1 00:00:01,487 --> 00:00:03,656 Beau Lotto: So, this game is very simple. 2 00:00:03,656 --> 00:00:07,703 All you have to do is read what you see. Right? 3 00:00:07,703 --> 00:00:10,904 So, I'm going to count to you, so we don't all do it together. 4 00:00:10,904 --> 00:00:13,403 Okay, one, two, three.Audience: Can you read this? 5 00:00:13,403 --> 00:00:17,782 BL: Amazing. What about this one? One, two, three.Audience: You are not reading this. 6 00:00:17,782 --> 00:00:23,098 BL: All right. One, two, three. (Laughter) 7 00:00:23,098 --> 00:00:27,895 If you were Portuguese, right? How about this one? One, two, three. 8 00:00:27,895 --> 00:00:29,873 Audience: What are you reading? 9 00:00:29,873 --> 00:00:33,331 BL: What are you reading? There are no words there. 10 00:00:33,331 --> 00:00:35,868 I said, read what you're seeing. Right? 11 00:00:35,868 --> 00:00:39,718 It literally says, "Wat ar ou rea in?" (Laughter) Right? 12 00:00:39,718 --> 00:00:43,546 That's what you should have said. Right? Why is this? 13 00:00:43,546 --> 00:00:47,082 It's because perception is grounded in our experience. 14 00:00:47,082 --> 00:00:49,979 Right? The brain takes meaningless information 15 00:00:49,979 --> 00:00:52,938 and makes meaning out of it, which means we never see 16 00:00:52,938 --> 00:00:55,194 what's there, we never see information, 17 00:00:55,194 --> 00:00:58,469 we only ever see what was useful to see in the past. 18 00:00:58,469 --> 00:01:01,205 All right? Which means, when it comes to perception, 19 00:01:01,205 --> 00:01:08,000 we're all like this frog. 20 00:01:08,000 --> 00:01:08,912 (Laughter) 21 00:01:08,912 --> 00:01:12,307 Right? It's getting information. It's generating behavior 22 00:01:12,307 --> 00:01:16,775 that's useful. (Laughter) 23 00:01:16,775 --> 00:01:23,807 (Laughter) 24 00:01:23,807 --> 00:01:29,789 (Video) Man: Ow! Ow! (Laughter) (Applause) 25 00:01:29,789 --> 00:01:32,501 BL: And sometimes, when things don't go our way, 26 00:01:32,501 --> 00:01:34,760 we get a little bit annoyed, right? 27 00:01:34,760 --> 00:01:37,490 But we're talking about perception here, right? 28 00:01:37,490 --> 00:01:41,855 And perception underpins everything we think, we know, 29 00:01:41,855 --> 00:01:44,726 we believe, our hopes, our dreams, the clothes we wear, 30 00:01:44,726 --> 00:01:48,469 falling in love, everything begins with perception. 31 00:01:48,469 --> 00:01:51,414 Now if perception is grounded in our history, it means 32 00:01:51,414 --> 00:01:54,873 we're only ever responding according to what we've done before. 33 00:01:54,873 --> 00:01:57,949 But actually, it's a tremendous problem, 34 00:01:57,949 --> 00:02:01,566 because how can we ever see differently? 35 00:02:01,566 --> 00:02:05,629 Now, I want to tell you a story about seeing differently, 36 00:02:05,629 --> 00:02:09,617 and all new perceptions begin in the same way. 37 00:02:09,617 --> 00:02:12,199 They begin with a question. 38 00:02:12,199 --> 00:02:15,437 The problem with questions is they create uncertainty. 39 00:02:15,437 --> 00:02:18,166 Now, uncertainty is a very bad thing. It's evolutionarily 40 00:02:18,166 --> 00:02:21,767 a bad thing. If you're not sure that's a predator, it's too late. 41 00:02:21,767 --> 00:02:23,127 Okay? (Laughter) 42 00:02:23,127 --> 00:02:26,287 Even seasickness is a consequence of uncertainty. 43 00:02:26,287 --> 00:02:28,539 Right? If you go down below on a boat, your inner ears 44 00:02:28,539 --> 00:02:30,715 are you telling you you're moving. Your eyes, because 45 00:02:30,715 --> 00:02:33,031 it's moving in register with the boat, say I'm standing still. 46 00:02:33,031 --> 00:02:37,686 Your brain cannot deal with the uncertainty of that information, and it gets ill. 47 00:02:37,686 --> 00:02:41,615 The question "why?" is one of the most dangerous things you can do, 48 00:02:41,615 --> 00:02:44,607 because it takes you into uncertainty. 