1 00:00:00,160 --> 00:00:07,680 This is Conservation and Science podcast, where we take a deep dive into topics of ecology, conservation and human wildlife interactions. 2 00:00:07,800 --> 00:00:13,680 I'm telling me, Serafinski and I always try to bring you diverse perspectives of an environmental story that I cover. 3 00:00:13,680 --> 00:00:19,840 And that means that sometimes you might hear voices or that are opposing ends of environmental debate, 4 00:00:19,840 --> 00:00:26,520 and that is fine, because what we need, we need more dialog and understanding and less fighting and division, in other words. 5 00:00:26,680 --> 00:00:30,840 I want you to listen to people you may have not listened to otherwise. 6 00:00:30,840 --> 00:00:36,640 And today our guest is scientist, adventure enterpreneur. 7 00:00:36,640 --> 00:00:41,880 And all those things is one man: Bert terHart. Bert, welcome to the show. It's great to be here. 8 00:00:41,880 --> 00:00:43,320 I'm really excited to speak with you. 9 00:00:43,320 --> 00:00:47,760 We've, I remember answering one of the questions and one of the questions you originally put to me 10 00:00:47,760 --> 00:00:52,400 say, I'm not exactly sure how all this AI and science or business stuff translates. 11 00:00:52,400 --> 00:00:57,360 And it's like, okay, well, I've done some other things, so that was pretty cool. I had fun writing that. So this is going to be great. 12 00:00:58,800 --> 00:00:59,840 Excellent. 13 00:00:59,840 --> 00:01:03,720 Listen, you are you are you, you must say like you wear many hats. 14 00:01:03,720 --> 00:01:10,600 You're a fellow of the Royal Canadian Geographical Society, explorer in residence for the BC Historical Society. 15 00:01:10,640 --> 00:01:12,400 You're a trained research scientist. 16 00:01:12,400 --> 00:01:15,000 You are CEO and lead brain dot AI. 17 00:01:15,000 --> 00:01:20,080 You founder of a Canadian interactive waterway inter initiative. 18 00:01:20,080 --> 00:01:22,720 Like, how do you think about yourself? 19 00:01:22,720 --> 00:01:27,000 How do you like you think about yourself as an adventurer, as an entrepreneur, as a scientist? 20 00:01:27,000 --> 00:01:27,640 Like what? 21 00:01:27,640 --> 00:01:33,120 How do you think about yourself? Well, if I had to if I had to say when I think about myself, I think about this. 22 00:01:33,120 --> 00:01:39,000 I think primarily about the thing I'm most passionate about, and that is science. 23 00:01:39,000 --> 00:01:43,200 So my perspective on everything is, is, scientific perspective. 24 00:01:43,200 --> 00:01:47,480 I'm I'm formally trained as a scientist. I have probably went to many degrees, 25 00:01:49,080 --> 00:01:53,080 but you know, that that said, everything I've ever done, including all the all 26 00:01:53,080 --> 00:02:01,320 that the crazy stuff for the ArcGIS or the BC Historical Society has always been with other, an historical context that relates to, 27 00:02:01,880 --> 00:02:09,440 how the place that we live has come to be, or it's from a scientific perspective, which is what kind of ecosystem am I? 28 00:02:09,440 --> 00:02:12,600 Am I traveling through and and what can I do 29 00:02:12,600 --> 00:02:18,960 to contribute to the global knowledge base, as it pertains to, to my passions as I move through that ecosystem? 30 00:02:18,960 --> 00:02:24,960 So that's paddling across Canada, sailing across an ocean, going out to Aleutian Islands, going into the Bering Sea. 31 00:02:25,160 --> 00:02:29,720 So there's always an opportunity for me to do, to do some kind of formal science as, as, as a citizen. 32 00:02:29,720 --> 00:02:35,160 So if you ask me what I am, I'm a I'm a science guy, like Bill Nye the Science guy. 33 00:02:35,160 --> 00:02:39,400 So how about that. So that exit that's that's clarified that clarifies that thing. 34 00:02:39,400 --> 00:02:40,920 And so that was my, 35 00:02:40,920 --> 00:02:47,600 my like thing that I was wondering, like you circumnavigate the globe and and the solo on the, on the sailing yacht, which is like wow man. 36 00:02:47,880 --> 00:02:55,960 I remember when I was a kid, I was, reading a book about a Polish explorer who to circumnavigate the globe solo. 37 00:02:56,400 --> 00:02:59,640 And yes, cool. I think Henrik Pascua was his name. 38 00:02:59,640 --> 00:03:07,840 And and I was just like, man, this is like so I have like, I read that book, like, what is happening on the boat, like what can happen now? 39 00:03:07,840 --> 00:03:11,320 Tell me like, and you can, you know, I'm always ask you this open question. 40 00:03:11,320 --> 00:03:14,920 So you may say, like how what motivated you to do this? 41 00:03:14,920 --> 00:03:18,360 But, what I'm particularly curious is like, have you like, 42 00:03:18,360 --> 00:03:26,160 while you're doing this, you then kind of your sciencey brain kicked in and you were connecting those things, 43 00:03:26,160 --> 00:03:32,920 or was it on the from the very get go that this is going to be like a some sort of like a scientific endeavor? 44 00:03:33,120 --> 00:03:33,440 Yeah. 45 00:03:33,440 --> 00:03:37,000 Well, as soon as I decided I was going to make that, I was going to do the, the 46 00:03:37,000 --> 00:03:43,400 this trip around the world, I went to some of my old, science contacts, some of the, you know, some people on my PhD committee, 47 00:03:43,800 --> 00:03:49,800 some other scientists I knew I knew who were that I had followed by by following their, their, their research, 48 00:03:49,800 --> 00:03:51,120 doing things that I was interested in. 49 00:03:51,120 --> 00:03:56,160 And then I, I did some things that were that was well outside my, my normal, I guess, training. 50 00:03:56,160 --> 00:04:00,000 So, I went to the instead of ocean sciences here in British Columbia. 51 00:04:00,000 --> 00:04:07,040 I went to the University of Hawaii and then I went to another, another university where I got hold of someone who was doing micro 52 00:04:07,440 --> 00:04:09,560 microplastics, in the ocean. 53 00:04:09,560 --> 00:04:16,520 So with the interest of ocean sciences, they have a very large program that, that that involves GPS tracked current drugs. 54 00:04:16,520 --> 00:04:20,760 So you throw in these, you throw these current drugs into the ocean, they're tracked by GPS. 55 00:04:20,760 --> 00:04:25,520 And we have they had very good resolution in the North Pacific, but virtually none in the Southern Ocean. 56 00:04:25,520 --> 00:04:30,280 So I took a bunch of these current drugs with the when I so I contacted the guy who's in charge of that study 57 00:04:30,280 --> 00:04:33,960 who happened to be on my old committee, and I said, hey, this is what I'm doing, 58 00:04:33,960 --> 00:04:38,440 and how would I put some of these current drugs in a place that you would never, ever, ever be able to get them in? 59 00:04:38,440 --> 00:04:40,960 Because it's very science is unbelievably expensive. 60 00:04:40,960 --> 00:04:47,480 You have to put people, equipment, resources, time and energy into places that are typically very far away. 61 00:04:47,480 --> 00:04:52,080 So if you're going to the you know, for me it's going into the Arctic or the Aleutian Islands or going, 62 00:04:52,080 --> 00:04:53,400 you know, all the way in the Southern Ocean. 63 00:04:53,400 --> 00:04:59,040 So I said, give me some of these drugs and I'll happily plop them in the ocean as I go around, you know, five great capes. 64 00:04:59,040 --> 00:05:00,240 So that was that was that. 65 00:05:00,240 --> 00:05:06,760 And I contacted a guy, out of the University of Hawaii who was doing micro and macro plastic surveys. 66 00:05:06,760 --> 00:05:11,640 And I said, look, I'm going around the world and I'm willing to spend an hour a day 67 00:05:11,640 --> 00:05:17,640 looking out, out on the boat for microplastics, things that you can actually see with the naked eye. 68 00:05:17,840 --> 00:05:21,120 So he said, sure. So that's what I did. I spent it when it was possible. 69 00:05:21,120 --> 00:05:26,040 I spent an hour outside the boat looking for, chunks of plastic floating in the ocean. 70 00:05:26,040 --> 00:05:28,720 And of course, no one throws over microplastics. 