WEBVTT
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Look at this email?
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What does it mean?
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Communication is the imparting or exchanging of information or news.
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The single biggest problem in communication is the illusion that
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it has taken place.
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Conversation is the oral exchange of sentiments, observations, opinions, or ideas.
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Forbes Books Radio presents the conversation with Clinton and Pageant.
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For years, parents, educators, and business leaders have tried to
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encourage more young women to pursue careers in science and engineering.
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But what if the problem isn't that we aren't trying
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hard enough. What if it's the way we're having the conversation.
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My guest today, Julie Newman, argues that instead of pushing
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girls towards STEM, we need to help them discover what
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might naturally just pull them toward it. Julie is the
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best selling author of Pull, Don't Push, Why STEM messaging
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the girls isn't working, and what to do instead. She's
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also an accomplished aerospace engineer who has worked on programs
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including the Impulse Mirror spacecraft, SpaceX, Falcon nine, Boeing Starliner,
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NASA Space Launch System, and the Europa Clipper mission. What
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I find particularly interesting about Julie's work is it isn't
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simply about engineering, which of course I love as an
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engineer myself. It's about communication, influence, leadership, and how the
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conversations we have can either open possibilities for people or
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unintentionally close them. Julie, welcome to the conversation.
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Thanks so much, Clint. I am so excited to be
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here today. You know, this is a topic very close
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to my heart obviously, and the aspect of communication is
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just so important.
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It absolutely is. If people don't want to have conversations,
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they want to send text messages and try to get
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it over as quickly as possible, but the collaboration happens
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in the conversation, in my perspective at.
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Least absolutely so.
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I had to think of all the people that come
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on to get on the show as superheroes, and so
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you're a superhero today, what is your ridin story? Because
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all superheroes have origin stories? What's yours?
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Yeah? Absolutely, so, you know, first of all, I'll turn
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it back on you, Clint. Why did you become an engineer?
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When do you feel like you first learned about engineering?
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So this is funny because when I was a kid,
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I knew I wanted to be a lutchal engineer from
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the time I was about ten years old. So I
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would ride my bicycle to the library. This is dating
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myself because you know, we didn't have scooters and lines.
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My bicycle to the library and check out books on
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robotics and lasers and my In my junior year of
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high school, I did a science project which was using
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a laser to create a hologram because they have a
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Star Wars big at the time, right, So I knew
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I wanted to be a Lutch engineer from the time
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I was about ten.
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Oh see, there you go. That's awesome. You know, for me,
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my original story, I think looking back, it was something
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similar where I knew earlier, but I didn't have the
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words to describe it. And it's a story that I
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hear repeated over and over again, especially with women and engineering.
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So for me growing up, I you know, had a
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whole slew of different interests as everyone else every kid does,
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and one of those was I really loved things like
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you know, Lego and connects, and then got myself involved
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in a lot of the science competitions at school and
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just always liked the more technical aspects. Loved learning things
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like that. In particular, I got involved in middle school
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with a competition called Science Olympiad, just a nationwide competition.
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Maybe some of your listeners have their kids in it
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right now, but for that I really got into my
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groove so building robots and model airplanes and model rockets
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and really just a whole slew of different fun things.
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But what was crazy was that it's called Science Olympiad.
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I really never associated the word engineer with what I
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would later do until honestly, I was picking out a
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major to go to college, where I was like, oh, okay,
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well I want to like make stuff and you know,
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invent things, and who does that? And then finally at
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that point is when the word engineering comes up. So
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for me it was at Caltech. Chose electrical engineering, frankly,
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without actually a lot of electronics experience. Really didn't have
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any of that in schools when I was going through,
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and I kind of thought of it as well, I
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can pick electrical or mechanical, and now I mean I
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can work on anything, and so I thought electrical seemed
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hard to learn, so I picked that one. And you know,
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I think it's it's it's fun to tell kids that story,
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especially because they always think that we had it all
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figured out right, and that sometimes actually it's just little
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nudges that actually led to the entire path of your future.
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So I took that from studying in college, and then
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really while I was in college, trying out a few
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different things, realizing I didn't quite like medical devices, I
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didn't quite like you know, more like chip fabrication things,
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and then ultimately ended up getting into an internship at SpaceX,
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and that was really what sealed the deal for me.
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Absolutely loved it, loved the people, loved the speed, love
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the impact, and really quickly rekindled my love of space,
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which I had had from my earliest days and had
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never really thought that I could do a career in it.
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And here we are, you know, decade and a half later,
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and it's been space the whole time, and I've been
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absolutely loving it. And so yeah, after college, after SpaceX
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went over to NASA Jet Propulsion Laboratory, worked on a
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number of really really cool satellites. But I'll say my
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favorite one to talk about is the europe Clipper mission,
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which you mentioned in the intro. That is a mission
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which is currently on its way to Jupiter. I designed
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part of the radar instrument, So from a blank sheet
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of paper to a series of boxes and systems that
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are working on the satellite. Today it's flying towards Jupiter
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and it will get there in twenty thirty, so mark
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your calendars. Will be investigating the moon of Jupiter Europa,
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which has a big liquid water ocean and the potential
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for extraterrestrial life, so keep your fingers crossed. After JPL,
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I then moved over to Boeing and worked on a
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number of really cool flagship programs over there as well.
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So a few you mentioned in there, the Space Launch
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System that was at the time the largest rocket that
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it ever launched SpaceX has since broken that. Good to them,
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and also briefly the Starliner crew vehicle, and a number
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of different satellite programs there, culminating in being the chief
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engineer for a large constant, a large geostationary satellite communications program,
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really really fun stuff and definitely the underpinnings of which
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are the communication and understanding the interplay of different people
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and products and disciplines, and something that over the course
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of my career I've definitely moved into a more interdisciplinary
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role from not just an electrical engineer I tend to
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myself an aerospace engineer now, not just an electrical engineer
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because I've grown into the other directions. But after Boeing
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then moved over to a startup. This was a startup
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called Outpost. They are developing a re entry vehicle, So
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I think a satellite that comes back from space really
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cool applications, particularly in the opening the in space manufacturing
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goods market and also the military logistics market. There, I
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was the VP of Engineering before moving to my current role,
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which is at Impulse. Impulse Space was founded by Tom Muehler,
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who was the first employee at SpaceX, the absolute expert
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in rocket propulsion, the reason that the Falcon nine rockets
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were so amazing, and I am his chief engineer for
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the satellite program called Mira, where again my role is
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really being that connector and making sure that our satellites work,
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making sure that it's managing risk and technical details, and
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growing the capability of the spacecraft over time.
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Well, I actually like the fact you call yourself an
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aerospace engineer now because it just to me, it just
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proved positive that electrical engineers can do anything.
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You can do anything. That's the whole point.
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Yeah, So let's define engineering, because you make a point
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in the book that common definitions like engineering is the
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application of math and science, or engineers built stuff for
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really inaccurate. So how do you define engineering?
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Yeah, so my favorite short way to explain it is
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that engineers work creatively in teams to solve problems that
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help people. And there's a chapter in the book. Thank
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you Clint for going through it. There's a chapter in
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my book where I walk through all these different definitions
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and why certain ones fall short, and in particular I've
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crafted this definition. You know, one sentence takes a long
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time to sort when you really want to get it
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to the real core. It's the I had more time,
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I'd written a short, shorter letter. Well, I spent a
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lot of time and I wrote a short letter. The
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the core pieces in there are Creativity is one of
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the key pieces that I think really defines engineering but
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is never used. It's something that resonates really really well
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with kids. You know, the the creative kids are often
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you know, sort of shuffled towards more of like the
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arts and the like. But then there's a different type
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of creativity, which is you know, building things and and
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systems for for the world, you know, refining things, getting
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to that craftsman nature of development of you know, making
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a thing and making it a little bit better and
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a little bit better until it's really like, you know,
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a steam engine running perfectly, so to speak, or maybe
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literally depending on your field. And then the other aspect
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keyword in their teamwork. Really the things that engineers work
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on are too big to be done alone. You will
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very very rarely find a solitary engineer, and similarly it's
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hard to find you know, Tom Mueller may be an
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exception where you can put a name to an amazing
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technology that was developed, it's much more frequently that it's
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a large team which is related to it. And also, honestly,
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Tom too would say that it was a large team
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developing the Falcon nine rocket as well Falcon nine engines.
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The core piece there is that teamwork is really a
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necessary aspect and being solitary will not make you a
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successful engineer. You have to learn to work with people.
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You have to learn to communicate and how to engage
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between different groups, because that's what makes you successful and
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that's what makes a final product work really well. Right, Like,
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there's many different disciplines even within engineering and you're not
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going to be an expert in all of them. You
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have to be able to if you're the electrical engineer,
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work with the mechanical engineer, or work with the test engineer,
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or work with manufacturing and near to really bring the
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whole thing together. So let's see we're creatively in teams
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to solve problems that help people solving problems. Another really
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core aspect and something that I think communicates really well.
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You know, engineers aren't off on you know, a research
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tangent to discover, you know, why this fruitfly does this
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particular thing that's super cool, but it is not a
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known problem that you need to solve. It is a
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thing you're learning, whereas engineers at companies are generally being
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brought in because the company has a problem and they
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want it solved by someone. And that is what engineers do,
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is they come in and they solve problems. And I
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think that's something that that kids especially can really connect to.
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They can understand like, oh, it's all sort of these
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little investigations or it's you know, making something work, and
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that is is really something that again when we're trying
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to bring the definition down to the explain like I
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five level or to the you know, the high school
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er sort of level, the everyone on the street who
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never thought about engineering at all level. That really communicates
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quite well. And in particular, the goal of my book
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is really to help educators understand engineering. That's one of
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the primary roadblocks to being able to help the girls
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learn about engineering is if the teachers who are interfacing
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with them don't know either, and don't know enough to
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even pull in engineers to talk to them, then well
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that's not going to end up with the outcome we want.
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So going back to the no single solitary engineers, you
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can't all be Sheldon, right, Sheldon is a is a
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TV show. He's not.
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Yeah, he's a real engineer. Well and the funny thing too, Yeah.
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Is so fun of the engineer on the show.
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Yeah. The Big Bang theory so is set on fictional JPL,
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NASA JPL and fictional Caltech, both of which I have
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extreme insights into. And I will tell you will find Sheldon,
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but they are not the most successful. And they're also
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like far outnumbered by people that you know, you would
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otherwise consider pretty normal by by everyone's standard, so to speak. Uh,
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and and so it is funny that that is the
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the picture that the media portrays of engineers and of scientists.
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That's often a very skewed representation, which is pretty interesting.
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Yeah, could you talk about it in the book you
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do you tend to find those people more in academia
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than you do other places.
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You know, academy, Yeah, yeah, yeah, you know, academia on
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its own is usually considered a more solitary pursuit, and
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so that's where a lot of you know, that personality
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type can be more successful, is more in a research direction.
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But I think even in academia, you know, network and
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interconnection and the interplay between different fields is a very
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very valuable asset as well. So again it's more common
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that interacting with other people makes you more successful than
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it is solitary does.
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I think if you do your research, you'll leve and
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see that some of the some of the people credited
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for being inventors of things, I think even went back
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to the light bulb and things like that, it's basically
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there was a team behind them. There was one person
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taking credit, but they employed a team that was really
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doing the work.
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So yeah, exactly. Yeah, there's very very few things where
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they were yes, invented by a person and then also
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proliferated out. You know, maybe you know, we can give
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what is it? It's shockly and the a couple people
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from Belt Labs get to say they made the transistor,
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but what they made is nothing that looks like what
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the current transistor is. We can say that, yeah, for sure.
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So you've worked at some very different environments and all
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the different companies we talked about earlier. I was wondering,
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how has each organization shaped your understanding of engineering and leadership.
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Oh, yeah, well I think it's more similar than people
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would expect. So I do have, Yeah, the fun advantage
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from the aerospace perspective of I've you know, I've been
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at NASA, I've been at Big Aerospace, I've been at
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Startup Aerospace, and I've seen SpaceX and now I'm at Impulse,
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and they're all a lot more similar than you would expect,
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and a piece of me actually, I like to look
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at it as they're all kind of the evolution of
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the same thing. So when you see earlier it's often
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you know, no one wants bureaucracy to take over. There's
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not an individual person who's like man I would love
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if we just bogged this entire company down and went
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as slow as possible and that we couldn't make decisions
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for years. Right, There's no one doing that, and so
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it's really an emergent behavior at large scale when you're
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not correcting for it. And that's really a key piece
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is you know, I think if I were to go
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to like a root cause on it, a big piece
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to a lot of that is, you know, not having
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the conversations that needed to be and letting problems linger,
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and the the the nature of you know, maybe the
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innovator's dilemma of continuing to do what has always worked
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because it has worked even though the situation has changed.
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And I really see that as a common theme and
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something as I've now moved my career towards smaller, newer
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companies to really focus more on Okay, we can see,
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we can see what the future could be. How do
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we avoid the pitfalls? Because other people have also tried
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to avoid the pitfalls and haven't been successful, So how
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do we try something different? How do we learn from
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what they went through and to really make sure that
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while we won't be perfect, we can make ourselves more
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efficient than before. So to speak.
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Now you've done a lot through outreach through for STEM,
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and I'm just wondering what finally convinced you to write
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the book. And the book again is pull, don't push?
