got a lot of 393 00:25:08,960 --> 00:25:14,280 Speaker 1: credit for leading Xerox UH to gradually shifting over to 394 00:25:14,480 --> 00:25:18,800 Speaker 1: two new industries. From what I've read, UM, she she 395 00:25:18,920 --> 00:25:21,960 Speaker 1: actually also is a part of the White House's program 396 00:25:22,000 --> 00:25:25,480 Speaker 1: on STEM Education, which is a science, Technology, engineering, and 397 00:25:25,560 --> 00:25:28,720 Speaker 1: mathematics um and as part of as the vice share 398 00:25:28,720 --> 00:25:32,200 Speaker 1: of the President's Export Council as well. Um but yeah, 399 00:25:32,200 --> 00:25:34,720 Speaker 1: she's a she's also has a hand in tech. She's 400 00:25:34,760 --> 00:25:38,560 Speaker 1: not just a business person, she um um is into 401 00:25:38,560 --> 00:25:40,679 Speaker 1: the technology side as well, and then she worked her 402 00:25:40,680 --> 00:25:43,080 Speaker 1: way up to the top. Yeah, and you know, Xerox 403 00:25:43,200 --> 00:25:46,160 Speaker 1: has a long history of innovation as well. Yes, so 404 00:25:46,400 --> 00:25:50,159 Speaker 1: we for those of us who have only been alive 405 00:25:50,240 --> 00:25:52,520 Speaker 1: for the last couple of decades, you may not realize 406 00:25:52,520 --> 00:25:57,160 Speaker 1: that Xerox goes far beyond the copy machine, right because 407 00:25:57,240 --> 00:26:00,840 Speaker 1: zero that that's what we think of. I'd i'd argue 408 00:26:00,840 --> 00:26:02,760 Speaker 1: that's what most people think of when they hear Xerox. 409 00:26:02,800 --> 00:26:04,720 Speaker 1: In fact, it's it's one of those terms that's become 410 00:26:04,800 --> 00:26:08,119 Speaker 1: so universal that's become a generic term for a copy machine, 411 00:26:08,119 --> 00:26:11,120 Speaker 1: a Xerox machine, to the company's chagrin. Right, just like 412 00:26:11,200 --> 00:26:14,560 Speaker 1: you know, clean ex, band aids, Jello, etcetera. These are 413 00:26:14,600 --> 00:26:17,960 Speaker 1: all companies that have had products that become so well 414 00:26:18,000 --> 00:26:21,480 Speaker 1: known that they became the generic term for that whatever 415 00:26:21,520 --> 00:26:24,040 Speaker 1: it was. There's a whole list out there, Google it. Yeah, 416 00:26:24,280 --> 00:26:28,000 Speaker 1: there you go, there's a good one. Um So anyway, Yeah, 417 00:26:28,280 --> 00:26:32,920 Speaker 1: Xerox was has has always been a company that's really 418 00:26:32,960 --> 00:26:36,679 Speaker 1: been known for innovation. I mean, thanks to Xerox, we 419 00:26:36,800 --> 00:26:40,600 Speaker 1: have things like graphical user interfaces and the computer mouse. 420 00:26:41,240 --> 00:26:45,800 Speaker 1: These came out of the research and development departments within Xerox. 421 00:26:46,040 --> 00:26:50,600 Speaker 1: So it's a company that already has a history with innovation. 422 00:26:50,680 --> 00:26:55,240 Speaker 1: It's good to see a new focus on that as well. 423 00:26:55,320 --> 00:26:58,000 Speaker 1: And that innovation may come in the form of technology, 424 00:26:58,320 --> 00:27:01,080 Speaker 1: or it may come in the form of they're innovative 425 00:27:01,080 --> 00:27:03,960 Speaker 1: in that they're getting into fields that they haven't done before. 426 00:27:04,400 --> 00:27:08,200 Speaker 1: The important thing is to really embrace that. And she can't. 427 00:27:08,240 --> 00:27:09,920 Speaker 1: Like I said, she came up through the ranks too, 428 00:27:09,920 --> 00:27:12,840 Speaker 1: so she's not somebody that they brought in to handle 429 00:27:12,880 --> 00:27:16,200 Speaker 1: this job. She earned it. Yeah, inside well, not that 430 00:27:16,200 --> 00:27:18,800 Speaker 1: that isn't earning it, but she earned it working her 431 00:27:18,800 --> 00:27:23,280 Speaker 1: way up through the company, which I yeah, I I. 432 00:27:24,000 --> 00:27:26,879 Speaker 1: You know, there's not to take away from anyone who 433 00:27:27,119 --> 00:27:31,080 Speaker 1: makes their way in in whatever business and then comes 434 00:27:31,160 --> 00:27:33,160 Speaker 1: over to become a leader of something else. I mean, 435 00:27:33,200 --> 00:27:36,199 Speaker 1: obviously that in itself is a really tough thing to 436 00:27:36,240 --> 00:27:38,679 Speaker 1: do and it takes a very special person to do that. 437 00:27:38,760 --> 00:27:41,320 Speaker 1: But yeah, fearinga over at a T and T and 438 00:27:41,400 --> 00:27:43,760 Speaker 1: Lusen and then coming over to HP. That don't mean 439 00:27:43,800 --> 00:27:46,880 Speaker 1: to disparage that at all, but to rise up from 440 00:27:46,920 --> 00:27:49,520 Speaker 1: the ranks. Yeah. No, that's a great story because it 441 00:27:49,600 --> 00:27:52,760 Speaker 1: not only means that they have the ability to lead, 442 00:27:52,880 --> 00:27:55,760 Speaker 1: but that they actually have that history with the company 443 