1 00:00:00,120 --> 00:00:03,000 Speaker 1: It is indeed National Science Week, and we know that 2 00:00:03,120 --> 00:00:05,800 Speaker 1: chances are if you've been asked to imagine an engineer 3 00:00:06,000 --> 00:00:10,200 Speaker 1: or a scientist forty years ago, it's highly likely you 4 00:00:10,240 --> 00:00:11,399 Speaker 1: wouldn't have pitched a woman. 5 00:00:11,560 --> 00:00:12,360 Speaker 2: But times and. 6 00:00:12,440 --> 00:00:17,320 Speaker 1: Stereotype stereotypes, I should say I'm most definitely changing and 7 00:00:17,360 --> 00:00:21,840 Speaker 1: today Australian women working in science and making enormous achievements. 8 00:00:22,160 --> 00:00:25,080 Speaker 1: And this year's National Science Week is aiming to inspire 9 00:00:25,280 --> 00:00:30,160 Speaker 1: even more women and girls to get involved in science now. 10 00:00:30,200 --> 00:00:33,760 Speaker 1: Annie Lamb is a forensic scientist who heads up the 11 00:00:33,760 --> 00:00:37,599 Speaker 1: AFP's Forensic Operations Team in Canberra Now. 12 00:00:37,600 --> 00:00:40,600 Speaker 2: In two thousand and two, she was one of the forensic. 13 00:00:40,200 --> 00:00:45,080 Speaker 1: Specialists which was deployed to Indonesia in the aftermath of 14 00:00:45,159 --> 00:00:48,840 Speaker 1: the Balley bombings looking for clues which would help identify 15 00:00:49,000 --> 00:00:51,720 Speaker 1: and lead to the arrest of the suspects. And I'm 16 00:00:51,840 --> 00:00:55,200 Speaker 1: very pleased to say that Annie Lamb joins me on 17 00:00:55,280 --> 00:00:56,360 Speaker 1: the line right now. 18 00:00:56,400 --> 00:00:57,160 Speaker 2: Good morning to you. 19 00:00:57,200 --> 00:01:00,560 Speaker 3: Annie, Hi there, thanks for having me, Thank. 20 00:01:00,400 --> 00:01:03,040 Speaker 2: You so much for joining us. Annie. 21 00:01:03,040 --> 00:01:06,520 Speaker 1: What is it about science, and in particular forensic science 22 00:01:06,560 --> 00:01:08,039 Speaker 1: that first got your hooked? 23 00:01:09,800 --> 00:01:12,000 Speaker 3: So I'm a bit of a problem solver, So That's 24 00:01:12,040 --> 00:01:15,840 Speaker 3: why I gravitated towards science and maths in particular, because 25 00:01:16,200 --> 00:01:17,959 Speaker 3: you know, I find if you have a problem, if 26 00:01:17,959 --> 00:01:20,759 Speaker 3: you do the research or follow a formula, you generally 27 00:01:20,800 --> 00:01:24,400 Speaker 3: get the question the answers that you want. And forensic 28 00:01:24,440 --> 00:01:27,039 Speaker 3: science is the application of science to the law. So 29 00:01:27,680 --> 00:01:30,280 Speaker 3: using science to solve crimes, and that ticks all the 30 00:01:30,319 --> 00:01:30,920 Speaker 3: boxes for me. 31 00:01:31,160 --> 00:01:32,240 Speaker 2: Yeah, right now. 32 00:01:32,640 --> 00:01:34,920 Speaker 1: Obviously, you know, one of the things that a lot 33 00:01:34,959 --> 00:01:37,959 Speaker 1: of our listeners will be very familiar with was the 34 00:01:38,000 --> 00:01:42,480 Speaker 1: Barley bombings, and that is because we're so our proximity 35 00:01:42,480 --> 00:01:46,080 Speaker 1: obviously to Bali, but also because our National Critical Care 36 00:01:46,160 --> 00:01:49,600 Speaker 1: and Trauma Response Center, well, the team there was created 37 00:01:50,040 --> 00:01:53,080 