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Yeah, yeah, the you know, I never the origin for
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the book never quite made it into the book in
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the original iteration. But you know, you started with the
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superhero story, and I would say the beginning of the
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book maybe was like it'll communicate, but like kind of
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the more like the super villain story. Like I was
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at an outreach event and gosh, I don't know this
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was this was actually early twenty twenty, before everything happened
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and or twenty nineteen, No, twenty nineteen. In twenty nineteen,
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I was sitting in an event and this was a
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really really great event where we had brought in something
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like three hundred girls from across the school district and
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had brought in a lot of professional women in STEM.
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And there was a speaker who was up there, and
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the longer she talked, it sounded like a great presentation.
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And this is someone who had been featured on you know,
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like real television as a local woman in STEM and things.
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And the longer she talked, the matter and matter I
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got like I was literally furiously writing angry notes on
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my paper of like, you know, you said this, but
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then aarrow what they actually hear is this, And you know,
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it comes back to a quote that I think you
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have in your book and you say a few times
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of you know, the scariest thing or the most risky
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thing about communication is the assumption that it has happened,
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or the illusion that it has happened. So she thought
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she was communicating this really inspiring message, but what she
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was actually doing was pushing the girls away. And a
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lot of that is in you know, speaking about it
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as making the whole universe of STEM very scary. You know,
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if you say to a room full of middle school
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and high school girls, hey, everyone thinks that women don't
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belong in STEM, but I'm here to tell you that
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they're wrong. Is well, you just told them that everyone
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thinks that this is not for them, and that's really
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not the way to do it, especially when she herself
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had a very very cool career doing very cool things
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that she could be talking about that would be inspiring.
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And so what I had found and what this this
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one presentation then finally culminated in is. I then suddenly
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started to see the matrix of every event that I
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had been to, where they'd always tapped into this real
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negativity and this real you know push mindset of really
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feeding into this isn't for you, this isn't for you,
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This isn't for you, but we're here to tell you
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can do it anyways, or you know, the math is
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really really hard, but it's really really worth it and
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it's really really important, or things like oh yeah, well,
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growing up, I was the weird kid and no one
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liked me at all, and that's why I'm a great engineer.
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And you'd actually hear, well usually be scientists as well.
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They're almost never engineers at these events, which is the
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other primary problem. But you know, you come up with
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these stories, and then it really doesn't take a rocket
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scientist or a rocking engineer to listen to those statements
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and say, huh, I wonder, I wonder if maybe that's
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not encouraging, right, And so fundamentally it just became so
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obvious to me. And you know, teachers have such a
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hard job, and educators have such a hard job, and
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the ones especially setting up these events and really trying
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to help their students. They're just hearts of gold, right,
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And you know, I can see from all of them
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because I've worked with so many outreach events and now
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help with Science Olympiad. You know, they're overworked and underfunded
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and the easiest thing to do is what everyone else
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has done before, and that allows them to get through
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these events, and they don't really necessarily have the time
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and space to pause and think about why they're saying
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these things or how these things are being interpreted, and
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so largely the book. You know, I went home with
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like ten pages of papers that ended up being a
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you know, the early foundations of the book. But I
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went home and I was like, how can I help
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And how can I just tie it all in a nice,
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a nice communicative bow where they can understand where I'm
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coming from, because I'm the one from the other side
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that saw it work for me, and I'm the one that,
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you know, was it was a girl who would have
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loved being in those rooms. And if I see myself,
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you know, sitting at that event as a young kid
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and it being a negative impact towards my future career,
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which I absolutely love. I'm so happy that what I'm
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doing and frankly too, I am since releasing the book
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and since speaking more and going through the topics of
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the book. You know, the kids are one thing and
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absolutely warms my heart every time one of them tells
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me they're more excited about engineering or they now they
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want to be an engineer. Actually, I have a really
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lovely story of a girl who was at one of
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these events after I had published the book and after
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I was presenting and you know, keeping it all in line,
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and she reached out to me years later and said,
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you might not remember me. She found me on LinkedIn.
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You might not remember me, but I just wanted to
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say I'm an engineer because we talked at this event
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and now I'm studying mechanical engineering at Berkeley. And then
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she reached out later and she got her first job
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and she's in aerospace in LA and it's just so cool.
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But you know, thinking from the side of the kids
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is one thing. But the other thing that has really,
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you know, really driven it home for me emotionally on
400
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the impact of this message is really more the adults.
401
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So it's the women who come up to me, who
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are the teacher in the room or the mom in
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the room, and they come up to me and they say, wow,
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I never knew any of that. I could have been
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an engineer when I was younger, and no one ever
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told me. And now it all makes sense that that's
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what I should have done. And instead they went and
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they did other things. And you can never walk to paths.
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But the number of women who come up and say, wow,
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if I had sat in this room when I was
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middle school, high school age, I think I would have
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become an engineer is really, I think, proof point for
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how impactful it could be.
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I think, I see, I love the way you wrote
415
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the book and the examples you use. One of the
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things you're just talking about, I can actually see where
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this this scientist or engineering was speaking and about everybody
418
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tells you this. You can kind of see where Look
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what all I overcame, you know, to get here, so
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that you see that. And then there's kind of the
421
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ugly Duckley story about people think I'm weird, but I'm
422
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a great engineer now, and that probably resonates with some people.
423
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But if you want to get more people involved, then
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it needs to be it needs to be more open,
425
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and I think a positive message pushes that more than
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just the I had to overcome all these things to
427
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get here.
428
00:23:51.799 --> 00:23:54.960
Yeah. Yeah, there's a subtlety to it, and it's really
429
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a question of, you know, matching the message to the
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room and so having the reverence for the women that
431
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did have really difficult times or went through huge challenges
432
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is really important. But the best way to honor what
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00:24:09.839 --> 00:24:12.599
they went through is not to push girls away from
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doing it too. It's to help them learn all of
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the great things about it and to be able to
436
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make the choice for themselves if they if they think
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engineering is right for them.
438
00:24:23.519 --> 00:24:25.799
So let's talk more about push versus pull. So what
439
00:24:25.920 --> 00:24:28.279
is the essential difference between pushing someone toward a career
440
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and pulling them toward a possibility.
441
00:24:30.759 --> 00:24:35.319
Yeah, So it's a lot of these a lot of
442
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these events and language that we use with children, it's
443
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often sort of you know, you can almost imagine like
444
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standing behind them and kind of shoving them in the
445
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right direction of or or or kind of putting things
446
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on top of them. As far as narratives, and one
447
00:24:50.319 --> 00:24:54.119
of those is, yes, the really dated narratives of you know,
448
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if you go become a female engineer, all of your
449
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male coworkers will hate you, like I've never found that,
450
00:25:01.640 --> 00:25:05.079
and you know, there's there's people when people working together
451
00:25:05.240 --> 00:25:08.160
is always always has its issues. But frankly it's a
452
00:25:08.160 --> 00:25:11.200
lot better than it used to be, and it's something
453
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that's not the norm anymore. So pushing is really forcing
454
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something on onto the kids, whereas pulling is more of
455
00:25:21.119 --> 00:25:24.279
think of it more like enticing. Right, it's telling them, oh,
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hey did you know that? Uh, the top paid college
457
00:25:29.200 --> 00:25:32.519
majors are all in engineering, Like you know, just thought
458
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you should know that, and that will pull them.
459
00:25:36.480 --> 00:25:36.759
You know.
460
00:25:37.319 --> 00:25:39.319
You know, if money is if you want to make
461
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a lot of money, you know, maybe you think about it, right,
462
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or hey, if you if you want to change the
463
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course of humanity and maybe make it so that we
464
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have people on Mars one day, you know, you could
465
00:25:49.920 --> 00:25:53.400
look at engineering. That might be an interesting, interesting path
466
00:25:53.480 --> 00:25:57.119
for you. So it's really more about you know, I'm
467
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a big advocate for helping kids make the decisions themselves,
468
00:26:03.440 --> 00:26:06.759
because ultimately you can't really force them, or if you do,
469
00:26:06.839 --> 00:26:09.759
they're going to resent it later, and so why would
470
00:26:09.799 --> 00:26:12.640
we try? Right, It's much easier. It's honestly a lot
471
00:26:12.680 --> 00:26:16.720
more fun too. So I you know, when I'm out speaking,
472
00:26:16.799 --> 00:26:19.039
I would so much rather talk about all the fun
473
00:26:19.079 --> 00:26:21.039
things that I have done in my career and the
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00:26:21.119 --> 00:26:24.240
cool stories where you know, we were down in the
475
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trenches fixing this problem and then we solved it and
476
00:26:26.519 --> 00:26:29.160
we all felt so wonderful, and I'd so much rather
477
00:26:29.240 --> 00:26:32.279
talk about that than, you know, any of the negativity
478
00:26:32.920 --> 00:26:36.000
that so often gets ninety nine percent of the airtime.
479
00:26:37.200 --> 00:26:39.119
Well, you know, you make a point also in the book.
480
00:26:39.119 --> 00:26:41.599
Then another, I guess pull conversation could be that if
481
00:26:41.640 --> 00:26:43.640
you want to have a family, engineering is a way
482
00:26:43.640 --> 00:26:45.960
to go, because it doesn't you're not a lawyer trying
483
00:26:46.000 --> 00:26:47.759
to put in ninety one hundred hours a week to
484
00:26:47.839 --> 00:26:50.920
get partner and yeah, you prove positive, right, you have
485
00:26:51.640 --> 00:26:52.759
a growing family as well.
486
00:26:53.400 --> 00:26:57.839
Yeah, yeah, And I think that's something that also resonates
487
00:26:57.839 --> 00:27:01.480
really well with the girls. You know, a lot of
488
00:27:02.559 --> 00:27:04.960
a lot of kids to take an example, right, and
489
00:27:05.000 --> 00:27:07.880
actually myself included. When I was young, I thought about
490
00:27:07.880 --> 00:27:09.920
being a doctor, and I thought I would love to
491
00:27:09.920 --> 00:27:12.359
be a doctor. But then I looked at some numbers
492
00:27:12.400 --> 00:27:14.240
and I was like, wow, you've got to be at
493
00:27:14.240 --> 00:27:16.759
school a long time. And I want to do things
494
00:27:16.799 --> 00:27:19.759
that are also not just being a doctor. And so
495
00:27:19.880 --> 00:27:22.960
for me, that kind of made me not want that path.
496
00:27:23.319 --> 00:27:26.400
And what a lot of kids don't realize is they
497
00:27:26.440 --> 00:27:29.400
conflate science with engineering if they even think about engineering
498
00:27:29.400 --> 00:27:32.720
at all. And then scientists, pretty much exclusively, you have
499
00:27:32.759 --> 00:27:36.039
to go down the much longer schooling path to be
500
00:27:36.039 --> 00:27:40.000
successful as a scientist, usually a master's PhD program many years.
501
00:27:40.599 --> 00:27:44.519
But in engineering, actually the vast majority don't have graduate
502
00:27:44.559 --> 00:27:47.839
degrees and can be very very successful without graduate degrees.
503
00:27:48.119 --> 00:27:52.000
And if anything, many many engineers, myself included, would argue
504
00:27:52.039 --> 00:27:55.319
that the four two end years you spend doing a PhD,
505
00:27:55.799 --> 00:27:58.000
you actually might learn more if you were at your
506
00:27:58.079 --> 00:28:02.640
job doing cool things and learn on the job. But yeah,
507
00:28:02.680 --> 00:28:05.559
so for me, you know, a piece to engineering is
508
00:28:05.559 --> 00:28:08.240
it's about solving these problems, and you can't do them
509
00:28:08.599 --> 00:28:10.839
for eighty hours a week necessarily, or at least you
510
00:28:10.839 --> 00:28:15.519
can't do that forever, and so it's really providing that
511
00:28:15.599 --> 00:28:18.640
value and then solving those problems that that makes it.
512
00:28:19.599 --> 00:28:22.480
Engineers are very valuable to companies and so companies have
513
00:28:22.559 --> 00:28:26.279
to kind of give the best perks and uh, you know,
514
00:28:26.400 --> 00:28:31.559
be more accommodating of their the workforce of engineers. So
515
00:28:31.640 --> 00:28:35.480
for me, it's been incredibly valuable. I my husband's also
516
00:28:35.519 --> 00:28:39.880
an engineer, and we have three kids right now, that's
517
00:28:39.880 --> 00:28:42.799
something that yeah, certainly had I for example, if I
518
00:28:42.880 --> 00:28:44.880
were coming out of residency and had been a doctor
519
00:28:44.920 --> 00:28:46.279
for a few years, to be a lot harder to
520
00:28:46.440 --> 00:28:51.160
already have three kids. And fun fact surprise is I
521
00:28:51.160 --> 00:28:56.160
actually have more on the way. Uh just waterline here. Yeah,
522
00:28:56.319 --> 00:29:03.799
we've very lucky have a twin coming. We started crazily enough,
523
00:29:03.839 --> 00:29:07.039
we started with a set of twins and twin boys,
524
00:29:07.519 --> 00:29:10.039
then had a girl, and then now we're having twins again.
525
00:29:10.119 --> 00:29:11.079
We're getting one to each.
526
00:29:11.359 --> 00:29:15.880
So well that's a balance. Yeah, how do you engineer that?