00:27:55,800 --> 00:27:59,359 Speaker 1: and that you get a feeling that that's someone who 444 00:28:01,080 --> 00:28:04,439 Speaker 1: the philosophy of the company, of the mission statement of 445 00:28:04,440 --> 00:28:06,880 Speaker 1: the company is more than just words on paper. It's 446 00:28:06,960 --> 00:28:11,479 Speaker 1: someone who has really believed in that. Because trust me, 447 00:28:11,520 --> 00:28:13,399 Speaker 1: I mean, when you're looking at people who are leading 448 00:28:13,400 --> 00:28:17,120 Speaker 1: a company, you have to realize these are people who 449 00:28:17,160 --> 00:28:21,080 Speaker 1: have had opportunities to leave and go somewhere else and 450 00:28:21,119 --> 00:28:24,280 Speaker 1: do something big, but they chose to stay with that company. 451 00:28:25,200 --> 00:28:31,399 Speaker 1: That's a huge statement too. Yeah, she's she's definitely a 452 00:28:31,440 --> 00:28:35,520 Speaker 1: fascinating uh person, And I'm somebody I don't think you 453 00:28:35,560 --> 00:28:37,560 Speaker 1: don't hear her name like you do some of the 454 00:28:37,600 --> 00:28:43,560 Speaker 1: other leaders of corporations out there, so I wanted to 455 00:28:43,600 --> 00:28:46,120 Speaker 1: make sure we talked about her. There's the co founder 456 00:28:46,280 --> 00:28:51,920 Speaker 1: of HTC ah Yeah, share Wong and Uh there's somebody 457 00:28:51,920 --> 00:28:53,959 Speaker 1: else who you don't hear. Yeah, you don't hear her 458 00:28:54,040 --> 00:28:58,360 Speaker 1: name very very frequently. And she's an extremely wealthy woman, 459 00:29:00,200 --> 00:29:03,160 Speaker 1: but she was one of the co founders for HTC 460 00:29:03,760 --> 00:29:07,160 Speaker 1: and HTC recently, HTC has been having a pretty rough 461 00:29:07,200 --> 00:29:10,200 Speaker 1: time in the United States in particular, But for a 462 00:29:10,200 --> 00:29:14,600 Speaker 1: while HTC was really an up and coming, like they 463 00:29:14,640 --> 00:29:18,120 Speaker 1: seemed to come out nowhere, right. I had never even 464 00:29:18,200 --> 00:29:21,840 Speaker 1: heard of HTC before the first Android phone in the 465 00:29:21,920 --> 00:29:25,240 Speaker 1: United States, the g one. When when there was the 466 00:29:25,360 --> 00:29:29,880 Speaker 1: HTCG one. When that launched, I I thought, h t S, 467 00:29:30,080 --> 00:29:32,320 Speaker 1: I don't know who this is. And I looked into 468 00:29:32,360 --> 00:29:34,400 Speaker 1: it and said, well, you know they've got you know this, 469 00:29:34,560 --> 00:29:38,320 Speaker 1: they designed mobile hardware. It's I'll give it a try. 470 00:29:38,440 --> 00:29:41,240 Speaker 1: And then I was really taken with the form factor 471 00:29:41,240 --> 00:29:44,240 Speaker 1: and I very much enjoyed that phone, and in fact, 472 00:29:44,800 --> 00:29:50,120 Speaker 1: I currently use an HTC phone as my phone. UM so, yeah, 473 00:29:50,640 --> 00:29:54,280 Speaker 1: they went from a name that in the United States 474 00:29:54,320 --> 00:29:57,840 Speaker 1: had next to no recognition to becoming a dominant player 475 00:29:57,880 --> 00:30:02,760 Speaker 1: in the smartphone space, uh, very very quickly. Now recently 476 00:30:02,920 --> 00:30:07,280 Speaker 1: that that landscape has changed somewhat, I would argue that 477 00:30:07,360 --> 00:30:10,360 Speaker 1: the dominant players in the smartphone space right now are 478 00:30:10,520 --> 00:30:13,960 Speaker 1: well Apple, because Apple has been since the instruction of 479 00:30:14,000 --> 00:30:17,080 Speaker 1: the iPhone. In fact, one could argue that Apple is 480 00:30:17,200 --> 00:30:20,240 Speaker 1: the company. In fact, I don't even think you have 481 00:30:20,240 --> 00:30:23,840 Speaker 1: to argue with Apple is the company that made smartphones 482 00:30:23,920 --> 00:30:26,720 Speaker 1: a popular choice for consumers in the United States. You know, 483 00:30:26,880 --> 00:30:29,320 Speaker 1: professionals had been using them for a while, but they 484 00:30:29,360 --> 00:30:33,560 Speaker 1: hadn't really made a a break in the consumer market 485 00:30:33,640 --> 00:30:38,520 Speaker 1: until the iPhone. But HTC was then a pretty heavy competitor. Recently, 486 00:30:38,560 --> 00:30:41,960 Speaker 1: I'd say that Apple and Samsung are probably the two 487 00:30:42,400 --> 00:30:44,600 Speaker 1: dominant players in that space in the United States. But 488 00:30:44,800 --> 00:30:48,920 Speaker 1: HTC is still producing lots of different handsets and for 489 00:30:49,160 --> 00:30:53,280 Speaker 1: many different UM carriers, so you can find it across 490 00:30:53,280 --> 00:30:56,560 Speaker 1: different carriers. It's not like it's a specific one. And 491 00:30:56,600 --> 00:31:00,360 Speaker 1: I know you You also wanted to mention Saffra Cats. Yes, 492 00:31:01,160 --> 00:31:05,560 Speaker 1: who is the president of Oracle Um She uh she 493 