71 00:05:28,720 --> 00:05:34,560 They throw over microplastics, you know, a bottle or something like that, or a or a fish crate, and then it degrades, of course. 72 00:05:34,560 --> 00:05:41,400 So, and if you stare out at the same piece of thing, whether it's water or grass or forest, 73 00:05:41,640 --> 00:05:44,640 pretty soon you have a very, very good idea of what doesn't belong there. 74 00:05:44,640 --> 00:05:50,400 So you get very good at at identifying things at that, that are floating. Obviously that shouldn't be there. 75 00:05:50,400 --> 00:06:00,240 And then I, I contacted another scientist who was doing microplastics, and that meant doing plankton trawls behind the boat and then basically, 76 00:06:00,240 --> 00:06:06,920 isolating those samples, ensuring that they were stable and, and, and carrying them with me around the world until I got back. 77 00:06:06,920 --> 00:06:09,080 Well, that that that proved to be too difficult. 78 00:06:09,080 --> 00:06:15,080 And that proved to be too hard because I had lots of other things to do on the boat, like, you know, beyond just staying alive. 79 00:06:15,520 --> 00:06:20,240 So yes, sailing actually, so that that proved to be a bit too much. 80 00:06:20,240 --> 00:06:26,120 But the other thing I did was, I tried to, do bird counts of albatross. 81 00:06:26,120 --> 00:06:26,760 Albatross? 82 00:06:26,760 --> 00:06:31,160 In the Southern Ocean, there's the population is basically, 83 00:06:31,160 --> 00:06:37,600 at at the near catastrophic levels because of the overfishing of their primary food source, which is squid. 84 00:06:37,600 --> 00:06:39,480 And they were live in the Southern Ocean. 85 00:06:39,480 --> 00:06:43,320 And that part of the world is virtually unpublished because no one gets there. 86 00:06:43,320 --> 00:06:47,840 So if you happen to be sailing around there and you're actually out there counting birds, that's incredibly valuable. 87 00:06:47,840 --> 00:06:55,200 So so that's that was, I as soon as I decided I was going to sail around the world, I decided I was going to do it first. 88 00:06:55,520 --> 00:06:58,160 I was going to engage in things that I'm passionate about. 89 00:06:58,160 --> 00:07:01,080 This is this is fantastic, story. 90 00:07:01,080 --> 00:07:05,040 And this is fantastic that you were willing to do that, to do those things. 91 00:07:05,040 --> 00:07:09,600 And, look, we're going to come back to many things that you already mentioned. 92 00:07:09,600 --> 00:07:17,920 But I just want to say, like right on the get go, you know what you're we're looking at, you know, how the things supposed to look like 93 00:07:18,720 --> 00:07:25,440 I'm curious like in general like how they were looking like, so what what were the changes that you seen? 94 00:07:25,440 --> 00:07:30,520 What was the, you know, like a out of place or alarming things that you saw? 95 00:07:30,520 --> 00:07:35,240 Well, I guess the first thing that I would say that that was, that was most alarming was running into the 96 00:07:35,240 --> 00:07:38,400 to the Chinese industrialized fishing fleet. 97 00:07:38,400 --> 00:07:39,480 Offshore. 98 00:07:39,480 --> 00:07:46,440 And I was, as I went by the Falkland Islands, which is, you know, between Cape Horn, in between South America and South Africa. 99 00:07:47,160 --> 00:07:54,560 I was warned by the, by the, by the people who can, by Falklands people and Falklands that and the British who, 100 00:07:54,800 --> 00:08:02,160 who actually managed that, that particular part of the world in terms of the in terms of fisheries and their coastal fisheries 101 00:08:02,160 --> 00:08:08,160 up to 200 miles offshore, they said you have to watch out for the Chinese industrialized commercial fishing fleet. 102 00:08:08,440 --> 00:08:13,080 They're fishing illegally. They're not supposed they're fishing in a place where where they're not supposed to be. 103 00:08:13,080 --> 00:08:17,280 They have everything turned off, all the AIS, everything. They're basically black. 104 00:08:17,280 --> 00:08:24,080 And if you run into them and they they'll well, basically, if they run you over, they couldn't care less. 105 00:08:24,080 --> 00:08:29,240 So I ran into them twice. It was probably I mean, you don't see very many ships at all. 106 00:08:29,240 --> 00:08:34,800 And, suddenly as I'm sailing in the middle of the night, I get this warning on AIS, 107 00:08:34,800 --> 00:08:40,520 the automatic identification system that every then I had on board just to just to keep me from doing that sort of thing. 108 00:08:40,520 --> 00:08:43,440 And the thing just lights up and I. 109 00:08:43,440 --> 00:08:44,720 And there's nothing on the horizon. 110 00:08:44,720 --> 00:08:49,520 There's no lights at all outside. Which is strange because this is AIS is line of sight. 111 00:08:49,520 --> 00:08:54,960 And, suddenly as I'm looking out on the horizon, I see that the light of 112 00:08:54,960 --> 00:09:00,640 of basically 1000ft, packer, which is the thing that stays at sea 365 days a year. 113 00:09:00,640 --> 00:09:05,000 All it does is process the the catch of all these other sort of, 114 00:09:05,000 --> 00:09:11,280 satellite vessels, these other boats that are going out and fishing, and they come back to this giant thing like an aircraft carrier. 115 00:09:11,640 --> 00:09:17,160 It's huge processes of fish. And then these other boats come and take it back to market and take it away. 116 00:09:17,160 --> 00:09:21,960 So this giant thing lights up and I get on the radio and say, you know what's going on? Who are you? 117 00:09:21,960 --> 00:09:27,000 You know, which which way should I go? Because, a vessel at sea that's fishing has the right of way. 118 00:09:27,000 --> 00:09:32,920 So I don't have the right away. I have to get out of this guy's way. And there's the. The English is. 119 00:09:32,920 --> 00:09:35,840 Well, there's no reason to expect that the people are speaking English. 120 00:09:35,840 --> 00:09:39,160 But it was the English was was almost incomprehensible. 121 00:09:39,160 --> 00:09:42,120 And it was just it was just go behind, go behind. 122 00:09:42,120 --> 00:09:49,320 And then suddenly in front of me, there's like a chain of boats every all the lights turn on at once, and I see the big one, 123 00:09:49,320 --> 00:09:52,760 and I'm supposed to go behind this thing, and then all the lights turn off again. 124 00:09:52,760 --> 00:09:58,080 So it's it, it's it contravenes everything that's supposed to happen at sea. 125 00:09:58,080 --> 00:10:04,080 So, and I was warned about it because if you these guys are, if you run into them, then you'll never be seen again. 126 00:10:04,120 --> 00:10:09,520 Let's go to bit the boats. I might as a small boat. They would hit me and I would I be the only person that knew. 127 00:10:10,560 --> 00:10:13,800 And, what they're fishing for primarily is, 128 00:10:13,800 --> 00:10:20,040 Well, there's fishing for all kinds of things, but they fish for squid, and squid is what albatross eat, and they're just. 129 00:10:20,040 --> 00:10:22,040 They're just raping it. 130 00:10:22,040 --> 00:10:23,640 I mean, it's it's shocking. 131 00:10:23,640 --> 00:10:28,040 It's shocking how much, how much that they, they can that they can process. 132 00:10:28,040 --> 00:10:34,040 So actually, you know, when I was a graduate student, this is a long time ago now, this was like the late 80s. 133 00:10:34,080 --> 00:10:41,280 There was a not there was enough fishing net in the water to go from Vancouver to Tokyo. 134 00:10:42,400 --> 00:10:50,880 That's how much that's how much gillnet was in the water at any at any day, any any given day of the, of the, of the week, month or year. 135 00:10:51,560 --> 00:10:56,240 And of course, they're fishing for a particular fish, but the bycatch is everything else. 136 00:10:56,240 --> 00:11:04,280 It's dolphin and it's, it's, it's whales and it's, it's sharks and it's turtles, you know, and it's salmon. 137 00:11:04,280 --> 00:11:11,520 Because we were concerned about salmon fishing at the time, there was return migration routes of sockeye salmon and it's it really is. 138 00:11:12,240 --> 00:11:15,200 It is absolutely. It's worse than you think. 