1 00:00:00,920 --> 00:00:03,360 Speaker 1: Ja and Amanda jam Nation. 2 00:00:03,720 --> 00:00:06,120 Speaker 2: Look, there's so much going on in the science world 3 00:00:06,200 --> 00:00:10,080 Speaker 2: right now, the takeover of AI, climate change, the real 4 00:00:10,160 --> 00:00:14,440 Speaker 2: possibility of aliens in our midst Do we have any questions? Well, 5 00:00:14,480 --> 00:00:18,240 Speaker 2: it's National Science Week and we have astrophysicist, self confessed 6 00:00:18,320 --> 00:00:22,280 Speaker 2: space nerd, former bachelor Dr Matt Agnu here to answer 7 00:00:22,320 --> 00:00:24,119 Speaker 2: all these very pressing questions. 8 00:00:24,120 --> 00:00:25,759 Speaker 1: Hello, Matt, good morning. 9 00:00:26,040 --> 00:00:27,000 Speaker 3: Good to talk to you again. 10 00:00:27,040 --> 00:00:28,720 Speaker 1: Mate, it's been a while. 11 00:00:28,840 --> 00:00:30,760 Speaker 2: It has been a while. Nice to chat with you. 12 00:00:30,960 --> 00:00:33,600 Speaker 2: Let's start with these alien life forms. We saw the 13 00:00:33,600 --> 00:00:36,959 Speaker 2: Senate inquiry into this. There now seems to be actual 14 00:00:37,159 --> 00:00:40,720 Speaker 2: evidence that the government has hidden that there are alien 15 00:00:40,760 --> 00:00:41,400 Speaker 2: life forms. 16 00:00:42,360 --> 00:00:46,400 Speaker 1: Okay, let's unpack this. So, firstly, there's no actual evidence. 17 00:00:47,240 --> 00:00:50,280 Speaker 1: All that's happened in this hearing is someone saying they've 18 00:00:50,320 --> 00:00:53,880 Speaker 1: either seen something or actually, more commonly, he said that 19 00:00:53,960 --> 00:00:57,080 Speaker 1: he's interviewed other people who say they've seen something. So 20 00:00:57,680 --> 00:01:03,320 Speaker 1: there's still several layers removed from anything that's remotely considered evidence. 21 00:01:04,040 --> 00:01:07,280 Speaker 1: And there's a famous saying by Carl Sagan who said 22 00:01:07,760 --> 00:01:13,600 Speaker 1: extraordinary claims require extraordinary evidence, and there is not extraordinary evidence. 23 00:01:13,640 --> 00:01:18,080 Speaker 1: There's no evidence, So it still is very much in 24 00:01:18,120 --> 00:01:21,520 Speaker 1: the realm of you know, I've seen this this kind 25 00:01:21,520 --> 00:01:25,640 Speaker 1: of My uncle works at Nintendo Energy. But yeah, there's 26 00:01:25,680 --> 00:01:29,679 Speaker 1: still very little, very little to say or suggest that 27 00:01:29,720 --> 00:01:31,360 Speaker 1: there is any alien life form. 28 00:01:32,200 --> 00:01:35,200 Speaker 3: Do you believe in alien life forms? Matt? Do you 29 00:01:35,200 --> 00:01:36,200 Speaker 3: believe they're out there? 30 00:01:37,080 --> 00:01:39,319 Speaker 1: I do. I do. I think it would be humorous 31 00:01:39,360 --> 00:01:42,240 Speaker 1: to think that we're the only life in the universe. 32 00:01:42,360 --> 00:01:46,640 Speaker 1: The numbers are just absolutely staggering. So the likelihood that 33 00:01:46,680 --> 00:01:50,440 Speaker 1: we're the only life is pardon the pun, astronomically small. 34 00:01:50,960 --> 00:01:53,800 Speaker 1: And yeah, I think that the difference whether it's it's 35 00:01:53,920 --> 00:01:58,600 Speaker 1: just microbial or bacterial or really simplistic life or really 36 00:01:58,640 --> 00:02:02,360 Speaker 1: intelligent advance civilized life, I think that's the difference, And 37 00:02:02,400 --> 00:02:05,680 Speaker 1: the latter I think is much less likely, or if 38 00:02:05,680 --> 00:02:09,760 Speaker 1: it is likely, it is very difficult for the distances 39 00:02:09,800 --> 00:02:12,480 Speaker 1: to be traveled between not just stars but galaxies, and 40 00:02:12,520 --> 00:02:14,399 Speaker 1: so we may not ever encounter them. 41 00:02:14,560 --> 00:02:16,959 Speaker 3: One thing I wanted to ask you about was AI. 42 00:02:17,240 --> 00:02:19,480 Speaker 4: Everyone's talking about AI and my wife is this belief 43 00:02:19,480 --> 00:02:20,839 Speaker 4: that AI is going to kill us all. 44 00:02:21,000 --> 00:02:23,239 Speaker 3: But then on the weekend I was joining to this 45 00:02:23,320 --> 00:02:26,000 Speaker 3: young fellow. He works for a council and he had 46 00:02:26,000 --> 00:02:27,120 Speaker 3: a raging hangover. 47 00:02:27,160 --> 00:02:29,720 Speaker 4: I had to do a presentation, so he used chat 48 00:02:29,840 --> 00:02:33,519 Speaker 4: GPT and just put it in there for his presentation, 49 00:02:33,960 --> 00:02:35,799 Speaker 4: and they gave him a standing ovation. 