1 00:00:03,200 --> 00:00:06,480 Speaker 1: Welcome to stuff Mom never told you. From how Supports 2 00:00:06,519 --> 00:00:14,720 Speaker 1: dot com. Hello, and welcome to the podcast. I'm Kristen 3 00:00:14,840 --> 00:00:17,919 Speaker 1: and I'm Caroline, and this is the e in our 4 00:00:18,120 --> 00:00:22,880 Speaker 1: STEM series, which means we're talking about engineering today. That's right, 5 00:00:22,920 --> 00:00:26,240 Speaker 1: there's only one more episode left in our four part series, 6 00:00:26,280 --> 00:00:28,720 Speaker 1: which would be not yes, don't forget to tune back 7 00:00:28,720 --> 00:00:30,760 Speaker 1: in for that one, but for this one, we are 8 00:00:30,800 --> 00:00:35,920 Speaker 1: talking about the very multifaceted, surprisingly multifaceted. I'm sorry to 9 00:00:35,920 --> 00:00:38,640 Speaker 1: say that I did not realize that field of engineering. 10 00:00:38,840 --> 00:00:41,760 Speaker 1: And to keep things off with a fun linguistic fact 11 00:00:41,760 --> 00:00:45,960 Speaker 1: about engineering, It is derived from the Latin word ingenium, 12 00:00:46,000 --> 00:00:51,159 Speaker 1: which means skills, genius, and invention, no pressure. Isn't that beautiful? 13 00:00:51,240 --> 00:00:54,520 Speaker 1: That is beautiful? Who knew there was such beauty in 14 00:00:54,960 --> 00:00:59,279 Speaker 1: the very word engineering? But who also knew that there 15 00:00:59,320 --> 00:01:01,840 Speaker 1: were so many different aspects to it? Like I just said, 16 00:01:01,960 --> 00:01:06,520 Speaker 1: I mean, I engineering people out there are are engineering listeners. 17 00:01:06,560 --> 00:01:08,760 Speaker 1: I want to hear about all the different things that 18 00:01:08,800 --> 00:01:11,400 Speaker 1: you do, because there are so many different areas that 19 00:01:11,600 --> 00:01:14,560 Speaker 1: engineering majors can pursue. And I think what we're going 20 00:01:14,600 --> 00:01:16,960 Speaker 1: to get into a little bit is talking about the 21 00:01:17,000 --> 00:01:20,039 Speaker 1: importance of educating our students, not just our girls, but 22 00:01:20,080 --> 00:01:22,480 Speaker 1: our boys too, about the different options that they have 23 00:01:22,640 --> 00:01:25,560 Speaker 1: available to them once they go to college and pick 24 00:01:25,600 --> 00:01:29,480 Speaker 1: a specialization. Number one. One of the specializations that my 25 00:01:29,640 --> 00:01:34,440 Speaker 1: friend Clay, for instance, has pursued is civil engineering. UM. 26 00:01:34,440 --> 00:01:37,759 Speaker 1: That's one of the oldest disciplines within the engineering profession 27 00:01:37,760 --> 00:01:41,240 Speaker 1: and deals with designing and creating infrastructure like roads, bridges, 28 00:01:41,280 --> 00:01:44,240 Speaker 1: and ports, as well as energy and water systems. And 29 00:01:44,280 --> 00:01:48,120 Speaker 1: then there's things like mechanical engineering, which designs and analyzes 30 00:01:48,200 --> 00:01:52,600 Speaker 1: objects and systems in motion. You have environmental engineers who 31 00:01:52,600 --> 00:01:56,520 Speaker 1: work more outside looking at man's impact on nature, doing 32 00:01:56,560 --> 00:02:01,680 Speaker 1: things like restoration of areas after natural disasters. Then there's 33 00:02:01,760 --> 00:02:05,560 Speaker 1: biomedical engineering. This is one that has been really popular 34 00:02:05,640 --> 00:02:09,519 Speaker 1: of late to with women in college because it takes 35 00:02:09,720 --> 00:02:14,919 Speaker 1: the traditional engineering expertise and applies it to biology and medicine. 36 00:02:14,919 --> 00:02:18,760 Speaker 1: This is where you get into making life saving devices 37 00:02:18,840 --> 00:02:21,720 Speaker 1: like pacemakers. Yeah, and it's a field that I think 38 00:02:21,760 --> 00:02:24,400 Speaker 1: really takes a lot of flexibility and the ability to 39 00:02:24,480 --> 00:02:26,400 Speaker 1: kind of roll with the punches, because I think in 40 00:02:26,880 --> 00:02:31,079 Speaker 1: biomedical engineering in particular, you're you're really kind of creating 41 00:02:31,120 --> 00:02:34,320 Speaker 1: new technology as you go and so you've got to 42 00:02:34,400 --> 00:02:37,320 Speaker 1: kind of, as with all of these disciplines, you've got 43 00:02:37,360 --> 00:02:39,800 Speaker 1: to be able to pull from many different areas of 44 00:02:39,840 --> 00:02:45,000 Speaker 1: your education. Yeah, and beyond that, there's aerospace, agricultural, chemical, electrical, 45 00:02:45,000 --> 00:02:51,720 Speaker 1: health and safety, engineering and beyond and simply making kids aware, 46 00:02:51,800 --> 00:02:56,440 Speaker 1: Like you said, Caroline, of the vast fields you could 47 00:02:56,440 --> 00:03:00,520 Speaker 1: go into via engineering is one of the main keys 48 00:03:00,639 --> 00:03:04,880 Speaker 1: of getting girls from a younger age interested in this 49 00:03:05,120 --> 00:03:08,480 Speaker 1: e in stem. That's right, And let's talk about some 50 00:03:08,520 --> 00:03:12,880 Speaker 1: of the women who did get interested in the e UM. 51 00:03:13,080 --> 00:03:17,000 Speaker 1: Some of our trailblazers include Martha Coston, who UM, as 52 00:03:17,080 --> 00:03:20,600 Speaker 1: a twenty one year old widow with four children, helped 53 00:03:20,639 --> 00:03:23,240 Speaker 1: engineer a signal system so that ships could light up 54 00:03:23,240 --> 00:03:26,239 Speaker 1: their locations on land and see during the Civil War. 55 00:03:26,560 --> 00:03:30,440 Speaker 1: Just to give you some actual historical context, her husband 56 00:03:30,440 --> 00:03:34,080 Speaker 1: had designed this system that basically wouldn't function. It wouldn't work, 57 00:03:34,320 --> 00:03:37,680 Speaker 1: and so lo and behold, Martha Costin tweaks it and 58 00:03:37,720 --> 00:03:40,560 Speaker 1: the Navy ended up buying her system in eighteen fifty 59 00:03:40,640 --> 00:03:43,760 Speaker 1: nine for twenty thousand dollars. Yeah, and then moving into 60 00:03:43,800 --> 00:03:47,560 Speaker 1: the twentieth century, fans of the book and the two movies, 61 00:03:47,920 --> 00:03:50,360 Speaker 1: cheaper by the Dozen might be familiar with the name 62 00:03:50,640 --> 00:03:54,800 Speaker 1: Lillian Gilbrith. She was an industrial engineering genius and also 63 00:03:55,240 --> 00:03:59,480 Speaker 1: a mother of twelve. How those two things work together seamlessly, 64 00:03:59,520 --> 00:04:02,440 Speaker 1: I don't know, um. But in nineteen fifteen she earned 65 00:04:02,440 --> 00:04:06,440 Speaker 1: a PhD from Brown and then became the first female 66 00:04:06,480 --> 00:04:10,200 Speaker 1: member of the American Society of Mechanical Engineers. But what 67 00:04:10,400 --> 00:04:15,080 Speaker 1: her specialty was was industrial engineering. She's known as the 68 00:04:15,160 --> 00:04:18,280 Speaker 1: mother of modern management and the first Lady of engineering 69 00:04:18,279 --> 00:04:23,000 Speaker 1: because of all these innovations with that she used. Via 70 00:04:23,440 --> 00:04:26,400 Speaker 1: her industrial psychology degree that she earned. She was the 71 00:04:26,480 --> 00:04:29,520 Speaker 1: first person even to get that degree. Yeah, she used 72 00:04:29,560 --> 00:04:32,240 Speaker 1: a lot of her skills to focus on of all 73 00:04:32,360 --> 00:04:36,800 Speaker 1: things ergonomics, floor plans, and offices, even all the way 74 00:04:36,800 --> 00:04:39,960 Speaker 1: down to the very workflow, like as you go through 75 00:04:39,960 --> 00:04:42,720 Speaker 1: your day, so the way that your office was set up, 76 00:04:42,800 --> 00:04:45,400 Speaker 1: how you sat at your particular desk, and then the 77 00:04:45,400 --> 00:04:47,960 Speaker 1: work you did while you were there. She mapped it 78 00:04:48,000 --> 00:04:51,760 Speaker 1: out and according to Cheaper by the Dozen, she applied 79 00:04:52,440 --> 00:04:55,839 Speaker 1: and even tested out those kinds of industrial designs in 80 00:04:55,960 --> 00:04:58,680 Speaker 1: her home, which was kind of like a mini office 81 00:04:58,680 --> 00:05:02,240 Speaker 1: space when you have fourteen people plus running around there. 