00:31:05,720 --> 00:31:09,200 Speaker 1: has a uh A law degree from the University of 494 00:31:09,200 --> 00:31:14,280 Speaker 1: Pennsylvania UM and uh A b A and BS from 495 00:31:15,040 --> 00:31:20,080 Speaker 1: University of Pennsylvania's Wharton School, which is a prestigious business school. Um. 496 00:31:20,200 --> 00:31:24,080 Speaker 1: Yeah she she actually um had been CFO of the 497 00:31:24,120 --> 00:31:27,760 Speaker 1: company from two thousand five to two thousand eight UM 498 00:31:27,840 --> 00:31:31,560 Speaker 1: and then had you know, chief financial office. Yes, that's good, 499 00:31:31,600 --> 00:31:34,640 Speaker 1: thank you. I'm usually the one who does that, but 500 00:31:35,200 --> 00:31:36,920 Speaker 1: you know, this is This is another name that may 501 00:31:36,920 --> 00:31:38,800 Speaker 1: not be familiar to our listeners, but she had been 502 00:31:38,840 --> 00:31:41,680 Speaker 1: at the company for quite some time and uh it 503 00:31:41,880 --> 00:31:47,320 Speaker 1: was you know, definitely actually since and had been very 504 00:31:47,360 --> 00:31:51,360 Speaker 1: instrumental in the company's success. Now. Oracle is another is 505 00:31:51,360 --> 00:31:54,960 Speaker 1: one of those tech companies too that it powers a 506 00:31:54,960 --> 00:31:58,120 Speaker 1: lot of stuff, but the average person on the street 507 00:31:58,200 --> 00:32:00,240 Speaker 1: may not necessarily know who. We're gonna have to do 508 00:32:00,280 --> 00:32:02,600 Speaker 1: an episode on Oracle at some point. Well, then there's 509 00:32:02,640 --> 00:32:05,000 Speaker 1: Larry Ellison. Yeah, I need to do an episode on 510 00:32:05,000 --> 00:32:07,800 Speaker 1: an Oracle, need to do an episode on Cisco. I mean, 511 00:32:07,840 --> 00:32:10,720 Speaker 1: there's some big companies that are really important in technology 512 00:32:10,760 --> 00:32:13,240 Speaker 1: that you know, anyone who works in tech, they know 513 00:32:13,320 --> 00:32:15,840 Speaker 1: the name yea. But for the rest of us who 514 00:32:15,920 --> 00:32:18,080 Speaker 1: might be interested in technology, but we don't live in 515 00:32:18,080 --> 00:32:21,440 Speaker 1: that world necessarily. These names are the ones we've heard, 516 00:32:21,480 --> 00:32:25,480 Speaker 1: but we don't really have a Like they do something 517 00:32:25,520 --> 00:32:29,120 Speaker 1: with computers, like that's that's what it Our knowledge tends 518 00:32:29,160 --> 00:32:31,360 Speaker 1: to boil down to. So we'll have to do episodes 519 00:32:31,400 --> 00:32:36,880 Speaker 1: that focus on these companies. Um. Yeah, So actually that's 520 00:32:36,880 --> 00:32:39,280 Speaker 1: a good point because I I didn't collect a lot 521 00:32:39,320 --> 00:32:43,360 Speaker 1: of notation on Sandy Lerner from Cisco but she was 522 00:32:43,360 --> 00:32:47,400 Speaker 1: one of the founders of Cisco. Um. That's funny. There's 523 00:32:47,400 --> 00:32:49,880 Speaker 1: always somebody else that I want to do these that 524 00:32:49,960 --> 00:32:51,840 Speaker 1: I go, oh, yeah, I will say I will say 525 00:32:51,840 --> 00:32:54,480 Speaker 1: something about someone who works at Cisco, a woman who 526 00:32:54,520 --> 00:33:00,160 Speaker 1: holds a leadership position there. Oh, Kathy O'Connell. Yes, us 527 00:33:00,160 --> 00:33:04,480 Speaker 1: the communications director at Cisco. So it's her job to 528 00:33:04,520 --> 00:33:09,520 Speaker 1: be able to communicate with the public about what Cisco does. 529 00:33:10,040 --> 00:33:13,320 Speaker 1: You know, why it's important, the developments that the company 530 00:33:13,400 --> 00:33:15,880 Speaker 1: is making, and be able to explain the technology in 531 00:33:15,880 --> 00:33:19,160 Speaker 1: a way that the lay person can understand. And I 532 00:33:19,360 --> 00:33:23,160 Speaker 1: had the pleasure of being on a panel with Kathy 533 00:33:23,200 --> 00:33:27,880 Speaker 1: O'Connell at an event called the Engage Dig Day this year. 534 00:33:27,960 --> 00:33:30,120 Speaker 1: It was earlier this year that this year being two 535 00:33:30,160 --> 00:33:32,440 Speaker 1: thousand and twelve. For those of you who are listening 536 00:33:32,480 --> 00:33:37,240 Speaker 1: in the future, Hi, do we have jet packs yet? Anyway, 537 00:33:37,320 --> 00:33:40,440 Speaker 1: Cathy o'con and I appeared on a panel about the 538 00:33:40,480 --> 00:33:45,160 Speaker 1: Internet of Things, which we've done an episode on. But yeah, 539 00:33:45,160 --> 00:33:49,520 Speaker 1: that concept of Internet connections that go beyond a mobile 540 00:33:49,520 --> 00:33:53,360 Speaker 1: device or a laptop when you're at a hot spot 541 00:33:53,480 --> 00:33:57,600 Speaker 1: or whatever. It's it's where the Internet has incorporated lots 542 00:33:57,600 --> 00:34:01,000 Speaker 1: of different data gathered from sensors could be in anything 543 00:34:01,240 --> 00:34:07,760 Speaker 1: from a security camera to your refrigerator, to your television 544 00:34:07,920 --> 00:34:12,560 Speaker 1: to whatever. And uh So we had this discussion and 545 00:34:12,640 --> 00:34:16,040 Speaker 1: it was absolutely fascinating and it was a real pleasure 546 00:34:16,080 --> 00:34:20,000 Speaker 1: meeting her and hearing her perspectives on what the future 547 00:34:20,040 --> 00:34:22,600 Speaker 1: holds as far as the Internet of Things is concerned. 