527
00:29:16.480 --> 00:29:19.599
I know, right, I don't think you can. But when
528
00:29:19.599 --> 00:29:22.200
I figure it out, I'll let you know. But I'll
529
00:29:22.240 --> 00:29:25.119
say engineering systems do help our household function.
530
00:29:26.079 --> 00:29:28.079
You have to with that many kids. Well you only
531
00:29:28.079 --> 00:29:30.720
got three now, but we're two more. Wow, I have
532
00:29:30.759 --> 00:29:34.160
two kids. I can't imagine five. That's a lot. So
533
00:29:34.440 --> 00:29:36.480
you know, we've been talking about messaging, and you know,
534
00:29:36.519 --> 00:29:38.440
you and I were joking in the green room before
535
00:29:38.440 --> 00:29:41.279
we started this recording. In the book, you use the
536
00:29:41.319 --> 00:29:44.200
Navy slogan join the Navy, see the world and not
537
00:29:44.359 --> 00:29:46.759
join the Navy have a really difficult time on a
538
00:29:46.759 --> 00:29:48.880
boat for a while, and so having been six years
539
00:29:48.880 --> 00:29:50.839
in the navy, I actually made it even worse. I said.
540
00:29:51.119 --> 00:29:53.240
They don't say, joined the Navy, work twelve hours a day,
541
00:29:53.240 --> 00:29:55.319
seven days a week, sleep in a birthing area with
542
00:29:55.359 --> 00:29:58.960
seventy three other stinky guys, because that's what ends up being.
543
00:29:59.079 --> 00:30:00.920
They don't usually put that on pamphlets, right.
544
00:30:00.960 --> 00:30:03.839
They don't usually. Speaking of recruit you mentioned recruiting earlier
545
00:30:03.839 --> 00:30:07.000
than you know, the recruiters, they don't they Yeah, funny,
546
00:30:07.119 --> 00:30:09.279
I never never occurred to me. Sailors made for ships,
547
00:30:09.279 --> 00:30:11.240
and ships are made for sea, and we signed up
548
00:30:11.240 --> 00:30:12.680
for six years. You can spend five and a half
549
00:30:12.720 --> 00:30:15.079
of those at sea, but they should They don't tell
550
00:30:15.119 --> 00:30:15.599
you that part.
551
00:30:16.240 --> 00:30:18.799
Yeah, yeah, And and that's the crazy thing is I
552
00:30:18.799 --> 00:30:22.400
have literally seen, you know, pamphlets for girls and STEM
553
00:30:22.480 --> 00:30:26.119
events where the whole thing is just covered in statistics
554
00:30:26.160 --> 00:30:28.960
about how few women there are an engine in stem
555
00:30:29.599 --> 00:30:31.880
uh and and you know how hard it's going to
556
00:30:31.960 --> 00:30:34.279
be and all of that stuff. When yeah, they didn't
557
00:30:34.279 --> 00:30:37.920
devote any airtime to or any of the space to oh,
558
00:30:38.000 --> 00:30:40.519
look at the open waters, look at all the places
559
00:30:40.519 --> 00:30:42.799
in the earth a're going to travel, it'll all be water.
560
00:30:43.480 --> 00:30:49.480
H But the marketing aspect to it, it really is. Yeah,
561
00:30:49.519 --> 00:30:52.559
the marketing one o one of sell the positives, right, Yeah,
562
00:30:52.559 --> 00:30:55.720
that's always that's always the intro statement. It's it's very
563
00:30:55.799 --> 00:30:58.240
rare that a salesperson is going to tell you just
564
00:30:58.359 --> 00:31:00.640
to walk in that room and say all of the
565
00:31:00.680 --> 00:31:03.920
worst things about the thing you're trying to sell. I mean,
566
00:31:03.960 --> 00:31:06.920
there's a tactic to that, but it doesn't it doesn't
567
00:31:06.960 --> 00:31:10.599
doesn't really communicate except to very particular audiences.
568
00:31:11.039 --> 00:31:12.759
Yeah, you don't go out dating that way either. Hey,
569
00:31:12.799 --> 00:31:15.000
I drink a lot and I smoke and I using
570
00:31:15.240 --> 00:31:15.920
things like that.
571
00:31:16.599 --> 00:31:20.720
Yeah, yeah, it's maybe it will find the right person,
572
00:31:20.799 --> 00:31:22.559
but there won't be that many of them.
573
00:31:23.880 --> 00:31:25.720
That's that's that's a good way to say it. And
574
00:31:25.920 --> 00:31:28.319
there's a as I said, I went to Georgia Tech,
575
00:31:28.480 --> 00:31:30.880
and there's a song about Georgia Tech called the Ratio
576
00:31:30.920 --> 00:31:32.799
and it talks about the ratio of men to women
577
00:31:32.839 --> 00:31:34.680
because he used to be forty four hundred to one,
578
00:31:35.160 --> 00:31:37.319
you know, and it's clearly gotten better. But the refrain
579
00:31:37.400 --> 00:31:40.039
from the song is just so great. And the refrain
580
00:31:40.200 --> 00:31:42.640
is the odds are good, but the goods are odd.
581
00:31:42.920 --> 00:31:49.200
So yep, that's been stated many a time, and you
582
00:31:49.240 --> 00:31:53.240
know it's kind of this this reinforcing it's fun and funny,
583
00:31:53.319 --> 00:31:56.079
but then it eventually you have to realize that. Then
584
00:31:56.119 --> 00:31:59.720
that messaging flows down where people actually think that, yeah,
585
00:32:00.039 --> 00:32:03.279
and you know, we're all weird in different ways for sure,
586
00:32:03.359 --> 00:32:07.240
but the you know, there's there's actually a lot of
587
00:32:07.279 --> 00:32:11.400
advantages to for example, being a woman in stem in
588
00:32:11.559 --> 00:32:17.119
the modern era where you know the song in reverse
589
00:32:17.240 --> 00:32:20.920
is you know, a bit better the ratio wise, so
590
00:32:21.240 --> 00:32:23.640
I will admit to having found my husband in college
591
00:32:24.160 --> 00:32:28.240
and an inverse ratio doesn't really hurt you there, and
592
00:32:28.599 --> 00:32:32.799
the same thing of I actually mentioned it in an
593
00:32:32.839 --> 00:32:35.079
intro chapter on the book, but or one of the
594
00:32:35.119 --> 00:32:38.839
chapters in the book that you know, from a job
595
00:32:38.880 --> 00:32:43.359
search perspective, a lot of companies really really would love
596
00:32:43.519 --> 00:32:48.160
to improve their ratios, and statistically everyone can't win, so
597
00:32:48.200 --> 00:32:50.680
that means you're a hot commodity when it comes to
598
00:32:50.960 --> 00:32:53.319
trying to get you into the different companies. You know,
599
00:32:53.359 --> 00:32:58.319
it's a very meritocratic field in general. But if you
600
00:32:59.000 --> 00:33:01.759
are really good and you also just so happen to
601
00:33:02.240 --> 00:33:05.279
be female, well that lets them fix their statistics, which
602
00:33:05.359 --> 00:33:11.000
especially at larger, larger organizations or government affiliated organizations, matters
603
00:33:11.160 --> 00:33:14.319
to them. And so you know, when I was coming
604
00:33:14.359 --> 00:33:18.400
out of college, I had companies fighting over me for
605
00:33:19.160 --> 00:33:22.000
wanting me, and I, you know, I wish it weren't true,
606
00:33:22.079 --> 00:33:23.960
but you know, we all know there's a little piece
607
00:33:24.000 --> 00:33:27.559
there that you know, it was a small advantage because frankly,
608
00:33:27.920 --> 00:33:29.599
I could look at the numbers and I could see
609
00:33:29.599 --> 00:33:32.279
that I had more job offers than you know, my
610
00:33:32.359 --> 00:33:35.160
male peers, and for better or worse, that was true.
611
00:33:35.599 --> 00:33:39.599
But that's also real, and that is something that we
612
00:33:39.640 --> 00:33:42.039
don't say to kids either. We don't tell them, oh, yeah,
613
00:33:42.160 --> 00:33:45.720
you'll you know, you might have like two thirds men
614
00:33:45.759 --> 00:33:48.440
to one third women in most of your meetings like
615
00:33:48.720 --> 00:33:53.599
at work, but also you'll get preferentially hired and you
616
00:33:53.720 --> 00:33:57.480
might get a salary bump sooner. There's actually really really
617
00:33:57.519 --> 00:34:01.000
good statistics that early in early in the career women
618
00:34:01.039 --> 00:34:05.160
actually get higher raises in engineering compared to men too,
619
00:34:05.359 --> 00:34:07.680
And that's a statistic that never gets talked about, which
620
00:34:07.720 --> 00:34:11.440
is pretty funny, and that women actually are more successful
621
00:34:11.559 --> 00:34:16.280
moving into management roles early in engineering as well. And
622
00:34:16.320 --> 00:34:18.000
a big piece to that, which I talk about in
623
00:34:18.039 --> 00:34:23.400
the book is I think the communication aspect right, when
624
00:34:23.440 --> 00:34:27.800
we look at the large statistical distributions of things, it
625
00:34:27.920 --> 00:34:32.719
is a true statement that more women are better at
626
00:34:33.440 --> 00:34:37.360
communication than men are. You know, not that you can
627
00:34:37.400 --> 00:34:39.719
say anything about one individual, but your audience is smart
628
00:34:39.800 --> 00:34:41.559
enough to know at least a little bit of statistics.
629
00:34:41.679 --> 00:34:45.239
And I know you remember all those classes, but you know,
630
00:34:45.719 --> 00:34:49.360
on the whole there's actually a very funny correlation one
631
00:34:49.360 --> 00:34:51.880
that I come back to. So if you look at
632
00:34:52.119 --> 00:34:56.679
just the top percentile of students who scored well on
633
00:34:56.719 --> 00:34:59.920
the math A s at, there's a very interesting correlation
634
00:35:00.119 --> 00:35:09.199
you find, which is that if a boy has a
635
00:35:09.239 --> 00:35:13.920
good SAT math score, it actually doesn't influence much their
636
00:35:14.199 --> 00:35:18.320
likelihood of having a good score on the writing section
637
00:35:18.400 --> 00:35:22.079
the English or writing sections of the SAT. However, if
638
00:35:22.119 --> 00:35:27.320
you subset for the girls who got good SAT math scores,
639
00:35:27.800 --> 00:35:30.880
actually there's a much higher correlation that they also have
640
00:35:31.000 --> 00:35:35.360
high verbal scores, which is funny that you will see
641
00:35:35.360 --> 00:35:40.760
often these girls they have more options, right, they are
642
00:35:40.800 --> 00:35:42.400
good at verbal and they are good at math, and
643
00:35:42.440 --> 00:35:44.440
so they think, oh well, I could go become a lawyer,
644
00:35:44.519 --> 00:35:46.719
or I could go become an engineer, and so they
645
00:35:46.760 --> 00:35:49.400
fork and they split in these different ones, and what
646
00:35:49.440 --> 00:35:52.599
they never hear is, oh, actually being the combination of
647
00:35:52.639 --> 00:35:55.039
the two of those and being good at both will
648
00:35:55.079 --> 00:35:57.400
make you an even better engineer than all of the
649
00:35:57.440 --> 00:36:00.400
ones that didn't also have the hyperbal score, which is fine,
650
00:36:01.320 --> 00:36:01.840
but it.
651
00:36:01.800 --> 00:36:04.760
Works out because as clearly the unicorn, I took the
652
00:36:04.920 --> 00:36:07.119
SAT twice and scored the exact same on math and
653
00:36:07.199 --> 00:36:09.800
verbal both times, as far as the scores were equal.
654
00:36:10.519 --> 00:36:13.079
But and you know, going back to school and being
655
00:36:13.079 --> 00:36:16.360
an engineer, I knew my communication skills are much better
656
00:36:16.400 --> 00:36:17.280
than the people around me.
657
00:36:17.800 --> 00:36:18.039
Yeah.
658
00:36:18.159 --> 00:36:20.719
I always joked that there are people getting better grades,
659
00:36:20.760 --> 00:36:22.639
but they hadn't showered for three days and I had
660
00:36:22.639 --> 00:36:25.679
a date that weekend, you know. But so social skills mattered,
661
00:36:25.840 --> 00:36:28.440
But yeh want verbal skills and communication skills, those are.
662
00:36:28.440 --> 00:36:33.360
Huge, Yeah, completely huge. And the bar to be you know,
663
00:36:33.480 --> 00:36:35.760
the best at math in the whole wide world is
664
00:36:35.800 --> 00:36:38.360
a very high bar. But to be sufficiently good at
665
00:36:38.440 --> 00:36:41.400
math and also very and also being a good communicator
666
00:36:41.920 --> 00:36:45.239
is much easier to achieve and actually much more valuable
667
00:36:45.280 --> 00:36:46.000
in the workplace.
668
00:36:46.679 --> 00:36:49.559
Yeah, so you alluded to this earlier, and we're talking
669
00:36:49.559 --> 00:36:52.400
about kind of ratios and statistics. Here, let's dig a
670
00:36:52.440 --> 00:36:57.079
little deeper and you talk about the fact that placing science, technology, engineering,
671
00:36:57.079 --> 00:36:59.559
and mathematics under the same under the single label of
672
00:36:59.639 --> 00:37:02.960
STEM kind of obscures the opportunity, and you feel like
673
00:37:03.079 --> 00:37:05.519
engineers aren't getting enough love in that. So talk about
674
00:37:05.559 --> 00:37:06.519
that for us.