50 00:02:36,120 --> 00:02:39,160 Speaker 2: But there's more to AI than just chat GPT. Should 51 00:02:39,160 --> 00:02:40,079 Speaker 2: we be scared, Matt? 52 00:02:41,040 --> 00:02:43,959 Speaker 1: I think we just want to be considered. I think AI, 53 00:02:44,160 --> 00:02:47,880 Speaker 1: like any technology, can tremendously enrich our lives and certainly 54 00:02:47,960 --> 00:02:50,720 Speaker 1: save us a lot of additional In the past, it's 55 00:02:50,720 --> 00:02:53,160 Speaker 1: been physical labor. Here it can be mental labor, and 56 00:02:53,200 --> 00:02:55,640 Speaker 1: so it can be really beneficial to us. But there's 57 00:02:56,000 --> 00:02:58,240 Speaker 1: I guess two things to consider. One is we want 58 00:02:58,240 --> 00:03:01,040 Speaker 1: to make sure that it augments us rather than replaces us. 59 00:03:01,120 --> 00:03:05,080 Speaker 1: I think complete replacement obviously opens a real Pandora's box 60 00:03:05,120 --> 00:03:08,200 Speaker 1: of it existential crises. But the other thing is that 61 00:03:08,280 --> 00:03:12,040 Speaker 1: AI is susceptible to the same biases that we have 62 00:03:12,120 --> 00:03:15,680 Speaker 1: in society. And this has been seen where because the 63 00:03:15,760 --> 00:03:19,280 Speaker 1: training data we feed these algorithms is based on our 64 00:03:19,320 --> 00:03:24,520 Speaker 1: own society, there's evidence or there's been instances where certain 65 00:03:24,520 --> 00:03:28,680 Speaker 1: algorithms have been sexist or racist because they've inherited data 66 00:03:29,000 --> 00:03:34,280 Speaker 1: that has something wrong, some bias, some disproportionate representation of things, 67 00:03:35,120 --> 00:03:37,160 Speaker 1: and so we end up with these algrhithms that are 68 00:03:37,200 --> 00:03:39,480 Speaker 1: racist or sexist, or or biggoted it in some other way. 69 00:03:39,680 --> 00:03:42,000 Speaker 1: And so it can be really great, it can be 70 00:03:42,040 --> 00:03:44,120 Speaker 1: really beneficial to our lives, but we do need to 71 00:03:44,120 --> 00:03:45,800 Speaker 1: be careful and we do need to be measured with 72 00:03:46,240 --> 00:03:47,400 Speaker 1: those kinds of things. 73 00:03:47,200 --> 00:03:49,520 Speaker 4: And particularly as we head towards a referendum with the 74 00:03:49,600 --> 00:03:52,480 Speaker 4: yes no vote. And we had the Prime Minister on 75 00:03:52,560 --> 00:03:54,920 Speaker 4: earlier in the week and he was talking about how 76 00:03:55,400 --> 00:03:57,040 Speaker 4: the algorithms are affecting that. 77 00:03:57,600 --> 00:04:02,240 Speaker 2: And I'd seen indigenous face on my socials saying no, 78 00:04:02,400 --> 00:04:04,600 Speaker 2: and I thought, I wonder what's behind that, And apparently 79 00:04:04,680 --> 00:04:09,200 Speaker 2: there's a whole stack of AI generated Indigenous faces saying no. 80 00:04:09,280 --> 00:04:09,600 Speaker 4: That's it. 81 00:04:10,080 --> 00:04:13,760 Speaker 1: There's a real kind of seeing is not necessarily believing 82 00:04:13,800 --> 00:04:18,280 Speaker 1: at the moment because the artificial intelligence ability to it's 83 00:04:18,400 --> 00:04:21,240 Speaker 1: referred to as deep faking, where it can take your 84 00:04:21,279 --> 00:04:23,520 Speaker 1: face or it can create a new face and can 85 00:04:23,800 --> 00:04:27,479 Speaker 1: make it say things, and it can mimic both the 86 00:04:27,839 --> 00:04:30,599 Speaker 1: visual of the face talking but also the audio of 87 00:04:30,640 --> 00:04:37,280 Speaker 1: the face speaking. So there is problems where misinformation can 88 00:04:37,320 --> 00:04:42,680 Speaker 1: be generated so rapidly and so accurately to mimic real 89 00:04:42,760 --> 00:04:47,080 Speaker 1: life that it does raise an issue with misinformation. Yeah, 90 00:04:47,120 --> 00:04:49,240 Speaker 1: I mean this is an outcome of science, but also 91 00:04:49,320 --> 00:04:54,120 Speaker 1: highlights why science and a scientific literate population is so important. 92 00:04:54,320 --> 00:04:55,719 Speaker 3: This is why science is great. 93 00:04:55,800 --> 00:04:58,360 Speaker 4: Do your research or leave it up to Matt Agnew 94 00:04:58,520 --> 00:04:59,520 Speaker 4: to do the research. 95 00:05:00,120 --> 00:05:02,359 Speaker 2: To go into a beauty contest is misinformation? 96 00:05:02,560 --> 00:05:03,359 Speaker 3: Miss Sash? 97 00:05:03,680 --> 00:05:06,120 Speaker 1: Yes, yes, I like it. I like it. 98 00:05:07,279 --> 00:05:11,080 Speaker 4: There should be some conditions applying here, Matt. It's always 99 00:05:11,120 --> 00:05:13,000 Speaker 4: great to talk to you. To get involved in National 100 00:05:13,040 --> 00:05:15,599 Speaker 4: Science Week heads to scienceweek dot net dot Are you 101 00:05:15,920 --> 00:05:16,839 Speaker 4: talked about Agnew? 102 00:05:16,920 --> 00:05:18,040 Speaker 3: Thank you for joining us. 103 00:05:18,520 --> 00:05:20,120 Speaker 1: No, thank you. It's always a pleasure.