548 00:34:23,200 --> 00:34:26,360 Speaker 1: Um So, I wanted to mention her since you had 549 00:34:27,160 --> 00:34:30,360 Speaker 1: since we both talked about Cisco there briefly, it was 550 00:34:30,440 --> 00:34:33,359 Speaker 1: just a personal connection. The other women that are on 551 00:34:33,400 --> 00:34:38,160 Speaker 1: this list I have never uh personally met. I admire them, 552 00:34:38,200 --> 00:34:41,960 Speaker 1: but I've never met them. Um Oh, there's someone I 553 00:34:41,960 --> 00:34:44,799 Speaker 1: wanted to mention, Elizabeth Barron. I don't know. Did you 554 00:34:44,880 --> 00:34:49,319 Speaker 1: run across this name? Yeah. So she's a technical specialist 555 00:34:50,080 --> 00:34:53,640 Speaker 1: who works for the Ford Motor Company and her specialty 556 00:34:53,880 --> 00:35:00,120 Speaker 1: is virtual reality. So, um I was reading about her 557 00:35:00,160 --> 00:35:02,759 Speaker 1: and the thing that was interesting was, well, a couple 558 00:35:02,760 --> 00:35:05,239 Speaker 1: of different things were interesting. First of all, she gave 559 00:35:05,239 --> 00:35:07,960 Speaker 1: her background about how she got interested in the whole 560 00:35:08,320 --> 00:35:11,719 Speaker 1: virtual reality field in the first place. Uh And I 561 00:35:12,040 --> 00:35:15,719 Speaker 1: can actually quote here she says, basically, I am a 562 00:35:15,760 --> 00:35:18,080 Speaker 1: geek by nature. When I was young, I love gizmos, 563 00:35:18,080 --> 00:35:21,239 Speaker 1: photography and science. I was fascinated by the physics of light, 564 00:35:21,719 --> 00:35:24,800 Speaker 1: color and optical properties. I learned the art and science 565 00:35:24,800 --> 00:35:27,680 Speaker 1: of developing and printing photographs. I followed that calling and 566 00:35:27,719 --> 00:35:30,440 Speaker 1: it led to an education and career in computer graphics. 567 00:35:30,920 --> 00:35:33,799 Speaker 1: So here's someone who's looks at light and says, that's 568 00:35:33,800 --> 00:35:36,200 Speaker 1: really cool. I want to know everything there is to know, 569 00:35:37,200 --> 00:35:40,120 Speaker 1: which is I mean, curiosity is one of those traits 570 00:35:40,160 --> 00:35:43,880 Speaker 1: that I find personally one of the that's one of 571 00:35:43,960 --> 00:35:48,560 Speaker 1: my favorite traits in human Yeah, just the human experience 572 00:35:49,120 --> 00:35:53,080 Speaker 1: is the desire to know and to discover, and she 573 00:35:53,200 --> 00:35:57,239 Speaker 1: certainly embodies that. And she talked about how it was 574 00:35:57,239 --> 00:36:01,239 Speaker 1: a real challenge to get a virtual reality department within 575 00:36:01,320 --> 00:36:03,400 Speaker 1: the Ford Motor Company. When she got there, it was 576 00:36:03,440 --> 00:36:07,160 Speaker 1: hard to convince people that this was a valuable asset 577 00:36:07,239 --> 00:36:10,680 Speaker 1: to the company. And she managed to get a small 578 00:36:10,719 --> 00:36:15,440 Speaker 1: amount of funding and it was, you know, just barely 579 00:36:15,520 --> 00:36:17,759 Speaker 1: enough to get moving, but she kept pushing and she 580 00:36:17,920 --> 00:36:22,760 Speaker 1: got it together, and she showed that this immersive virtual 581 00:36:22,800 --> 00:36:26,839 Speaker 1: reality environment could be a very valuable tool when you're 582 00:36:26,840 --> 00:36:31,200 Speaker 1: developing vehicles that you know, with a very sophisticated simulator model, 583 00:36:31,800 --> 00:36:34,640 Speaker 1: you can really test stuff out before you ever get 584 00:36:34,680 --> 00:36:38,120 Speaker 1: to the actual physical prototype stage where you're really committing 585 00:36:38,200 --> 00:36:40,960 Speaker 1: lots of money to a project. So if you can 586 00:36:41,000 --> 00:36:43,600 Speaker 1: test it in a virtual environment, then you say, you know, 587 00:36:43,719 --> 00:36:47,240 Speaker 1: this design is great, except that according to this virtual model, 588 00:36:48,120 --> 00:36:53,640 Speaker 1: there's a killer blind spot that I just can't fix here, 589 00:36:53,800 --> 00:36:57,279 Speaker 1: I mean the physical If we if we represent, you know, 590 00:36:57,440 --> 00:37:00,680 Speaker 1: create a physical model based upon this, uh, that's gonna 591 00:37:00,680 --> 00:37:02,799 Speaker 1: be a serious problem. So maybe we should rethink that 592 00:37:02,880 --> 