49 00:02:44,607 --> 00:02:47,486 And yet, the irony is, the only way we can ever 50 00:02:47,486 --> 00:02:51,022 do anything new is to step into that space. 51 00:02:51,022 --> 00:02:54,246 So how can we ever do anything new? Well fortunately, 52 00:02:54,246 --> 00:02:57,830 evolution has given us an answer, right? 53 00:02:57,830 --> 00:03:01,425 And it enables us to address even the most difficult 54 00:03:01,425 --> 00:03:06,104 of questions. The best questions are the ones that create the most uncertainty. 55 00:03:06,104 --> 00:03:10,060 They're the ones that question the things we think to be true already. Right? 56 00:03:10,060 --> 00:03:12,049 It's easy to ask questions about how did life begin, 57 00:03:12,049 --> 00:03:15,357 or what extends beyond the universe, but to question what you think to be true already 58 00:03:15,357 --> 00:03:18,358 is really stepping into that space. 59 00:03:18,358 --> 00:03:23,168 So what is evolution's answer to the problem of uncertainty? 60 00:03:23,168 --> 00:03:24,941 It's play. 61 00:03:24,941 --> 00:03:29,134 Now play is not simply a process. Experts in play will tell you 62 00:03:29,134 --> 00:03:31,749 that actually it's a way of being. 63 00:03:31,749 --> 00:03:34,640 Play is one of the only human endeavors where uncertainty 64 00:03:34,640 --> 00:03:38,966 is actually celebrated. Uncertainty is what makes play fun. 65 00:03:38,966 --> 00:03:43,241 Right? It's adaptable to change. Right? It opens possibility, 66 00:03:43,241 --> 00:03:47,350 and it's cooperative. It's actually how we do our social bonding, 67 00:03:47,350 --> 00:03:49,076 and it's intrinsically motivated. What that means 68 00:03:49,076 --> 00:03:53,682 is that we play to play. Play is its own reward. 69 00:03:53,682 --> 00:03:57,573 Now if you look at these five ways of being, 70 00:03:57,573 --> 00:04:00,294 these are the exact same ways of being you need 71 00:04:00,294 --> 00:04:02,330 in order to be a good scientist. 72 00:04:02,330 --> 00:04:05,357 Science is not defined by the method section of a paper. 73 00:04:05,357 --> 00:04:08,497 It's actually a way of being, which is here, and this is true 74 00:04:08,497 --> 00:04:11,150 for anything that is creative. 75 00:04:11,150 --> 00:04:15,353 So if you add rules to play, you have a game. 76 00:04:15,353 --> 00:04:18,143 That's actually what an experiment is. 77 00:04:18,143 --> 00:04:20,062 So armed with these two ideas, 78 00:04:20,062 --> 00:04:24,384 that science is a way of being and experiments are play, 79 00:04:24,384 --> 00:04:27,837 we asked, can anyone become a scientist? 80 00:04:27,837 --> 00:04:31,337 And who better to ask than 25 eight- to 10-year-old children? 81 00:04:31,337 --> 00:04:34,844 Because they're experts in play. So I took my bee arena 82 00:04:34,844 --> 00:04:38,391 down to a small school in Devon, and the aim of this 83 00:04:38,391 --> 00:04:42,635 was to not just get the kids to see science differently, 84 00:04:42,635 --> 00:04:47,233 but, through the process of science, to see themselves differently. Right? 85 00:04:47,233 --> 00:04:50,641 The first step was to ask a question. 86 00:04:50,641 --> 00:04:53,521 Now, I should say that we didn't get funding for this study 87 00:04:53,521 --> 00:04:56,851 because the scientists said small children couldn't make 88 00:04:56,851 --> 00:05:01,153 a useful contribution to science, and the teachers said kids couldn't do it. 89 00:05:01,153 --> 00:05:04,887 So we did it anyway. Right? Of course. 90 00:05:04,887 --> 00:05:07,706 So, here are some of the questions. I put them in small print 91 00:05:07,706 --> 00:05:12,146 so you wouldn't bother reading it. Point is that five of the questions that the kids came up with 92 00:05:12,146 --> 00:05:16,764 were actually the basis of science publication the last five to 15 years. Right? 