82 00:05:02,560 --> 00:05:05,360 Speaker 1: And then moving on to Maryland Jorgensen Reese who had 83 00:05:05,400 --> 00:05:07,720 Speaker 1: a deep love for math, but she didn't want to 84 00:05:07,839 --> 00:05:10,640 Speaker 1: be a teacher. She wanted to do something more with 85 00:05:10,800 --> 00:05:14,039 Speaker 1: her background, and so in nineteen fifty four, she became 86 00:05:14,080 --> 00:05:18,520 Speaker 1: California's first female fully licensed civil engineer, going on to 87 00:05:18,640 --> 00:05:24,320 Speaker 1: oversee Los Angeles's San Diego Santa Monica Freeway interchange. And 88 00:05:24,440 --> 00:05:27,600 Speaker 1: next up we have Beatrice A. Hicks, who was clearly 89 00:05:27,600 --> 00:05:31,520 Speaker 1: a genius. She not only just got a master's and physics, 90 00:05:31,560 --> 00:05:37,520 Speaker 1: she also pursued chemical engineering, aerospace engineering, and electrical engineering 91 00:05:37,520 --> 00:05:40,960 Speaker 1: and really just made her name as this engineering polly 92 00:05:41,040 --> 00:05:44,280 Speaker 1: math who could shape shift all of these different skills 93 00:05:44,279 --> 00:05:46,960 Speaker 1: that she had acquired for all of those different fields. 94 00:05:47,279 --> 00:05:51,159 Speaker 1: And in nineteen fifty she co founded the Society of 95 00:05:51,200 --> 00:05:55,400 Speaker 1: Women Engineers NICE, which still is around. Yeah. And then 96 00:05:55,440 --> 00:05:59,200 Speaker 1: we have Ellen Henrietta Swallow Richards, who is the first 97 00:05:59,200 --> 00:06:01,800 Speaker 1: woman to graduate from m I T and also the 98 00:06:01,839 --> 00:06:05,680 Speaker 1: founder of home economics. But not what you would think 99 00:06:05,720 --> 00:06:09,080 Speaker 1: of as traditional stereotypical home economics, like baking a cake 100 00:06:09,520 --> 00:06:12,360 Speaker 1: or learning how to run the dishwasher. It's more like 101 00:06:12,520 --> 00:06:16,280 Speaker 1: focusing on safe food practices, healthy and affordable meal planning, 102 00:06:16,320 --> 00:06:19,240 Speaker 1: and being more efficient also in taking care of a 103 00:06:19,279 --> 00:06:23,039 Speaker 1: home and family. And those are just five names. There 104 00:06:23,040 --> 00:06:25,720 Speaker 1: are plenty more because there is a rich history of 105 00:06:25,760 --> 00:06:31,360 Speaker 1: women in engineering, but when we look at the picture today, 106 00:06:31,839 --> 00:06:35,120 Speaker 1: there aren't a ton of women who are pursuing these fields, 107 00:06:35,160 --> 00:06:38,440 Speaker 1: at least compared to men. And before we get into 108 00:06:38,520 --> 00:06:42,240 Speaker 1: today's women and engineering numbers, I first wanted to offer 109 00:06:42,320 --> 00:06:46,040 Speaker 1: up this quote from the magazine The Woman Engineer. This 110 00:06:46,120 --> 00:06:49,919 Speaker 1: is from one of its additions in nineteen nineteen, and 111 00:06:50,040 --> 00:06:52,559 Speaker 1: they wrote, the outlook for women in the engineering world 112 00:06:52,560 --> 00:06:55,479 Speaker 1: has become increasingly gloomy, and with the passing of the 113 00:06:55,520 --> 00:06:59,080 Speaker 1: Restoration of Pre War Practices Bill, the position seems a 114 00:06:59,120 --> 00:07:03,880 Speaker 1: little bliss And I thought that was kind of funny comparison. 115 00:07:04,000 --> 00:07:07,960 Speaker 1: That's nineteen nineteen and not that things are hopeless, but 116 00:07:08,240 --> 00:07:11,520 Speaker 1: still women are trying to figure out how exactly to 117 00:07:11,600 --> 00:07:16,160 Speaker 1: break into this still very male dominated industry. Absolutely, that 118 00:07:16,240 --> 00:07:19,920 Speaker 1: Pre War Practices Bill basically said that women kind of 119 00:07:19,960 --> 00:07:24,080 Speaker 1: just aren't allowed to work as engineers anymore because there 120 00:07:24,120 --> 00:07:26,760 Speaker 1: was they were all of these rules and regulations regarding unions, 121 00:07:26,840 --> 00:07:28,240 Speaker 1: and you had to be in a union to be 122 00:07:28,240 --> 00:07:32,120 Speaker 1: an engineer, but women weren't allowed in unions. So therefore, 123 00:07:32,200 --> 00:07:35,200 Speaker 1: thus ergo they could not be engineers. Yeah, and they 124 00:07:35,200 --> 00:07:38,680 Speaker 1: were suffering a lot because during World War One, similar 125 00:07:38,720 --> 00:07:41,360 Speaker 1: to what happened in World War Two, there were all 126 00:07:41,400 --> 00:07:44,440 Speaker 1: these dudes who left their jobs, and so these newly 127 00:07:44,520 --> 00:07:46,960 Speaker 1: minted women engineers were able to fill those ranks. But 128 00:07:47,040 --> 00:07:49,320 Speaker 1: then the war ends and the guys are like, you know, 129 00:07:49,360 --> 00:07:52,800 Speaker 1: on out, ladies, you know, back to your kitchens. Because 130 00:07:52,840 --> 00:07:55,640 Speaker 1: that was from a British publication, right, well, it's funny. 131 00:07:55,640 --> 00:07:58,560 Speaker 1: I was talking to my roommate about the stuff and 132 00:07:58,800 --> 00:08:02,600 Speaker 1: I was reading him this quote from the Woman Engineer 133 00:08:02,640 --> 00:08:05,440 Speaker 1: and he's like, well, I mean, but it's gotten better, right, like, 134 00:08:05,560 --> 00:08:08,520 Speaker 1: you know, it's like it's probably approaching equal by now, 135 00:08:08,640 --> 00:08:11,640 Speaker 1: right And I was like, oh no, not even close. 136 00:08:11,760 --> 00:08:16,560 Speaker 1: And he looked confounded because he thought, well, I I 137 00:08:16,640 --> 00:08:18,720 Speaker 1: just thought that's the way that all of these things 138 00:08:18,800 --> 00:08:21,400 Speaker 1: were going, you know, that things are becoming more equal. 139 00:08:21,440 --> 00:08:25,160 Speaker 1: And I said, look, it's just as grim and gloomy, 140 00:08:25,200 --> 00:08:28,680 Speaker 1: you know now as it was just about. Yeah. Today 141 00:08:28,720 --> 00:08:32,280 Speaker 1: in the United States, women are earning around of the 142 00:08:32,320 --> 00:08:35,600 Speaker 1: bachelor's degrees in engineering, but a lot of times if 143 00:08:35,600 --> 00:08:40,599 Speaker 1: they're better at math, they might pursue biomedical sciences instead. 