139 00:11:15,200 --> 00:11:22,600 And, there's no real incentive to do anything about it because, these are peat that they're fishing in, in international waters, 140 00:11:22,600 --> 00:11:26,000 but they're fishing illegally, which, which might be bycatch or maybe not, 141 00:11:26,000 --> 00:11:33,520 or or maybe they're fishing very close to, to say, the Falkland Islands with other fishing very close to any place that there's banks. 142 00:11:33,520 --> 00:11:39,360 So, and the banks are typically near, near continental coasts. So it's 143 00:11:40,360 --> 00:11:43,680 yeah, that's, it's way worse than you think. 144 00:11:43,680 --> 00:11:44,480 So it's fishing. 145 00:11:44,480 --> 00:11:46,800 So it's fishing once again, I don't want to sound like a guy 146 00:11:46,800 --> 00:11:52,800 who's picking out picking on the fishing or fishing industry once again, but they they're probably the worst. 147 00:11:52,840 --> 00:11:53,880 Yeah, they're the worst moments. 148 00:11:53,880 --> 00:12:00,440 I mean, if you think of if you think everyone, I think it knows the a bit of the saga that that had to go on with whaling. 149 00:12:00,440 --> 00:12:03,640 But there was, you know, whaling was outlawed. And then there's, there's people still fish. 150 00:12:03,640 --> 00:12:07,120 There was people still fishing illegally for whales for a very long time. 151 00:12:07,120 --> 00:12:07,760 And the, you know, 152 00:12:07,760 --> 00:12:14,280 the international community has to wield a very large club before it, before those particular countries who are doing those things stop. 153 00:12:15,200 --> 00:12:18,680 And most of you know, the 80% number is huge because, 154 00:12:19,760 --> 00:12:24,280 firstly, we don't eat that much fish compared to other countries who who eat an enormous amount of fish. 155 00:12:24,280 --> 00:12:28,960 Like there's some shocking statistic. So I was in the Aleutian Islands, for example, on Kodiak. 156 00:12:28,960 --> 00:12:30,720 I was actually at the time doing 157 00:12:30,720 --> 00:12:38,000 helping UBC Forestry University, British Columbia Forestry, doing genetic distribution of Sitka spruce, which is really cool. 158 00:12:38,000 --> 00:12:40,440 Sitka spruce is is an invasive species. Actually. 159 00:12:40,440 --> 00:12:42,120 It travels from California all the way up, 160 00:12:42,120 --> 00:12:48,240 you know, through the northwest and then down in the Alaskan panhandle and ends at the first of the Aleutian Islands. 161 00:12:48,720 --> 00:12:53,240 So there is a couple PhD students and a technician who were who were doing trickery. 162 00:12:53,240 --> 00:12:56,720 They were coring to, to, to test, you know, where do these trees come from? 163 00:12:56,720 --> 00:13:01,480 How did they jump? Basically from the mainland to Kodiak. It was very cool. It was very fun. 164 00:13:01,480 --> 00:13:08,640 But we ended up in Kodiak Island, you know, getting science, getting scientific stuff on board equipment and whatnot and people. 165 00:13:09,200 --> 00:13:17,920 And there's, there's a fish processing plant there that processes 3 million pounds of sockeye, natural sockeye a year. 166 00:13:18,360 --> 00:13:25,640 It runs on the fish oil that it produces is completely self-sustaining, which sounds wonderful, except all that fish goes to dog food. 167 00:13:26,160 --> 00:13:27,160 Well, this. 168 00:13:28,120 --> 00:13:30,160 So there's no winning, right? 169 00:13:30,160 --> 00:13:32,160 There just seems to be no winning. 170 00:13:32,160 --> 00:13:34,960 Exactly. You just shake your head. Oh, they're finally doing something good. 171 00:13:34,960 --> 00:13:39,200 But then it's like, you're kidding me, right? Dog food. Is that right? Is that what we're doing? 172 00:13:39,200 --> 00:13:41,800 Is that why we're going to burn through, you know, 3 million pounds? 173 00:13:41,800 --> 00:13:48,440 So there's but okay, so that's that's kind of the that the dark side that let me give you a brighter story. 174 00:13:48,440 --> 00:13:54,440 So there is a very yeah, there is there is a very good young scientist who had a very good idea. 175 00:13:54,840 --> 00:13:56,760 And in the Southern Ocean albatross, 176 00:13:56,760 --> 00:14:03,400 these were the great albatross, the 12ft wingspan, you know, these birds that flap their wings literally once every half hour spend. 177 00:14:03,400 --> 00:14:04,200 They're almost there. 178 00:14:04,200 --> 00:14:09,520 And while they spend it, they spend two years at sea and then go back to the place that they were, that they were hatched and then mate. 179 00:14:09,520 --> 00:14:15,000 And then they go back to sea. So they travel enormous distances and cover enormous, 180 00:14:16,080 --> 00:14:17,040 areas. 181 00:14:17,040 --> 00:14:23,880 So what this guy did was he strapped a magnetometer and a GPS tracker to an albatross, 182 00:14:24,480 --> 00:14:30,360 and, they captured like a they captured, I think, something like 160 albatross. 183 00:14:30,360 --> 00:14:33,600 And they, they put this equipment on them, and then they turned them loose. 184 00:14:33,600 --> 00:14:37,720 And every time the magnetometer goes off, it has to be near a ship. 185 00:14:37,720 --> 00:14:42,480 And albatross love finding ships because there's, you know, there's usually something good to eat. 186 00:14:42,480 --> 00:14:45,720 And if there's not something good to eat, they, they're just they're just tremendous company 187 00:14:45,720 --> 00:14:49,560 because, every time I stopped in the Southern Ocean when I was becalmed, 188 00:14:49,560 --> 00:14:53,800 I was just surrounded by these albatross, which is which is how I was able to count. 189 00:14:53,800 --> 00:15:01,560 But, so with this, I figured that if there's if the magnetometer goes off, it's a ship, and if it's a ship, it has to have an air signal. 190 00:15:01,920 --> 00:15:06,840 And if there's no AI signal, they're there illegally and therefore probably fishing. 191 00:15:06,840 --> 00:15:15,800 So, these albatross over the course of a year, covers something like 46,000,000mi² of the Southern Ocean flying everywhere. 192 00:15:16,080 --> 00:15:23,160 And the data he got was, was a part of this study that that says 80% of the fishing catches illegal was part of that study. 193 00:15:23,640 --> 00:15:27,760 A small part, but it was, it was science on a shoestring at its best. 194 00:15:27,760 --> 00:15:32,280 And the data that that they got was invaluable because it's otherwise there's no way to know. 195 00:15:32,280 --> 00:15:38,880 And you, you can't just say, well, we're going to do it remotely because that costs an incredible pile of money to get satellite 196 00:15:38,880 --> 00:15:44,040 time to go back and, you know, stare at the Southern Ocean where there's nothing but nothing but nothing. 197 00:15:44,040 --> 00:15:46,360 But to get albatross to do it was brilliant. 198 00:15:46,360 --> 00:15:52,440 And, the data they got about, you know, where boats should be and shouldn't be, the people that were there, that should be 199 00:15:52,440 --> 00:16:00,120 and shouldn't be, and what they were doing if it was illegal or illegal was, was was again, like I say, very valuable. 200 00:16:00,120 --> 00:16:02,160 So there's, there's lots of room. 201 00:16:03,680 --> 00:16:04,200 There's lots of 202 00:16:04,200 --> 00:16:10,200 room for, for people who, who like to do science at a shoestring and come up with a good idea because there's lots of data. 203 00:16:10,200 --> 00:16:17,800 If everybody needs data and, the places where data is, is needed is everywhere that you can imagine 204 00:16:17,800 --> 00:16:23,800 because the ecosystem is, as I'm sure you, you would agree, is under attack just about everywhere, everywhere we step. 205 00:16:24,080 --> 00:16:27,280 Yes. That's that's that's it. Unfortunate. True. 206 00:16:27,280 --> 00:16:34,600 Whether whether the whether the attack is, you know, intentional or unintentional, it's it's under pressure one way or another. 207 00:16:34,760 --> 00:16:36,240 This is fantastic story I love it. 208 00:16:36,240 --> 00:16:43,080 The albatross who are just like, know it, unknowingly snooping on the on the illegal fishing. 209 00:16:43,080 --> 00:16:47,880 This is this is absolutely brilliant. But I just want to quickly touch on one other thing that you mentioned. 