1 00:00:11,641 --> 00:00:15,302 Growing up, I changed career paths many times. 2 00:00:15,302 --> 00:00:16,300 First, 3 00:00:16,300 --> 00:00:18,849 I wanted to be a teacher like my mom. 4 00:00:18,962 --> 00:00:22,918 And then, I wanted to be a singer, the next Taylor Swift. 5 00:00:22,918 --> 00:00:25,449 Finally, I wanted to be an actress 6 00:00:25,449 --> 00:00:28,569 because what 10-year-old doesn't want to be on Disney Channel. 7 00:00:28,569 --> 00:00:31,379 Whatever I thought my future occupation would be, 8 00:00:31,379 --> 00:00:33,409 an engineer was not it. 9 00:00:33,409 --> 00:00:35,680 Engineering wasn't even on my radar. 10 00:00:35,970 --> 00:00:37,037 In my opinion, 11 00:00:37,037 --> 00:00:39,124 math and science weren't for girls. 12 00:00:39,124 --> 00:00:41,007 They were for nerdy boys. 13 00:00:41,007 --> 00:00:43,265 It sounds silly, but it's true. 14 00:00:43,265 --> 00:00:48,057 When I was a kid, I imagined engineers and scientists and mathematicians 15 00:00:48,057 --> 00:00:50,458 as really smart men in lab coats 16 00:00:50,458 --> 00:00:53,614 discussing complex theorems, years beyond my understanding. 17 00:00:54,074 --> 00:00:56,266 I thought women in STEM were anomalies. 18 00:00:56,426 --> 00:00:59,858 And for a woman to be an engineer, she had to be some kind of prodigy. 19 00:01:00,608 --> 00:01:02,522 And then one day, 20 00:01:02,522 --> 00:01:05,635 my older stepsister told me that she wanted to be an engineer. 21 00:01:05,635 --> 00:01:08,374 And I realized then that women in STEM weren't prodigies. 22 00:01:08,444 --> 00:01:10,018 They could be anyone. 23 00:01:10,018 --> 00:01:12,904 A female engineer doesn't have to be a prodigy, 24 00:01:12,904 --> 00:01:16,182 just like a male engineer doesn't have to be a prodigy. 25 00:01:16,182 --> 00:01:19,530 And I decided then that I wanted to be an engineer too. 26 00:01:20,190 --> 00:01:23,266 After making the choice to follow this new career path, 27 00:01:23,266 --> 00:01:26,326 I started to realize it's a whole lot easier for guys. 28 00:01:26,486 --> 00:01:28,633 In most cases, from the time they develop, 29 00:01:28,633 --> 00:01:31,848 boys are taught how to use tools and put things together. 30 00:01:31,848 --> 00:01:34,045 They're the ones who are pushed towards cars, 31 00:01:34,045 --> 00:01:36,554 and we're the ones that are pushed towards Barbies. 32 00:01:36,554 --> 00:01:39,337 Toys that inspire passion to go to engineering, 33 00:01:39,337 --> 00:01:42,645 like robots and Legos, are typically marketed towards boys. 34 00:01:42,974 --> 00:01:46,342 And the ones marketed towards girls aren't trucks or spaceships - 35 00:01:46,342 --> 00:01:48,697 they're princess castles and pet shops. 36 00:01:48,957 --> 00:01:51,650 I think it's the little things that cause the gender gap 37 00:01:51,650 --> 00:01:53,095 in science and math careers. 38 00:01:53,095 --> 00:01:56,181 The rare little comment that girls aren't as smart as boys - 39 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. 40 00:02:00,162 --> 00:02:01,247 It's nobody's fault. 41 00:02:01,247 --> 00:02:02,859 We unconsciously do these things 42 00:02:02,859 --> 00:02:05,378 because gender differences and inequalities are things 43 00:02:05,378 --> 00:02:07,774 that have been around for a long time. 44 00:02:07,774 --> 00:02:09,683 And now, they're drilled into our heads. 45 00:02:09,683 --> 00:02:11,821 We solved a lot of this back in the early days 46 00:02:11,821 --> 00:02:14,330 with women's suffrage and equal education. 47 00:02:14,356 --> 00:02:17,076 And now it's time for us to fix the little things, 48 00:02:17,076 --> 00:02:20,097 so that we can grow even closer to achieving equality. 49 00:02:20,807 --> 00:02:24,090 The lack of women in STEM isn't all across the board, however. 50 00:02:24,090 --> 00:02:27,380 In fact, in areas such as medical science and social science, 51 00:02:27,380 --> 00:02:30,177 the ratio is actually very balanced. 52 00:02:30,177 --> 00:02:32,783 But in areas that are often considered more "taxing," 53 00:02:32,783 --> 00:02:35,317 such as computer science and mathematics, 54 00:02:35,317 --> 00:02:37,702 women make up about a quarter of the workforce. 55 00:02:37,962 --> 00:02:39,725 I want that number to even out. 56 00:02:39,725 --> 00:02:42,719 There's a constant fallacy that's spoken from the beginning: 57 00:02:43,069 --> 00:02:46,167 teasing, stereotyping, marginalization. 