1 00:00:01,440 --> 00:00:04,600 Speaker 1: Thirty ten minutes after nine o'clock. Can we shift gears 2 00:00:04,640 --> 00:00:07,119 Speaker 1: slightly now to take a look at what the Internet 3 00:00:07,160 --> 00:00:10,920 Speaker 1: has decided we should be talking about today. We welcome 4 00:00:11,200 --> 00:00:14,280 Speaker 1: Robert Freedoman into the studio for Bob's Wire. 5 00:00:14,680 --> 00:00:18,239 Speaker 2: Good morning, Yeah, morning, Saska. I mean, this is kind 6 00:00:18,280 --> 00:00:20,319 Speaker 2: of a big story and I've seen it across quite 7 00:00:20,360 --> 00:00:22,479 Speaker 2: a lot of the big media houses, and that is 8 00:00:22,520 --> 00:00:28,040 Speaker 2: about India's census. And it caught my eye because according 9 00:00:28,080 --> 00:00:30,080 Speaker 2: to what a lot of people are saying online, one 10 00:00:30,120 --> 00:00:34,360 Speaker 2: point four billion people estimated to kind of currently be 11 00:00:34,479 --> 00:00:35,800 Speaker 2: the population of India. 12 00:00:36,640 --> 00:00:39,120 Speaker 3: We're talking about a population of eight billion in the world. 13 00:00:39,200 --> 00:00:42,480 Speaker 2: They're saying it's close to twenty percent of the world's population. 14 00:00:43,400 --> 00:00:47,640 Speaker 3: That's insane. It is insane, and it's a giant census. 15 00:00:48,040 --> 00:00:51,120 Speaker 2: You know, we can't even copiare can you imagine having 16 00:00:51,159 --> 00:00:55,400 Speaker 2: to now do this? It's they say, reportedly it is 17 00:00:56,080 --> 00:00:58,360 Speaker 2: they do run every decade, but it's the first in 18 00:00:58,480 --> 00:01:04,039 Speaker 2: sixteen years because of delay around COVID and other administrative setbacks, and. 19 00:01:03,960 --> 00:01:06,280 Speaker 3: So now they are about to launch. 20 00:01:06,000 --> 00:01:10,360 Speaker 2: After sixteen years into this massive survey. But they've already 21 00:01:10,360 --> 00:01:13,160 Speaker 2: done apparently they've already started. I think it started in April. 22 00:01:13,440 --> 00:01:17,319 Speaker 2: They've employed three million, as somebody said, an army of 23 00:01:17,440 --> 00:01:22,440 Speaker 2: three million generators to it's a combination of digital. I 24 00:01:22,440 --> 00:01:24,760 Speaker 2: think it all all be inputed digitally. But you have 25 00:01:24,840 --> 00:01:27,920 Speaker 2: to understand that in the thousands and thousands of remote 26 00:01:27,959 --> 00:01:31,679 Speaker 2: villages in India, people are not digitally literate. They don't 27 00:01:31,680 --> 00:01:35,039 Speaker 2: have access to digital. So in the cities it's one thing. 28 00:01:35,160 --> 00:01:36,920 Speaker 2: But we're talking about people going. 29 00:01:36,760 --> 00:01:41,200 Speaker 3: To remote villages we're talking about right, and that I 30 00:01:41,280 --> 00:01:42,240 Speaker 3: can't even imagine. 31 00:01:42,240 --> 00:01:45,559 Speaker 2: And we know that censuses CENSI censuses. 32 00:01:46,160 --> 00:01:49,640 Speaker 3: Oh no idea. Please let us know. 33 00:01:51,200 --> 00:01:56,320 Speaker 2: Out there is how governments then allocate budgets. 34 00:01:56,360 --> 00:01:57,360 Speaker 3: I mean you don't you know. 35 00:01:57,320 --> 00:02:02,680 Speaker 2: It's how you work out housing needs, its social grant needs. 36 00:02:03,040 --> 00:02:07,960 Speaker 2: How many you know young girls have children? And you 37 00:02:08,000 --> 00:02:12,440 Speaker 2: know it's incredibly all that planning. We're planning for buildings, 38 00:02:12,480 --> 00:02:16,359 Speaker 2: for amenities, for service, de liberty, liter electricity, water, blah 39 00:02:16,440 --> 00:02:21,360 Speaker 2: blah blah blah. And so they do use the census, 40 00:02:21,600 --> 00:02:25,400 Speaker 2: it's called it that the census to determine those kinds 41 00:02:25,480 --> 00:02:27,880 Speaker 2: of things. Obviously, it takes a long time for that 42 00:02:27,960 --> 00:02:29,160 Speaker 2: whole thing to process. 43 00:02:29,880 --> 00:02:31,959 Speaker 1: I mean I think it takes until the next, this 44 00:02:32,120 --> 00:02:34,520 Speaker 1: is like how long do they actually have to collect 45 00:02:34,760 --> 00:02:36,200 Speaker 1: all the information. 