210 00:16:47,880 --> 00:16:49,000 You mentioned microplastic. 211 00:16:49,000 --> 00:16:52,000 Yeah, we hear about microplastic everywhere. 212 00:16:52,000 --> 00:16:55,520 Like everybody knows about microplastic. It's everywhere. 213 00:16:55,520 --> 00:16:59,640 But it probably is the first time I heard about microplastic. 214 00:16:59,640 --> 00:17:07,240 So could you like, explain it laid out to our listeners, the issue of microplastic, 215 00:17:07,240 --> 00:17:16,280 what what part of the whole plastic pollution it is and whether, you know, what are the science related to microplastic? 216 00:17:16,280 --> 00:17:20,760 Well, there's there's two sources of, of of microplastic in the oceans. 217 00:17:20,760 --> 00:17:24,280 There's there's microplastic that ends up in the ocean as a result of river runoff. 218 00:17:24,280 --> 00:17:30,320 So, and river runoff, you can assume, is coming from industrialized areas because most of the coast is is 219 00:17:30,320 --> 00:17:38,360 industrialized in most of the world, and all the microplastic is not coming from places like, you know, places like the Antarctic 220 00:17:38,360 --> 00:17:44,360 where there's no industrialization, there's no runoff, and there's and there's and there's no big plastics to turn into little plastics. 221 00:17:44,600 --> 00:17:50,440 So obviously, microplastics are plastics at one time that were large, that are now small. 222 00:17:50,440 --> 00:17:53,160 So there's one source which is river runoff. 223 00:17:53,160 --> 00:17:57,600 The other source is people throw stuff into the ocean. Plastics and it degrades. 224 00:17:57,600 --> 00:18:01,920 It degrades as a result of UV radiation. And of course, it's constantly being washed by the ocean. 225 00:18:01,920 --> 00:18:05,480 So the ocean is basically it's, it's salty. 226 00:18:05,480 --> 00:18:07,440 So, and it's water. 227 00:18:07,440 --> 00:18:09,920 So it's, it's a very good asset, actually. 228 00:18:09,920 --> 00:18:13,960 It's very it's very good bleach, which is why wood gets bleach, which is, you know, 229 00:18:13,960 --> 00:18:16,480 you throw something in the, in salt water and ends up getting bleach. 230 00:18:16,480 --> 00:18:20,960 So there's the fact that the, the, whatever you put into the ocean is, is attacked chemically. 231 00:18:20,960 --> 00:18:26,640 And then and then it's, it's a, it's attacked, radiological by UV radiation. 232 00:18:26,640 --> 00:18:32,600 So the source of the source of microplastic that comes in the ocean beyond river runoff is from ships, 233 00:18:32,600 --> 00:18:37,840 ships at sea or, or industrialization where people are throwing big chunks of plastic into the ocean. 234 00:18:37,840 --> 00:18:49,400 And it's a massive problem because at any one time there's 60,000 container ships at sea, 60,000, and they're concentrated on the, 235 00:18:49,440 --> 00:18:55,440 on the on the shipping routes, the ship, they're not spread out over the oceans equally, they're spread out over the shipping routes. 236 00:18:55,560 --> 00:19:00,480 So on the shipping routes or shipping lanes, there's at least 60,000 container ships. There's the cruise ships. 237 00:19:00,480 --> 00:19:01,320 Then there's everything, 238 00:19:01,320 --> 00:19:06,960 and there's all the fishermen who are fishing, not necessarily in the shipping routes, but in their own specific areas. 239 00:19:06,960 --> 00:19:11,560 So and the places in those places that are shipping routes or people are fishing, 240 00:19:11,560 --> 00:19:17,800 there's large ships throwing over large chunks of plastic and there's there's certainly isn't. 241 00:19:17,800 --> 00:19:22,320 There's international law about what you shouldn't, but you shouldn't, should not throw over the side. 242 00:19:22,320 --> 00:19:26,080 But there's virtually no there's regulation, but there's no enforcement. 243 00:19:26,080 --> 00:19:30,120 So of course, the tendency is for these ships to throw stuff over the side. 244 00:19:30,120 --> 00:19:34,760 And the amount of stuff that gets thrown over the side of ships would would shock you. 245 00:19:34,760 --> 00:19:37,680 There's places like, for example, up in Haida Gwaii. 246 00:19:37,680 --> 00:19:43,840 I'm not sure if you know where that is, but it's a World Heritage Site that Unesco World Heritage Site off the coast of British Columbia, 247 00:19:44,440 --> 00:19:47,040 and there's no industrialization there at all. 248 00:19:47,040 --> 00:19:51,800 It's all been turned off, and the only place that it ends up there is plastic that washes up on the beaches 249 00:19:51,800 --> 00:19:54,080 between is exposed to the North Pacific. 250 00:19:54,080 --> 00:20:00,000 So, as a volunteer, we would go there or I would go there whenever I was in Haida Gwaii, and we would pick plastics up 251 00:20:00,000 --> 00:20:05,040 off the beach as, as part of a Canadian government. Paid for initiative. 252 00:20:05,040 --> 00:20:13,320 And every year we could take we could take anywhere from 2000 to 4000 pounds of plastic off the beach in this one little tiny island group. 253 00:20:13,640 --> 00:20:19,920 And it's all it's giant jugs of what used to be oil people, fishermen changing oil at sea. 254 00:20:19,920 --> 00:20:25,680 There's there's fish crates. There's there's there's net that goes on for miles and there's tons of it. 255 00:20:25,680 --> 00:20:30,480 There's absolutely tons of it. And if it doesn't end up on the beach, it just continually circulating around the world. 256 00:20:30,480 --> 00:20:36,960 And, and, you know, the, the oceanic gyres like the Gulf Stream or the curiosity or the or the goolies or the South Pole, 257 00:20:37,320 --> 00:20:40,480 whatever, there's all these, these currents, and they just sit there and, 258 00:20:40,480 --> 00:20:47,640 you know, rotate around the world's oceans and they turn big plastics through sunlight and chemical reaction in the ocean into little plastic. 259 00:20:48,160 --> 00:20:54,120 So there's these two sources, runoff and then big plastics turning into little plastics by, by people throwing things off ships. 260 00:20:54,120 --> 00:20:56,040 And it's a problem. 261 00:20:56,040 --> 00:21:03,760 It's it's tons and tons and tons, thousands and thousands and thousands of metric tons of plastic being tossed off ships every year. 262 00:21:04,200 --> 00:21:11,200 What's your what's your take on the this initiative or this is a company, ocean cleanup because, 263 00:21:11,400 --> 00:21:18,800 some, some even in the scientific circles are, criticizing them, some other people thinking this is the best thing ever. 264 00:21:19,400 --> 00:21:24,480 What's your take on ocean cleanup? Well, I think the balance is somewhere in between the two. 265 00:21:24,480 --> 00:21:31,240 I think the the the this notion that there's a giant sea of, of plastic floating in the ocean the size of Texas is a fallacy. 266 00:21:31,240 --> 00:21:32,360 It doesn't exist. 267 00:21:32,360 --> 00:21:38,360 So if you if you if you create a problem, if you create a solution to fix up the giant, you know, floating island of plastic, 268 00:21:38,360 --> 00:21:42,640 then the problem doesn't exist. I'm not exactly sure what you're fixing. 269 00:21:42,640 --> 00:21:51,280 So, so, but, but, but the idea that there has to be some way for us to, Well, I hate to use the word vacuum because that 270 00:21:51,320 --> 00:21:57,280 that would then imply that there's, there's a concentration of it, but there has to be, some way for us to deal with the plastics. 271 00:21:57,280 --> 00:21:58,680 That's that's, 272 00:21:59,840 --> 00:22:01,200 that gets tossed over the side. 273 00:22:01,200 --> 00:22:09,120 And, and sadly, even though there's a tremendous, there's, there's, there's thousands of metric tons of plastic being tossed over the side. 274 00:22:09,640 --> 00:22:14,680 The oceans are very, very, very large, large beyond imagining. 275 00:22:14,680 --> 00:22:23,520 So even if you only see, let's say that you see, you know, one chunk of plastic every half a square mile or half a square mile, 276 00:22:23,520 --> 00:22:32,000 if you imagine, you know, you're sitting in a place that's that's 500km or 500m by 500m or, well, half a mile. 277 00:22:32,000 --> 00:22:36,560 Yeah. It sorry, 1.6 or say 800m. Right. 