675
00:37:06.519 --> 00:37:10.679
Oh yeah, it really, it's so true. So when I
676
00:37:10.719 --> 00:37:12.920
came to just the STEM acronym, you see the STEM
677
00:37:13.000 --> 00:37:18.000
acronym everywhere, and you know, props to Blanking on the
678
00:37:18.079 --> 00:37:21.159
name of the woman who coined it. But it's been
679
00:37:21.280 --> 00:37:23.280
very effective in getting it out into the marketing and
680
00:37:23.280 --> 00:37:27.360
into the education sphere. But then if you actually ask like, okay, like,
681
00:37:27.440 --> 00:37:31.519
but what are each of them? That it's very obvious
682
00:37:31.639 --> 00:37:34.360
to educators to the general public, like oh, I know
683
00:37:34.400 --> 00:37:37.599
what science is cool, okay, okay, And I know what
684
00:37:37.679 --> 00:37:42.039
math is okay cool, And then they're like, okay, technology
685
00:37:42.039 --> 00:37:46.440
and engineering that's the other stuff. That's the like computers
686
00:37:47.000 --> 00:37:50.320
and the people who use the science and math, And
687
00:37:50.360 --> 00:37:55.400
that's as good as you get. And frankly, you know,
688
00:37:55.480 --> 00:37:57.559
it's no wonder that the science and math are better
689
00:37:57.599 --> 00:38:01.400
understood because science and math are in every every high
690
00:38:01.400 --> 00:38:05.800
school curriculum, every middle school, you know, elementary school curriculum.
691
00:38:06.039 --> 00:38:08.079
So it's no wonder that people understand that better and
692
00:38:08.119 --> 00:38:12.880
the educators understand that better. Even today there's a bit
693
00:38:13.000 --> 00:38:18.320
of engineering making it into high schools and lower but
694
00:38:18.480 --> 00:38:22.239
it's still quite rare, and honestly when it's when it's done,
695
00:38:22.239 --> 00:38:26.960
it's often mostly science just where they say engineering then
696
00:38:27.199 --> 00:38:30.079
than it is anything else. But yeah, what I've found
697
00:38:31.440 --> 00:38:34.079
at a lot of these outreach events, right, panel formats
698
00:38:34.119 --> 00:38:36.679
are great, they're very easy for for a lot of
699
00:38:36.679 --> 00:38:39.480
people at events. They're very effective, very high roi in
700
00:38:39.519 --> 00:38:42.559
my opinion, But what I've seen so many times is
701
00:38:42.639 --> 00:38:47.519
you know Ford chairs and you know the if you
702
00:38:47.559 --> 00:38:52.920
were to put you know, a scientist, a technologist, which
703
00:38:52.960 --> 00:38:55.920
I generally would associate to to give your audience the
704
00:38:55.960 --> 00:38:59.639
definition uh more with like the computer science and software
705
00:38:59.800 --> 00:39:05.639
world universe scientist, a programmer, an engineer, and a mathematician
706
00:39:05.800 --> 00:39:13.079
on the stage would be a horribly inaccurate distribution of
707
00:39:13.159 --> 00:39:17.239
the population of those employed in those fields. Actually, if
708
00:39:17.280 --> 00:39:20.079
you wanted to be able to show all of the
709
00:39:20.159 --> 00:39:22.920
STEM acronym on one stage at a time, you have
710
00:39:22.960 --> 00:39:26.760
to get to thirty three chairs and that is, in
711
00:39:26.880 --> 00:39:29.880
order to have just one mathematician, because there are so
712
00:39:30.119 --> 00:39:35.679
few mathematicians employed in the workforce as mathematicians, and you
713
00:39:35.679 --> 00:39:37.960
would have I believe the numbers from memory, and it's
714
00:39:38.000 --> 00:39:40.320
been a bit since I looked at them. You'd have
715
00:39:40.400 --> 00:39:46.360
five scientists and thirteen programmers and fourteen engineers on the stage.
716
00:39:46.840 --> 00:39:51.039
But it's so much more common to see a stage
717
00:39:51.079 --> 00:39:53.480
of those four chairs where they're all filled by scientists
718
00:39:54.000 --> 00:39:58.320
or they're scientists and mathematicians. And that's because that's what
719
00:39:58.639 --> 00:40:02.199
the educators know. Right. You can think of trying to
720
00:40:02.239 --> 00:40:04.760
have a nice swath of different scientists of oh, I'll
721
00:40:04.760 --> 00:40:06.880
get a chemist, and I'll have a biologist, and I'll
722
00:40:06.880 --> 00:40:10.079
have a physicist, and suddenly, oh that's all my chair is. Okay,
723
00:40:10.079 --> 00:40:14.280
I'm done. But if you were to randomly select, you know,
724
00:40:14.360 --> 00:40:18.400
from the probability from the population, you know, think back
725
00:40:18.440 --> 00:40:21.360
to your early math days of going to randomly pull
726
00:40:21.440 --> 00:40:24.039
marbles out if you were in to poor marbles and
727
00:40:24.119 --> 00:40:26.639
end up with four scientists on a stage that is
728
00:40:26.679 --> 00:40:30.599
a likelihood of happening of point zero five percent. So
729
00:40:30.679 --> 00:40:34.800
it's incredibly skewed to this representation that you're only putting
730
00:40:34.840 --> 00:40:38.199
scientists up there when you're just even within the STEM subset.
731
00:40:39.079 --> 00:40:41.840
By contrast, if you were going to have a stage
732
00:40:41.880 --> 00:40:45.840
of just scientists or excuse me, just engineers and programmers,
733
00:40:46.960 --> 00:40:49.000
the chances that those would be the only people on
734
00:40:49.039 --> 00:40:54.880
stage is about fifty to fifty. It's statistically like totally normal,
735
00:40:54.960 --> 00:40:57.280
would be totally fine. And I have never seen it
736
00:40:57.360 --> 00:40:59.679
happen a single time when I was not the organizer,
737
00:41:00.480 --> 00:41:05.159
not even once. The simple fact of the matter that
738
00:41:05.320 --> 00:41:09.960
people don't understand is there are if you combine all
739
00:41:10.000 --> 00:41:13.519
mathematicians and all scientists employed in the US workforce, there
740
00:41:13.559 --> 00:41:18.199
are more than double that many in engineering. And the
741
00:41:18.760 --> 00:41:24.840
you know, there's the current. You know, from the latest data,
742
00:41:25.239 --> 00:41:29.159
engineering is about fourteen percent women at latest in the workforce.
743
00:41:29.199 --> 00:41:31.559
It's getting a bit better. Those are from statistics a
744
00:41:31.559 --> 00:41:33.840
few years ago, so I think we've probably gotten a
745
00:41:33.840 --> 00:41:38.840
few points since then. But the field of the sciences
746
00:41:38.880 --> 00:41:42.480
is already at forty something percent, and some sub disciplines
747
00:41:42.559 --> 00:41:45.719
like biology are actually overrepresented. They're more at like sixty
748
00:41:45.719 --> 00:41:51.079
percent women. And so if you were to just pull
749
00:41:51.880 --> 00:41:55.440
the percentage, the ratio of men to women in the field,
750
00:41:55.559 --> 00:41:57.800
let's just add women to engineering until we're up to
751
00:41:57.840 --> 00:42:00.760
the ratio that the sciences are at right, that's going
752
00:42:00.840 --> 00:42:05.199
to be adding two million women to engineering, and so
753
00:42:05.360 --> 00:42:07.800
in a big way. You know, one of the core
754
00:42:07.880 --> 00:42:10.400
topics of why I wrote this book in the first
755
00:42:10.400 --> 00:42:12.559
place is one I want to help. I want to
756
00:42:12.559 --> 00:42:14.800
help the kids, I want to help everything. But also,
757
00:42:15.119 --> 00:42:18.519
you know, more selfishly, for the engineering industry, we need
758
00:42:18.559 --> 00:42:21.679
more engineers. You know, one of the hottest things right
759
00:42:21.719 --> 00:42:26.079
now in especially the aerospace engineering engineering industry, is that
760
00:42:26.119 --> 00:42:28.199
it's just so hard to hire because there aren't enough
761
00:42:28.199 --> 00:42:31.239
engineers to do the work. And that is one of
762
00:42:31.239 --> 00:42:33.800
the biggest risks to our entire industry is is that
763
00:42:33.840 --> 00:42:37.119
there aren't enough engineers. We could be doing more cool stuff.
764
00:42:37.159 --> 00:42:39.679
We could be getting to the future even faster if
765
00:42:39.679 --> 00:42:42.400
we had more engineers. And what I see in these
766
00:42:42.440 --> 00:42:47.760
distributions is, Okay, there's a huge untapped market for girls
767
00:42:47.960 --> 00:42:51.400
into engineering, and I could add a million or multiple
768
00:42:51.400 --> 00:42:55.519
million engineers to the workforce if we just help more
769
00:42:55.559 --> 00:42:56.440
girls learn about it.
770
00:42:58.280 --> 00:43:00.960
That's a pretty powerful And so if I'm out there
771
00:43:00.960 --> 00:43:03.880
listening and I have a daughter, maybe I should be
772
00:43:04.039 --> 00:43:06.480
pulling them, giving them proper messages because there's a lot
773
00:43:06.480 --> 00:43:09.480
more opportunities in engineering than it would be in science
774
00:43:09.840 --> 00:43:10.199
or math.
775
00:43:10.800 --> 00:43:14.280
Absolutely, yeah, and and by all means, I mean science
776
00:43:14.360 --> 00:43:17.559
is still very cool, very interesting, but you need to
777
00:43:17.599 --> 00:43:20.079
have a full picture to make an informed decision, right.
778
00:43:20.159 --> 00:43:22.960
And and what happens a lot now is we say
779
00:43:22.960 --> 00:43:25.480
follow your passion, but then we never tell them about
780
00:43:25.480 --> 00:43:27.719
something that they could be passionate about, and so they
781
00:43:27.760 --> 00:43:31.360
never learned, so they can never pick it. Qed Well.
782
00:43:31.360 --> 00:43:33.920
That concludes Part one of my conversation with Julie Newman,
783
00:43:34.079 --> 00:43:37.519
aerospace engineer and best selling author of Pull Don't Push.
784
00:43:38.079 --> 00:43:40.920
Coming up in part two, Julie challenges the familiar advice
785
00:43:40.960 --> 00:43:43.519
of telling kids to follow their passion and suggest a
786
00:43:43.519 --> 00:43:44.960
better way of framing the discussion.
787
00:43:45.599 --> 00:43:48.639
Ooh, what problems do you want to help solve for
788
00:43:48.719 --> 00:43:52.440
other people? That's the one I love coming back to, Okay,
789
00:43:53.480 --> 00:43:57.360
is find the motivation and then and then the way
790
00:43:57.719 --> 00:44:01.760
can become engineering. Or you know, if they say I
791
00:44:01.800 --> 00:44:05.280
want to solve climate change, great, Okay, you can write
792
00:44:05.280 --> 00:44:08.199
a billion papers, it'll it'll never make a difference. But
793
00:44:08.920 --> 00:44:11.079
you go and make the next wind turbine. You're making
794
00:44:11.079 --> 00:44:13.000
a difference, and you want to know who's making the
795
00:44:13.039 --> 00:44:14.480
wind turbine because that's engineers.
796
00:44:15.440 --> 00:44:18.679
Thanks for listening to the Conversation. To find out more
797
00:44:18.679 --> 00:44:23.320
about Clint, go to clintonmpaget dot com and pick up
798
00:44:23.360 --> 00:44:28.079
Clint's book How Teams Triumph Managing by Commitments at Amazon.
799
00:44:28.719 --> 00:44:33.119
The Conversation with Clinton M. Paget is a production of
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00:44:33.239 --> 00:44:43.480
Forbes Books
1
00:00:04.559 --> 00:00:05.480
Look at this email?
2
00:00:05.679 --> 00:00:06.320
What does it mean?
3
00:00:06.480 --> 00:00:10.160
Communication is the imparting or exchanging of information or news.
4
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The single biggest problem in communication is the illusion that
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it has taken place.
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Conversation is the oral exchange of sentiments, observations, opinions, or ideas.
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Forbes Books Radio presents the conversation with Clinton and Pageant.
8
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For years, parents, educators, and business leaders have tried to
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encourage more young women to pursue careers in science and engineering.
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But what if the problem isn't that we aren't trying
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hard enough. What if it's the way we're having the conversation.
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My guest today, Julie Newman, argues that instead of pushing
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girls towards STEM, we need to help them discover what
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might naturally just pull them toward it. Julie is the
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best selling author of Pull, Don't Push, Why STEM messaging
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the girls isn't working, and what to do instead. She's
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also an accomplished aerospace engineer who has worked on programs
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including the Impulse Mirror spacecraft, SpaceX, Falcon nine, Boeing Starliner,
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NASA Space Launch System, and the Europa Clipper mission. What
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I find particularly interesting about Julie's work is it isn't
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simply about engineering, which of course I love as an
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engineer myself. It's about communication, influence, leadership, and how the
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conversations we have can either open possibilities for people or
24
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unintentionally close them. Julie, welcome to the conversation.