93 00:05:16,764 --> 00:05:19,424 So they were asking questions that were significant 94 00:05:19,424 --> 00:05:21,554 to expert scientists. 95 00:05:21,554 --> 00:05:25,688 Now here, I want to share the stage with someone quite special. Right? 96 00:05:25,688 --> 00:05:28,300 She was one of the young people who was involved in this study, 97 00:05:28,300 --> 00:05:30,634 and she's now one of the youngest published scientists 98 00:05:30,634 --> 00:05:34,517 in the world. Right? She will now, once she comes onto stage, 99 00:05:34,517 --> 00:05:38,215 will be the youngest person to ever speak at TED. Right? 100 00:05:38,215 --> 00:05:41,090 Now, science and asking questions is about courage. 101 00:05:41,090 --> 00:05:44,290 Now she is the personification of courage, because she's 102 00:05:44,290 --> 00:05:45,677 going to stand up here and talk to you all. 103 00:05:45,677 --> 00:05:50,931 So Amy, would you please come up? (Applause) 104 00:05:50,931 --> 00:05:58,116 (Applause) 105 00:05:58,116 --> 00:06:00,635 So Amy's going to help me tell the story of what we call 106 00:06:00,635 --> 00:06:03,301 the Blackawton Bees Project, and first she's going to tell you 107 00:06:03,301 --> 00:06:05,846 the question that they came up with. So go ahead, Amy. 108 00:06:05,846 --> 00:06:07,565 Amy O'Toole: Thank you, Beau. We thought 109 00:06:07,565 --> 00:06:10,966 that it was easy to see the link between humans and apes 110 00:06:10,966 --> 00:06:13,990 in the way that we think, because we look alike. 111 00:06:13,990 --> 00:06:16,679 But we wondered if there's a possible link 112 00:06:16,679 --> 00:06:21,383 with other animals. It'd be amazing if humans and bees 113 00:06:21,383 --> 00:06:25,496 thought similar, since they seem so different from us. 114 00:06:25,496 --> 00:06:28,549 So we asked if humans and bees might solve 115 00:06:28,549 --> 00:06:30,956 complex problems in the same way. 116 00:06:30,956 --> 00:06:34,243 Really, we wanted to know if bees can also adapt 117 00:06:34,243 --> 00:06:37,950 themselves to new situations using previously learned rules 118 00:06:37,950 --> 00:06:42,164 and conditions. So what if bees can think like us? 119 00:06:42,164 --> 00:06:44,716 Well, it'd be amazing, since we're talking about an insect 120 00:06:44,716 --> 00:06:47,241 with only one million brain cells. 121 00:06:47,241 --> 00:06:49,383 But it actually makes a lot of sense they should, 122 00:06:49,383 --> 00:06:52,660 because bees, like us, can recognize a good flower 123 00:06:52,660 --> 00:06:56,273 regardless of the time of day, the light, the weather, 124 00:06:56,273 --> 00:07:02,015 or from any angle they approach it from. (Applause) 125 00:07:02,015 --> 00:07:05,797 BL: So the next step was to design an experiment, 126 00:07:05,797 --> 00:07:09,099 which is a game. So the kids went off and they designed 127 00:07:09,099 --> 00:07:12,400 this experiment, and so -- well, game -- and so, 128 00:07:12,400 --> 00:07:13,866 Amy, can you tell us what the game was, 129 00:07:13,866 --> 00:07:16,009 and the puzzle that you set the bees? 130 00:07:16,009 --> 00:07:19,032 AO: The puzzle we came up with was an if-then rule. 131 00:07:19,032 --> 00:07:22,677 We asked the bees to learn not just to go to a certain color, 132 00:07:22,677 --> 00:07:25,345 but to a certain color flower only 133 00:07:25,345 --> 00:07:26,977 when it's in a certain pattern. 134 00:07:26,977 --> 00:07:30,236 They were only rewarded if they went to the yellow flowers 135 00:07:30,236 --> 00:07:33,296 if the yellow flowers were surrounded by the blue, 136 00:07:33,296 --> 00:07:36,564 or if the blue flowers were surrounded by the yellow. 137 00:07:36,564 --> 00:07:39,149 Now there's a number of different rules the bees can learn 138 00:07:39,149 --> 00:07:42,574 to solve this puzzle. The interesting question is, which? 