278 00:22:36,560 --> 00:22:40,680 And there's one piece of plastic in this 800m by 800m square. 279 00:22:40,680 --> 00:22:43,320 That's you'd be it almost never see that. 280 00:22:43,320 --> 00:22:46,560 But the ocean is gazillions. Well, that's an exaggeration. 281 00:22:46,560 --> 00:22:50,520 But you can imagine the ocean is is way larger than, you know, one chunk. 282 00:22:50,520 --> 00:22:53,720 That's that's it's millions and millions of square miles. 283 00:22:53,720 --> 00:22:59,720 So there's one piece of plastic in an 800 meter square ends up being a mountain of plastic. 284 00:22:59,720 --> 00:23:05,120 So the problem the problem is that how do you actually, you know, use ocean cleanup to go around and find all those, those pieces. 285 00:23:05,120 --> 00:23:08,400 It's pretty hard. I think that's I think that's that's part of the problem. 286 00:23:08,400 --> 00:23:13,880 I think the problem I think the solution, well, we don't know everything that there is to know about microplate six. 287 00:23:13,880 --> 00:23:20,920 There's you know, I've heard there's some other research that says that would say that though, the maybe the problem is as bad as it it is 288 00:23:21,480 --> 00:23:23,840 or we think it is. I'm not sure I'm convinced by that. At all. 289 00:23:23,840 --> 00:23:30,880 But I think I think the future is, is getting up, you know, using some sort of material that's plastic esque 290 00:23:31,320 --> 00:23:37,520 that doesn't that that degrades or becomes completely soluble in ways that, that don't harm the environment. 291 00:23:37,840 --> 00:23:39,640 I mean, that's that's a big ask. 292 00:23:39,640 --> 00:23:43,480 I wouldn't know where to start with that problem, but, it's way easier to 293 00:23:43,480 --> 00:23:46,840 I would think you're not going to convince people to stop throwing stuff over the side. 294 00:23:46,840 --> 00:23:50,800 I don't I think that's just going to be too hard, especially without advancement. 295 00:23:50,800 --> 00:23:53,360 Yeah, without I mean, that's that's the problem, right? Yeah. 296 00:23:53,360 --> 00:23:59,320 Every time we speak, every time we speak about the laws and this and that, any environmental 297 00:23:59,320 --> 00:24:05,640 like whether it's like Europe here locally, Ireland or in the US or in Canada is always the same thing. 298 00:24:05,640 --> 00:24:11,960 Like we have plenty of laws, we don't need more law, we just need the enforcement of existing law. 299 00:24:11,960 --> 00:24:16,240 And I guess that's the that's the problem that everyone comes in is like, oh, we need a new law. 300 00:24:16,240 --> 00:24:21,400 It's like, no, like it's not needed. You just need to enforce what's already there, right? 301 00:24:21,400 --> 00:24:23,280 Yeah, yeah. You need you need enforcement. 302 00:24:23,280 --> 00:24:27,840 And enforcement implies incentive, which is well, basically a disincentive. 303 00:24:27,840 --> 00:24:32,560 So you need a better incentive structure to actually get people to change behaviors. 304 00:24:32,560 --> 00:24:38,560 And, that the incentive and I think this is a behavior that because people have been throwing stuff away for, 305 00:24:38,920 --> 00:24:42,160 for tens of thousands of years, I live on a small island. 306 00:24:42,160 --> 00:24:46,320 First Nations people have been here for maybe two, 3000, maybe five, who knows? 307 00:24:46,320 --> 00:24:49,560 Probably more closer to 5000 years. 308 00:24:49,560 --> 00:24:53,720 And they've been throwing stuff away for, for for very long, for a very long time. 309 00:24:53,720 --> 00:24:56,600 Everywhere you look basically it's a midden amidships. 310 00:24:56,600 --> 00:25:00,440 Where I live, a midden is nothing more than a that then an old garbage heap. 311 00:25:00,440 --> 00:25:04,920 But what they threw away were, were seashells, you know, crushed seashells. 312 00:25:04,920 --> 00:25:08,960 So that doesn't hurt the environment at all. But it's still people throwing stuff away. 313 00:25:08,960 --> 00:25:13,200 So I think to to get people to change that behavior would be very hard. 314 00:25:13,200 --> 00:25:17,760 I think you need I think you need to incentivize that by getting them 315 00:25:17,760 --> 00:25:24,040 to incentivize that, by coming up with it with a plastic that's that's slightly different than what we're using right now. 316 00:25:24,040 --> 00:25:28,960 We don't need to have I don't need to have a plastic bottle that lasts, you know, for 200 years. 317 00:25:28,960 --> 00:25:32,080 I need a plastic bottle that lasts for two hours. Right. 318 00:25:32,080 --> 00:25:35,840 I'm going to drink it and then and then do something else with it. 319 00:25:35,840 --> 00:25:43,200 So. And I have the you know, speaking about sailing is the same problem because we people started making, fiberglass sailboats 320 00:25:43,560 --> 00:25:46,400 with no idea how long a fiberglass sailboat would last. 321 00:25:46,400 --> 00:25:52,200 And it turns out that a fiberglass sailboat, the hull of it is going to last for 300 years, of course, 322 00:25:52,200 --> 00:25:57,600 but the rest of it is no longer functioning because everything else is, you know, the the hull remains, but everything else is gone. 323 00:25:57,600 --> 00:25:58,600 But what do you do with it? 324 00:25:58,600 --> 00:26:04,600 What do you do with these fiberglass hulls built in the 60s, late 60s and early 70s that nobody wants anymore 325 00:26:04,800 --> 00:26:09,680 and are just now floating and clogging up, you know, harbors and anchorages everywhere, 326 00:26:09,680 --> 00:26:14,920 and they're taking them when they can, turning them into smaller bits of plastic and putting them into a landfill. 327 00:26:14,920 --> 00:26:15,760 But it's a problem. 328 00:26:15,760 --> 00:26:20,000 And no one building sailboats, you know, 50, 60, 70 years ago was thinking that 329 00:26:20,000 --> 00:26:25,640 that the boat that they built, the only way to get rid of it is to turn it into smaller chunks of sailboat and put them in a landfill. 330 00:26:25,640 --> 00:26:33,040 So we, you know, so we need, we need, we need to deal with, with the fact that plastics are basically these forever 331 00:26:33,600 --> 00:26:35,120 and not just forever chemicals. 332 00:26:35,120 --> 00:26:41,640 They're forever bits, you know, big things turning into smaller things so that that that's to me that's 333 00:26:41,800 --> 00:26:47,920 I it's a problem that's I don't have any chemical, engineering, expertise at all. 334 00:26:47,920 --> 00:26:49,680 But we're going to have to fix that problem. 335 00:26:49,680 --> 00:26:50,960 We're going to have to fix it really quick 336 00:26:50,960 --> 00:26:56,960 because as the third World, I hate to use the world third world, but as other countries industrialize and become, 337 00:26:56,960 --> 00:27:03,360 become more like us in the, in, in, in terms of, you know, how we, how we consume things in the West, the problem is going to explode. 338 00:27:04,080 --> 00:27:09,160 It's bad enough as it is now, but it's going to explode. That's a that's a huge problem. That's a huge problem. Right? 339 00:27:09,160 --> 00:27:13,360 And we're not going to get into this, but I, you know, you know, like 340 00:27:13,360 --> 00:27:19,400 then because then those people who are rightfully so say, yeah, oh, you already done all that and now you're telling us we can. 341 00:27:19,440 --> 00:27:20,280 Yeah. Exactly. 342 00:27:20,280 --> 00:27:25,480 Yeah. So like this is like material for another for another podcast. 343 00:27:25,480 --> 00:27:29,360 But I just on the plastic, I just want to stay on the plastic for a second because here 344 00:27:29,360 --> 00:27:34,880 it is, is very interesting and something that I hear a lot. And surely our listeners will be interested. 