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Thanks so much, Clint. I am so excited to be
26
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here today. You know, this is a topic very close
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to my heart obviously, and the aspect of communication is
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just so important.
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It absolutely is. If people don't want to have conversations,
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they want to send text messages and try to get
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it over as quickly as possible, but the collaboration happens
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in the conversation, in my perspective at.
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Least absolutely so.
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I had to think of all the people that come
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on to get on the show as superheroes, and so
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you're a superhero today, what is your ridin story? Because
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all superheroes have origin stories? What's yours?
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Yeah? Absolutely, so, you know, first of all, I'll turn
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it back on you, Clint. Why did you become an engineer?
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When do you feel like you first learned about engineering?
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So this is funny because when I was a kid,
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I knew I wanted to be a lutchal engineer from
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the time I was about ten years old. So I
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would ride my bicycle to the library. This is dating
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myself because you know, we didn't have scooters and lines.
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My bicycle to the library and check out books on
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robotics and lasers and my In my junior year of
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high school, I did a science project which was using
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a laser to create a hologram because they have a
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Star Wars big at the time, right, So I knew
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I wanted to be a Lutch engineer from the time
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I was about ten.
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Oh see, there you go. That's awesome. You know, for me,
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my original story, I think looking back, it was something
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similar where I knew earlier, but I didn't have the
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words to describe it. And it's a story that I
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hear repeated over and over again, especially with women and engineering.
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So for me growing up, I you know, had a
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whole slew of different interests as everyone else every kid does,
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and one of those was I really loved things like
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you know, Lego and connects, and then got myself involved
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in a lot of the science competitions at school and
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just always liked the more technical aspects. Loved learning things
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like that. In particular, I got involved in middle school
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with a competition called Science Olympiad, just a nationwide competition.
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Maybe some of your listeners have their kids in it
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right now, but for that I really got into my
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groove so building robots and model airplanes and model rockets
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and really just a whole slew of different fun things.
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But what was crazy was that it's called Science Olympiad.
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I really never associated the word engineer with what I
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would later do until honestly, I was picking out a
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major to go to college, where I was like, oh, okay,
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well I want to like make stuff and you know,
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invent things, and who does that? And then finally at
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that point is when the word engineering comes up. So
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for me it was at Caltech. Chose electrical engineering, frankly,
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without actually a lot of electronics experience. Really didn't have
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any of that in schools when I was going through,
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and I kind of thought of it as well, I
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can pick electrical or mechanical, and now I mean I
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can work on anything, and so I thought electrical seemed
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hard to learn, so I picked that one. And you know,
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I think it's it's it's fun to tell kids that story,
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especially because they always think that we had it all
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figured out right, and that sometimes actually it's just little
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nudges that actually led to the entire path of your future.
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So I took that from studying in college, and then
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really while I was in college, trying out a few
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different things, realizing I didn't quite like medical devices, I
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didn't quite like you know, more like chip fabrication things,
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and then ultimately ended up getting into an internship at SpaceX,
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and that was really what sealed the deal for me.
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Absolutely loved it, loved the people, loved the speed, love
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the impact, and really quickly rekindled my love of space,
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which I had had from my earliest days and had
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never really thought that I could do a career in it.
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And here we are, you know, decade and a half later,
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and it's been space the whole time, and I've been
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absolutely loving it. And so yeah, after college, after SpaceX
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went over to NASA Jet Propulsion Laboratory, worked on a
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number of really really cool satellites. But I'll say my
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favorite one to talk about is the europe Clipper mission,
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which you mentioned in the intro. That is a mission
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which is currently on its way to Jupiter. I designed
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part of the radar instrument, So from a blank sheet
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of paper to a series of boxes and systems that
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are working on the satellite. Today it's flying towards Jupiter
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and it will get there in twenty thirty, so mark
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your calendars. Will be investigating the moon of Jupiter Europa,
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which has a big liquid water ocean and the potential
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for extraterrestrial life, so keep your fingers crossed. After JPL,
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I then moved over to Boeing and worked on a
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number of really cool flagship programs over there as well.
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So a few you mentioned in there, the Space Launch
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System that was at the time the largest rocket that
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it ever launched SpaceX has since broken that. Good to them,
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and also briefly the Starliner crew vehicle, and a number
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of different satellite programs there, culminating in being the chief
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engineer for a large constant, a large geostationary satellite communications program,
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really really fun stuff and definitely the underpinnings of which
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are the communication and understanding the interplay of different people
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and products and disciplines, and something that over the course
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of my career I've definitely moved into a more interdisciplinary
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role from not just an electrical engineer I tend to
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myself an aerospace engineer now, not just an electrical engineer
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because I've grown into the other directions. But after Boeing
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00:07:09.439 --> 00:07:12.720
then moved over to a startup. This was a startup
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00:07:12.720 --> 00:07:17.480
called Outpost. They are developing a re entry vehicle, So
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I think a satellite that comes back from space really
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cool applications, particularly in the opening the in space manufacturing
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goods market and also the military logistics market. There, I
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was the VP of Engineering before moving to my current role,
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which is at Impulse. Impulse Space was founded by Tom Muehler,
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00:07:38.680 --> 00:07:42.160
who was the first employee at SpaceX, the absolute expert
136
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in rocket propulsion, the reason that the Falcon nine rockets
137
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were so amazing, and I am his chief engineer for
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the satellite program called Mira, where again my role is
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really being that connector and making sure that our satellites work,
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making sure that it's managing risk and technical details, and
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growing the capability of the spacecraft over time.
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Well, I actually like the fact you call yourself an
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aerospace engineer now because it just to me, it just
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proved positive that electrical engineers can do anything.
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You can do anything. That's the whole point.
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Yeah, So let's define engineering, because you make a point
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in the book that common definitions like engineering is the
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application of math and science, or engineers built stuff for
149
00:08:23.519 --> 00:08:25.600
really inaccurate. So how do you define engineering?
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00:08:26.120 --> 00:08:29.560
Yeah, so my favorite short way to explain it is
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that engineers work creatively in teams to solve problems that
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help people. And there's a chapter in the book. Thank
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you Clint for going through it. There's a chapter in
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my book where I walk through all these different definitions
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and why certain ones fall short, and in particular I've
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crafted this definition. You know, one sentence takes a long
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time to sort when you really want to get it
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to the real core. It's the I had more time,
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I'd written a short, shorter letter. Well, I spent a
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lot of time and I wrote a short letter. The
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the core pieces in there are Creativity is one of
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the key pieces that I think really defines engineering but
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is never used. It's something that resonates really really well
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with kids. You know, the the creative kids are often
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you know, sort of shuffled towards more of like the
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arts and the like. But then there's a different type
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of creativity, which is you know, building things and and
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systems for for the world, you know, refining things, getting
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to that craftsman nature of development of you know, making
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a thing and making it a little bit better and
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a little bit better until it's really like, you know,
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a steam engine running perfectly, so to speak, or maybe
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literally depending on your field. And then the other aspect
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keyword in their teamwork. Really the things that engineers work
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on are too big to be done alone. You will
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very very rarely find a solitary engineer, and similarly it's
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hard to find you know, Tom Mueller may be an
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exception where you can put a name to an amazing
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technology that was developed, it's much more frequently that it's
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a large team which is related to it. And also, honestly,
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Tom too would say that it was a large team
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developing the Falcon nine rocket as well Falcon nine engines.
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The core piece there is that teamwork is really a
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necessary aspect and being solitary will not make you a
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successful engineer. You have to learn to work with people.
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You have to learn to communicate and how to engage
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between different groups, because that's what makes you successful and
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that's what makes a final product work really well. Right, Like,
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there's many different disciplines even within engineering and you're not
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going to be an expert in all of them. You
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have to be able to if you're the electrical engineer,
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work with the mechanical engineer, or work with the test engineer,
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or work with manufacturing and near to really bring the
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whole thing together. So let's see we're creatively in teams
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to solve problems that help people solving problems. Another really
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core aspect and something that I think communicates really well.
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You know, engineers aren't off on you know, a research
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tangent to discover, you know, why this fruitfly does this
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particular thing that's super cool, but it is not a
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known problem that you need to solve. It is a
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thing you're learning, whereas engineers at companies are generally being
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brought in because the company has a problem and they
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want it solved by someone. And that is what engineers do,
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is they come in and they solve problems. And I
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think that's something that that kids especially can really connect to.
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They can understand like, oh, it's all sort of these
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little investigations or it's you know, making something work, and
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that is is really something that again when we're trying
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to bring the definition down to the explain like I
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five level or to the you know, the high school
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er sort of level, the everyone on the street who
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never thought about engineering at all level. That really communicates
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quite well. And in particular, the goal of my book
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is really to help educators understand engineering. That's one of
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the primary roadblocks to being able to help the girls
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learn about engineering is if the teachers who are interfacing
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with them don't know either, and don't know enough to
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even pull in engineers to talk to them, then well
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that's not going to end up with the outcome we want.
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So going back to the no single solitary engineers, you
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can't all be Sheldon, right, Sheldon is a is a
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TV show. He's not.
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Yeah, he's a real engineer. Well and the funny thing too, Yeah.
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Is so fun of the engineer on the show.
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Yeah. The Big Bang theory so is set on fictional JPL,
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NASA JPL and fictional Caltech, both of which I have
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extreme insights into. And I will tell you will find Sheldon,
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but they are not the most successful. And they're also
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like far outnumbered by people that you know, you would
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otherwise consider pretty normal by by everyone's standard, so to speak. Uh,
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and and so it is funny that that is the
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the picture that the media portrays of engineers and of scientists.
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That's often a very skewed representation, which is pretty interesting.
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Yeah, could you talk about it in the book you
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do you tend to find those people more in academia
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than you do other places.
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You know, academy, Yeah, yeah, yeah, you know, academia on
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its own is usually considered a more solitary pursuit, and
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so that's where a lot of you know, that personality
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type can be more successful, is more in a research direction.
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But I think even in academia, you know, network and
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interconnection and the interplay between different fields is a very
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very valuable asset as well. So again it's more common
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that interacting with other people makes you more successful than
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it is solitary does.
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I think if you do your research, you'll leve and
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see that some of the some of the people credited
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for being inventors of things, I think even went back
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to the light bulb and things like that, it's basically
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there was a team behind them. There was one person
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taking credit, but they employed a team that was really
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doing the work.
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So yeah, exactly. Yeah, there's very very few things where
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they were yes, invented by a person and then also
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proliferated out. You know, maybe you know, we can give
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what is it? It's shockly and the a couple people
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from Belt Labs get to say they made the transistor,
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but what they made is nothing that looks like what
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the current transistor is. We can say that, yeah, for sure.
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So you've worked at some very different environments and all
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the different companies we talked about earlier. I was wondering,
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how has each organization shaped your understanding of engineering and leadership.
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Oh, yeah, well I think it's more similar than people
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would expect. So I do have, Yeah, the fun advantage
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from the aerospace perspective of I've you know, I've been
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at NASA, I've been at Big Aerospace, I've been at
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Startup Aerospace, and I've seen SpaceX and now I'm at Impulse,
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and they're all a lot more similar than you would expect,
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and a piece of me actually, I like to look
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at it as they're all kind of the evolution of
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the same thing. So when you see earlier it's often
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you know, no one wants bureaucracy to take over. There's
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not an individual person who's like man I would love
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if we just bogged this entire company down and went
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as slow as possible and that we couldn't make decisions
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for years. Right, There's no one doing that, and so
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it's really an emergent behavior at large scale when you're
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not correcting for it. And that's really a key piece
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is you know, I think if I were to go
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to like a root cause on it, a big piece
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to a lot of that is, you know, not having
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the conversations that needed to be and letting problems linger,
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and the the the nature of you know, maybe the
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innovator's dilemma of continuing to do what has always worked
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because it has worked even though the situation has changed.
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And I really see that as a common theme and
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something as I've now moved my career towards smaller, newer
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companies to really focus more on Okay, we can see,
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we can see what the future could be. How do
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we avoid the pitfalls? Because other people have also tried
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to avoid the pitfalls and haven't been successful, So how
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do we try something different? How do we learn from
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what they went through and to really make sure that
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while we won't be perfect, we can make ourselves more
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efficient than before. So to speak.
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Now you've done a lot through outreach through for STEM,
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and I'm just wondering what finally convinced you to write
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the book. And the book again is pull, don't push?
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Yeah, yeah, the you know, I never the origin for
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the book never quite made it into the book in
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the original iteration. But you know, you started with the
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superhero story, and I would say the beginning of the
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book maybe was like it'll communicate, but like kind of
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the more like the super villain story. Like I was
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at an outreach event and gosh, I don't know this
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was this was actually early twenty twenty, before everything happened
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and or twenty nineteen, No, twenty nineteen. In twenty nineteen,
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I was sitting in an event and this was a
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really really great event where we had brought in something
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like three hundred girls from across the school district and
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had brought in a lot of professional women in STEM.
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And there was a speaker who was up there, and
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the longer she talked, it sounded like a great presentation.
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And this is someone who had been featured on you know,
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like real television as a local woman in STEM and things.