144 00:08:41,040 --> 00:08:44,600 Speaker 1: But the American Society for Engineering Education reported that in 145 00:08:44,960 --> 00:08:48,280 Speaker 1: two thousand nine, women were awarded twenty two point nine 146 00:08:48,280 --> 00:08:52,600 Speaker 1: percent of engineering doctorates, which was more than any other time. 147 00:08:52,880 --> 00:08:55,400 Speaker 1: So we're getting more PhD s. We aren't we are 148 00:08:55,679 --> 00:09:00,439 Speaker 1: looking into engineering, we're getting involved with this, but still 149 00:09:01,360 --> 00:09:04,360 Speaker 1: four times as many men are enrolling and engineering compared 150 00:09:04,400 --> 00:09:07,920 Speaker 1: to women, right, And the gap is smaller. Actually when 151 00:09:07,920 --> 00:09:11,080 Speaker 1: you look at computer science, there's just two times as many, 152 00:09:11,200 --> 00:09:15,520 Speaker 1: just two times men, right, right, Um, And so to 153 00:09:15,679 --> 00:09:18,640 Speaker 1: look a little bit closer at some of the gender 154 00:09:18,640 --> 00:09:21,600 Speaker 1: differences in this field. This is coming from the study 155 00:09:21,600 --> 00:09:25,080 Speaker 1: Pipeline or Personal Preference Women in Engineering two thousand from 156 00:09:25,120 --> 00:09:28,319 Speaker 1: two thousand eight. And that side note pipeline shold sound 157 00:09:28,360 --> 00:09:30,160 Speaker 1: familiar because we've talked about it in one of our 158 00:09:30,200 --> 00:09:34,240 Speaker 1: earlier STEM episodes. Basically, the idea that there is this funnel, 159 00:09:34,320 --> 00:09:39,440 Speaker 1: this pipeline of women from very young ages elementary school, 160 00:09:39,480 --> 00:09:42,040 Speaker 1: middle school, high school all the way through to the 161 00:09:42,160 --> 00:09:45,840 Speaker 1: doctoral degree level, and it's leaking the whole way basically, 162 00:09:45,840 --> 00:09:48,120 Speaker 1: like women start out getting the same grades as men, 163 00:09:48,240 --> 00:09:51,000 Speaker 1: having the same interest in science as men and math, 164 00:09:51,120 --> 00:09:56,920 Speaker 1: and then it slowly starts to dissipate. So that's that background. UM. 165 00:09:57,000 --> 00:10:00,200 Speaker 1: But so this study found out that twelve point three 166 00:10:00,280 --> 00:10:04,360 Speaker 1: percent of the about a thousand female participants had changed 167 00:10:04,520 --> 00:10:08,080 Speaker 1: majors to engineering, compared to six point six percent of 168 00:10:08,160 --> 00:10:11,120 Speaker 1: male participants. And I think that that had something to 169 00:10:11,160 --> 00:10:16,400 Speaker 1: do with, again, these girls coming to college and realizing 170 00:10:16,840 --> 00:10:19,920 Speaker 1: all of the different options that engineering offered them, and 171 00:10:19,960 --> 00:10:22,760 Speaker 1: so they said, oh, maybe this is a better fit 172 00:10:22,880 --> 00:10:25,480 Speaker 1: because again it's from like from the very get go 173 00:10:25,600 --> 00:10:29,360 Speaker 1: with engineering, well a little bit different from something like 174 00:10:29,920 --> 00:10:33,320 Speaker 1: straight up science, tech or math, whereas engineering, I feel 175 00:10:33,360 --> 00:10:37,800 Speaker 1: like there's not as much just public knowledge about what 176 00:10:37,960 --> 00:10:40,000 Speaker 1: all you can do with it. So they think that 177 00:10:40,000 --> 00:10:44,320 Speaker 1: that might be responsible for that larger percentage of women 178 00:10:44,440 --> 00:10:47,520 Speaker 1: switching into engineering. And they thought it was notable that 179 00:10:47,600 --> 00:10:52,080 Speaker 1: over half of the female study participants had engineers in 180 00:10:52,160 --> 00:10:55,440 Speaker 1: their families compared to forty six point two percent of men. 181 00:10:55,559 --> 00:10:59,319 Speaker 1: So they were also more women who seemed directly influenced 182 00:10:59,360 --> 00:11:02,920 Speaker 1: by just seeing engineers around them. Yeah, exactly, And I 183 00:11:02,920 --> 00:11:05,000 Speaker 1: mean talking about stereotypes of the field, you know, a 184 00:11:05,040 --> 00:11:07,640 Speaker 1: lot of what we read points out the fact that, um, 185 00:11:07,679 --> 00:11:09,360 Speaker 1: and this isn't just for women this is just kind 186 00:11:09,360 --> 00:11:11,520 Speaker 1: of for all students in general. There's this perception of 187 00:11:11,600 --> 00:11:14,720 Speaker 1: engineering being like I'm going to get my hands greasy 188 00:11:14,760 --> 00:11:17,319 Speaker 1: and dirty, I'm going to be lifting heavy things and 189 00:11:17,320 --> 00:11:20,800 Speaker 1: putting cogs into machines all day long, and you know, 190 00:11:21,040 --> 00:11:23,680 Speaker 1: and and so what we're trying to drive the point 191 00:11:23,679 --> 00:11:25,679 Speaker 1: that we're trying to drive across is that there is 192 00:11:25,760 --> 00:11:28,840 Speaker 1: so much more to engineering. And so the study also 193 00:11:28,880 --> 00:11:32,720 Speaker 1: looked at kind of a breakdown of what uh men 194 00:11:32,760 --> 00:11:36,200 Speaker 1: and women kind of veer toward within these fields, and 195 00:11:36,240 --> 00:11:38,559 Speaker 1: they found that women were more comfortable with lab work, 196 00:11:38,600 --> 00:11:43,240 Speaker 1: performing experiments, and writing, whereas men were more comfortable working 197 00:11:43,240 --> 00:11:47,520 Speaker 1: with tools, designing new things, working with computers, making presentations, 198 00:11:47,600 --> 00:11:51,040 Speaker 1: and working with machines. But I think it's worth noting, though, 199 00:11:51,120 --> 00:11:56,080 Speaker 1: that being comfortable with something doesn't necessarily mean the same 200 00:11:56,080 --> 00:12:00,240 Speaker 1: thing as being proficient as it because Civil environment mental 201 00:12:00,280 --> 00:12:04,840 Speaker 1: engineering professor at the University of Colorado, Boulder, Angela biel Felt, 202 00:12:05,240 --> 00:12:08,720 Speaker 1: said that quote, women tend to leave engineering with higher 203 00:12:09,120 --> 00:12:11,839 Speaker 1: grade point averages than the men, but they perceive that 204 00:12:11,880 --> 00:12:15,800 Speaker 1: their technical skills are sometimes different, and they're not different 205 00:12:15,880 --> 00:12:19,440 Speaker 1: in reality. And I think that gets to this issue 206 00:12:19,440 --> 00:12:21,360 Speaker 1: of socialization that has come up a lot in this 207 00:12:21,520 --> 00:12:26,439 Speaker 1: women and Stem conversation too, and that negative self assessment 208 00:12:26,760 --> 00:12:29,200 Speaker 1: that goes on. Yeah, and and that's something we've talked 209 00:12:29,240 --> 00:12:33,400 Speaker 1: about in these these episodes that you know, women and 210 00:12:33,480 --> 00:12:36,720 Speaker 1: girls tend to think that they need to be you know, 211 00:12:36,880 --> 00:12:39,920 Speaker 1: triple the engineer or the mathematician or the scientists, that 212 00:12:39,960 --> 00:12:44,800 Speaker 1: the man is just to be considered you know acceptable. Yeah, 213 00:12:44,840 --> 00:12:48,520 Speaker 1: I think it goes into what happens the mindset, the 214 00:12:48,600 --> 00:12:51,800 Speaker 1: Rube Goldberg machine that trips off in the brain when 215 00:12:51,840 --> 00:12:55,920 Speaker 1: you really start to make headway into what is considered 216 00:12:56,160 --> 00:13:00,280 Speaker 1: a really masculine pursuit. Right. And it's interesting to note 217 00:13:00,360 --> 00:13:05,720 Speaker 1: kind of almost the different polls of of engineering that 218 00:13:05,840 --> 00:13:10,040 Speaker 1: men and women go towards. Because in civil engineering classes, 219 00:13:10,040 --> 00:13:13,120 Speaker 1: you know my friend Clay, who is a man, uh, 220 00:13:13,320 --> 00:13:15,760 Speaker 1: in that field, it's going to be mostly guys, but 221 00:13:15,800 --> 00:13:20,840 Speaker 1: the female numbers increase in fields like environmental engineering. But 222 00:13:21,120 --> 00:13:25,920 Speaker 1: women's numbers increase in other fields of engineering, including environmental engineering, 223 00:13:26,160 --> 00:13:30,000 Speaker 1: but particularly industrial engineering. So again for those of you 224 00:13:30,040 --> 00:13:33,040 Speaker 1: who might not be familiar with industrial engineering, it's more 225 00:13:33,080 --> 00:13:37,360 Speaker 1: focused on human centered systems, looking at things like design, 226 00:13:37,480 --> 00:13:43,360 