345 00:27:34,880 --> 00:27:39,160 Is that something that you can confirm that the majority 346 00:27:39,160 --> 00:27:45,480 of the plastic out there in the sea are actually fishing gear, like a ghost nets or some abandoned fishing gear? 347 00:27:45,520 --> 00:27:52,200 Well, I wouldn't say the majority of it, but I would say certainly a very, very large piece of it, because nets are, you know, nets. 348 00:27:52,320 --> 00:27:53,400 What do you do with that? 349 00:27:53,400 --> 00:27:58,320 What do you do with, you know, with, with, with with a gill net that gets destroyed when a whale gets in it or whatever 350 00:27:58,320 --> 00:28:04,400 the case might be, it's way easier to cut it off and and let it go away than it is to fix it. 351 00:28:05,200 --> 00:28:10,640 And and of course, the financial incentive to fixing it is very, very low because firstly, it's expensive. 352 00:28:10,640 --> 00:28:13,280 It would take forever and then the boat isn't fishing. 353 00:28:13,280 --> 00:28:18,360 So the incentive to just to get to use something new right off the bat 354 00:28:18,360 --> 00:28:24,360 is, is out of this world for those countries and those people in those companies that are, that are fishing 355 00:28:24,360 --> 00:28:30,960 where whether a boat at sea is very, very expensive to run it, it costs an enormous amount of money. 356 00:28:30,960 --> 00:28:33,680 And of course, these boats aren't going to be out there unless they're making money. 357 00:28:33,680 --> 00:28:40,440 So the incentive to to just to not repair anything, but just to fix it, just to get a part replace it is really, really 358 00:28:40,760 --> 00:28:42,280 the incentive for that is really strong. 359 00:28:42,280 --> 00:28:43,840 Like think of your own car. 360 00:28:43,840 --> 00:28:48,960 No one fixes a car anymore. They replace parts so what do you do with the old part? 361 00:28:48,960 --> 00:28:53,520 You just throw it away like it back in the day, like when my grandfather was at sea. 362 00:28:53,520 --> 00:28:56,880 He was a ship's engineer. They made everything. They had a machine shop on board. 363 00:28:56,880 --> 00:29:00,760 When something broke, they made a new one. They made it from a chunk of metal. 364 00:29:00,760 --> 00:29:07,360 And if they couldn't fix the new one by replacing bearings or re boring, whatever the case may be, they just made one on the spot. 365 00:29:07,360 --> 00:29:12,960 Well we don't, we don't fix things like that anymore. Cars are basically throwaway things for us. 366 00:29:12,960 --> 00:29:18,080 They get recycled, which means they're turned into, you know, they're flattened somewhere and they end up. 367 00:29:18,080 --> 00:29:22,560 I would think of tires like, we have a huge problem because we just throw stuff away. 368 00:29:22,560 --> 00:29:24,760 And of course that happens at sea. 369 00:29:24,760 --> 00:29:29,160 And it's they just they just throw everything away and replace it. 370 00:29:29,160 --> 00:29:35,040 The problem you're touching on this, it's huge because like what I heard, like it's maybe not totally related to 371 00:29:35,040 --> 00:29:36,160 the subject of the podcast. 372 00:29:36,160 --> 00:29:42,360 What I heard is like, some had an idea that they can reuse, recycle the old, tires. 373 00:29:42,720 --> 00:29:46,440 And that's what they, making this, this ground in the kindergarten. 374 00:29:46,440 --> 00:29:52,680 So it's kind of like a soft and and then kids when they throw and then it turns out like, oh, there's a small problem, 375 00:29:52,680 --> 00:29:59,240 but there is like a good, good peer reviewed size that that might cause cancer in kids because it's like, 376 00:29:59,240 --> 00:30:04,960 like it's it's just like it's like we creating the mass mass of this toxic waste. It's like, where are you? 377 00:30:04,960 --> 00:30:08,880 Where do you go from there? It's it's just, it's just sort of desperate. 378 00:30:08,880 --> 00:30:13,200 But tell me when you were out of the sea, have you noticed it a lot? 379 00:30:13,200 --> 00:30:15,720 Because you said, like, oh, you would notice this, this plastic. 380 00:30:15,720 --> 00:30:20,760 But I remember a couple of years ago, I was, watching, Volvo Ocean Race. 381 00:30:20,760 --> 00:30:27,560 And they had also this program, kind of like a raising awareness of people because obviously there's like a lot of eyes on the on the event. 382 00:30:28,080 --> 00:30:31,960 And I remember this footage, people, you know, they're they're showing from the bowl. 383 00:30:31,960 --> 00:30:36,320 They were like literally sailing through plastic in some places. 384 00:30:36,320 --> 00:30:40,400 So where was that like that most of the time for you 385 00:30:40,400 --> 00:30:46,480 or was it like that in certain areas like what's your what's your assessment based on being out there? 386 00:30:46,480 --> 00:30:49,320 I never saw any of that ever. 387 00:30:49,320 --> 00:30:54,840 And I sailed through those areas where those were where they're supposed where it was, where that was alleged to be. 388 00:30:54,840 --> 00:30:57,560 But the Volvo Ocean Race, it's a stage race. 389 00:30:57,560 --> 00:31:02,640 So they go they go in stages from one, from one basically continent and place to another. 390 00:31:02,640 --> 00:31:08,600 So they're they're approaching very large cities like Shanghai, Rio de Janeiro, Melbourne. 391 00:31:08,600 --> 00:31:14,760 So as you approach those places where there's a lot of ships and like a lot of commercial ship traffic, a lot of fishing traffic, 392 00:31:14,760 --> 00:31:15,720 because they're there. 393 00:31:15,720 --> 00:31:20,880 All the fish are concentrated on coastlines along the continental shelf, primarily. 394 00:31:20,880 --> 00:31:26,320 Well, I shouldn't say that primarily, but certainly the fishing is, is is more most productive, 395 00:31:26,320 --> 00:31:29,800 anywhere on the continental shelf in the continental break. 396 00:31:29,800 --> 00:31:34,880 But I was never I was not I was not near anywhere. Those places I crossed shipping lanes. 397 00:31:34,880 --> 00:31:39,040 And when I crossed shipping lanes, then there would be an, an increase in microplastics. 398 00:31:39,040 --> 00:31:41,320 I could actually see some and start counting. 399 00:31:41,320 --> 00:31:49,600 But it was always where there was, where there like, for example, there one of the ships I saw was, was a fishing was a fishing boat. 400 00:31:49,600 --> 00:31:53,160 They were fishing for black marlin out of Spain, actually fishing out of Mexico 401 00:31:54,240 --> 00:31:56,280 because they had out fish, the Atlantic Ocean. 402 00:31:56,280 --> 00:31:57,520 And we're now in the Pacific. 403 00:31:57,520 --> 00:32:01,920 They actually have to go that far to, you know, to to continue to catch, to make it profitable, to catch black marlin. 404 00:32:01,920 --> 00:32:04,080 Don't leave it, don't even start started. 405 00:32:04,080 --> 00:32:11,000 So yeah, I, so, so as I, I see the I see this boats fishing properly. 406 00:32:11,000 --> 00:32:13,280 I call them on the radio because I like some of that talk to. 407 00:32:13,280 --> 00:32:18,760 I talk to them and sure enough, sure enough I come across a piece of plastic. 408 00:32:18,760 --> 00:32:20,640 It I forget what, what exactly it was. 409 00:32:20,640 --> 00:32:27,000 It was a water bottle or something, but it was something thrown overboard by that ship because I was in that immediate vicinity. 410 00:32:27,360 --> 00:32:31,400 So that's one ship in one place. So imagine a bunch of ships are going into the same place. 411 00:32:31,400 --> 00:32:36,320 You find that stuff, it's like it's like sailing in to Ketchikan in Alaska. 412 00:32:36,320 --> 00:32:38,680 Ketchikan is where you have to clear the customs. 413 00:32:38,680 --> 00:32:44,720 In Alaska, if you go from Canada going north, and at any one time during the summer, there'll be this will be 414 00:32:44,720 --> 00:32:50,800 I shouldn't say that, but there can be up to five of these 1000 or 1200 foot cruise ships in this little tiny harbor, 415 00:32:50,800 --> 00:32:53,160 and they have to go in and come out in the same place. 416 00:32:53,160 --> 00:32:56,520 And there's laws, of course, but what you can't or cannot do in coastal waters. 417 00:32:56,520 --> 00:32:59,640 But as soon as you get three miles away from those places, 418 00:32:59,640 --> 00:33:05,360 then suddenly the rules change and you can tell that you're suddenly in that place where the rules are changing. 