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And the longer she talked, the matter and matter I
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got like I was literally furiously writing angry notes on
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my paper of like, you know, you said this, but
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then aarrow what they actually hear is this, And you know,
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it comes back to a quote that I think you
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have in your book and you say a few times
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of you know, the scariest thing or the most risky
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thing about communication is the assumption that it has happened,
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or the illusion that it has happened. So she thought
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she was communicating this really inspiring message, but what she
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was actually doing was pushing the girls away. And a
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lot of that is in you know, speaking about it
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as making the whole universe of STEM very scary. You know,
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if you say to a room full of middle school
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and high school girls, hey, everyone thinks that women don't
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belong in STEM, but I'm here to tell you that
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they're wrong. Is well, you just told them that everyone
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thinks that this is not for them, and that's really
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not the way to do it, especially when she herself
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had a very very cool career doing very cool things
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that she could be talking about that would be inspiring.
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And so what I had found and what this this
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one presentation then finally culminated in is. I then suddenly
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started to see the matrix of every event that I
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had been to, where they'd always tapped into this real
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negativity and this real you know push mindset of really
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feeding into this isn't for you, this isn't for you,
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This isn't for you, but we're here to tell you
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can do it anyways, or you know, the math is
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really really hard, but it's really really worth it and
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it's really really important, or things like oh yeah, well,
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growing up, I was the weird kid and no one
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liked me at all, and that's why I'm a great engineer.
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And you'd actually hear, well usually be scientists as well.
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They're almost never engineers at these events, which is the
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other primary problem. But you know, you come up with
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these stories, and then it really doesn't take a rocket
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scientist or a rocking engineer to listen to those statements
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and say, huh, I wonder, I wonder if maybe that's
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not encouraging, right, And so fundamentally it just became so
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obvious to me. And you know, teachers have such a
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hard job, and educators have such a hard job, and
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the ones especially setting up these events and really trying
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to help their students. They're just hearts of gold, right,
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And you know, I can see from all of them
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because I've worked with so many outreach events and now
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help with Science Olympiad. You know, they're overworked and underfunded
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and the easiest thing to do is what everyone else
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has done before, and that allows them to get through
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these events, and they don't really necessarily have the time
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and space to pause and think about why they're saying
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these things or how these things are being interpreted, and
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so largely the book. You know, I went home with
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like ten pages of papers that ended up being a
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you know, the early foundations of the book. But I
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went home and I was like, how can I help
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And how can I just tie it all in a nice,
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a nice communicative bow where they can understand where I'm
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coming from, because I'm the one from the other side
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that saw it work for me, and I'm the one that,
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you know, was it was a girl who would have
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loved being in those rooms. And if I see myself,
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you know, sitting at that event as a young kid
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and it being a negative impact towards my future career,
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which I absolutely love. I'm so happy that what I'm
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doing and frankly too, I am since releasing the book
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and since speaking more and going through the topics of
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the book. You know, the kids are one thing and
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absolutely warms my heart every time one of them tells
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me they're more excited about engineering or they now they
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want to be an engineer. Actually, I have a really
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lovely story of a girl who was at one of
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these events after I had published the book and after
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I was presenting and you know, keeping it all in line,
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and she reached out to me years later and said,
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you might not remember me. She found me on LinkedIn.
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You might not remember me, but I just wanted to
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say I'm an engineer because we talked at this event
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and now I'm studying mechanical engineering at Berkeley. And then
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she reached out later and she got her first job
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and she's in aerospace in LA and it's just so cool.
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But you know, thinking from the side of the kids
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is one thing. But the other thing that has really,
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you know, really driven it home for me emotionally on
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the impact of this message is really more the adults.
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So it's the women who come up to me, who
402
00:22:44.640 --> 00:22:46.240
are the teacher in the room or the mom in
403
00:22:46.279 --> 00:22:49.079
the room, and they come up to me and they say, wow,
404
00:22:49.759 --> 00:22:52.079
I never knew any of that. I could have been
405
00:22:52.079 --> 00:22:54.359
an engineer when I was younger, and no one ever
406
00:22:54.400 --> 00:22:57.519
told me. And now it all makes sense that that's
407
00:22:57.559 --> 00:22:59.240
what I should have done. And instead they went and
408
00:22:59.240 --> 00:23:01.519
they did other things. And you can never walk to paths.
409
00:23:02.000 --> 00:23:05.039
But the number of women who come up and say, wow,
410
00:23:05.079 --> 00:23:07.519
if I had sat in this room when I was
411
00:23:07.880 --> 00:23:10.559
middle school, high school age, I think I would have
412
00:23:10.559 --> 00:23:15.119
become an engineer is really, I think, proof point for
413
00:23:15.319 --> 00:23:16.480
how impactful it could be.
414
00:23:17.720 --> 00:23:20.240
I think, I see, I love the way you wrote
415
00:23:20.279 --> 00:23:23.119
the book and the examples you use. One of the
416
00:23:23.160 --> 00:23:25.319
things you're just talking about, I can actually see where
417
00:23:25.319 --> 00:23:29.599
this this scientist or engineering was speaking and about everybody
418
00:23:29.599 --> 00:23:32.119
tells you this. You can kind of see where Look
419
00:23:32.160 --> 00:23:34.680
what all I overcame, you know, to get here, so
420
00:23:34.720 --> 00:23:36.160
that you see that. And then there's kind of the
421
00:23:36.240 --> 00:23:38.720
ugly Duckley story about people think I'm weird, but I'm
422
00:23:38.799 --> 00:23:42.279
a great engineer now, and that probably resonates with some people.
423
00:23:42.319 --> 00:23:44.279
But if you want to get more people involved, then
424
00:23:44.279 --> 00:23:46.319
it needs to be it needs to be more open,
425
00:23:46.400 --> 00:23:48.559
and I think a positive message pushes that more than
426
00:23:48.640 --> 00:23:50.640
just the I had to overcome all these things to
427
00:23:50.640 --> 00:23:51.079
get here.
428
00:23:51.799 --> 00:23:54.960
Yeah. Yeah, there's a subtlety to it, and it's really
429
00:23:55.039 --> 00:23:58.839
a question of, you know, matching the message to the
430
00:23:58.920 --> 00:24:02.680
room and so having the reverence for the women that
431
00:24:02.720 --> 00:24:06.279
did have really difficult times or went through huge challenges
432
00:24:06.640 --> 00:24:09.759
is really important. But the best way to honor what
433
00:24:09.839 --> 00:24:12.599
they went through is not to push girls away from
434
00:24:12.640 --> 00:24:15.880
doing it too. It's to help them learn all of
435
00:24:15.920 --> 00:24:19.480
the great things about it and to be able to
436
00:24:19.519 --> 00:24:21.559
make the choice for themselves if they if they think
437
00:24:21.599 --> 00:24:23.039
engineering is right for them.
438
00:24:23.519 --> 00:24:25.799
So let's talk more about push versus pull. So what
439
00:24:25.920 --> 00:24:28.279
is the essential difference between pushing someone toward a career
440
00:24:28.279 --> 00:24:30.319
and pulling them toward a possibility.
441
00:24:30.759 --> 00:24:35.319
Yeah, So it's a lot of these a lot of
442
00:24:35.319 --> 00:24:38.640
these events and language that we use with children, it's
443
00:24:38.640 --> 00:24:41.319
often sort of you know, you can almost imagine like
444
00:24:41.440 --> 00:24:43.160
standing behind them and kind of shoving them in the
445
00:24:43.240 --> 00:24:47.880
right direction of or or or kind of putting things
446
00:24:47.920 --> 00:24:50.319
on top of them. As far as narratives, and one
447
00:24:50.319 --> 00:24:54.119
of those is, yes, the really dated narratives of you know,
448
00:24:54.640 --> 00:24:57.599
if you go become a female engineer, all of your
449
00:24:57.599 --> 00:25:00.559
male coworkers will hate you, like I've never found that,
450
00:25:01.640 --> 00:25:05.079
and you know, there's there's people when people working together
451
00:25:05.240 --> 00:25:08.160
is always always has its issues. But frankly it's a
452
00:25:08.160 --> 00:25:11.200
lot better than it used to be, and it's something
453
00:25:11.279 --> 00:25:16.880
that's not the norm anymore. So pushing is really forcing
454
00:25:17.000 --> 00:25:20.480
something on onto the kids, whereas pulling is more of
455
00:25:21.119 --> 00:25:24.279
think of it more like enticing. Right, it's telling them, oh,
456
00:25:24.279 --> 00:25:29.160
hey did you know that? Uh, the top paid college
457
00:25:29.200 --> 00:25:32.519
majors are all in engineering, Like you know, just thought
458
00:25:32.519 --> 00:25:35.240
you should know that, and that will pull them.
459
00:25:36.480 --> 00:25:36.759
You know.
460
00:25:37.319 --> 00:25:39.319
You know, if money is if you want to make
461
00:25:39.359 --> 00:25:41.720
a lot of money, you know, maybe you think about it, right,
462
00:25:42.240 --> 00:25:44.640
or hey, if you if you want to change the
463
00:25:44.680 --> 00:25:47.279
course of humanity and maybe make it so that we
464
00:25:47.319 --> 00:25:49.920
have people on Mars one day, you know, you could
465
00:25:49.920 --> 00:25:53.400
look at engineering. That might be an interesting, interesting path
466
00:25:53.480 --> 00:25:57.119
for you. So it's really more about you know, I'm
467
00:25:57.160 --> 00:26:03.240
a big advocate for helping kids make the decisions themselves,
468
00:26:03.440 --> 00:26:06.759
because ultimately you can't really force them, or if you do,
469
00:26:06.839 --> 00:26:09.759
they're going to resent it later, and so why would
470
00:26:09.799 --> 00:26:12.640
we try? Right, It's much easier. It's honestly a lot
471
00:26:12.680 --> 00:26:16.720
more fun too. So I you know, when I'm out speaking,
472
00:26:16.799 --> 00:26:19.039
I would so much rather talk about all the fun
473
00:26:19.079 --> 00:26:21.039
things that I have done in my career and the
474
00:26:21.119 --> 00:26:24.240
cool stories where you know, we were down in the
475
00:26:24.240 --> 00:26:26.519
trenches fixing this problem and then we solved it and
476
00:26:26.519 --> 00:26:29.160
we all felt so wonderful, and I'd so much rather
477
00:26:29.240 --> 00:26:32.279
talk about that than, you know, any of the negativity
478
00:26:32.920 --> 00:26:36.000
that so often gets ninety nine percent of the airtime.
479
00:26:37.200 --> 00:26:39.119
Well, you know, you make a point also in the book.
480
00:26:39.119 --> 00:26:41.599
Then another, I guess pull conversation could be that if
481
00:26:41.640 --> 00:26:43.640
you want to have a family, engineering is a way
482
00:26:43.640 --> 00:26:45.960
to go, because it doesn't you're not a lawyer trying
483
00:26:46.000 --> 00:26:47.759
to put in ninety one hundred hours a week to
484
00:26:47.839 --> 00:26:50.920
get partner and yeah, you prove positive, right, you have
485
00:26:51.640 --> 00:26:52.759
a growing family as well.
486
00:26:53.400 --> 00:26:57.839
Yeah, yeah, And I think that's something that also resonates
487
00:26:57.839 --> 00:27:01.480
really well with the girls. You know, a lot of
488
00:27:02.559 --> 00:27:04.960
a lot of kids to take an example, right, and
489
00:27:05.000 --> 00:27:07.880
actually myself included. When I was young, I thought about
490
00:27:07.880 --> 00:27:09.920
being a doctor, and I thought I would love to
491
00:27:09.920 --> 00:27:12.359
be a doctor. But then I looked at some numbers
492
00:27:12.400 --> 00:27:14.240
and I was like, wow, you've got to be at
493
00:27:14.240 --> 00:27:16.759
school a long time. And I want to do things
494
00:27:16.799 --> 00:27:19.759
that are also not just being a doctor. And so
495
00:27:19.880 --> 00:27:22.960
for me, that kind of made me not want that path.
496
00:27:23.319 --> 00:27:26.400
And what a lot of kids don't realize is they
497
00:27:26.440 --> 00:27:29.400
conflate science with engineering if they even think about engineering
498
00:27:29.400 --> 00:27:32.720
at all. And then scientists, pretty much exclusively, you have
499
00:27:32.759 --> 00:27:36.039
to go down the much longer schooling path to be
500
00:27:36.039 --> 00:27:40.000
successful as a scientist, usually a master's PhD program many years.
501
00:27:40.599 --> 00:27:44.519
But in engineering, actually the vast majority don't have graduate
502
00:27:44.559 --> 00:27:47.839
degrees and can be very very successful without graduate degrees.
503
00:27:48.119 --> 00:27:52.000
And if anything, many many engineers, myself included, would argue
504
00:27:52.039 --> 00:27:55.319
that the four two end years you spend doing a PhD,
505
00:27:55.799 --> 00:27:58.000
you actually might learn more if you were at your
506
00:27:58.079 --> 00:28:02.640
job doing cool things and learn on the job. But yeah,
507
00:28:02.680 --> 00:28:05.559
so for me, you know, a piece to engineering is
508
00:28:05.559 --> 00:28:08.240
it's about solving these problems, and you can't do them
509
00:28:08.599 --> 00:28:10.839
for eighty hours a week necessarily, or at least you
510
00:28:10.839 --> 00:28:15.519
can't do that forever, and so it's really providing that
511
00:28:15.599 --> 00:28:18.640
value and then solving those problems that that makes it.