Speaker 1: improvement and installation. In terms of how that interacts with people, materials, equipment, 227 00:13:43,760 --> 00:13:48,480 Speaker 1: and energy, and more than any other field, industrial engineering 228 00:13:48,480 --> 00:13:53,080 Speaker 1: tends to have the largest concentration of women, at around 229 00:13:53,080 --> 00:13:55,840 Speaker 1: thirty two per cent. So there was a study that 230 00:13:55,920 --> 00:14:00,640 Speaker 1: came out called Women in Industrial Engineering Stereotypes, Persistence and Perspective, 231 00:14:00,920 --> 00:14:03,280 Speaker 1: and it came out in two thousand and twelve looking 232 00:14:03,320 --> 00:14:06,880 Speaker 1: at why that was, because this was part of a 233 00:14:06,960 --> 00:14:10,719 Speaker 1: larger body of research digging into the different engineering disciplines 234 00:14:10,760 --> 00:14:13,280 Speaker 1: to see what was really appealing to women and what wasn't, 235 00:14:13,320 --> 00:14:15,880 Speaker 1: what women were sticking with and what they weren't, and 236 00:14:16,080 --> 00:14:18,920 Speaker 1: engineering stood out to them as a quote unquote pocket 237 00:14:18,920 --> 00:14:22,000 Speaker 1: of success. And something that came up really quickly in 238 00:14:22,040 --> 00:14:28,280 Speaker 1: this paper was that there's a stereotype among engineering folk 239 00:14:28,640 --> 00:14:33,000 Speaker 1: that industrial engineering is proceed to be easy, or they 240 00:14:33,320 --> 00:14:39,120 Speaker 1: some sometimes call it imaginary engineering. Uh weah, I'm going 241 00:14:39,200 --> 00:14:41,760 Speaker 1: to make a lot of like disappointed flash disapproving noises 242 00:14:41,800 --> 00:14:45,160 Speaker 1: about that one, because don't you think that, okay, male 243 00:14:45,200 --> 00:14:49,080 Speaker 1: dominated field, section of male dominated field that has the 244 00:14:49,120 --> 00:14:53,200 Speaker 1: most women in it, the highest concentration of women. Women 245 00:14:53,320 --> 00:14:57,160 Speaker 1: then perceived, already in gender stereotypes, to be not as 246 00:14:57,200 --> 00:15:03,200 Speaker 1: scientific or mathematically minded. So then you have some ill 247 00:15:03,360 --> 00:15:09,280 Speaker 1: informed individuals out there thinking, well, if women can do it, well, 248 00:15:09,280 --> 00:15:13,600 Speaker 1: it isn't just the male students who are perpetuating the idea, 249 00:15:13,640 --> 00:15:16,640 Speaker 1: it's also the women who are saying this too in 250 00:15:16,680 --> 00:15:21,600 Speaker 1: the study. But I think you're totally on point because 251 00:15:22,040 --> 00:15:25,200 Speaker 1: one of the number one phrases that popped up when 252 00:15:25,200 --> 00:15:29,440 Speaker 1: these researchers were asking female industrial engineering students why they 253 00:15:29,440 --> 00:15:32,560 Speaker 1: were really into industrial engineering, and the phrase that kept 254 00:15:32,600 --> 00:15:37,520 Speaker 1: coming up was people oriented, which stands in such contrast 255 00:15:37,600 --> 00:15:41,200 Speaker 1: if you think of civil engineering, which is that really 256 00:15:41,640 --> 00:15:46,160 Speaker 1: male heavy pocket of engineering that's all about bridges and 257 00:15:46,280 --> 00:15:50,120 Speaker 1: roads that's paved away through the mountains. You know, it's 258 00:15:50,200 --> 00:15:55,960 Speaker 1: it's a it seems it does seem like it's more feminine, right, Yeah, 259 00:15:56,000 --> 00:15:59,680 Speaker 1: And and especially since those focus group participants cited things 260 00:15:59,720 --> 00:16:04,360 Speaker 1: like a proachable faculty um, inherent femininity with things like 261 00:16:04,440 --> 00:16:08,320 Speaker 1: scheduling efficiency and communication, but also so stuability. But I 262 00:16:08,640 --> 00:16:12,160 Speaker 1: thought it was interesting that it's the only engineering major 263 00:16:12,200 --> 00:16:15,720 Speaker 1: that gains women and men from the third semester through 264 00:16:15,880 --> 00:16:19,400 Speaker 1: six year graduation. So it's clearly not just women who 265 00:16:19,480 --> 00:16:21,440 Speaker 1: are all of a sudden going like, oh well, maybe 266 00:16:21,440 --> 00:16:23,480 Speaker 1: I like that instead, maybe I like that better. There 267 00:16:23,480 --> 00:16:27,520 Speaker 1: are clearly some men out there who are also thinking like, oh, well, 268 00:16:27,640 --> 00:16:29,560 Speaker 1: you know, maybe I don't want to just focus on 269 00:16:29,600 --> 00:16:32,880 Speaker 1: bridges and roads. Maybe I do like the people aspect 270 00:16:32,960 --> 00:16:36,520 Speaker 1: of that discipline. Not that Caroline and I have anything 271 00:16:36,600 --> 00:16:40,440 Speaker 1: against bridges and row No. I I am so thankful 272 00:16:40,600 --> 00:16:44,040 Speaker 1: when there are roads to drive on, and even more 273 00:16:44,040 --> 00:16:48,240 Speaker 1: thankful when there is a properly constructed and inspected bridge 274 00:16:48,720 --> 00:16:51,560 Speaker 1: across which I may drive. And this has been a 275 00:16:51,640 --> 00:16:56,600 Speaker 1: civil engineering salute. But but there is something though about 276 00:16:56,680 --> 00:17:02,000 Speaker 1: that people aspect and possibly the idea of how engineering 277 00:17:02,200 --> 00:17:05,600 Speaker 1: can solve problems for people, can help people, can literally 278 00:17:06,040 --> 00:17:09,920 Speaker 1: save lives that some who are really invested in attracting 279 00:17:09,920 --> 00:17:14,280 Speaker 1: more women to engineering want to hone in on. So 280 00:17:14,320 --> 00:17:18,600 Speaker 1: we're gonna get into that altruistic aspect of engineering when 281 00:17:18,640 --> 00:17:22,000 Speaker 1: we come right back from a quick break. So we 282 00:17:22,119 --> 00:17:25,480 Speaker 1: left off we were talking about how the altruistic element 283 00:17:25,760 --> 00:17:29,600 Speaker 1: of engineering could be used as a powerful recruitment tool 284 00:17:29,960 --> 00:17:34,000 Speaker 1: to get more girls and women interested in this field, 285 00:17:34,080 --> 00:17:37,840 Speaker 1: because research does consistently show that women are more drawn 286 00:17:37,880 --> 00:17:42,240 Speaker 1: to fields of study that they believe will contribute to 287 00:17:42,400 --> 00:17:46,679 Speaker 1: the social good. And it's the same thing within engineering 288 00:17:46,720 --> 00:17:49,080 Speaker 1: where if you break out all those different fields, women 289 00:17:49,119 --> 00:17:52,800 Speaker 1: do tend to be drawn to those areas that seem 290 00:17:52,840 --> 00:17:55,520 Speaker 1: to have a direct application on people's lives. And a 291 00:17:55,560 --> 00:17:58,240 Speaker 1: lot of times when you talk to women engineers and 292 00:17:58,280 --> 00:18:00,679 Speaker 1: asked them why they love doing what they do, they say, well, 293 00:18:00,720 --> 00:18:04,520 Speaker 1: I help people, I'm solving problems, I'm making people's lives 294 00:18:04,600 --> 00:18:07,679 Speaker 1: better with my work. Sure, and this was confirmed by 295 00:18:07,680 --> 00:18:11,040 Speaker 1: the American Society of Mechanical Engineers because there's this growth 296 00:18:11,080 --> 00:18:14,800 Speaker 1: in women pursuing mechanical engineering in the medical and energy 297 00:18:14,880 --> 00:18:18,760 Speaker 1: fields because of these strong societal ties and the clear 298 00:18:18,800 --> 00:18:22,280 Speaker 1: cut positive impact that it has on people. It's something 299 00:18:22,320 --> 00:18:25,440 Speaker 1: that see Diane Matt, the executive director of the Women 300 00:18:25,480 --> 00:18:29,639 Speaker 1: in Engineering Proactive Network, basically calls social relevance, saying that 301 00:18:29,640 --> 00:18:33,600 Speaker 1: women are drawn to this high social relevance in this field. Yeah, 302 00:18:33,640 --> 00:18:36,360 Speaker 1: and there's something we should talk about two. In regard 303 00:18:36,440 --> 00:18:41,840 Speaker 1: to this altruistic pull within STEM, some have said that 304 00:18:42,000 --> 00:18:46,160 Speaker 1: the biological sciences, for instance, tend to be uh tend 305 00:18:46,160 --> 00:18:50,760 Speaker 1: to have more women pursuing them working in them because 306 00:18:51,160 --> 00:18:54,919 Speaker 1: there seems to be a closer connection to having an 307 00:18:54,960 --> 00:18:57,800 Speaker 1: impact on other people's lives within that kind of work. 308 00:18:57,840 --> 00:19:01,120 Speaker 1: And obviously you can divert from there to biomedical things. 