46 00:02:36,560 --> 00:02:40,280 Speaker 2: They're saying that between April first and fifteenth, Indian citizens 47 00:02:40,320 --> 00:02:42,880 Speaker 2: have the option to report all the vital data themselves, 48 00:02:42,880 --> 00:02:45,200 Speaker 2: so there's going to be some level of self reporting, 49 00:02:45,600 --> 00:02:46,559 Speaker 2: which again. 50 00:02:46,919 --> 00:02:49,919 Speaker 3: I don't know if that's a valid way to do it. 51 00:02:50,280 --> 00:02:54,560 Speaker 2: They are also web based facilities available in sixteen regional languages. 52 00:02:54,639 --> 00:02:57,640 Speaker 2: I mean we're talking just levels here. I mean, I 53 00:02:57,639 --> 00:03:00,639 Speaker 2: mean we probably would have a similar situation. There's something 54 00:03:00,680 --> 00:03:04,240 Speaker 2: like fifty three parameters and questions, which if you multiply 55 00:03:04,320 --> 00:03:07,320 Speaker 2: that by one point four billion people, that is happening 56 00:03:07,600 --> 00:03:10,480 Speaker 2: billions ka bilion questions that are going to be asked 57 00:03:10,520 --> 00:03:12,960 Speaker 2: and this has to all be processed. But quite a 58 00:03:13,000 --> 00:03:15,840 Speaker 2: few of the websites are saying that there's concern that 59 00:03:16,040 --> 00:03:18,760 Speaker 2: it will be used for political manipulation and that there 60 00:03:18,800 --> 00:03:22,640 Speaker 2: se they're hidden agendas lurking behind the India Census. So 61 00:03:22,720 --> 00:03:24,840 Speaker 2: I haven't gone into all the details of that, but 62 00:03:25,240 --> 00:03:28,760 Speaker 2: clearly it's a whole it's a whole world out there, 63 00:03:28,800 --> 00:03:31,840 Speaker 2: and there's just a lot of conversation right now about 64 00:03:31,960 --> 00:03:35,280 Speaker 2: the census because it is the biggest one quite the 65 00:03:35,360 --> 00:03:37,680 Speaker 2: world has literally the world has ever seen. 66 00:03:38,000 --> 00:03:40,280 Speaker 1: Well, I look forward to seeing what that final number 67 00:03:40,440 --> 00:03:41,080 Speaker 1: is once they. 68 00:03:41,040 --> 00:03:44,640 Speaker 2: Know, and if it's even accurate, I suppose, because you 69 00:03:44,680 --> 00:03:49,480 Speaker 2: know how accurate are the remote areas. 70 00:03:50,080 --> 00:03:52,840 Speaker 1: And this is why bobs, you still need people. They 71 00:03:52,880 --> 00:03:55,119 Speaker 1: don't forget. They say AI is coming for your job. 72 00:03:55,200 --> 00:03:56,280 Speaker 1: A is not going to do. 73 00:03:56,200 --> 00:03:59,240 Speaker 2: This, no that, And they're employing three million of them, 74 00:03:59,280 --> 00:04:00,680 Speaker 2: which is this is great. 75 00:04:00,840 --> 00:04:02,120 Speaker 3: Yeah. 76 00:04:02,560 --> 00:04:04,600 Speaker 2: The second one is just one of those you've got 77 00:04:04,600 --> 00:04:06,800 Speaker 2: to see the video type of stories that I'm telling 78 00:04:06,800 --> 00:04:09,280 Speaker 2: you about. So sometimes I talk about them, sometimes I don't. 79 00:04:09,320 --> 00:04:11,760 Speaker 2: But this one is so startling that if you get 80 00:04:11,760 --> 00:04:16,400 Speaker 2: a chance and you go and google motorcycle bursts into flames, 81 00:04:16,440 --> 00:04:20,599 Speaker 2: San Antonio, you'll definitely find it. And there was a 82 00:04:20,600 --> 00:04:25,120 Speaker 2: lot of surveillance footage from houses that took videos that 83 00:04:25,160 --> 00:04:28,279 Speaker 2: were then paired afters and it's this terrifying crash in 84 00:04:28,320 --> 00:04:30,919 Speaker 2: San Antonio. So you see four or five or six 85 00:04:31,480 --> 00:04:34,799 Speaker 2: schoolgoing children sort of on the corner of this road, 86 00:04:34,960 --> 00:04:36,760 Speaker 2: corner of these two streets. 87 00:04:36,360 --> 00:04:38,719 Speaker 3: And they sort of slowly they standing there. Some of 88 00:04:38,720 --> 00:04:39,760 Speaker 3: them are walking along. 89 00:04:40,279 --> 00:04:47,239 Speaker 2: Within like millan nanoseconds, a motorcycle crashes into the lamp post. 90 00:04:47,360 --> 00:04:51,280 Speaker 2: I think it's a lampost and explodes, and yet these 91 00:04:51,440 --> 00:04:54,760 Speaker 2: children all escaped and it's all done so quickly you've 92 00:04:54,760 --> 00:04:56,840 Speaker 2: got to keep watching it about ten times to see 93 00:04:56,839 --> 00:04:57,640 Speaker 2: what actually happened. 