512
00:28:19.599 --> 00:28:22.480
Engineers are very valuable to companies and so companies have
513
00:28:22.559 --> 00:28:26.279
to kind of give the best perks and uh, you know,
514
00:28:26.400 --> 00:28:31.559
be more accommodating of their the workforce of engineers. So
515
00:28:31.640 --> 00:28:35.480
for me, it's been incredibly valuable. I my husband's also
516
00:28:35.519 --> 00:28:39.880
an engineer, and we have three kids right now, that's
517
00:28:39.880 --> 00:28:42.799
something that yeah, certainly had I for example, if I
518
00:28:42.880 --> 00:28:44.880
were coming out of residency and had been a doctor
519
00:28:44.920 --> 00:28:46.279
for a few years, to be a lot harder to
520
00:28:46.440 --> 00:28:51.160
already have three kids. And fun fact surprise is I
521
00:28:51.160 --> 00:28:56.160
actually have more on the way. Uh just waterline here. Yeah,
522
00:28:56.319 --> 00:29:03.799
we've very lucky have a twin coming. We started crazily enough,
523
00:29:03.839 --> 00:29:07.039
we started with a set of twins and twin boys,
524
00:29:07.519 --> 00:29:10.039
then had a girl, and then now we're having twins again.
525
00:29:10.119 --> 00:29:11.079
We're getting one to each.
526
00:29:11.359 --> 00:29:15.880
So well that's a balance. Yeah, how do you engineer that?
527
00:29:16.480 --> 00:29:19.599
I know, right, I don't think you can. But when
528
00:29:19.599 --> 00:29:22.200
I figure it out, I'll let you know. But I'll
529
00:29:22.240 --> 00:29:25.119
say engineering systems do help our household function.
530
00:29:26.079 --> 00:29:28.079
You have to with that many kids. Well you only
531
00:29:28.079 --> 00:29:30.720
got three now, but we're two more. Wow, I have
532
00:29:30.759 --> 00:29:34.160
two kids. I can't imagine five. That's a lot. So
533
00:29:34.440 --> 00:29:36.480
you know, we've been talking about messaging, and you know,
534
00:29:36.519 --> 00:29:38.440
you and I were joking in the green room before
535
00:29:38.440 --> 00:29:41.279
we started this recording. In the book, you use the
536
00:29:41.319 --> 00:29:44.200
Navy slogan join the Navy, see the world and not
537
00:29:44.359 --> 00:29:46.759
join the Navy have a really difficult time on a
538
00:29:46.759 --> 00:29:48.880
boat for a while, and so having been six years
539
00:29:48.880 --> 00:29:50.839
in the navy, I actually made it even worse. I said.
540
00:29:51.119 --> 00:29:53.240
They don't say, joined the Navy, work twelve hours a day,
541
00:29:53.240 --> 00:29:55.319
seven days a week, sleep in a birthing area with
542
00:29:55.359 --> 00:29:58.960
seventy three other stinky guys, because that's what ends up being.
543
00:29:59.079 --> 00:30:00.920
They don't usually put that on pamphlets, right.
544
00:30:00.960 --> 00:30:03.839
They don't usually. Speaking of recruit you mentioned recruiting earlier
545
00:30:03.839 --> 00:30:07.000
than you know, the recruiters, they don't they Yeah, funny,
546
00:30:07.119 --> 00:30:09.279
I never never occurred to me. Sailors made for ships,
547
00:30:09.279 --> 00:30:11.240
and ships are made for sea, and we signed up
548
00:30:11.240 --> 00:30:12.680
for six years. You can spend five and a half
549
00:30:12.720 --> 00:30:15.079
of those at sea, but they should They don't tell
550
00:30:15.119 --> 00:30:15.599
you that part.
551
00:30:16.240 --> 00:30:18.799
Yeah, yeah, And and that's the crazy thing is I
552
00:30:18.799 --> 00:30:22.400
have literally seen, you know, pamphlets for girls and STEM
553
00:30:22.480 --> 00:30:26.119
events where the whole thing is just covered in statistics
554
00:30:26.160 --> 00:30:28.960
about how few women there are an engine in stem
555
00:30:29.599 --> 00:30:31.880
uh and and you know how hard it's going to
556
00:30:31.960 --> 00:30:34.279
be and all of that stuff. When yeah, they didn't
557
00:30:34.279 --> 00:30:37.920
devote any airtime to or any of the space to oh,
558
00:30:38.000 --> 00:30:40.519
look at the open waters, look at all the places
559
00:30:40.519 --> 00:30:42.799
in the earth a're going to travel, it'll all be water.
560
00:30:43.480 --> 00:30:49.480
H But the marketing aspect to it, it really is. Yeah,
561
00:30:49.519 --> 00:30:52.559
the marketing one o one of sell the positives, right, Yeah,
562
00:30:52.559 --> 00:30:55.720
that's always that's always the intro statement. It's it's very
563
00:30:55.799 --> 00:30:58.240
rare that a salesperson is going to tell you just
564
00:30:58.359 --> 00:31:00.640
to walk in that room and say all of the
565
00:31:00.680 --> 00:31:03.920
worst things about the thing you're trying to sell. I mean,
566
00:31:03.960 --> 00:31:06.920
there's a tactic to that, but it doesn't it doesn't
567
00:31:06.960 --> 00:31:10.599
doesn't really communicate except to very particular audiences.
568
00:31:11.039 --> 00:31:12.759
Yeah, you don't go out dating that way either. Hey,
569
00:31:12.799 --> 00:31:15.000
I drink a lot and I smoke and I using
570
00:31:15.240 --> 00:31:15.920
things like that.
571
00:31:16.599 --> 00:31:20.720
Yeah, yeah, it's maybe it will find the right person,
572
00:31:20.799 --> 00:31:22.559
but there won't be that many of them.
573
00:31:23.880 --> 00:31:25.720
That's that's that's a good way to say it. And
574
00:31:25.920 --> 00:31:28.319
there's a as I said, I went to Georgia Tech,
575
00:31:28.480 --> 00:31:30.880
and there's a song about Georgia Tech called the Ratio
576
00:31:30.920 --> 00:31:32.799
and it talks about the ratio of men to women
577
00:31:32.839 --> 00:31:34.680
because he used to be forty four hundred to one,
578
00:31:35.160 --> 00:31:37.319
you know, and it's clearly gotten better. But the refrain
579
00:31:37.400 --> 00:31:40.039
from the song is just so great. And the refrain
580
00:31:40.200 --> 00:31:42.640
is the odds are good, but the goods are odd.
581
00:31:42.920 --> 00:31:49.200
So yep, that's been stated many a time, and you
582
00:31:49.240 --> 00:31:53.240
know it's kind of this this reinforcing it's fun and funny,
583
00:31:53.319 --> 00:31:56.079
but then it eventually you have to realize that. Then
584
00:31:56.119 --> 00:31:59.720
that messaging flows down where people actually think that, yeah,
585
00:32:00.039 --> 00:32:03.279
and you know, we're all weird in different ways for sure,
586
00:32:03.359 --> 00:32:07.240
but the you know, there's there's actually a lot of
587
00:32:07.279 --> 00:32:11.400
advantages to for example, being a woman in stem in
588
00:32:11.559 --> 00:32:17.119
the modern era where you know the song in reverse
589
00:32:17.240 --> 00:32:20.920
is you know, a bit better the ratio wise, so
590
00:32:21.240 --> 00:32:23.640
I will admit to having found my husband in college
591
00:32:24.160 --> 00:32:28.240
and an inverse ratio doesn't really hurt you there, and
592
00:32:28.599 --> 00:32:32.799
the same thing of I actually mentioned it in an
593
00:32:32.839 --> 00:32:35.079
intro chapter on the book, but or one of the
594
00:32:35.119 --> 00:32:38.839
chapters in the book that you know, from a job
595
00:32:38.880 --> 00:32:43.359
search perspective, a lot of companies really really would love
596
00:32:43.519 --> 00:32:48.160
to improve their ratios, and statistically everyone can't win, so
597
00:32:48.200 --> 00:32:50.680
that means you're a hot commodity when it comes to
598
00:32:50.960 --> 00:32:53.319
trying to get you into the different companies. You know,
599
00:32:53.359 --> 00:32:58.319
it's a very meritocratic field in general. But if you
600
00:32:59.000 --> 00:33:01.759
are really good and you also just so happen to
601
00:33:02.240 --> 00:33:05.279
be female, well that lets them fix their statistics, which
602
00:33:05.359 --> 00:33:11.000
especially at larger, larger organizations or government affiliated organizations, matters
603
00:33:11.160 --> 00:33:14.319
to them. And so you know, when I was coming
604
00:33:14.359 --> 00:33:18.400
out of college, I had companies fighting over me for
605
00:33:19.160 --> 00:33:22.000
wanting me, and I, you know, I wish it weren't true,
606
00:33:22.079 --> 00:33:23.960
but you know, we all know there's a little piece
607
00:33:24.000 --> 00:33:27.559
there that you know, it was a small advantage because frankly,
608
00:33:27.920 --> 00:33:29.599
I could look at the numbers and I could see
609
00:33:29.599 --> 00:33:32.279
that I had more job offers than you know, my
610
00:33:32.359 --> 00:33:35.160
male peers, and for better or worse, that was true.
611
00:33:35.599 --> 00:33:39.599
But that's also real, and that is something that we
612
00:33:39.640 --> 00:33:42.039
don't say to kids either. We don't tell them, oh, yeah,
613
00:33:42.160 --> 00:33:45.720
you'll you know, you might have like two thirds men
614
00:33:45.759 --> 00:33:48.440
to one third women in most of your meetings like
615
00:33:48.720 --> 00:33:53.599
at work, but also you'll get preferentially hired and you
616
00:33:53.720 --> 00:33:57.480
might get a salary bump sooner. There's actually really really
617
00:33:57.519 --> 00:34:01.000
good statistics that early in early in the career women
618
00:34:01.039 --> 00:34:05.160
actually get higher raises in engineering compared to men too,
619
00:34:05.359 --> 00:34:07.680
And that's a statistic that never gets talked about, which
620
00:34:07.720 --> 00:34:11.440
is pretty funny, and that women actually are more successful
621
00:34:11.559 --> 00:34:16.280
moving into management roles early in engineering as well. And
622
00:34:16.320 --> 00:34:18.000
a big piece to that, which I talk about in
623
00:34:18.039 --> 00:34:23.400
the book is I think the communication aspect right, when
624
00:34:23.440 --> 00:34:27.800
we look at the large statistical distributions of things, it
625
00:34:27.920 --> 00:34:32.719
is a true statement that more women are better at
626
00:34:33.440 --> 00:34:37.360
communication than men are. You know, not that you can
627
00:34:37.400 --> 00:34:39.719
say anything about one individual, but your audience is smart
628
00:34:39.800 --> 00:34:41.559
enough to know at least a little bit of statistics.
629
00:34:41.679 --> 00:34:45.239
And I know you remember all those classes, but you know,
630
00:34:45.719 --> 00:34:49.360
on the whole there's actually a very funny correlation one
631
00:34:49.360 --> 00:34:51.880
that I come back to. So if you look at
632
00:34:52.119 --> 00:34:56.679
just the top percentile of students who scored well on
633
00:34:56.719 --> 00:34:59.920
the math A s at, there's a very interesting correlation
634
00:35:00.119 --> 00:35:09.199
you find, which is that if a boy has a
635
00:35:09.239 --> 00:35:13.920
good SAT math score, it actually doesn't influence much their
636
00:35:14.199 --> 00:35:18.320
likelihood of having a good score on the writing section
637
00:35:18.400 --> 00:35:22.079
the English or writing sections of the SAT. However, if
638
00:35:22.119 --> 00:35:27.320
you subset for the girls who got good SAT math scores,
639
00:35:27.800 --> 00:35:30.880
actually there's a much higher correlation that they also have
640
00:35:31.000 --> 00:35:35.360
high verbal scores, which is funny that you will see
641
00:35:35.360 --> 00:35:40.760
often these girls they have more options, right, they are
642
00:35:40.800 --> 00:35:42.400
good at verbal and they are good at math, and
643
00:35:42.440 --> 00:35:44.440
so they think, oh well, I could go become a lawyer,
644
00:35:44.519 --> 00:35:46.719
or I could go become an engineer, and so they
645
00:35:46.760 --> 00:35:49.400
fork and they split in these different ones, and what
646
00:35:49.440 --> 00:35:52.599
they never hear is, oh, actually being the combination of
647
00:35:52.639 --> 00:35:55.039
the two of those and being good at both will
648
00:35:55.079 --> 00:35:57.400
make you an even better engineer than all of the
649
00:35:57.440 --> 00:36:00.400
ones that didn't also have the hyperbal score, which is fine,
650
00:36:01.320 --> 00:36:01.840
but it.
651
00:36:01.800 --> 00:36:04.760
Works out because as clearly the unicorn, I took the
652
00:36:04.920 --> 00:36:07.119
SAT twice and scored the exact same on math and
653
00:36:07.199 --> 00:36:09.800
verbal both times, as far as the scores were equal.
654
00:36:10.519 --> 00:36:13.079
But and you know, going back to school and being
655
00:36:13.079 --> 00:36:16.360
an engineer, I knew my communication skills are much better
656
00:36:16.400 --> 00:36:17.280
than the people around me.
657
00:36:17.800 --> 00:36:18.039
Yeah.