419 00:33:05,360 --> 00:33:08,880 So the if for the Volvo Ocean Race, they would have been going through areas 420 00:33:08,880 --> 00:33:13,240 where there would be a concentration of ships and a concentration of people, so they would see something like that. 421 00:33:13,240 --> 00:33:17,360 But I never saw something like that just because I wasn't in those places. 422 00:33:17,360 --> 00:33:23,960 But it I mean, I know that I follow the race, I know that I think I have a think I remember as well the footage 423 00:33:23,960 --> 00:33:28,560 because it was very interesting to me, not just the sailing, but what they were doing in terms of science. 424 00:33:28,560 --> 00:33:31,600 And that's a really good example of citizen science. Like anyone can do that. 425 00:33:31,600 --> 00:33:33,840 Anyone that's passionate about something, 426 00:33:33,840 --> 00:33:39,840 there's there's a scientist who spent their lifetime who has spent his or her life studying that thing that you're interested in as well. 427 00:33:40,000 --> 00:33:41,760 But they've done it professionally. 428 00:33:41,760 --> 00:33:44,920 And so they the example I use are is surfers are surfers everywhere. 429 00:33:44,920 --> 00:33:52,160 People love to surf all around the world, and scientists are very interested in how materials are transported down coastlines. 430 00:33:52,440 --> 00:33:54,360 It's called literal transport. 431 00:33:54,360 --> 00:33:59,840 And, it has a it has a very it has a huge impact on how industrial waste comes out of a river 432 00:33:59,840 --> 00:34:05,760 and then ends up being, you know, spread along the coast because there's there's physical processes that govern that. 433 00:34:05,760 --> 00:34:08,120 And, and people spend a lifetime studying it. 434 00:34:08,120 --> 00:34:14,120 But one of the, one of the things littoral transport is affected primarily by waves and beyond currents. 435 00:34:14,120 --> 00:34:18,520 Currents are generally offshore, but by waves hitting the beach, which is what surfers love. 436 00:34:18,520 --> 00:34:23,520 Surfers are very good at saying, you know how big the waves are, and they're there almost all the time 437 00:34:23,520 --> 00:34:25,520 and there's a scientist or there's, there's, there's 438 00:34:25,520 --> 00:34:31,680 there's probably a thousand scientists, at least in the world who've spent there, spent their whole career studying literal transport. 439 00:34:32,400 --> 00:34:39,240 So if you go surfing, you can you can say, well, the waves today were 6ft or 8ft or, you know, breaking 100m offshore or 200m offshore. 440 00:34:39,720 --> 00:34:44,400 That's incredible. That's incredibly valuable to someone who's studying lateral transport. 441 00:34:44,400 --> 00:34:47,880 So there's a way to combine something you're passionate about. And surfers tend to be very passionate. 442 00:34:47,880 --> 00:34:53,400 They go out and you know, the weather's horrible. They're out there all the time and they're at all times of the year. 443 00:34:53,400 --> 00:34:59,560 And then that's they're just literally looking at the data that the scientists are just craving and absolutely need. 444 00:35:00,120 --> 00:35:00,960 So there's two ways. 445 00:35:00,960 --> 00:35:04,320 There's always a way to combine things that you're that you're crazy, 446 00:35:04,320 --> 00:35:08,400 that you're crazy in love with with with a scientist who's crazy in love with the same sort of thing. 447 00:35:08,400 --> 00:35:14,440 And, and listen, we're going to come back to the citizen science because, you know, we talk about this as well. 448 00:35:14,440 --> 00:35:20,440 Like, for example, anglers and even like in Ireland like, you know, Fisheries Ireland, they have it like an app, 449 00:35:21,480 --> 00:35:26,280 like you said, anglers that are out there, there, you know, rain or good in bad weather. 450 00:35:26,280 --> 00:35:31,800 And they just data that they gather or tagging fish and so on. 451 00:35:31,800 --> 00:35:33,960 It's just it's just incredible. 452 00:35:33,960 --> 00:35:37,320 Listen, but I just want to switch gears for a second. 453 00:35:37,320 --> 00:35:42,200 To something that is dear to my heart and which is a policymaking. 454 00:35:42,200 --> 00:35:47,600 And you spoke about the policymaking, the impacts of policymaking, but of poor policymaking. 455 00:35:47,600 --> 00:35:53,880 And I, I am, you know, question as I'm asking to to various guests and I'm pondering myself, 456 00:35:54,320 --> 00:36:04,120 you know, how how to connect or how to make the policymakers making this making, you know, quote unquote good decision. 457 00:36:04,120 --> 00:36:07,520 Right. And this is already loaded because like, what is good decision? 458 00:36:07,520 --> 00:36:13,600 And this is like a story that I shared on on one of the episodes when like one of the scientific conferences, I was sitting, 459 00:36:14,000 --> 00:36:18,560 next to a policymaker person who is who is a policymaker. 460 00:36:18,560 --> 00:36:22,840 And, you know, after a few glasses of wine, the, you know, conversations open up. 461 00:36:22,840 --> 00:36:24,600 And I was just like, My God, 462 00:36:25,600 --> 00:36:25,960 right. 463 00:36:25,960 --> 00:36:28,240 And and that was on the scientific conference. 464 00:36:28,240 --> 00:36:34,080 So, so that person was there to listen to scientists, what they're saying. Right. 465 00:36:34,080 --> 00:36:39,200 But but the takeaway was like essentially like all those scientists, they don't know how to make it odds. It's just. Right. 466 00:36:39,200 --> 00:36:45,680 So so you can, you know, again, it's a very open question that no, not even say it's a question. 467 00:36:45,680 --> 00:36:47,120 It's a discussion point. 468 00:36:47,120 --> 00:36:54,120 But I am curious from your experience, you know, like, what are the best ways to talk to policymakers 469 00:36:54,480 --> 00:36:58,560 to incentivize them to, to make it right decisions? 470 00:36:58,560 --> 00:37:05,520 Or maybe it's not about policymakers, maybe it's about their, you know, their bosses, but because inside, you know, my take on this, 471 00:37:06,320 --> 00:37:09,960 and you may correct me if I'm wrong, is like the policymaker that they don't care about science. 472 00:37:09,960 --> 00:37:16,040 They they need to you they do the service to their boss, and their boss needs to be elected in four years. 473 00:37:16,240 --> 00:37:16,760 Yeah. 474 00:37:16,760 --> 00:37:23,000 And that's and just you there's it is impossible to make a good environmental policy 475 00:37:23,280 --> 00:37:27,440 because like you mentioned, environmental policy in a state of affairs that we have right now, 476 00:37:27,440 --> 00:37:33,760 usually not going to be popular and it's going to be it's going to be inconvenient. 477 00:37:33,760 --> 00:37:42,160 And no politician wants to do inconvenient things because they know the next four years they out how to how to even approach this problem. 478 00:37:42,360 --> 00:37:50,120 Well, I think that, you know, fundamentally there's I look at it very, very simply, there's two things that policy revolves around. 479 00:37:50,640 --> 00:37:55,880 One is something that sounds good and one is the other is something that does good. 480 00:37:55,880 --> 00:37:58,680 And they're wildly they can be wildly different things. 481 00:37:58,680 --> 00:38:04,640 And it turns out that politicians are very good at in general, they they like to sound good because that's easy. 482 00:38:04,640 --> 00:38:10,000 It's the easy path, but they very rarely want to do good, because doing good is hard. 483 00:38:10,000 --> 00:38:17,240 It's hard to, to, to, to disincentivize, you know, behaviors that are hardwired or disincentivize behaviors that are, 484 00:38:17,520 --> 00:38:19,200 that are financially rewarding. 485 00:38:19,200 --> 00:38:23,280 So you have to like I it's it's my responsibility. 