309 00:19:01,119 --> 00:19:02,720 Speaker 1: You want to become a doctor, you want to help people, 310 00:19:02,720 --> 00:19:05,159 Speaker 1: you want to save lives, etcetera. Same thing going on 311 00:19:05,440 --> 00:19:08,639 Speaker 1: within engineering. And there's even an Intel sponsored study that 312 00:19:08,760 --> 00:19:12,320 Speaker 1: asked teens to read a series of statements about engineering, 313 00:19:12,560 --> 00:19:15,640 Speaker 1: and the ones that motivated the girls the most were 314 00:19:15,680 --> 00:19:20,600 Speaker 1: about how surprise surprise engineering helps fix global problems like 315 00:19:20,680 --> 00:19:24,159 Speaker 1: clean water solutions. And I can understand that if I 316 00:19:24,200 --> 00:19:26,879 Speaker 1: was told when I was fifteen, hey, hey kid, you 317 00:19:26,920 --> 00:19:29,960 Speaker 1: want to solve some clean water issues? Tell my how 318 00:19:30,080 --> 00:19:33,120 Speaker 1: shign me up? Can I podcast it? Can I bring 319 00:19:33,160 --> 00:19:37,040 Speaker 1: the cat um? Well, So, now that we've talked about 320 00:19:37,040 --> 00:19:40,320 Speaker 1: this incredible altruistic angle and the fact that you really 321 00:19:40,359 --> 00:19:44,440 Speaker 1: can change lives and entire communities with your engineering background, 322 00:19:45,000 --> 00:19:47,720 Speaker 1: let's let's talk about some salaries. Yeah, you can also 323 00:19:47,800 --> 00:19:51,200 Speaker 1: make a lot of money. That's also something if someone 324 00:19:51,240 --> 00:19:52,919 Speaker 1: to tap me on the Sheila said, hey kid, you 325 00:19:52,920 --> 00:19:54,359 Speaker 1: want to save some lives and make a ton of 326 00:19:54,400 --> 00:19:58,080 Speaker 1: cash doing it. Yeah. The National Association of Colleges and 327 00:19:58,160 --> 00:20:02,800 Speaker 1: Employers shows u just how lucrative a career it can be. 328 00:20:02,840 --> 00:20:06,280 Speaker 1: I mean, engineering makes up like the top the top 329 00:20:06,320 --> 00:20:10,840 Speaker 1: like six I think jobs. So computer engineering you can 330 00:20:10,880 --> 00:20:15,600 Speaker 1: make over seventy thousand dollars, chemical engineering more than sixty six, 331 00:20:15,680 --> 00:20:19,440 Speaker 1: computer science more than sixty four. Yeah, and it goes 332 00:20:19,480 --> 00:20:21,159 Speaker 1: all the way down at the bottom of the barrel. 333 00:20:21,359 --> 00:20:24,719 Speaker 1: If we have civil engineering starting out at just fifty 334 00:20:24,800 --> 00:20:31,199 Speaker 1: seven six. Uh so even even that is really lucrative. 335 00:20:31,520 --> 00:20:34,959 Speaker 1: And uh it's too bad that there can't be more 336 00:20:35,040 --> 00:20:39,359 Speaker 1: quote unquote pockets of success like industrial engineering, because at 337 00:20:39,440 --> 00:20:44,760 Speaker 1: least according to a UK survey among three hundred female engineers, 338 00:20:44,960 --> 00:20:49,480 Speaker 1: the job satisfaction is really high. Although caveat, as you 339 00:20:49,560 --> 00:20:52,760 Speaker 1: there should always be a caveat with surveys. The survey 340 00:20:52,840 --> 00:20:57,359 Speaker 1: was sponsored by Atkins, which is an engineering firm, but 341 00:20:57,480 --> 00:21:01,720 Speaker 1: it found of women said their jobs were rewarding and 342 00:21:01,800 --> 00:21:07,240 Speaker 1: satisfying and didn't see gender as holding them back. But 343 00:21:07,320 --> 00:21:11,080 Speaker 1: it is worth noting that of these women they talked 344 00:21:11,080 --> 00:21:15,080 Speaker 1: to were inspired to pursue engineering thanks to a family member, 345 00:21:15,160 --> 00:21:19,440 Speaker 1: usually their dad, and were inspired by a teacher. So look, 346 00:21:19,480 --> 00:21:22,800 Speaker 1: I mean that is that is like tangible evidence of 347 00:21:22,920 --> 00:21:26,399 Speaker 1: how important it is to have people in our children's 348 00:21:26,520 --> 00:21:30,240 Speaker 1: lives inspiring them to go do something that maybe they 349 00:21:30,240 --> 00:21:34,120 Speaker 1: hadn't thought of how important it is just to normalize 350 00:21:34,760 --> 00:21:38,000 Speaker 1: an entire field of study. Yeah, and that's one of 351 00:21:38,040 --> 00:21:40,239 Speaker 1: the reasons why a lot of these respondents went on 352 00:21:40,280 --> 00:21:42,879 Speaker 1: to say that there needs to be a greater awareness 353 00:21:42,920 --> 00:21:45,760 Speaker 1: of what an engineer does, as we have hammered home 354 00:21:45,800 --> 00:21:49,160 Speaker 1: a number of times on the podcast and improved mentorship 355 00:21:49,280 --> 00:21:52,320 Speaker 1: for girls. And that was something too that came up 356 00:21:52,400 --> 00:21:56,280 Speaker 1: in our conversation a while ago with Goldie Blocks founder 357 00:21:56,600 --> 00:22:00,200 Speaker 1: Deborah Sterling, who was a Stanford engineer. She career did 358 00:22:00,200 --> 00:22:03,639 Speaker 1: this toy called Goldie Blocks, which is specifically designed to 359 00:22:04,040 --> 00:22:08,640 Speaker 1: get girls excited about engineering, to teach them engineering fundamentals 360 00:22:08,760 --> 00:22:12,359 Speaker 1: in a fun and engaging and girl friendly kind of way. 361 00:22:12,400 --> 00:22:15,320 Speaker 1: Because when she was growing up, even though she ended 362 00:22:15,359 --> 00:22:17,360 Speaker 1: up becoming an engineer, she would have had no idea 363 00:22:17,560 --> 00:22:19,960 Speaker 1: as a kid that that would even be a possibility 364 00:22:20,080 --> 00:22:23,560 Speaker 1: because in front of her all she saw or princesses 365 00:22:23,560 --> 00:22:26,080 Speaker 1: and barbies and pink things, and she was like, I 366 00:22:26,119 --> 00:22:29,719 Speaker 1: was building things with my barbies, but I didn't know 367 00:22:29,800 --> 00:22:31,840 Speaker 1: that that was engineering. And I think it wasn't until 368 00:22:31,920 --> 00:22:36,640 Speaker 1: high school that a teacher alerted her to that, well, 369 00:22:36,720 --> 00:22:39,239 Speaker 1: all of this stuff that we've been learning in our 370 00:22:39,280 --> 00:22:42,560 Speaker 1: stem episodes has really inspired me because Christmas time is 371 00:22:42,600 --> 00:22:44,879 Speaker 1: coming up and I have a five year old niece, 372 00:22:45,840 --> 00:22:48,080 Speaker 1: and I don't think they all listen to the podcast. 373 00:22:48,160 --> 00:22:50,560 Speaker 1: I think it's safe to talk about this. But um, 374 00:22:50,640 --> 00:22:55,639 Speaker 1: I found this dollhouse set that basically has a like 375 00:22:55,680 --> 00:22:58,560 Speaker 1: a battery pack attached to it, and you can run 376 00:22:59,119 --> 00:23:03,199 Speaker 1: these currents and actually light up your dollhouse and you 377 00:23:03,240 --> 00:23:06,240 Speaker 1: build walls, you hang lamps, you do all sorts of stuff. 