658
00:36:18.159 --> 00:36:20.719
I always joked that there are people getting better grades,
659
00:36:20.760 --> 00:36:22.639
but they hadn't showered for three days and I had
660
00:36:22.639 --> 00:36:25.679
a date that weekend, you know. But so social skills mattered,
661
00:36:25.840 --> 00:36:28.440
But yeh want verbal skills and communication skills, those are.
662
00:36:28.440 --> 00:36:33.360
Huge, Yeah, completely huge. And the bar to be you know,
663
00:36:33.480 --> 00:36:35.760
the best at math in the whole wide world is
664
00:36:35.800 --> 00:36:38.360
a very high bar. But to be sufficiently good at
665
00:36:38.440 --> 00:36:41.400
math and also very and also being a good communicator
666
00:36:41.920 --> 00:36:45.239
is much easier to achieve and actually much more valuable
667
00:36:45.280 --> 00:36:46.000
in the workplace.
668
00:36:46.679 --> 00:36:49.559
Yeah, so you alluded to this earlier, and we're talking
669
00:36:49.559 --> 00:36:52.400
about kind of ratios and statistics. Here, let's dig a
670
00:36:52.440 --> 00:36:57.079
little deeper and you talk about the fact that placing science, technology, engineering,
671
00:36:57.079 --> 00:36:59.559
and mathematics under the same under the single label of
672
00:36:59.639 --> 00:37:02.960
STEM kind of obscures the opportunity, and you feel like
673
00:37:03.079 --> 00:37:05.519
engineers aren't getting enough love in that. So talk about
674
00:37:05.559 --> 00:37:06.519
that for us.
675
00:37:06.519 --> 00:37:10.679
Oh yeah, it really, it's so true. So when I
676
00:37:10.719 --> 00:37:12.920
came to just the STEM acronym, you see the STEM
677
00:37:13.000 --> 00:37:18.000
acronym everywhere, and you know, props to Blanking on the
678
00:37:18.079 --> 00:37:21.159
name of the woman who coined it. But it's been
679
00:37:21.280 --> 00:37:23.280
very effective in getting it out into the marketing and
680
00:37:23.280 --> 00:37:27.360
into the education sphere. But then if you actually ask like, okay, like,
681
00:37:27.440 --> 00:37:31.519
but what are each of them? That it's very obvious
682
00:37:31.639 --> 00:37:34.360
to educators to the general public, like oh, I know
683
00:37:34.400 --> 00:37:37.599
what science is cool, okay, okay, And I know what
684
00:37:37.679 --> 00:37:42.039
math is okay cool, And then they're like, okay, technology
685
00:37:42.039 --> 00:37:46.440
and engineering that's the other stuff. That's the like computers
686
00:37:47.000 --> 00:37:50.320
and the people who use the science and math, And
687
00:37:50.360 --> 00:37:55.400
that's as good as you get. And frankly, you know,
688
00:37:55.480 --> 00:37:57.559
it's no wonder that the science and math are better
689
00:37:57.599 --> 00:38:01.400
understood because science and math are in every every high
690
00:38:01.400 --> 00:38:05.800
school curriculum, every middle school, you know, elementary school curriculum.
691
00:38:06.039 --> 00:38:08.079
So it's no wonder that people understand that better and
692
00:38:08.119 --> 00:38:12.880
the educators understand that better. Even today there's a bit
693
00:38:13.000 --> 00:38:18.320
of engineering making it into high schools and lower but
694
00:38:18.480 --> 00:38:22.239
it's still quite rare, and honestly when it's when it's done,
695
00:38:22.239 --> 00:38:26.960
it's often mostly science just where they say engineering then
696
00:38:27.199 --> 00:38:30.079
than it is anything else. But yeah, what I've found
697
00:38:31.440 --> 00:38:34.079
at a lot of these outreach events, right, panel formats
698
00:38:34.119 --> 00:38:36.679
are great, they're very easy for for a lot of
699
00:38:36.679 --> 00:38:39.480
people at events. They're very effective, very high roi in
700
00:38:39.519 --> 00:38:42.559
my opinion, But what I've seen so many times is
701
00:38:42.639 --> 00:38:47.519
you know Ford chairs and you know the if you
702
00:38:47.559 --> 00:38:52.920
were to put you know, a scientist, a technologist, which
703
00:38:52.960 --> 00:38:55.920
I generally would associate to to give your audience the
704
00:38:55.960 --> 00:38:59.639
definition uh more with like the computer science and software
705
00:38:59.800 --> 00:39:05.639
world universe scientist, a programmer, an engineer, and a mathematician
706
00:39:05.800 --> 00:39:13.079
on the stage would be a horribly inaccurate distribution of
707
00:39:13.159 --> 00:39:17.239
the population of those employed in those fields. Actually, if
708
00:39:17.280 --> 00:39:20.079
you wanted to be able to show all of the
709
00:39:20.159 --> 00:39:22.920
STEM acronym on one stage at a time, you have
710
00:39:22.960 --> 00:39:26.760
to get to thirty three chairs and that is, in
711
00:39:26.880 --> 00:39:29.880
order to have just one mathematician, because there are so
712
00:39:30.119 --> 00:39:35.679
few mathematicians employed in the workforce as mathematicians, and you
713
00:39:35.679 --> 00:39:37.960
would have I believe the numbers from memory, and it's
714
00:39:38.000 --> 00:39:40.320
been a bit since I looked at them. You'd have
715
00:39:40.400 --> 00:39:46.360
five scientists and thirteen programmers and fourteen engineers on the stage.
716
00:39:46.840 --> 00:39:51.039
But it's so much more common to see a stage
717
00:39:51.079 --> 00:39:53.480
of those four chairs where they're all filled by scientists
718
00:39:54.000 --> 00:39:58.320
or they're scientists and mathematicians. And that's because that's what
719
00:39:58.639 --> 00:40:02.199
the educators know. Right. You can think of trying to
720
00:40:02.239 --> 00:40:04.760
have a nice swath of different scientists of oh, I'll
721
00:40:04.760 --> 00:40:06.880
get a chemist, and I'll have a biologist, and I'll
722
00:40:06.880 --> 00:40:10.079
have a physicist, and suddenly, oh that's all my chair is. Okay,
723
00:40:10.079 --> 00:40:14.280
I'm done. But if you were to randomly select, you know,
724
00:40:14.360 --> 00:40:18.400
from the probability from the population, you know, think back
725
00:40:18.440 --> 00:40:21.360
to your early math days of going to randomly pull
726
00:40:21.440 --> 00:40:24.039
marbles out if you were in to poor marbles and
727
00:40:24.119 --> 00:40:26.639
end up with four scientists on a stage that is
728
00:40:26.679 --> 00:40:30.599
a likelihood of happening of point zero five percent. So
729
00:40:30.679 --> 00:40:34.800
it's incredibly skewed to this representation that you're only putting
730
00:40:34.840 --> 00:40:38.199
scientists up there when you're just even within the STEM subset.
731
00:40:39.079 --> 00:40:41.840
By contrast, if you were going to have a stage
732
00:40:41.880 --> 00:40:45.840
of just scientists or excuse me, just engineers and programmers,
733
00:40:46.960 --> 00:40:49.000
the chances that those would be the only people on
734
00:40:49.039 --> 00:40:54.880
stage is about fifty to fifty. It's statistically like totally normal,
735
00:40:54.960 --> 00:40:57.280
would be totally fine. And I have never seen it
736
00:40:57.360 --> 00:40:59.679
happen a single time when I was not the organizer,
737
00:41:00.480 --> 00:41:05.159
not even once. The simple fact of the matter that
738
00:41:05.320 --> 00:41:09.960
people don't understand is there are if you combine all
739
00:41:10.000 --> 00:41:13.519
mathematicians and all scientists employed in the US workforce, there
740
00:41:13.559 --> 00:41:18.199
are more than double that many in engineering. And the
741
00:41:18.760 --> 00:41:24.840
you know, there's the current. You know, from the latest data,
742
00:41:25.239 --> 00:41:29.159
engineering is about fourteen percent women at latest in the workforce.
743
00:41:29.199 --> 00:41:31.559
It's getting a bit better. Those are from statistics a
744
00:41:31.559 --> 00:41:33.840
few years ago, so I think we've probably gotten a
745
00:41:33.840 --> 00:41:38.840
few points since then. But the field of the sciences
746
00:41:38.880 --> 00:41:42.480
is already at forty something percent, and some sub disciplines
747
00:41:42.559 --> 00:41:45.719
like biology are actually overrepresented. They're more at like sixty
748
00:41:45.719 --> 00:41:51.079
percent women. And so if you were to just pull
749
00:41:51.880 --> 00:41:55.440
the percentage, the ratio of men to women in the field,
750
00:41:55.559 --> 00:41:57.800
let's just add women to engineering until we're up to
751
00:41:57.840 --> 00:42:00.760
the ratio that the sciences are at right, that's going
752
00:42:00.840 --> 00:42:05.199
to be adding two million women to engineering, and so
753
00:42:05.360 --> 00:42:07.800
in a big way. You know, one of the core
754
00:42:07.880 --> 00:42:10.400
topics of why I wrote this book in the first
755
00:42:10.400 --> 00:42:12.559
place is one I want to help. I want to
756
00:42:12.559 --> 00:42:14.800
help the kids, I want to help everything. But also,
757
00:42:15.119 --> 00:42:18.519
you know, more selfishly, for the engineering industry, we need
758
00:42:18.559 --> 00:42:21.679
more engineers. You know, one of the hottest things right
759
00:42:21.719 --> 00:42:26.079
now in especially the aerospace engineering engineering industry, is that
760
00:42:26.119 --> 00:42:28.199
it's just so hard to hire because there aren't enough
761
00:42:28.199 --> 00:42:31.239
engineers to do the work. And that is one of
762
00:42:31.239 --> 00:42:33.800
the biggest risks to our entire industry is is that
763
00:42:33.840 --> 00:42:37.119
there aren't enough engineers. We could be doing more cool stuff.
764
00:42:37.159 --> 00:42:39.679
We could be getting to the future even faster if
765
00:42:39.679 --> 00:42:42.400
we had more engineers. And what I see in these
766
00:42:42.440 --> 00:42:47.760
distributions is, Okay, there's a huge untapped market for girls
767
00:42:47.960 --> 00:42:51.400
into engineering, and I could add a million or multiple
768
00:42:51.400 --> 00:42:55.519
million engineers to the workforce if we just help more
769
00:42:55.559 --> 00:42:56.440
girls learn about it.
770
00:42:58.280 --> 00:43:00.960
That's a pretty powerful And so if I'm out there
771
00:43:00.960 --> 00:43:03.880
listening and I have a daughter, maybe I should be
772
00:43:04.039 --> 00:43:06.480
pulling them, giving them proper messages because there's a lot
773
00:43:06.480 --> 00:43:09.480
more opportunities in engineering than it would be in science
774
00:43:09.840 --> 00:43:10.199
or math.
775
00:43:10.800 --> 00:43:14.280
Absolutely, yeah, and and by all means, I mean science
776
00:43:14.360 --> 00:43:17.559
is still very cool, very interesting, but you need to
777
00:43:17.599 --> 00:43:20.079
have a full picture to make an informed decision, right.
778
00:43:20.159 --> 00:43:22.960
And and what happens a lot now is we say
779
00:43:22.960 --> 00:43:25.480
follow your passion, but then we never tell them about
780
00:43:25.480 --> 00:43:27.719
something that they could be passionate about, and so they
781
00:43:27.760 --> 00:43:31.360
never learned, so they can never pick it. Qed Well.
782
00:43:31.360 --> 00:43:33.920
That concludes Part one of my conversation with Julie Newman,
783
00:43:34.079 --> 00:43:37.519
aerospace engineer and best selling author of Pull Don't Push.
784
00:43:38.079 --> 00:43:40.920
Coming up in part two, Julie challenges the familiar advice
785
00:43:40.960 --> 00:43:43.519
of telling kids to follow their passion and suggest a
786
00:43:43.519 --> 00:43:44.960
better way of framing the discussion.
787
00:43:45.599 --> 00:43:48.639
Ooh, what problems do you want to help solve for
788
00:43:48.719 --> 00:43:52.440
other people? That's the one I love coming back to, Okay,
789
00:43:53.480 --> 00:43:57.360
is find the motivation and then and then the way
790
00:43:57.719 --> 00:44:01.760
can become engineering. Or you know, if they say I
791
00:44:01.800 --> 00:44:05.280
want to solve climate change, great, Okay, you can write
792
00:44:05.280 --> 00:44:08.199
a billion papers, it'll it'll never make a difference. But
793
00:44:08.920 --> 00:44:11.079
you go and make the next wind turbine. You're making
794
00:44:11.079 --> 00:44:13.000
a difference, and you want to know who's making the
795
00:44:13.039 --> 00:44:14.480
wind turbine because that's engineers.
796
00:44:15.440 --> 00:44:18.679
Thanks for listening to the Conversation. To find out more
797
00:44:18.679 --> 00:44:23.320
about Clint, go to clintonmpaget dot com and pick up
798
00:44:23.360 --> 00:44:28.079
Clint's book How Teams Triumph Managing by Commitments at Amazon.
799
00:44:28.719 --> 00:44:33.119
The Conversation with Clinton M. Paget is a production of
800
00:44:33.239 --> 00:44:43.480
Forbes Books