Speaker 1: after the Barley bombings, so some of our wonderful medical 38 00:01:53,120 --> 00:01:57,240 Speaker 1: staff were deployed and you indeed were deployed pretty quickly 39 00:01:57,320 --> 00:02:00,880 Speaker 1: to Bali to those bombing sites into thousand and two. 40 00:02:01,640 --> 00:02:04,600 Speaker 1: As a young forensic scientist, what was that like for you? 41 00:02:06,040 --> 00:02:08,400 Speaker 3: Oh, yes, you know, so I was the two thousand 42 00:02:08,400 --> 00:02:10,639 Speaker 3: and two I was a crime scene investigator based in 43 00:02:10,680 --> 00:02:14,280 Speaker 3: the Act. So my crime scene role was was you know, 44 00:02:14,320 --> 00:02:16,640 Speaker 3: pretty much going to a lot of the burglary crimes 45 00:02:16,639 --> 00:02:19,720 Speaker 3: here and you know, stolen cars and things like that. 46 00:02:19,880 --> 00:02:21,920 Speaker 3: So you know, when I got the call up to 47 00:02:22,280 --> 00:02:26,920 Speaker 3: deploy to Bali, it was obviously was it was a 48 00:02:27,000 --> 00:02:31,919 Speaker 3: really chance to perform this role that you know, it's 49 00:02:31,960 --> 00:02:35,720 Speaker 3: obviously quite significant because we deployed with all our equipment 50 00:02:35,840 --> 00:02:39,519 Speaker 3: and we're working as a big team, big forensic team 51 00:02:39,600 --> 00:02:41,959 Speaker 3: now because you know, we're doing the same thing, we're 52 00:02:42,280 --> 00:02:45,359 Speaker 3: processing a crime scene, but now we're working alongside lots 53 00:02:45,400 --> 00:02:48,400 Speaker 3: of technical specialists you know, bomb scene examiners and chemists 54 00:02:48,400 --> 00:02:52,160 Speaker 3: well to gather the evidence and clues. It really was 55 00:02:52,240 --> 00:02:54,560 Speaker 3: quite significant for me because it was a real learning 56 00:02:54,600 --> 00:02:55,480 Speaker 3: experience as well. 57 00:02:56,320 --> 00:02:57,120 Speaker 2: I bet it was. 58 00:02:57,240 --> 00:03:00,760 Speaker 1: It's you know, it would have been unbelievable really traveling 59 00:03:00,800 --> 00:03:05,120 Speaker 1: across to Bali and knowing, you know, like how how 60 00:03:05,360 --> 00:03:08,760 Speaker 1: tragic that situation had been for so many Australian families 61 00:03:08,800 --> 00:03:12,120 Speaker 1: and how important that work was that you had to 62 00:03:12,160 --> 00:03:14,800 Speaker 1: get underway and do. Yeah. 63 00:03:14,840 --> 00:03:17,680 Speaker 3: Absolutely, I mean, you know, day to day there were 64 00:03:17,720 --> 00:03:20,720 Speaker 3: a lot of tasks and you know, the team at 65 00:03:20,720 --> 00:03:23,040 Speaker 3: one point over there, I would say it was up 66 00:03:23,080 --> 00:03:26,320 Speaker 3: to one hundred of us. We all had had different roles, 67 00:03:26,360 --> 00:03:29,639 Speaker 3: but we all had the roles based on daily taskings. 68 00:03:29,960 --> 00:03:33,760 Speaker 3: We'd have our team leaders that manage these. So you know, 69 00:03:33,800 --> 00:03:35,640 Speaker 3: if you were needed at the bomb scene that day, 70 00:03:35,720 --> 00:03:37,440 Speaker 3: you would help out there. You have your role there 71 00:03:37,640 --> 00:03:40,440 Speaker 3: at the maw Tree, you know, at the local police 72 00:03:40,480 --> 00:03:43,880 Speaker 3: station to assist them with their examinations. So it really 73 00:03:44,000 --> 00:03:46,600 Speaker 3: was a well oiled machine, you know, to make sure 74 00:03:46,680 --> 00:03:49,000 Speaker 3: everything was done and had to be done. 75 00:03:49,240 --> 00:03:50,680 Speaker 2: Yeah, what would. 