378 00:23:06,280 --> 00:23:11,080 Speaker 1: And so she is into anything anything that is pink, 379 00:23:11,240 --> 00:23:14,640 Speaker 1: purple and sparkly, and so a dollhouse would be neat. 380 00:23:14,680 --> 00:23:17,000 Speaker 1: And if she can learn some spatial reasoning skills while 381 00:23:17,080 --> 00:23:18,919 Speaker 1: she does it, then that's even better. Yeah, and some 382 00:23:19,000 --> 00:23:22,520 Speaker 1: electrical engineering too. It sounds like, well, anti Caroline is 383 00:23:22,560 --> 00:23:27,080 Speaker 1: trying to get a little Sarah into some engineering. You're 384 00:23:27,119 --> 00:23:31,120 Speaker 1: planting the stem seeds, Caroline. Indeed, I ane um, but 385 00:23:31,560 --> 00:23:34,720 Speaker 1: we do have to bring our high down for a 386 00:23:34,800 --> 00:23:38,960 Speaker 1: moment and move away from that survey that was very happy, 387 00:23:39,000 --> 00:23:43,359 Speaker 1: go lucky, because that's not always the case with women 388 00:23:43,359 --> 00:23:47,880 Speaker 1: and engineering, as is expected when you go into these 389 00:23:48,320 --> 00:23:51,280 Speaker 1: fields that are very much in the words of a 390 00:23:51,320 --> 00:23:56,240 Speaker 1: female engineer boys clubs. Um, there was a University of 391 00:23:56,280 --> 00:24:00,200 Speaker 1: Wisconsin Milwaukee Center for the Study of the Workplace report 392 00:24:00,320 --> 00:24:02,960 Speaker 1: that came out in two thousand and eight looking at 393 00:24:02,960 --> 00:24:06,080 Speaker 1: women and engineering, and it found that, first of all, 394 00:24:06,600 --> 00:24:10,440 Speaker 1: a third of women graduating from engineering programs don't enter 395 00:24:10,920 --> 00:24:14,920 Speaker 1: engineering jobs because they see them as inflexible or non 396 00:24:14,960 --> 00:24:17,880 Speaker 1: supportive of women. Come on now, I mean, how many 397 00:24:17,920 --> 00:24:20,159 Speaker 1: times have we heard that about different I mean just 398 00:24:20,240 --> 00:24:23,960 Speaker 1: different arenas in general. Yeah, as far as I mean, 399 00:24:24,000 --> 00:24:26,560 Speaker 1: as far as supporting women goes. They also found that 400 00:24:26,640 --> 00:24:30,000 Speaker 1: half of women's surveyed who left engineering jobs did so 401 00:24:30,200 --> 00:24:33,560 Speaker 1: because of working conditions, too much travel, too little advancement 402 00:24:33,600 --> 00:24:36,159 Speaker 1: and pay, and one in three left because of a 403 00:24:36,240 --> 00:24:39,520 Speaker 1: hostile work environment. And there probably is a lot of 404 00:24:39,800 --> 00:24:43,840 Speaker 1: unconscious and conscious bias at work because these engineering fields 405 00:24:43,840 --> 00:24:47,680 Speaker 1: are still so male dominated. But female engineers who worked 406 00:24:47,680 --> 00:24:51,840 Speaker 1: in companies that valued and recognize their contributions, invested in 407 00:24:51,880 --> 00:24:56,240 Speaker 1: training and professional development expressed the greatest levels of satisfaction 408 00:24:56,280 --> 00:24:59,320 Speaker 1: within their jobs and careers. Which you could probably apply 409 00:24:59,440 --> 00:25:02,560 Speaker 1: that to any type of job that supports you and 410 00:25:02,640 --> 00:25:07,520 Speaker 1: wants to see you succeed. But in a realm like engineering, 411 00:25:08,000 --> 00:25:12,879 Speaker 1: it's so critical to set up support structures outside of 412 00:25:13,000 --> 00:25:16,160 Speaker 1: college at the end of the pipeline. Where the pipeline 413 00:25:16,200 --> 00:25:19,159 Speaker 1: is supposed to end up the pool, the engineering pool. 414 00:25:19,520 --> 00:25:22,040 Speaker 1: I'm not going to extend this pipeline metaphor any farther 415 00:25:22,760 --> 00:25:26,240 Speaker 1: because the gap is so huge, not just in the 416 00:25:26,320 --> 00:25:29,560 Speaker 1: United States but around the world. For instance, in in 417 00:25:29,600 --> 00:25:32,920 Speaker 1: the U s And Canada, in the engineering workforce, women 418 00:25:33,000 --> 00:25:36,119 Speaker 1: make up only but that's not as bad as it 419 00:25:36,160 --> 00:25:39,800 Speaker 1: is in the UK. No, the UK, it's only seven percent, 420 00:25:40,119 --> 00:25:43,679 Speaker 1: And in Australia women make up nine point six percent 421 00:25:43,800 --> 00:25:47,720 Speaker 1: of the engineering workforce, but it's awesome over in Latvia 422 00:25:47,920 --> 00:25:51,119 Speaker 1: which is thirty percent and Bulgaria which has twenty nine 423 00:25:51,160 --> 00:25:53,600 Speaker 1: point three percent. Yeah. I think that came up as 424 00:25:53,640 --> 00:25:58,280 Speaker 1: well in our tech episode because it's similar with computer 425 00:25:58,400 --> 00:26:01,960 Speaker 1: science where Eastern year up. They're all about getting some 426 00:26:02,040 --> 00:26:07,040 Speaker 1: women into some STEM and this probably is a reason 427 00:26:07,119 --> 00:26:10,960 Speaker 1: why we're seeing so much government initiative with getting girls 428 00:26:11,000 --> 00:26:15,040 Speaker 1: engaged in STEM because guess what folks of the engineering 429 00:26:15,040 --> 00:26:21,000 Speaker 1: workforce in China or women, Yeah, we're trailing. Yeah, we're trailing. 430 00:26:21,119 --> 00:26:25,080 Speaker 1: And people are seeing this as a potential detriment to 431 00:26:25,440 --> 00:26:29,200 Speaker 1: our economy because why do women in engineering matter on 432 00:26:29,280 --> 00:26:32,399 Speaker 1: a practical sense. It's not just because we want parody 433 00:26:32,480 --> 00:26:35,880 Speaker 1: for everything fifty fifty for all know, it has very 434 00:26:35,920 --> 00:26:42,120 Speaker 1: real world implications because diversity foster's innovation. We need innovation. Yeah, 435 00:26:42,160 --> 00:26:44,080 Speaker 1: like there was some percentage I can't remember, But our 436 00:26:44,160 --> 00:26:47,560 Speaker 1: g d P is actually suffering because of the fact 437 00:26:48,000 --> 00:26:52,280 Speaker 1: that we don't have the brightest minds in these fields, 438 00:26:52,280 --> 00:26:54,520 Speaker 1: in the stem fields and engineering in particular. And I'm 439 00:26:54,560 --> 00:26:56,960 Speaker 1: not that's not to say that the people in engineering 440 00:26:56,960 --> 00:26:59,720 Speaker 1: aren't right, but when you are only taking from one 441 00:27:00,000 --> 00:27:05,080 Speaker 1: cool of people, from one pipeline to bring that metaphor back, um, 442 00:27:05,119 --> 00:27:07,480 Speaker 1: that means that you're taking, yeah, the best, but then 443 00:27:07,520 --> 00:27:09,320 Speaker 1: you're also having to go down to fill the rest 444 00:27:09,320 --> 00:27:11,680 Speaker 1: of your spots too, maybe the middle of the pack. 445 00:27:12,560 --> 00:27:14,639 Speaker 1: But why don't you go over to the other pool 446 00:27:14,680 --> 00:27:18,600 Speaker 1: and take the top of their candidates also, because that 447 00:27:18,800 --> 00:27:21,439 Speaker 1: is the way that you get more innovation, right, And 448 00:27:21,480 --> 00:27:26,720 Speaker 1: even speaking more specifically to two women's involvement, there's even 449 00:27:26,800 --> 00:27:30,920 Speaker 1: some feminist theory of gender and engineering talking about how 450 00:27:30,960 --> 00:27:33,960 Speaker 1: the two really are interwoven because a lot of times 451 00:27:34,080 --> 00:27:37,840 Speaker 1: we're talking about all of these systems that are human centered, 452 00:27:38,320 --> 00:27:41,639 Speaker 