94 00:04:57,800 --> 00:04:59,000 Speaker 3: But even more. 95 00:04:58,839 --> 00:05:04,360 Speaker 2: Wild is but the motorcyclist actually kind of flung got 96 00:05:04,400 --> 00:05:07,640 Speaker 2: flung off, and I saw there was almost flames coming 97 00:05:07,640 --> 00:05:10,080 Speaker 2: off him, but he kind of like scampered across the 98 00:05:10,160 --> 00:05:14,560 Speaker 2: road and he survived and apparently he's actually I think 99 00:05:14,600 --> 00:05:17,919 Speaker 2: he's got minor injuries, but he's okay. And you know, 100 00:05:17,920 --> 00:05:19,640 Speaker 2: people came out and I think started trying to put 101 00:05:19,640 --> 00:05:21,039 Speaker 2: the flames after the God knows. 102 00:05:21,160 --> 00:05:22,360 Speaker 3: It's just one of those videos. 103 00:05:22,400 --> 00:05:24,320 Speaker 2: I know there's a lot of explosions going on in 104 00:05:24,320 --> 00:05:27,560 Speaker 2: the world that are, you know, very different, but if 105 00:05:27,560 --> 00:05:29,840 Speaker 2: you just sometimes focus on these things as well, they 106 00:05:29,880 --> 00:05:31,280 Speaker 2: still are startling. 107 00:05:31,720 --> 00:05:34,200 Speaker 3: And I lucky o those kids. I mean, that's the 108 00:05:34,240 --> 00:05:34,919 Speaker 3: main thing. 109 00:05:34,800 --> 00:05:37,760 Speaker 2: Is how lucky that split second. 110 00:05:38,200 --> 00:05:40,440 Speaker 3: Of what could have gone so so wrong. It would 111 00:05:40,440 --> 00:05:42,960 Speaker 3: have been a very different headline. Gosh. 112 00:05:43,000 --> 00:05:47,159 Speaker 2: And then finally another kind of controversial one, A dog 113 00:05:47,240 --> 00:05:49,720 Speaker 2: honking a car horn has gone viral. 114 00:05:49,760 --> 00:05:51,200 Speaker 3: The video has gone viral. 115 00:05:51,520 --> 00:05:54,880 Speaker 2: Okay, so a very cute labradoodle, a white kind of 116 00:05:55,160 --> 00:06:00,320 Speaker 2: beij white labradoodle sitting in a car in Kilany in Iceland, 117 00:06:00,440 --> 00:06:02,599 Speaker 2: in a town in Ireland, on a street, the high 118 00:06:02,640 --> 00:06:05,040 Speaker 2: street type thing with all the shops running along it. 119 00:06:05,920 --> 00:06:08,560 Speaker 2: And a woman was walking past and she saw so 120 00:06:08,640 --> 00:06:10,839 Speaker 2: there were two labradoodles. He had his body in the 121 00:06:10,880 --> 00:06:13,640 Speaker 2: car with him. He got behind the driver's seat and 122 00:06:13,640 --> 00:06:16,600 Speaker 2: he started with his one poor for he started his 123 00:06:16,680 --> 00:06:20,719 Speaker 2: two characters. And this is a horrible serious sag don't 124 00:06:20,800 --> 00:06:22,800 Speaker 2: leave your dogs in the car. But look, it didn't 125 00:06:22,839 --> 00:06:25,120 Speaker 2: look particularly hot. I'm going to say that maybe the 126 00:06:25,160 --> 00:06:25,880 Speaker 2: window is a bit o. 127 00:06:26,240 --> 00:06:32,200 Speaker 1: You can get it now, But like I think, quite 128 00:06:32,240 --> 00:06:35,599 Speaker 1: a smart dog, very smart. But also I'm wondering, like 129 00:06:35,680 --> 00:06:37,719 Speaker 1: maybe the dog he was in a bit of stress. 130 00:06:37,720 --> 00:06:40,640 Speaker 3: Well exactly, that's the sad side of the stories. And 131 00:06:40,720 --> 00:06:43,240 Speaker 3: why do people believe their dogs in cars? And I 132 00:06:43,240 --> 00:06:45,600 Speaker 3: mean in South Africa, please do not it's so hot. Yeah, 133 00:06:45,720 --> 00:06:48,520 Speaker 3: he's done yesterday. While don't leave your kid in the 134 00:06:48,560 --> 00:06:50,680 Speaker 3: car either. Well, I mean we've all heard of those 135 00:06:50,720 --> 00:06:53,760 Speaker 3: tragic stories. Yeah, you know, but well done on this labradoodle. 136 00:06:53,800 --> 00:06:57,240 Speaker 3: Did they They didn't show, so we don't know, you know, happen. 137 00:06:57,360 --> 00:07:00,000 Speaker 2: Story just sort of ends there, so we all left 138 00:07:00,120 --> 00:07:03,560 Speaker 2: wanting you'll find out up. 139 00:07:05,600 --> 00:07:06,400 Speaker 3: Thank you so much