58 00:02:46,167 --> 00:02:47,637 Countless articles discuss 59 00:02:47,637 --> 00:02:50,744 how women feel out of place in classes relating to STEM, 60 00:02:50,744 --> 00:02:53,784 due to reasons such as other classmates mocking them 61 00:02:53,784 --> 00:02:56,536 or a professor not paying as much attention to them 62 00:02:56,536 --> 00:02:59,198 or a lack of other female classmates in the class. 63 00:03:00,498 --> 00:03:02,711 And if gender inequality isn't a reason enough 64 00:03:02,711 --> 00:03:04,685 for wanting more women involved in STEM, 65 00:03:04,685 --> 00:03:06,838 take into account the scientific discoveries 66 00:03:06,838 --> 00:03:08,455 that have been made by women. 67 00:03:08,515 --> 00:03:12,479 Cardiovascular disease symptoms were always being based off male symptoms. 68 00:03:13,299 --> 00:03:16,583 Despite the fact that it manifests very differently in men and women, 69 00:03:16,753 --> 00:03:18,364 the average male is the model 70 00:03:18,364 --> 00:03:20,972 for investigating diseases and designing treatment 71 00:03:20,972 --> 00:03:23,710 because men were the ones doing the research. 72 00:03:23,830 --> 00:03:26,349 For years, women died from incorrect diagnoses 73 00:03:26,349 --> 00:03:27,979 because no one took into account 74 00:03:27,979 --> 00:03:30,169 that a person's sex could have such an effect 75 00:03:30,169 --> 00:03:31,849 on how a disease appeared. 76 00:03:31,849 --> 00:03:34,998 Now that more women are getting more involved in medical research, 77 00:03:34,998 --> 00:03:38,288 however, they themselves are taking into account these differences 78 00:03:38,288 --> 00:03:40,363 and are consequently saving lives. 79 00:03:40,693 --> 00:03:44,219 Women have been advancing their fields farther ahead for centuries. 80 00:03:45,264 --> 00:03:47,818 Ada Lovelace created a plan for a machine 81 00:03:47,818 --> 00:03:50,796 that could perform complex mathematical calculations. 82 00:03:51,086 --> 00:03:53,280 She did this in the early 1800s. 83 00:03:53,280 --> 00:03:55,215 It was never built during her lifetime, 84 00:03:55,215 --> 00:03:59,018 but her plans were used a century later to build the world's first computers. 85 00:03:59,528 --> 00:04:04,293 One of the world's first electronic computers, called the "ENIAC," 86 00:04:04,293 --> 00:04:07,196 was programmed by six female mathematicians. 87 00:04:07,626 --> 00:04:11,769 Now, Amy Sheng, an engineer, is developing a smartphone attachment 88 00:04:11,769 --> 00:04:12,792 called CellScope, 89 00:04:12,792 --> 00:04:16,280 which allows mothers to detect ear infections in their children. 90 00:04:16,540 --> 00:04:19,221 Hadiyah-Nicole Green, a medical physicist, 91 00:04:19,221 --> 00:04:21,009 is designing a cancer treatment 92 00:04:21,009 --> 00:04:24,789 that uses lasers to destroy cancer cells exclusively. 93 00:04:24,789 --> 00:04:28,799 Despite these achievements, women are still isolated in STEM fields. 94 00:04:28,799 --> 00:04:31,866 I can also get into other problems such as the gender pay gap. 95 00:04:31,866 --> 00:04:35,002 But the fact is that we have made so much progress, 96 00:04:35,002 --> 00:04:38,055 and yet we are still miles away from the finish line. 97 00:04:38,055 --> 00:04:40,965 It's because of the internalized beliefs we don't get it, 98 00:04:40,965 --> 00:04:43,436 plus it's the type for both men and for women. 99 00:04:43,436 --> 00:04:47,327 Project Implicit conducted an investigation on half a million people, 100 00:04:47,327 --> 00:04:49,273 and found that 70% of them 101 00:04:49,273 --> 00:04:53,564 automatically associate men with science and women with the arts. 102 00:04:54,142 --> 00:04:56,070 My goal is to get the word out there 103 00:04:56,070 --> 00:04:59,427 that any little girl or boy can be anything they want to be, 104 00:04:59,427 --> 00:05:00,677 including an engineer. 105 00:05:00,677 --> 00:05:04,175 They don't have to be a prodigy to be a scientist or mathematician. 106 00:05:04,175 --> 00:05:05,979 As long as they work hard, 107 00:05:05,979 --> 00:05:08,176 they can be anything they would like to be. 108 00:05:08,176 --> 00:05:10,917 Parents, teachers, and friends shouldn't hold them back. 109 00:05:10,917 --> 00:05:12,392 They should encourage them. 110 00:05:12,392 --> 00:05:14,972 I want that internalized bias to be gone 111 00:05:14,972 --> 00:05:18,000 because that's what stopped me from wanting to be an engineer 112 00:05:18,000 --> 00:05:19,070 when I was little. 113 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. 114 00:05:22,871 --> 00:05:24,053 Thank you. 115 00:05:24,053 --> 00:05:27,031 (Applause) (Cheers)