1: and we're they're they're making things they're making those roads 453 00:27:41,680 --> 00:27:47,680 Speaker 1: and bridges and biomedical devices and clean water sheds, all 454 00:27:47,680 --> 00:27:51,919 Speaker 1: of those things for not just male consumers obviously, but 455 00:27:51,960 --> 00:27:56,040 Speaker 1: also for female consumers and for kids. And as Don Bonfield, 456 00:27:56,040 --> 00:27:59,600 Speaker 1: who's the VP of the Women's Engineering Society said, women 457 00:27:59,680 --> 00:28:02,800 Speaker 1: bring diversity that a non mixed team doesn't have. And 458 00:28:02,800 --> 00:28:05,479 Speaker 1: the skills that they bring include a desire to produce 459 00:28:05,600 --> 00:28:10,400 Speaker 1: an excellent product that delights to customer and solves a problem. Right, 460 00:28:10,400 --> 00:28:13,720 Speaker 1: I mean, just think about the items, to use a 461 00:28:13,760 --> 00:28:17,040 Speaker 1: general word, that we are not getting because some of 462 00:28:17,080 --> 00:28:20,240 Speaker 1: those great minds did not end up in engineering or 463 00:28:20,359 --> 00:28:24,080 Speaker 1: left engineering because it was unwelcoming. And I mean another 464 00:28:24,160 --> 00:28:26,080 Speaker 1: problem that you run into, like you said, I mean 465 00:28:26,160 --> 00:28:29,239 Speaker 1: you you you lose that innovation when you don't have 466 00:28:29,480 --> 00:28:32,320 Speaker 1: women's minds on the team as well. But you also 467 00:28:32,600 --> 00:28:36,320 Speaker 1: create problems. You're not just avoiding good solutions, you're creating 468 00:28:36,320 --> 00:28:40,040 Speaker 1: problems because we have the issue of air bags. What 469 00:28:40,160 --> 00:28:43,840 Speaker 1: about airbags? You say, well, because it was a male 470 00:28:44,080 --> 00:28:48,760 Speaker 1: team that created these safety devices, they were created from 471 00:28:48,800 --> 00:28:53,160 Speaker 1: male bodies, and so women and children in vehicles, Actually, 472 00:28:53,640 --> 00:28:56,400 Speaker 1: we're getting injured by the very safety devices that we're 473 00:28:56,400 --> 00:28:58,760 Speaker 1: supposed to save their lives. Yeah, and there have also 474 00:28:58,800 --> 00:29:02,800 Speaker 1: been issues of voice recognition software that only recognized male 475 00:29:02,880 --> 00:29:06,680 Speaker 1: voices because it was an all male team building them. Now, 476 00:29:06,680 --> 00:29:08,880 Speaker 1: clearly you could swing the other way and say that 477 00:29:08,920 --> 00:29:11,760 Speaker 1: you'd have similar problems crop up if you had all 478 00:29:11,840 --> 00:29:15,240 Speaker 1: female teams working on things. That's why the name of 479 00:29:15,240 --> 00:29:20,680 Speaker 1: the game is about diversity and bringing multiple minds to 480 00:29:20,800 --> 00:29:26,080 Speaker 1: the table to foster innovation. Because I think Dr Mary Gilly, 481 00:29:26,120 --> 00:29:29,520 Speaker 1: who works with e A Technology, said it best. She said, 482 00:29:29,840 --> 00:29:32,360 Speaker 1: we have more chances of better serving the needs of 483 00:29:32,400 --> 00:29:36,240 Speaker 1: society as a whole if those working in engineering reflect 484 00:29:36,280 --> 00:29:39,920 Speaker 1: across section of society. Yeah. And I mean Margaret Bailey, 485 00:29:39,920 --> 00:29:43,360 Speaker 1: who's a professor of mechanical engineering at the Rochester Institute 486 00:29:43,360 --> 00:29:47,480 Speaker 1: of Technology in New York, summed it up by saying, hey, look, 487 00:29:47,520 --> 00:29:50,800 Speaker 1: you're just going to see entirely different outcomes in general. 488 00:29:50,840 --> 00:29:53,800 Speaker 1: I mean you're going to see better products. I mean, 489 00:29:54,440 --> 00:29:58,960 Speaker 1: happier consumers, but also happier engineers. I mean, I think, 490 00:29:59,000 --> 00:30:02,360 Speaker 1: I think if there's a shift in this field, you know, 491 00:30:02,520 --> 00:30:07,840 Speaker 1: hopefully we can get more women involved and more of 492 00:30:07,880 --> 00:30:12,360 Speaker 1: the old guard more accepting and welcoming as well. Yeah, 493 00:30:12,440 --> 00:30:15,440 Speaker 1: and it's exciting to know that there are those Lilyan 494 00:30:15,480 --> 00:30:19,320 Speaker 1: Gilbreath's out there, those trailblazers who have done incredible things, 495 00:30:19,320 --> 00:30:22,080 Speaker 1: and that there are women working right now who are 496 00:30:22,160 --> 00:30:26,200 Speaker 1: doing incredible things, but we need more of them, which 497 00:30:26,240 --> 00:30:28,480 Speaker 1: is why I'm quitting the podcast to become an engineer. 498 00:30:29,440 --> 00:30:32,840 Speaker 1: No please, I'll tell you what it excited me. Honestly, 499 00:30:33,040 --> 00:30:36,320 Speaker 1: just learning about engineering. It honestly made me feel like 500 00:30:36,360 --> 00:30:39,240 Speaker 1: a senior in high school looking through the college pamphlets 501 00:30:39,280 --> 00:30:44,400 Speaker 1: thinking about, Oh, all these incredible things people are doing. Um, 502 00:30:44,480 --> 00:30:50,840 Speaker 1: but I do really want to hear from engineers out there, male, female, whomever, 503 00:30:51,440 --> 00:30:54,160 Speaker 1: because I would I would love to get an inside 504 00:30:54,360 --> 00:30:57,719 Speaker 1: view of what it is really like because there are 505 00:30:57,760 --> 00:31:03,160 Speaker 1: those vastly different workplace survey results saying oh, everything's great, No, 506 00:31:03,280 --> 00:31:06,120 Speaker 1: everything's terrible, huh. So let us know what it's like. 507 00:31:06,240 --> 00:31:09,920 Speaker 1: And also if there any notable women engineers that we 508 00:31:10,000 --> 00:31:13,080 Speaker 1: should promote, let us know all of your engineering thoughts. 509 00:31:13,080 --> 00:31:15,400 Speaker 1: Mom Stuff at discovery dot com is where you can 510 00:31:15,440 --> 00:31:18,520 Speaker 1: send your letters. You can also tweet us at Mom's 511 00:31:18,560 --> 00:31:22,600 Speaker 1: Stuff podcast or send us a message on Facebook. And 512 00:31:22,680 --> 00:31:28,280 Speaker 1: now back to our letters. So I've got a letter 513 00:31:28,360 --> 00:31:33,360 Speaker 1: here from MG who is a Mexican physicist, and she 514 00:31:33,440 --> 00:31:37,960 Speaker 1: had some thoughts on our women in Science episode, and 515 00:31:38,200 --> 00:31:40,600 Speaker 1: she said, while growing up, I didn't experience such a 516 00:31:40,640 --> 00:31:44,200 Speaker 1: strong gender bias in science education. I've always been good 517 00:31:44,200 --> 00:31:46,440 Speaker 1: in math, and I've always felt proud about it. But 518 00:31:46,520 --> 00:31:48,320 Speaker 1: once I was in the last year of high school, 519 00:31:48,320 --> 00:31:51,800 Speaker 1: the picture change. In Mexico, one has to choose a 520 00:31:51,800 --> 00:31:54,920 Speaker 1: major when applying to a university, and once in university, 521 00:31:55,080 --> 00:31:58,600 Speaker 1: one takes the corresponding courses. I e's not possible to 522 00:31:58,640 --> 00:32:01,720 Speaker 1: decide a major actor and old. I was very interested 523 00:32:01,720 --> 00:32:04,200 Speaker 1: in both math and physics, and before deciding which major 524 00:32:04,240 --> 00:32:06,320 Speaker 1: I would study, I went to the university to talk 525 00:32:06,320 --> 00:32:09,160 Speaker 1: with several researchers to make up my mind, and although 526 00:32:09,160 --> 00:32:11,040 Speaker 1: the information they gave me was useful, I was very 527 00:32:11,040 --> 00:32:14,120 Speaker 1: disappointed by the lack of women researchers. The