00:37:06,040 Speaker 1: now before we ever build anything, before it really becomes 593 00:37:06,080 --> 00:37:10,040 Speaker 1: a killer problem. I I feel like our discussion would 594 00:37:10,040 --> 00:37:14,160 Speaker 1: be remiss if we didn't mention Cheryl Sandberg, the CEO 595 00:37:14,280 --> 00:37:19,600 Speaker 1: of Facebook chief operating officer. Uh. She that's again not 596 00:37:19,800 --> 00:37:24,759 Speaker 1: her only tech uh job. She wasn't had a minor 597 00:37:24,880 --> 00:37:28,880 Speaker 1: role as vice president of Global Online Sales and Operations 598 00:37:28,880 --> 00:37:31,640 Speaker 1: at Google. She may have heard of that company. She's 599 00:37:31,680 --> 00:37:34,840 Speaker 1: also she was also the chief of staff to the 600 00:37:34,960 --> 00:37:39,319 Speaker 1: United States Secretary of the Treasury back in uh from 601 00:37:39,400 --> 00:37:41,759 Speaker 1: ninety six to two thousand one, where she was just 602 00:37:41,800 --> 00:37:46,239 Speaker 1: trying to solve tiny little problems like um forgiving debt 603 00:37:46,320 --> 00:37:51,880 Speaker 1: in the developing world. Well you know, she's tiny, tiny issue. 604 00:37:52,200 --> 00:37:54,719 Speaker 1: Well then there you know her credentials, you know, or 605 00:37:54,880 --> 00:37:58,240 Speaker 1: it's just a master's degree in Business Administration and MBA 606 00:37:58,800 --> 00:38:03,360 Speaker 1: with highest distinction from Harvard Business School and suma koum laude. 607 00:38:03,760 --> 00:38:07,239 Speaker 1: That's Latin for you can't get any higher than this 608 00:38:07,800 --> 00:38:12,120 Speaker 1: degree in economics from Harvard. So she seems reasonably qualified. 609 00:38:13,040 --> 00:38:18,800 Speaker 1: I think reasonably qualified is an appropriate explanation of her abilities. Yeah. Actually, 610 00:38:18,880 --> 00:38:21,439 Speaker 1: though she's a she's another one of those people that, 611 00:38:22,200 --> 00:38:25,279 Speaker 1: even though she's not the CEO of the company, she 612 00:38:25,440 --> 00:38:30,680 Speaker 1: has She's also been sort of a standout in the media. Um, 613 00:38:30,800 --> 00:38:34,680 Speaker 1: she has spoken for for Facebook on several occasions. She's 614 00:38:34,719 --> 00:38:37,759 Speaker 1: somebody where they know whose whose face I have seen 615 00:38:37,800 --> 00:38:40,760 Speaker 1: in the news and um, you know, they do employ 616 00:38:40,800 --> 00:38:44,439 Speaker 1: her as a spokesperson from time to time. Uh that 617 00:38:44,480 --> 00:38:47,000 Speaker 1: would follow as her role as chief operating officer. But 618 00:38:48,280 --> 00:38:52,440 Speaker 1: they obviously feel qualified that she's qualified to be a 619 00:38:52,560 --> 00:38:56,520 Speaker 1: leader and uh as a spokesperson for the company. And 620 00:38:56,840 --> 00:39:02,040 Speaker 1: someone else who is uh fascinating person involved with technology. 621 00:39:02,120 --> 00:39:06,720 Speaker 1: She didn't make her name and engineering but Melinda Gates 622 00:39:06,840 --> 00:39:09,839 Speaker 1: to who met some guy at the company she worked 623 00:39:09,840 --> 00:39:13,279 Speaker 1: for and decided to marry him Billy. Yeah, but she 624 00:39:14,320 --> 00:39:19,680 Speaker 1: has has been involved with product development at Microsoft. UM 625 00:39:19,760 --> 00:39:22,759 Speaker 1: and uh she uh she married Bill Gates and in 626 00:39:22,880 --> 00:39:27,799 Speaker 1: ninety four and uh basically after that, um really known 627 00:39:27,840 --> 00:39:31,560 Speaker 1: for philanthropic work, yes, and has really built the Bill 628 00:39:31,600 --> 00:39:35,680 Speaker 1: and Melinda Gates Foundation into one of the world's leading 629 00:39:36,000 --> 00:39:42,200 Speaker 1: philanthropic organizations. It's absolutely phenomenal, absolutely um. So uh you know, 630 00:39:42,440 --> 00:39:45,120 Speaker 1: and she's just that she's an interesting lady too. Just 631 00:39:45,200 --> 00:39:48,720 Speaker 1: doing a little reading about her, she's a really cool 632 00:39:48,800 --> 00:39:51,120 Speaker 1: person to to get to know. Not that I know 633 00:39:51,200 --> 00:39:53,680 Speaker 1: her personally, but from what from what I freaking what 634 00:39:53,719 --> 00:39:57,120 Speaker 1: we can glean. Um. And I'd also like to mention 635 00:39:57,600 --> 00:40:03,520 Speaker 1: another programmer for the Navy Rear, Admiral Grace Murray Hopper. Wow, 636 00:40:03,600 --> 00:40:07,560 Speaker 1: I didn't come across this, oh you Uh. Born in 637 00:40:08,160 --> 00:40:13,520 Speaker 1: nine six, she graduated from Vasser in got her PhD 638 00:40:13,560 --> 00:40:17,480 Speaker 1: in math from Yale in ninety four. Um. She actually 639 00:40:18,080 --> 00:40:21,480 Speaker 1: was a professor at Vasser for a while and joined 640 00:40:21,520 --> 00:40:25,280 Speaker 1: the Naval Reserve, so she was a backup belly button. Uh. 