76 00:03:50,560 --> 00:03:54,280 Speaker 1: You consider the most sort of significant forensic moment in 77 00:03:54,320 --> 00:03:55,320 Speaker 1: that investigation? 78 00:03:57,880 --> 00:04:00,600 Speaker 3: Yes, so you know, obviously we had the primary crime scenes. 79 00:04:00,640 --> 00:04:03,120 Speaker 3: We had those, you know, the bomb scenes, sit we 80 00:04:03,160 --> 00:04:05,960 Speaker 3: had to get the evidence and the clues to say, well, 81 00:04:06,000 --> 00:04:09,440 Speaker 3: what happened here, you know, what was the device you know, 82 00:04:09,480 --> 00:04:13,280 Speaker 3: in Patty's bar and in Sari and the US consulate. 83 00:04:13,840 --> 00:04:16,400 Speaker 3: But what was most significant for me was my involvement 84 00:04:16,440 --> 00:04:19,599 Speaker 3: in the secondary crime scenes. So so these are the 85 00:04:19,680 --> 00:04:24,360 Speaker 3: scenes where all the suspects we're using the premises where 86 00:04:24,360 --> 00:04:27,640 Speaker 3: they're used to to plan these meetings. They use these 87 00:04:27,720 --> 00:04:31,760 Speaker 3: rooms to get together to you know, talk about how 88 00:04:31,839 --> 00:04:34,600 Speaker 3: they were going to you know, do the attack and 89 00:04:34,960 --> 00:04:39,240 Speaker 3: build the build the i DS, the devices. So you know, 90 00:04:39,400 --> 00:04:41,880 Speaker 3: it was a real significant breakthrough when we were able 91 00:04:41,920 --> 00:04:44,719 Speaker 3: to follow the investigation team and then get all these 92 00:04:44,760 --> 00:04:48,160 Speaker 3: evidence to kind of get all the pieces together and 93 00:04:48,240 --> 00:04:52,720 Speaker 3: form a brief about exactly who was involved and what happened. 94 00:04:53,080 --> 00:04:56,520 Speaker 2: Yeah, how I mean, how has that lo? How has 95 00:04:56,600 --> 00:04:57,760 Speaker 2: that whole. 96 00:04:58,680 --> 00:05:01,160 Speaker 1: Incident and working on over there in BALI sort of 97 00:05:01,200 --> 00:05:03,680 Speaker 1: shaped your career then, you know, following on from. 98 00:05:03,520 --> 00:05:07,279 Speaker 4: That, Yeah, it was you know, as I said, it 99 00:05:07,320 --> 00:05:10,560 Speaker 4: was a real learning experience and it really showed me, 100 00:05:11,320 --> 00:05:14,200 Speaker 4: you know, the scope of what we can be involved 101 00:05:14,200 --> 00:05:16,960 Speaker 4: in it in working in forensic science. 102 00:05:17,640 --> 00:05:19,839 Speaker 3: You know, with AFP in particular, we have such a 103 00:05:19,880 --> 00:05:23,520 Speaker 3: broad remit. You know, we support Act policing in community policing, 104 00:05:24,320 --> 00:05:27,960 Speaker 3: but we have national investigations and then we also have 105 00:05:28,680 --> 00:05:31,920 Speaker 3: you know, the you know, to protect Australians off shore, 106 00:05:32,080 --> 00:05:35,279 Speaker 3: so you know, deploying overseas. So it really made me 107 00:05:35,360 --> 00:05:39,960 Speaker 3: relize what a big team effort it is. And you know, 108 00:05:40,080 --> 00:05:44,479 Speaker 3: and