139 00:07:42,574 --> 00:07:45,354 What was really exciting about this project was we, 140 00:07:45,354 --> 00:07:47,697 and Beau, had no idea whether it would work. 141 00:07:47,697 --> 00:07:50,151 It was completely new, and no one had done it before, 142 00:07:50,151 --> 00:07:53,874 including adults. (Laughter) 143 00:07:53,874 --> 00:07:57,338 BL: Including the teachers, and that was really hard for the teachers. 144 00:07:57,338 --> 00:08:00,242 It's easy for a scientist to go in and not have a clue what he's doing, 145 00:08:00,242 --> 00:08:02,786 because that's what we do in the lab, but for a teacher 146 00:08:02,786 --> 00:08:04,411 not to know what's going to happen at the end of the day -- 147 00:08:04,411 --> 00:08:07,010 so much of the credit goes to Dave Strudwick, who was 148 00:08:07,010 --> 00:08:09,219 the collaborator on this project. Okay? 149 00:08:09,219 --> 00:08:11,951 So I'm not going to go through the whole details of the study 150 00:08:11,951 --> 00:08:14,589 because actually you can read about it, but the next step 151 00:08:14,589 --> 00:08:18,234 is observation. So here are some of the students 152 00:08:18,234 --> 00:08:21,002 doing the observations. They're recording the data 153 00:08:21,002 --> 00:08:26,046 of where the bees fly. 154 00:08:26,046 --> 00:08:28,069 (Video) Dave Strudwick: So what we're going to do —Student: 5C. 155 00:08:28,069 --> 00:08:32,059 Dave Strudwick: Is she still going up here?Student: Yeah. 156 00:08:32,059 --> 00:08:35,656 Dave Strudwick: So you keep track of each.Student: Henry, can you help me here? 157 00:08:35,656 --> 00:08:38,560 BL: "Can you help me, Henry?" What good scientist says that, right? 158 00:08:38,560 --> 00:08:43,270 Student: There's two up there. 159 00:08:43,270 --> 00:08:46,144 And three in here. 160 00:08:46,144 --> 00:08:48,419 BL: Right? So we've got our observations. We've got our data. 161 00:08:48,419 --> 00:08:52,192 They do the simple mathematics, averaging, etc., etc. 162 00:08:52,192 --> 00:08:54,123 And now we want to share. That's the next step. 163 00:08:54,123 --> 00:08:55,731 So we're going to write this up and try to submit this 164 00:08:55,731 --> 00:08:58,587 for publication. Right? So we have to write it up. 165 00:08:58,587 --> 00:09:03,100 So we go, of course, to the pub. All right? (Laughter) 166 00:09:03,100 --> 00:09:05,384 The one on the left is mine, okay? (Laughter) 167 00:09:05,384 --> 00:09:07,470 Now, I tell them, a paper has four different sections: 168 00:09:07,470 --> 00:09:10,277 an introduction, a methods, a results, a discussion. 169 00:09:10,277 --> 00:09:12,881 The introduction says, what's the question and why? 170 00:09:12,881 --> 00:09:16,000 Methods, what did you do? Results, what was the observation? 171 00:09:16,000 --> 00:09:18,143 And the discussion is, who cares? Right? 172 00:09:18,143 --> 00:09:20,602 That's a science paper, basically. (Laughter) 173 00:09:20,602 --> 00:09:25,131 So the kids give me the words, right? I put it into a narrative, 174 00:09:25,131 --> 00:09:28,378 which means that this paper is written in kidspeak. 175 00:09:28,378 --> 00:09:30,906 It's not written by me. It's written by Amy 176 00:09:30,906 --> 00:09:34,226 and the other students in the class. As a consequence, 177 00:09:34,226 --> 00:09:40,243 this science paper begins, "Once upon a time ... " (Laughter) 178 00:09:40,243 --> 00:09:45,555 The results section, it says: "Training phase, the puzzle ... duh duh duuuuuhhh." Right? (Laughter) 179 00:09:45,555 --> 00:09:47,751 And the methods, it says, "Then we put the bees 180 00:09:47,751 --> 00:09:51,068 into the fridge (and made bee pie)," smiley face. Right? (Laughter) 181 00:09:51,068 --> 00:09:54,901 This is a science paper. We're going to try to get it published. 182 00:09:54,901 --> 00:09:57,735 So here's the title page. We have a number of authors there. 