641 00:40:25,560 --> 00:40:28,839 Speaker 1: She was a lieutenant junior grade in in ninety four 642 00:40:28,880 --> 00:40:33,040 Speaker 1: and and became uh part of the Bureau of Ordnance 643 00:40:33,760 --> 00:40:38,920 Speaker 1: and uh started working on the electronic computer. I'm surprised 644 00:40:38,920 --> 00:40:42,799 Speaker 1: you don't know Dr Hopper's name actually because she is 645 00:40:42,800 --> 00:40:48,799 Speaker 1: the person who discovered the first computer bug. Literally they 646 00:40:48,840 --> 00:40:53,160 Speaker 1: still have it. It was a moth caught in between 647 00:40:53,360 --> 00:40:56,200 Speaker 1: relay number seventy panel F of the Mark two ake 648 00:40:56,280 --> 00:40:59,360 Speaker 1: and relay calculator when they were testing it at Harvard 649 00:40:59,520 --> 00:41:05,640 Speaker 1: on set number nine, and they actually found a bug, 650 00:41:05,880 --> 00:41:09,120 Speaker 1: a moth in the machine removed it. As I recall, 651 00:41:09,200 --> 00:41:12,439 Speaker 1: we actually talked about this. We did, we did, and 652 00:41:12,600 --> 00:41:15,439 Speaker 1: uh they still they have a record of it being 653 00:41:15,600 --> 00:41:19,560 Speaker 1: debugged with the moth taped to the paper and we 654 00:41:19,640 --> 00:41:23,080 Speaker 1: still use that term today. Yes, it was at the 655 00:41:23,200 --> 00:41:27,040 Speaker 1: Naval Surface Surface Warfare Center Computer Museum in Dahlgren, Virginia. 656 00:41:27,080 --> 00:41:30,880 Speaker 1: You can actually see the first computer bug, which I 657 00:41:30,880 --> 00:41:34,920 Speaker 1: imagine is a bit crunchy by this time. But um, 658 00:41:34,960 --> 00:41:39,719 Speaker 1: absolutely one of the world's first practical programmers. I don't 659 00:41:39,719 --> 00:41:43,160 Speaker 1: mean to take that away from Ada Lovelace, but uh, 660 00:41:43,400 --> 00:41:49,160 Speaker 1: definitely involved in early early actual electronic computing. UM and 661 00:41:49,440 --> 00:41:54,879 Speaker 1: a fascinating person on her on her own. UM. So yeah, 662 00:41:54,920 --> 00:41:57,680 Speaker 1: she retired in UH in nineteen sixty six, but then 663 00:41:57,920 --> 00:42:01,000 Speaker 1: went back into active duty. So she she finally retired 664 00:42:01,640 --> 00:42:04,880 Speaker 1: UM from the Navy as a rear admiral and in 665 00:42:05,360 --> 00:42:09,440 Speaker 1: five and was still active in industry and education according 666 00:42:09,440 --> 00:42:13,440 Speaker 1: to her biography as of when she when she passed away. 667 00:42:13,560 --> 00:42:18,520 Speaker 1: So really really cool person that most people, again have 668 00:42:18,680 --> 00:42:20,560 Speaker 1: no idea who she is. But if you want to 669 00:42:20,560 --> 00:42:23,240 Speaker 1: know who invented the computer bug, what was the bug itself, 670 00:42:23,280 --> 00:42:27,600 Speaker 1: but she helped discover it. There's some women that I 671 00:42:27,640 --> 00:42:32,840 Speaker 1: think we should mention because they specifically make it a 672 00:42:33,000 --> 00:42:38,640 Speaker 1: priority to try and promote the tech technology industry to 673 00:42:39,000 --> 00:42:43,239 Speaker 1: other women, and to to promote science education, you know 674 00:42:43,320 --> 00:42:46,480 Speaker 1: that STEM education you were talking about earlier, really pushing 675 00:42:46,520 --> 00:42:49,239 Speaker 1: that so that so that women who are interested in 676 00:42:49,280 --> 00:42:52,279 Speaker 1: this don't feel like they're that like one, that they 677 00:42:52,320 --> 00:42:55,399 Speaker 1: stand out, or that they're unusual. There's nothing unusual about it, 678 00:42:56,520 --> 00:42:59,840 Speaker 1: or that there's, you know, anything weird about pursuing that 679 00:43:00,080 --> 00:43:02,560 Speaker 1: they shouldn't feel weird about it, and that they should 680 00:43:02,600 --> 00:43:06,560 Speaker 1: have every opportunity to pursue that because frankly, the world 681 00:43:06,600 --> 00:43:10,399 Speaker 1: needs gifted people in these fields. That's what we need. 682 00:43:10,719 --> 00:43:13,280 Speaker 1: So if there's someone who's interested in it, they should 683 00:43:13,400 --> 00:43:16,359 Speaker 1: certainly pursue it. So there are a few women who 684 00:43:16,440 --> 00:43:19,880 Speaker 1: have really gone out of their way to make organizations 685 00:43:20,440 --> 00:43:25,240 Speaker 1: that are supportive of other women who are either seeking 686 00:43:25,360 --> 00:43:27,759 Speaker 1: a job in the tech industry or who already have 687 00:43:27,840 --> 00:43:31,680 Speaker 1: a job in the tech industry. UM. Carolyn Layton is 688 00:43:31,680 --> 00:43:34,560 Speaker 1: one of those. She's a founder of the Women in 689 00:43:34,640 --> 00:43:38,680 Speaker 1: Technology International organization and that coordinates events for women who 690 00:43:38,680 --> 00:43:43,760 