WEBVTT 00:00:11.641 --> 00:00:15.302 Growing up, I changed career paths many times. 00:00:15.302 --> 00:00:16.300 First, 00:00:16.300 --> 00:00:18.849 I wanted to be a teacher like my mom. 00:00:18.962 --> 00:00:22.918 And then, I wanted to be a singer, the next Taylor Swift. 00:00:22.918 --> 00:00:25.449 Finally, I wanted to be an actress 00:00:25.449 --> 00:00:28.569 because what 10-year-old doesn't want to be on Disney Channel. NOTE Paragraph 00:00:28.569 --> 00:00:31.379 Whatever I thought my future occupation would be, 00:00:31.379 --> 00:00:33.409 an engineer was not it. 00:00:33.409 --> 00:00:35.680 Engineering wasn't even on my radar. 00:00:35.970 --> 00:00:37.037 In my opinion, 00:00:37.037 --> 00:00:39.124 math and science weren't for girls. 00:00:39.124 --> 00:00:41.007 They were for nerdy boys. 00:00:41.007 --> 00:00:43.265 It sounds silly, but it's true. 00:00:43.265 --> 00:00:48.057 When I was a kid, I imagined engineers and scientists and mathematicians 00:00:48.057 --> 00:00:50.458 as really smart men in lab coats 00:00:50.458 --> 00:00:53.614 discussing complex theorems, years beyond my understanding. 00:00:54.074 --> 00:00:56.266 I thought women in STEM were anomalies. 00:00:56.426 --> 00:00:59.858 And for a woman to be an engineer, she had to be some kind of prodigy. 00:01:00.608 --> 00:01:02.522 And then one day, 00:01:02.522 --> 00:01:05.635 my older stepsister told me that she wanted to be an engineer. 00:01:05.635 --> 00:01:08.374 And I realized then that women in STEM weren't prodigies. 00:01:08.444 --> 00:01:10.018 They could be anyone. 00:01:10.018 --> 00:01:12.904 A female engineer doesn't have to be a prodigy, 00:01:12.904 --> 00:01:16.182 just like a male engineer doesn't have to be a prodigy. 00:01:16.182 --> 00:01:19.530 And I decided then that I wanted to be an engineer too. NOTE Paragraph 00:01:20.190 --> 00:01:23.266 After making the choice to follow this new career path, 00:01:23.266 --> 00:01:26.326 I started to realize it's a whole lot easier for guys. 00:01:26.486 --> 00:01:28.633 In most cases, from the time they develop, 00:01:28.633 --> 00:01:31.848 boys are taught how to use tools and put things together. 00:01:31.848 --> 00:01:34.045 They're the ones who are pushed towards cars, 00:01:34.045 --> 00:01:36.554 and we're the ones that are pushed towards Barbies. 00:01:36.554 --> 00:01:39.337 Toys that inspire passion to go to engineering, 00:01:39.337 --> 00:01:42.645 like robots and Legos, are typically marketed towards boys. 00:01:42.974 --> 00:01:46.342 And the ones marketed towards girls aren't trucks or spaceships - 00:01:46.342 --> 00:01:48.697 they're princess castles and pet shops. 00:01:48.957 --> 00:01:51.650 I think it's the little things that cause the gender gap 00:01:51.650 --> 00:01:53.095 in science and math careers. 00:01:53.095 --> 00:01:56.181 The rare little comment that girls aren't as smart as boys - 00:01:56.181 --> 00:02:00.162 a son being taught how to fix a car while a daughter is taught how to cook. 00:02:00.162 --> 00:02:01.247 It's nobody's fault. 00:02:01.247 --> 00:02:02.859 We unconsciously do these things 00:02:02.859 --> 00:02:05.378 because gender differences and inequalities are things 00:02:05.378 --> 00:02:07.774 that have been around for a long time. 00:02:07.774 --> 00:02:09.683 And now, they're drilled into our heads. 00:02:09.683 --> 00:02:11.821 We solved a lot of this back in the early days 00:02:11.821 --> 00:02:14.330 with women's suffrage and equal education. 00:02:14.356 --> 00:02:17.076 And now it's time for us to fix the little things, 00:02:17.076 --> 00:02:20.097 so that we can grow even closer to achieving equality. NOTE Paragraph 00:02:20.807 --> 00:02:24.090 The lack of women in STEM isn't all across the board, however. 00:02:24.090 --> 00:02:27.380 In fact, in areas such as medical science and social science, 00:02:27.380 --> 00:02:30.177 the ratio is actually very balanced. 00:02:30.177 --> 00:02:32.783 But in areas that are often considered more "taxing," 00:02:32.783 --> 00:02:35.317 such as computer science and mathematics, 00:02:35.317 --> 00:02:37.702 women make up about a quarter of the workforce. 00:02:37.962 --> 00:02:39.725 I want that number to even out. 00:02:39.725 --> 00:02:42.719 There's a constant fallacy that's spoken from the beginning: 00:02:43.069 --> 00:02:46.167 teasing, stereotyping, marginalization. 