183 00:09:57,735 --> 00:10:00,586 All the ones in bold are eight to 10 years old. 184 00:10:00,586 --> 00:10:02,636 The first author is Blackawton Primary School, because 185 00:10:02,636 --> 00:10:05,882 if it were ever referenced, it would be "Blackawton et al," 186 00:10:05,882 --> 00:10:08,939 and not one individual. So we submit it to a public access journal, 187 00:10:08,939 --> 00:10:12,271 and it says this. It said many things, but it said this. 188 00:10:12,271 --> 00:10:16,190 "I'm afraid the paper fails our initial quality control checks in several different ways." (Laughter) 189 00:10:16,190 --> 00:10:18,750 In other words, it starts off "once upon a time," 190 00:10:18,750 --> 00:10:21,276 the figures are in crayon, etc. (Laughter) 191 00:10:21,276 --> 00:10:25,629 So we said, we'll get it reviewed. So I sent it to Dale Purves, 192 00:10:25,629 --> 00:10:29,162 who is at the National Academy of Science, one of the leading neuroscientists in the world, 193 00:10:29,162 --> 00:10:32,611 and he says, "This is the most original science paper I have ever read" — (Laughter) — 194 00:10:32,611 --> 00:10:34,708 "and it certainly deserves wide exposure." 195 00:10:34,708 --> 00:10:38,979 Larry Maloney, expert in vision, says, "The paper is magnificent. 196 00:10:38,979 --> 00:10:42,345 The work would be publishable if done by adults." 197 00:10:42,345 --> 00:10:44,324 So what did we do? We send it back to the editor. 198 00:10:44,324 --> 00:10:45,913 They say no. 199 00:10:45,913 --> 00:10:48,367 So we asked Larry and Natalie Hempel to write 200 00:10:48,367 --> 00:10:52,374 a commentary situating the findings for scientists, right, 201 00:10:52,374 --> 00:10:56,502 putting in the references, and we submit it to Biology Letters. 202 00:10:56,502 --> 00:10:59,829 And there, it was reviewed by five independent referees, 203 00:10:59,829 --> 00:11:04,250 and it was published. Okay? (Applause) 204 00:11:04,250 --> 00:11:10,250 (Applause) 205 00:11:10,250 --> 00:11:13,271 It took four months to do the science, 206 00:11:13,271 --> 00:11:16,499 two years to get it published. (Laughter) 207 00:11:16,499 --> 00:11:21,334 Typical science, actually, right? So this makes Amy and 208 00:11:21,334 --> 00:11:23,767 her friends the youngest published scientists in the world. 209 00:11:23,767 --> 00:11:25,783 What was the feedback like? 210 00:11:25,783 --> 00:11:28,668 Well, it was published two days before Christmas, 211 00:11:28,668 --> 00:11:32,671 downloaded 30,000 times in the first day, right? 212 00:11:32,671 --> 00:11:36,711 It was the Editors' Choice in Science, which is a top science magazine. 213 00:11:36,711 --> 00:11:39,253 It's forever freely accessible by Biology Letters. 214 00:11:39,253 --> 00:11:42,933 It's the only paper that will ever be freely accessible by this journal. 215 00:11:42,933 --> 00:11:45,632 Last year, it was the second-most downloaded paper 216 00:11:45,632 --> 00:11:49,736 by Biology Letters, and the feedback from not just scientists 217 00:11:49,736 --> 00:11:52,284 and teachers but the public as well. 218 00:11:52,284 --> 00:11:54,056 And I'll just read one. 219 00:11:54,056 --> 00:11:56,546 "I have read 'Blackawton Bees' recently. I don't have 220 00:11:56,546 --> 00:11:58,859 words to explain exactly how I am feeling right now. 221 00:11:58,859 --> 00:12:01,338 What you guys have done is real, true and amazing. 222 00:12:01,338 --> 00:12:04,447 Curiosity, interest, innocence and zeal are the most basic 223 00:12:04,447 --> 00:12:06,171 and most important things to do science. 224 00:12:06,171 --> 00:12:08,649 Who else can have these qualities more than children? 225 00:12:08,649 --> 00:12:12,190 Please congratulate your children's team from my side." 226 00:12:12,190 --> 00:12:15,573 So I'd like to conclude with a physical metaphor. 