Speaker 1: are interested or employed within technology fields. UH. There's Alison 691 00:43:44,160 --> 00:43:47,439 Speaker 1: Capin who is the founder of Women Who Tech, which 692 00:43:47,480 --> 00:43:53,080 Speaker 1: is another organization. They hold events that have panels discussing 693 00:43:53,200 --> 00:43:57,799 Speaker 1: various uh topics within the field of technology that specifically 694 00:43:57,800 --> 00:44:02,040 Speaker 1: pertained to women, but also go beyond the whole gender 695 00:44:02,120 --> 00:44:07,120 Speaker 1: question as well. So these are and there are plenty 696 00:44:07,120 --> 00:44:10,200 Speaker 1: of other examples. Those are two that I specifically just 697 00:44:10,239 --> 00:44:14,160 Speaker 1: pulled out from my list who have worked hard to 698 00:44:14,200 --> 00:44:19,400 Speaker 1: try and promote technology as a viable pursuit for women 699 00:44:19,600 --> 00:44:22,600 Speaker 1: who are interested in it. Yeah, I've I've seen uh 700 00:44:22,920 --> 00:44:29,560 Speaker 1: more tech camps promoted and opportunities for kids actually of 701 00:44:29,640 --> 00:44:33,640 Speaker 1: both genders. UM, but you know, specifically for girls to 702 00:44:33,840 --> 00:44:38,520 Speaker 1: to to get involved in learning how to program uh, 703 00:44:38,600 --> 00:44:43,600 Speaker 1: for people to um um get into making. As a 704 00:44:43,600 --> 00:44:47,680 Speaker 1: matter of fact, I recommend checking out on YouTube super 705 00:44:47,719 --> 00:44:52,759 Speaker 1: Awesome Sylvia's show. UM. She's a young lady who is 706 00:44:52,880 --> 00:44:56,360 Speaker 1: into making her own electronics. Her dad is a I believe, 707 00:44:56,360 --> 00:45:00,640 Speaker 1: a podcaster on his own tech podcaster. Um. And she 708 00:45:00,680 --> 00:45:03,200 Speaker 1: has a show where she teaches, you know, she shows 709 00:45:03,239 --> 00:45:06,359 Speaker 1: how to make to build different kits. Um. She will 710 00:45:06,400 --> 00:45:09,759 Speaker 1: warn you that soldering can be dangerous, which is good um. 711 00:45:10,120 --> 00:45:13,240 Speaker 1: And just I just love seeing kids who are interested 712 00:45:13,280 --> 00:45:16,520 Speaker 1: in it, but especially, like I said, young women, probably 713 00:45:16,560 --> 00:45:20,200 Speaker 1: because of my own uh, my own kids. UM. But 714 00:45:20,920 --> 00:45:24,080 Speaker 1: I'm glad to see that, well you think about it, technology, 715 00:45:24,800 --> 00:45:29,040 Speaker 1: electronic technology and computers is still even in its uh 716 00:45:29,280 --> 00:45:32,440 Speaker 1: formed as we know it now, still a very young industry. 717 00:45:32,560 --> 00:45:35,120 Speaker 1: So I'm I'm glad to see that there are more 718 00:45:35,120 --> 00:45:39,680 Speaker 1: people encouraging kids to get involved, especially girls and young women. 719 00:45:40,120 --> 00:45:45,680 Speaker 1: And uh, I'm sure that the disparity between the genders, 720 00:45:46,239 --> 00:45:48,319 Speaker 1: you know, as years go on, is going to uh 721 00:45:48,640 --> 00:45:52,320 Speaker 1: to even out more. I certainly hope so, uh you know, 722 00:45:52,400 --> 00:45:55,080 Speaker 1: I I frankly sometimes I get a little worried about 723 00:45:55,400 --> 00:45:59,120 Speaker 1: STEM education across the board here in the United States, 724 00:45:59,160 --> 00:46:04,120 Speaker 1: not know, not just directed toward towards women, but you know, 725 00:46:04,239 --> 00:46:06,800 Speaker 1: just just the state, just the state of STEM education 726 00:46:06,800 --> 00:46:10,440 Speaker 1: in the United States at all. So I hope to 727 00:46:10,560 --> 00:46:14,279 Speaker 1: see more kids interested in science and I think I 728 00:46:14,360 --> 00:46:16,360 Speaker 1: actually do. And and part of it is because we 729 00:46:16,400 --> 00:46:18,920 Speaker 1: have we live in a in an era of incredible 730 00:46:18,960 --> 00:46:23,400 Speaker 1: scientific discovery, and I think that's helping encourage kids to 731 00:46:23,480 --> 00:46:26,360 Speaker 1: look into it more, which means that we have to 732 00:46:26,440 --> 00:46:30,560 Speaker 1: create the programs that support this because one, we're gonna 733 00:46:30,640 --> 00:46:32,279 Speaker 1: need it in the future. And too, that's what the 734 00:46:32,360 --> 00:46:36,120 Speaker 1: kids need, that's what they want. So and I say 735 00:46:36,120 --> 00:46:40,719 Speaker 1: that as a liberal arts graduate, I'm a I'm an 736 00:46:40,719 --> 00:46:44,480 Speaker 1: English major. What do you do with a BA in English? 