00:02:46.167 --> 00:02:47.637 Countless articles discuss 00:02:47.637 --> 00:02:50.744 how women feel out of place in classes relating to STEM, 00:02:50.744 --> 00:02:53.784 due to reasons such as other classmates mocking them 00:02:53.784 --> 00:02:56.536 or a professor not paying as much attention to them 00:02:56.536 --> 00:02:59.198 or a lack of other female classmates in the class. 00:03:00.498 --> 00:03:02.711 And if gender inequality isn't a reason enough 00:03:02.711 --> 00:03:04.685 for wanting more women involved in STEM, 00:03:04.685 --> 00:03:06.838 take into account the scientific discoveries 00:03:06.838 --> 00:03:08.455 that have been made by women. 00:03:08.515 --> 00:03:12.479 Cardiovascular disease symptoms were always being based off male symptoms. 00:03:13.299 --> 00:03:16.583 Despite the fact that it manifests very differently in men and women, 00:03:16.753 --> 00:03:18.364 the average male is the model 00:03:18.364 --> 00:03:20.972 for investigating diseases and designing treatment 00:03:20.972 --> 00:03:23.710 because men were the ones doing the research. 00:03:23.830 --> 00:03:26.349 For years, women died from incorrect diagnoses 00:03:26.349 --> 00:03:27.979 because no one took into account 00:03:27.979 --> 00:03:30.169 that a person's sex could have such an effect 00:03:30.169 --> 00:03:31.849 on how a disease appeared. 00:03:31.849 --> 00:03:34.998 Now that more women are getting more involved in medical research, 00:03:34.998 --> 00:03:38.288 however, they themselves are taking into account these differences 00:03:38.288 --> 00:03:40.363 and are consequently saving lives. NOTE Paragraph 00:03:40.693 --> 00:03:44.219 Women have been advancing their fields farther ahead for centuries. 00:03:45.264 --> 00:03:47.818 Ada Lovelace created a plan for a machine 00:03:47.818 --> 00:03:50.796 that could perform complex mathematical calculations. 00:03:51.086 --> 00:03:53.280 She did this in the early 1800s. 00:03:53.280 --> 00:03:55.215 It was never built during her lifetime, 00:03:55.215 --> 00:03:59.018 but her plans were used a century later to build the world's first computers. 00:03:59.528 --> 00:04:04.293 One of the world's first electronic computers, called the "ENIAC," 00:04:04.293 --> 00:04:07.196 was programmed by six female mathematicians. 00:04:07.626 --> 00:04:11.769 Now, Amy Sheng, an engineer, is developing a smartphone attachment 00:04:11.769 --> 00:04:12.792 called CellScope, 00:04:12.792 --> 00:04:16.280 which allows mothers to detect ear infections in their children. 00:04:16.540 --> 00:04:19.221 Hadiyah-Nicole Green, a medical physicist, 00:04:19.221 --> 00:04:21.009 is designing a cancer treatment 00:04:21.009 --> 00:04:24.789 that uses lasers to destroy cancer cells exclusively. 00:04:24.789 --> 00:04:28.799 Despite these achievements, women are still isolated in STEM fields. 00:04:28.799 --> 00:04:31.866 I can also get into other problems such as the gender pay gap. 00:04:31.866 --> 00:04:35.002 But the fact is that we have made so much progress, 00:04:35.002 --> 00:04:38.055 and yet we are still miles away from the finish line. 00:04:38.055 --> 00:04:40.965 It's because of the internalized beliefs we don't get it, 00:04:40.965 --> 00:04:43.436 plus it's the type for both men and for women. 00:04:43.436 --> 00:04:47.327 Project Implicit conducted an investigation on half a million people, 00:04:47.327 --> 00:04:49.273 and found that 70% of them 00:04:49.273 --> 00:04:53.564 automatically associate men with science and women with the arts. NOTE Paragraph 00:04:54.142 --> 00:04:56.070 My goal is to get the word out there 00:04:56.070 --> 00:04:59.427 that any little girl or boy can be anything they want to be, 00:04:59.427 --> 00:05:00.677 including an engineer. 00:05:00.677 --> 00:05:04.175 They don't have to be a prodigy to be a scientist or mathematician. 00:05:04.175 --> 00:05:05.979 As long as they work hard, 00:05:05.979 --> 00:05:08.176 they can be anything they would like to be. 00:05:08.176 --> 00:05:10.917 Parents, teachers, and friends shouldn't hold them back. 00:05:10.917 --> 00:05:12.392 They should encourage them. 00:05:12.392 --> 00:05:14.972 I want that internalized bias to be gone 00:05:14.972 --> 00:05:18.000 because that's what stopped me from wanting to be an engineer 00:05:18.000 --> 00:05:19.070 when I was little. 00:05:19.070 --> 00:05:22.871 And I don't want to stop anyone else from wanting to be an engineer ever again. 00:05:22.871 --> 00:05:24.053 Thank you. 00:05:24.053 --> 00:05:27.031 (Applause) (Cheers)