227 00:12:15,573 --> 00:12:18,541 Can I do it on you? (Laughter) 228 00:12:18,541 --> 00:12:21,634 Oh yeah, yeah, yeah, come on. Yeah yeah. Okay. 229 00:12:21,634 --> 00:12:26,811 Now, science is about taking risks, so this is an incredible risk, right? (Laughter) 230 00:12:26,811 --> 00:12:32,909 For me, not for him. Right? Because we've only done this once before. (Laughter) 231 00:12:32,909 --> 00:12:34,485 And you like technology, right? 232 00:12:34,485 --> 00:12:36,661 Shimon Schocken: Right, but I like myself. 233 00:12:36,661 --> 00:12:39,612 BL: This is the epitome of technology. Right. Okay. 234 00:12:39,612 --> 00:12:43,220 Now ... (Laughter) 235 00:12:43,220 --> 00:12:46,100 Okay. (Laughter) 236 00:12:46,100 --> 00:12:50,184 Now, we're going to do a little demonstration, right? 237 00:12:50,184 --> 00:12:54,203 You have to close your eyes, and you have to point 238 00:12:54,203 --> 00:12:57,360 where you hear me clapping. All right? 239 00:12:57,360 --> 00:13:01,758 (Clapping) 240 00:13:01,758 --> 00:13:04,902 (Clapping) 241 00:13:04,902 --> 00:13:07,805 Okay, how about if everyone over there shouts. One, two, three? 242 00:13:07,805 --> 00:13:10,706 Audience: (Shouts) 243 00:13:10,706 --> 00:13:15,152 (Laughter) 244 00:13:15,152 --> 00:13:18,323 (Shouts) (Laughter) 245 00:13:18,323 --> 00:13:21,964 Brilliant. Now, open your eyes. We'll do it one more time. 246 00:13:21,964 --> 00:13:24,766 Everyone over there shout. (Shouts) 247 00:13:24,766 --> 00:13:30,698 Where's the sound coming from? (Laughter) (Applause) 248 00:13:30,698 --> 00:13:34,928 Thank you very much. (Applause) 249 00:13:34,928 --> 00:13:38,641 What's the point? The point is what science does for us. 250 00:13:38,641 --> 00:13:41,047 Right? We normally walk through life responding, 251 00:13:41,047 --> 00:13:43,259 but if we ever want to do anything different, we have to 252 00:13:43,259 --> 00:13:45,948 step into uncertainty. When he opened his eyes, 253 00:13:45,948 --> 00:13:48,330 he was able to see the world in a new way. 254 00:13:48,330 --> 00:13:51,498 That's what science offers us. It offers the possibility 255 00:13:51,498 --> 00:13:55,514 to step on uncertainty through the process of play, right? 256 00:13:55,514 --> 00:13:58,538 Now, true science education I think should be about 257 00:13:58,538 --> 00:14:01,937 giving people a voice and enabling to express that voice, 258 00:14:01,937 --> 00:14:06,306 so I've asked Amy to be the last voice in this short story. 259 00:14:06,306 --> 00:14:09,411 So, Amy? 260 00:14:09,411 --> 00:14:11,964 AO: This project was really exciting for me, 261 00:14:11,964 --> 00:14:14,635 because it brought the process of discovery to life, 262 00:14:14,635 --> 00:14:17,546 and it showed me that anyone, and I mean anyone, 263 00:14:17,546 --> 00:14:20,299 has the potential to discover something new, 264 00:14:20,299 --> 00:14:24,371 and that a small question can lead into a big discovery. 265 00:14:24,371 --> 00:14:27,023 Changing the way a person thinks about something 266 00:14:27,023 --> 00:14:30,735 can be easy or hard. It all depends on the way the person 267 00:14:30,735 --> 00:14:32,223 feels about change. 268 00:14:32,223 --> 00:14:34,675 But changing the way I thought about science was 269 00:14:34,675 --> 00:14:36,950 surprisingly easy. Once we played the games 270 00:14:36,950 --> 00:14:39,368 and then started to think about the puzzle, 271 00:14:39,368 --> 00:14:43,225 I then realized that science isn't just a boring subject, 272 00:14:43,225 --> 00:14:46,419 and that anyone can discover something new. 273 00:14:46,419 --> 00:14:49,619 You just need an opportunity. My opportunity came 274 00:14:49,619 --> 00:14:52,255 in the form of Beau, and the Blackawton Bee Project. 275 00:14:52,255 --> 00:14:56,616 Thank you.BL: Thank you very much. (Applause) 276 00:14:56,616 --> 00:15:04,363 (Applause)