ratio of 528 00:32:14,200 --> 00:32:17,360 Speaker 1: men to women researchers in physics and math, at least 529 00:32:17,360 --> 00:32:20,120 Speaker 1: in the university I attended, is around one and ten. 530 00:32:20,680 --> 00:32:24,920 Speaker 1: This uninspiring scenario prevailed during my undergraduate studies and my 531 00:32:25,000 --> 00:32:29,280 Speaker 1: master's studies, which I just finished Congratulations. Despite that, I'm 532 00:32:29,320 --> 00:32:32,960 Speaker 1: extremely motivated to pursue a life career in physics. And 533 00:32:33,000 --> 00:32:35,800 Speaker 1: from time to time not having female role models that 534 00:32:35,840 --> 00:32:39,040 Speaker 1: I can relate to is demotivating. I have many anecdotes 535 00:32:39,040 --> 00:32:41,040 Speaker 1: that I could share, but to be brief, my viewpoint 536 00:32:41,120 --> 00:32:42,360 Speaker 1: is that one of the main reasons there are a 537 00:32:42,360 --> 00:32:44,520 Speaker 1: few women in science is because of our culture. I 538 00:32:44,560 --> 00:32:46,800 Speaker 1: even dared a fingerpoint that the pervasive idea that the 539 00:32:46,920 --> 00:32:49,720 Speaker 1: ultimate some may say only purpose of women on earth 540 00:32:49,800 --> 00:32:52,360 Speaker 1: is to procreate has a bad impact on women's self 541 00:32:52,400 --> 00:32:55,600 Speaker 1: image since it tends to diminish any other achievement a 542 00:32:55,640 --> 00:33:00,360 Speaker 1: woman can have in her life. So thanks MG, and 543 00:33:00,440 --> 00:33:04,160 Speaker 1: congratulations on that. Physics masters. Well, I have a letter 544 00:33:04,240 --> 00:33:08,800 Speaker 1: here from Elizabeth. She is a postdoctoral researcher in astrophysics 545 00:33:08,880 --> 00:33:12,160 Speaker 1: currently working at the Max Plank Institute for Astronomy. So 546 00:33:12,240 --> 00:33:16,520 Speaker 1: we I mean essentially have like a science celebrity writing 547 00:33:16,640 --> 00:33:20,080 Speaker 1: us right now, But she had some things to say. 548 00:33:20,280 --> 00:33:22,720 Speaker 1: She says this is purely anecdotal, but growing up in 549 00:33:22,760 --> 00:33:25,240 Speaker 1: a small town in Portugal, I was always very fascinated 550 00:33:25,240 --> 00:33:28,560 Speaker 1: by science, especially astronomy, and I did well in math 551 00:33:28,600 --> 00:33:31,040 Speaker 1: and physics at school. I have a twin brother who 552 00:33:31,080 --> 00:33:34,400 Speaker 1: himself has always been more inclined to the humanities. People 553 00:33:35,000 --> 00:33:37,800 Speaker 1: like friends teachers and family found it very puzzling and 554 00:33:37,880 --> 00:33:41,200 Speaker 1: kept commenting on how we could quote unquote reversed the 555 00:33:41,280 --> 00:33:43,640 Speaker 1: gender roles when we chose what to pursue in high 556 00:33:43,640 --> 00:33:46,440 Speaker 1: school and college. It seemed natural for some people that 557 00:33:46,520 --> 00:33:48,840 Speaker 1: I should have been the humanities inclined twin and my 558 00:33:48,880 --> 00:33:51,600 Speaker 1: brother should have been the science incline one. We weren't 559 00:33:51,680 --> 00:33:54,040 Speaker 1: raised in the most gender blind way. For example, I 560 00:33:54,080 --> 00:33:56,480 Speaker 1: played with a lot of pink stuff and ponies and barbies, 561 00:33:56,520 --> 00:33:59,440 Speaker 1: and my brother had the more masculine toys like robots 562 00:33:59,440 --> 00:34:01,880 Speaker 1: and legos, and overall I was very much encouraged to 563 00:34:01,880 --> 00:34:05,080 Speaker 1: pursue feminine activities like learning to cook and such. But 564 00:34:05,120 --> 00:34:07,560 Speaker 1: the fascination with nature, physics, and the beauty of the 565 00:34:07,680 --> 00:34:10,600 Speaker 1: night sky one over all of that. But I would 566 00:34:10,640 --> 00:34:13,040 Speaker 1: say I had to be quite strong willed to pursue 567 00:34:13,080 --> 00:34:16,880 Speaker 1: that interest against all stereotypes. Not to mention, after physicist 568 00:34:17,040 --> 00:34:19,560 Speaker 1: is not really a common career path in Portugal, let 569 00:34:19,560 --> 00:34:22,280 Speaker 1: alone in my small town. I am sure that girls 570 00:34:22,320 --> 00:34:24,359 Speaker 1: and women could be as good as boys and men, 571 00:34:24,440 --> 00:34:26,840 Speaker 1: and math and science, and any differences we see in 572 00:34:26,880 --> 00:34:31,000 Speaker 1: the student or scientist population results from ingrained sexist biases 573 00:34:31,040 --> 00:34:34,279 Speaker 1: in our culture, and these biases can be damaging at 574 00:34:34,280 --> 00:34:36,319 Speaker 1: any level. I have seen it through my school years 575 00:34:36,320 --> 00:34:39,000 Speaker 1: but also now my academic path. I am very lucky 576 00:34:39,040 --> 00:34:41,840 Speaker 1: to work in a research institute where a large fraction 577 00:34:41,880 --> 00:34:45,120 Speaker 1: of researchers or female not quite fifty though, and the 578 00:34:45,160 --> 00:34:47,520 Speaker 1: work environment is one of the most female friendly ones 579 00:34:47,600 --> 00:34:51,200 Speaker 1: I know. However, you can see how lifelong prejudices and 580 00:34:51,239 --> 00:34:55,400 Speaker 1: biases can affect specifically women. Typically, women are less vocal 581 00:34:55,440 --> 00:34:58,359 Speaker 1: and less dominant in discussions than men, even when they 582 00:34:58,360 --> 00:35:02,600 Speaker 1: have comparable scientific ex rotise. Women in academia definitely tend 583 00:35:02,640 --> 00:35:06,040 Speaker 1: to suffer from imposter syndrome more than men, as you 584 00:35:06,120 --> 00:35:08,480 Speaker 1: discussed in the line in episode, which I think is 585 00:35:08,480 --> 00:35:11,320 Speaker 1: a center of the field still being very male dominated. 586 00:35:11,719 --> 00:35:13,960 Speaker 1: Hopefully things are improving for the better as more and 587 00:35:14,000 --> 00:35:17,480 Speaker 1: more women get PhDs in science fields and more women's 588 00:35:17,520 --> 00:35:21,400 Speaker 1: scientists with visibility outside of academia equals more role models 589 00:35:21,440 --> 00:35:26,319 Speaker 1: for young girls, which is really good news. Good news indeed, Elizabeth, 590 00:35:26,440 --> 00:35:29,120 Speaker 1: thank you so much for writing and telling your story, 591 00:35:29,560 --> 00:35:32,000 Speaker 1: and thanks to all of the scientists that we've been 592 00:35:32,080 --> 00:35:35,839 Speaker 1: hearing from lately. We want to hear from everybody. Mom 593 00:35:35,920 --> 00:35:38,960 Speaker 1: Stuff Discovery dot Com is where you can send your letters. 594 00:35:39,000 --> 00:35:41,560 Speaker 1: You can also tweet us at mom Stuff podcast or 595 00:35:41,760 --> 00:35:44,359 Speaker 1: send us a message on Facebook like a stair while 596 00:35:44,400 --> 00:35:47,319 Speaker 1: you're at it. And for some more fun stuff, we're 597 00:35:47,360 --> 00:35:50,480 Speaker 1: on Instagram at stuff mom Never Told You and on 598 00:35:50,560 --> 00:35:52,640 Speaker 1: Tumbler as well. It's stuff I've Never Told You dot 599 00:35:52,680 --> 00:35:56,120 Speaker 1: tumbler dot com. And for your viewing pleasure, we have 600 00:35:56,400 --> 00:35:59,040 Speaker 1: a YouTube channel that you should definitely go check out. 601 00:35:59,400 --> 00:36:02,480 Speaker 1: It's YouTube dot com slash stuff Mom Never Told You, 602 00:36:02,840 --> 00:36:09,040 Speaker 1: and don't forget to subscribe for more on this and 603 00:36:09,120 --> 00:36:11,680 Speaker 1: thousands of other topics, Does it How stuff works dot 604 00:36:11,719 --> 00:36:20,640 Speaker 1: com