737 00:46:44,960 --> 00:46:50,319 Speaker 1: The digital humanities? Yes? So, uh, Like we said, this 738 00:46:50,400 --> 00:46:52,719 Speaker 1: was just sort of an overview of some of the 739 00:46:53,040 --> 00:46:57,560 Speaker 1: the amazing women who have really led the technological industry 740 00:46:57,600 --> 00:47:01,600 Speaker 1: over the last several years. And there are so many more. 741 00:47:02,480 --> 00:47:06,840 Speaker 1: We could do easily a two hour long podcast just 742 00:47:06,960 --> 00:47:11,120 Speaker 1: talking about a handful of them. And as we said before, 743 00:47:11,239 --> 00:47:15,000 Speaker 1: many of these women deserve an entire episode in their 744 00:47:15,640 --> 00:47:17,919 Speaker 1: of their own just to really cover everything that they've 745 00:47:17,920 --> 00:47:22,399 Speaker 1: done and the contributions they've made. Two women and to technology. Yeah, 746 00:47:22,400 --> 00:47:24,719 Speaker 1: and this is keep in mind that this is not 747 00:47:24,800 --> 00:47:29,360 Speaker 1: to to um to disparage anyone who uh is in 748 00:47:29,480 --> 00:47:33,080 Speaker 1: programming or somebody you know, in in a different role 749 00:47:33,120 --> 00:47:35,800 Speaker 1: in the tech industry. We we picked out people who 750 00:47:36,080 --> 00:47:40,680 Speaker 1: have become notable, uh you know, noticeable really, I guess 751 00:47:41,400 --> 00:47:45,280 Speaker 1: through their their roles as leaders in their or organizations. 752 00:47:45,280 --> 00:47:48,000 Speaker 1: But there are women at many levels in all kinds 753 00:47:48,000 --> 00:47:51,160 Speaker 1: of tech companies who should be lauded for, uh for 754 00:47:51,200 --> 00:47:53,520 Speaker 1: what they do because they play an important role. So 755 00:47:54,400 --> 00:47:56,600 Speaker 1: one of them, Yeah, exactly. My wife works in the 756 00:47:56,640 --> 00:48:02,000 Speaker 1: technology field. She holds a very technical position at a 757 00:48:02,120 --> 00:48:05,160 Speaker 1: very large company. And moreover than that, I think my 758 00:48:05,160 --> 00:48:06,880 Speaker 1: wife needs to be lauded for the fact that she 759 00:48:06,880 --> 00:48:09,120 Speaker 1: hasn't yet to strangle me. Yeah. I was going to 760 00:48:09,200 --> 00:48:11,279 Speaker 1: mention that, but I'm glad you brought it up. Yeah. Yeah, 761 00:48:11,520 --> 00:48:14,040 Speaker 1: my coworkers feel like strangling me, and they spend a 762 00:48:14,080 --> 00:48:16,239 Speaker 1: fraction of the amount of time that my wife has 763 00:48:16,280 --> 00:48:19,640 Speaker 1: to spend with me, So that's saying something. So yeah, 764 00:48:19,640 --> 00:48:22,040 Speaker 1: I'm I'm glad we we touched on on some of these, 765 00:48:22,080 --> 00:48:24,319 Speaker 1: and I think, uh, several of these people, as you 766 00:48:24,360 --> 00:48:27,640 Speaker 1: said earlier, to might might be good subjects for future 767 00:48:27,640 --> 00:48:31,120 Speaker 1: podcasts on some of the tech biographies that you're doing. Yeah, 768 00:48:31,280 --> 00:48:33,960 Speaker 1: so we will probably revisit some of these in the future, certainly. 769 00:48:34,040 --> 00:48:36,600 Speaker 1: So I would like to recommend to any of our 770 00:48:36,640 --> 00:48:39,359 Speaker 1: listeners out there. If there's someone in particular you would 771 00:48:39,400 --> 00:48:42,640 Speaker 1: like us to talk about in the future episode, let's know. 772 00:48:42,920 --> 00:48:45,960 Speaker 1: Or if there's just some other specific topic that you 773 00:48:46,000 --> 00:48:49,640 Speaker 1: are dying to hear about, let us know a send 774 00:48:49,640 --> 00:48:51,919 Speaker 1: as an email or I just as tech stuff at 775 00:48:51,960 --> 00:48:54,800 Speaker 1: discovery dot com, or drop us a line on Twitter 776 00:48:54,920 --> 00:48:58,160 Speaker 1: or Facebook. Are handled. There is text stuff hs W 777 00:48:58,480 --> 00:49:00,399 Speaker 1: and Chris and I will talk to you again really 778 00:49:00,480 --> 00:49:04,240 Speaker 1: soon for more on this and thousands of other topics. 779 00:49:04,400 --> 00:49:10,839 Speaker 1: Does it staff works dot com. See guys, I told 780 00:49:10,840 --> 00:49:13,480 Speaker 1: you we talked to you again really soon. That really 781 00:49:13,520 --> 00:49:16,600 Speaker 1: soon is right now. I'm just reminding you that we 782 00:49:16,680 --> 00:49:19,520 Speaker 1: have our photo upload widget live on the site at 783 00:49:19,640 --> 00:49:22,920 Speaker 1: www dot how stuff works dot com. Slash upgrade your 784 00:49:23,000 --> 00:49:25,640 Speaker 1: tech Toyota is giving us the chance to let you 785 00:49:25,760 --> 00:49:30,000 Speaker 1: share your creativity. So send us those pictures of your modifications, 786 00:49:30,040 --> 00:49:33,400 Speaker 1: your tech ideas, those gadgets that you've created, all those hacks. 787 00:49:33,640 --> 00:49:37,160 Speaker 1: If you're steampunking everything in sight, put on your goggles 788 00:49:37,160 --> 00:49:40,120 Speaker 1: and show that to us. We can't wait to see them. 789 00:49:40,280 --> 00:49:42,880 Speaker 1: Brought to you by the reinvented two thousand twelve camera. 790 00:49:43,160 --> 00:49:44,399 Speaker 1: It's ready, are you