since then, obviously we've grown to have a lot 109 00:05:44,520 --> 00:05:47,640 Speaker 3: more of the technical specialists, you know, the digital forensics 110 00:05:47,640 --> 00:05:52,880 Speaker 3: and forensic intelligence teams, and working together is really quite 111 00:05:52,920 --> 00:05:55,200 Speaker 3: an achievement and it's you know, it's different every day 112 00:05:55,800 --> 00:05:57,800 Speaker 3: and yeah, I enjoy it. 113 00:05:58,160 --> 00:05:58,960 Speaker 2: Yeah, I bet you do. 114 00:05:59,080 --> 00:06:01,000 Speaker 1: And you know, honestly, it's not one of those like 115 00:06:01,080 --> 00:06:03,719 Speaker 1: I suppose from the outset, and it's probably the wrong 116 00:06:04,000 --> 00:06:05,760 Speaker 1: you know, it's the wrong view for a. 117 00:06:05,680 --> 00:06:06,360 Speaker 2: Lot of us to have. 118 00:06:06,400 --> 00:06:08,839 Speaker 1: But you don't really think, like when you think of 119 00:06:08,880 --> 00:06:11,720 Speaker 1: the AFP, you don't really think about the science behind it. 120 00:06:11,839 --> 00:06:14,360 Speaker 1: You don't think about forensic science. But it is such 121 00:06:14,360 --> 00:06:16,400 Speaker 1: a critical and important role. 122 00:06:17,800 --> 00:06:18,040 Speaker 2: Yeah. 123 00:06:18,080 --> 00:06:21,440 Speaker 3: Absolutely, you know, i'd say we're probably in the shadows 124 00:06:21,440 --> 00:06:23,800 Speaker 3: of the front line. You know, we're always supporting the 125 00:06:23,800 --> 00:06:26,320 Speaker 3: front line, and you know what's really important is that 126 00:06:26,400 --> 00:06:29,599 Speaker 3: the you know, we have the frontline police to attend first, 127 00:06:30,000 --> 00:06:33,240 Speaker 3: you know, to make sure you know, primarily that the 128 00:06:33,279 --> 00:06:36,040 Speaker 3: scene is safe, that everyone else is safe, and then 129 00:06:36,080 --> 00:06:39,480 Speaker 3: we come in, you know, to do the investigation to 130 00:06:39,680 --> 00:06:41,960 Speaker 3: the crime scene. Also, some of our work I think 131 00:06:42,080 --> 00:06:44,680 Speaker 3: goes on for quite a long time, you know, a 132 00:06:44,720 --> 00:06:48,320 Speaker 3: few months in the lab and then you know, after 133 00:06:48,360 --> 00:06:50,760 Speaker 3: that we kind of move on to different things. But yeah, 134 00:06:51,040 --> 00:06:53,880 Speaker 3: the work goes on in the background. So no, you 135 00:06:53,920 --> 00:06:55,680 Speaker 3: don't get a lot of that unless I guess if 136 00:06:55,680 --> 00:06:57,600 Speaker 3: you follow it in the courtroom. 137 00:06:57,800 --> 00:07:01,239 Speaker 1: Yeah, and when you decided, like when you first started 138 00:07:01,320 --> 00:07:04,360 Speaker 1: studying science and you know, when you were younger, did 139 00:07:04,360 --> 00:07:07,000 Speaker 1: you ever imagine that you'd end up working in forensic 140 00:07:07,040 --> 00:07:08,120 Speaker 1: science for the AFP. 141 00:07:09,920 --> 00:07:12,320 Speaker 3: I look, I actually have to say it was probably 142 00:07:12,320 --> 00:07:14,840 Speaker 3: a bit of luck. You know. When I was leading 143 00:07:14,920 --> 00:07:17,440 Speaker 3: high school and trying to find something in science, you know, 144 00:07:17,560 --> 00:07:19,840 Speaker 3: I read about forensic science and thought, okah, you know, 145 00:07:19,880 --> 00:07:24,360 Speaker 3: that sounds pretty interesting. And then during university I had 146 00:07:24,360 --> 00:07:27,520 Speaker 3: the opportunity to actually do my honest projects with the AFP. 147 00:07:28,080 --> 00:07:30,840 Speaker 3: So that really then puts the idea in my head 148 00:07:30,880 --> 00:07:33,520 Speaker 3: that you know, going into law enforcement is where I 149 00:07:33,520 --> 00:07:36,560 Speaker 3: want to be. And the lucky is that, you know, 150 00:07:36,720 --> 00:07:39,720 Speaker 3: at the end of my course, the AFP was recruiting 151 00:07:40,160 --> 00:07:41,440 Speaker 3: and here I am. 152 00:07:41,480 --> 00:07:44,280 Speaker 1: How wonderful And of course it is National Science Week 153 00:07:44,360 --> 00:07:46,880 Speaker 1: and I know that there is a real push as 154 00:07:46,960 --> 00:07:49,520 Speaker 1: part of National Science work this week to really try 155 00:07:49,560 --> 00:07:52,680 Speaker 1: to inspire even more women and girls to get involved 156 00:07:53,200 --> 00:07:54,040 Speaker 1: in science. 157 00:07:54,400 --> 00:07:55,800 Speaker 2: How do you reckon we can do that? 158 00:07:57,880 --> 00:08:00,120 Speaker 3: I think we really need to kind of start looking 159 00:08:00,160 --> 00:08:02,920 Speaker 3: outside box, you know, just just buss some of those 160 00:08:02,960 --> 00:08:05,600 Speaker 3: stereotypes of the myths of the nerdy type. You know, 161 00:08:06,080 --> 00:08:09,040 Speaker 3: science doesn't have to be someone you know, in a 162 00:08:09,120 --> 00:08:11,720 Speaker 3: lab coat in a lab, even though they are very 163 00:08:11,720 --> 00:08:14,320 Speaker 3: critical roles. But if that's not for you, and you know, 164 00:08:14,400 --> 00:08:16,560 Speaker 3: you like the traveling, or you'd like the problem solving, 165 00:08:16,680 --> 00:08:18,960 Speaker 3: or you like working in the team environments. You know, 166 00:08:19,120 --> 00:08:21,560 Speaker 3: look outside. You know, forensic science, we do have a 167 00:08:21,560 --> 00:08:25,160 Speaker 3: lot of discipline. We're still working with biologist fingerprint experts, 168 00:08:26,280 --> 00:08:29,480 Speaker 3: but we're you know, constantly expanding. We need to work 169 00:08:29,520 --> 00:08:33,280 Speaker 3: collaboratively and you know, if there's a lot of like 170 00:08:33,320 --> 00:08:37,560 Speaker 3: minded people here working forensics and just yeah, so if 171 00:08:37,559 --> 00:08:41,280 Speaker 3: you if you've got those attributes, absolutely go and have 172 00:08:41,320 --> 00:08:41,720 Speaker 3: a look. 173 00:08:41,920 --> 00:08:43,079 Speaker 2: Oh good on you, Annie. 174 00:08:43,080 --> 00:08:45,360 Speaker 1: It's lovely to speak to you this morning, and and 175 00:08:45,480 --> 00:08:48,680 Speaker 1: so insightful. I reckon it's a wonderful profession, you know, 176 00:08:48,800 --> 00:08:51,440 Speaker 1: for for our young girls to be to be looking 177 00:08:51,480 --> 00:08:53,680 Speaker 1: at and and it sounds as though it's taken you 178 00:08:53,720 --> 00:08:56,920 Speaker 1: around the world and to some incredibly interesting jobs. 179 00:08:58,000 --> 00:08:59,600 Speaker 3: Absolutely, thank you for the chart. 180 00:08:59,760 --> 00:09:01,480 Speaker 2: Thanks Sanny, I really appreciate it.