486 00:38:23,280 --> 00:38:29,280 I view it as my responsibility to my responsibility to engage with good policy 487 00:38:29,440 --> 00:38:35,520 and then, not just engage with it, but amplify those policies in any way that I can, which is to bring awareness, 488 00:38:35,880 --> 00:38:41,880 bring people's awareness to things that that just don't, that aren't doing good at all. 489 00:38:42,440 --> 00:38:50,800 And they're all around us like we we hear politicians or policymakers sounding good all the time, and we don't. 490 00:38:50,800 --> 00:38:55,440 It's not rocket science to figure out if that's actually doing good, sounding good and doing good 491 00:38:55,440 --> 00:39:01,680 like we're if if we weren't able to differentiate as a species between those two things, there would be no humans working on the planet 492 00:39:02,240 --> 00:39:08,640 because we if you're embedded in nature, are truly embedded in nature, then you nature is unforgiving. 493 00:39:09,080 --> 00:39:12,960 It will not. It doesn't tolerate in any way, shape or form bad policy. 494 00:39:12,960 --> 00:39:20,000 I cannot decide that I'm going to go sleep naked in the forest, you know, for a week, because in two days I'll be dead, right? 495 00:39:20,000 --> 00:39:21,560 That's just bad policy. 496 00:39:21,560 --> 00:39:26,240 It sounds good. I'm meant to go out and hug trees for the next, you know, seven days straight, naked. 497 00:39:26,240 --> 00:39:29,040 But it doesn't do any good, doesn't do me any good. 498 00:39:29,040 --> 00:39:32,040 And it certainly doesn't do the tree any good and bad policy. 499 00:39:32,040 --> 00:39:41,040 You can also engage with with bad policy badly, which would be, for example, throwing paint on a Van Gogh painting that it's you're 500 00:39:41,920 --> 00:39:47,480 you're engaging with a bad policy in a way that doesn't make any sense, because you're not you're not bringing awareness to the policy. 501 00:39:47,480 --> 00:39:52,800 You're just bringing awareness to yourself. So I don't like that kind of activism because it doesn't do any good. 502 00:39:52,800 --> 00:39:54,120 It only turns people away. 503 00:39:55,280 --> 00:39:57,760 It certainly turns people away who might be sitting on the fence. 504 00:39:57,760 --> 00:40:02,600 And the vast majority of people are sitting on the fence because they don't exactly know. 505 00:40:02,600 --> 00:40:05,840 Or maybe they're I shouldn't say they don't know. I think that's unfair. 506 00:40:05,840 --> 00:40:08,080 I think that they just they just they haven't been 507 00:40:08,080 --> 00:40:14,080 they haven't been given enough information to say, okay, this is sounding good, but it's not doing any good. 508 00:40:14,280 --> 00:40:18,880 So when you when you find and you can't, you can't solve every problem. 509 00:40:18,880 --> 00:40:21,720 But you can you can be engaged in those things that you're passionate about. 510 00:40:21,720 --> 00:40:26,360 So I, I'm, I'm engaged. I love I love the water. 511 00:40:26,360 --> 00:40:30,120 I've been I mean that's been my formal 512 00:40:30,120 --> 00:40:36,560 that's, that's, that's consumed me formally and informally because I'm and I'm an oceanographer by training. 513 00:40:37,360 --> 00:40:41,400 I, you know, paddle a canoe sailboat. I'm always on the water doing something. 514 00:40:41,400 --> 00:40:47,880 So I'm, I'm constantly looking at policy that and try to engage with with policy that does good. 515 00:40:47,880 --> 00:40:56,280 So as an example, this summer I'm supposed to be paddling through, a lot of Canadian wilderness with, First Nations person 516 00:40:56,280 --> 00:41:05,600 and an, an actual PhD hydrologist to study the impacts of dams on, on, on downstream ecosystems. 517 00:41:05,840 --> 00:41:10,120 So this first Nations guy been living he's been living there for generations. 518 00:41:10,120 --> 00:41:15,720 And there's generational knowledge that he knows because he lives off the land and relies on the water 519 00:41:15,720 --> 00:41:19,640 for not just transport, but for food and for everything else you can imagine. 520 00:41:19,640 --> 00:41:25,360 And there's a hydrologist who actually knows, you know, something or two about dams and how they work and what they're doing, 521 00:41:25,360 --> 00:41:27,120 what they're trying to achieve. 522 00:41:27,120 --> 00:41:34,120 So they're paddling a great big chunk of the Canadian wilderness, taking data, you know, making observational data as citizen scientists, 523 00:41:34,120 --> 00:41:41,280 one when one formally no one formally trained as a scientist or when citizen scientist to try to get an understanding of what really 524 00:41:41,560 --> 00:41:43,240 of what the policy is 525 00:41:43,240 --> 00:41:50,240 and the impacts of that policy by Canadian government on, you know, closing the dam and opening the dams to, to generate electricity. 526 00:41:51,000 --> 00:41:58,640 So there's good and bad policy about about about how that process, about how they do that because they have to generate electricity. 527 00:41:58,640 --> 00:42:05,560 Do they let and there's, there's, if you do it poorly, then you're basically just, you know, flooding, 528 00:42:06,000 --> 00:42:10,400 everything downstream, you know, three times or twice a day and destroying everything. 529 00:42:10,400 --> 00:42:12,880 Or you can come up with a more measured approach. 530 00:42:12,880 --> 00:42:16,480 So they're engaging in something that does good 531 00:42:17,760 --> 00:42:21,800 around a policy that doesn't sound good. 532 00:42:21,800 --> 00:42:29,240 So it's a perfect example of of what you can do, and in a very focused way, because you can't be involved in everything. 533 00:42:29,240 --> 00:42:33,120 It's just there's just too much. But there will be something that you're passionate about. 534 00:42:33,120 --> 00:42:39,960 There will be policy around that, like fishing, for example, and you and or surfing or whatever the case might be. 535 00:42:39,960 --> 00:42:43,320 And you can find out what the policies are surrounding that, that are, 536 00:42:43,320 --> 00:42:49,960 that are affecting you personally because it's something that you're engaged in and then choose to engage, with those policies. 537 00:42:49,960 --> 00:42:52,560 And if it's bad policy, all you can do is make your voice heard. 538 00:42:52,560 --> 00:42:56,800 You can make you can make your voice heard like you're doing on a podcast here, like we're doing you can 539 00:42:56,800 --> 00:43:02,720 you can write to people who are voting and say, oh, how unhappy you are, because that's still incredibly powerful. 540 00:43:02,720 --> 00:43:08,560 There's, there's there's nothing more powerful than a politician getting a letter from a, from a constituent 541 00:43:08,560 --> 00:43:10,960 who excoriates them for being a jackass 542 00:43:12,080 --> 00:43:14,200 and calls them out like, you voted for this. 543 00:43:14,200 --> 00:43:15,080 It's ridiculous. 544 00:43:15,080 --> 00:43:17,960 Why did you do that? Like, why are you selling out? 545 00:43:17,960 --> 00:43:21,200 And I mean it, that's way more effective. 546 00:43:21,200 --> 00:43:28,160 And you can don't just send a letter to that one person, you send it to everybody on that list of, you know, the person up and down the chain, 547 00:43:28,440 --> 00:43:32,040 and then people become accountable for what comes out of their mouth and what they're doing. 548 00:43:32,040 --> 00:43:39,480 And that's the only way that I know that I know of to, to engage, you know, formally as a citizen scientists 549 00:43:39,480 --> 00:43:46,040 and then formally as a constituent and then inform me, like, like we're doing here around policies that that, that you disagree with. 550 00:43:46,280 --> 00:43:50,040 That's a good point to engage in a positive way. 551 00:43:50,040 --> 00:43:54,600 And, and we said it many times on the, on this podcast, like write to your politicians, 552 00:43:54,600 --> 00:44:00,880 you know, you send a letter or send an email like just do something but just, you know, like, excuse me. 553 00:44:00,880 --> 00:44:01,320 My word. 554 00:44:01,320 --> 00:44:03,720 Bitching on social media doesn't cut it. 555 00:44:03,720 --> 00:44:08,200 It's it's it's it's you used to be to take it one step further. 556 00:44:08,200 --> 00:44:12,280 But listen, I have a question for you. You're an entrepreneur as well. 557 00:44:12,280 --> 00:44:16,320 Lead brain, don't I, tell me, 558 00:44:17,840 --> 00:44:20,240 how do you navigate, 559 00:44:20,240 --> 00:44:29,080 the the the complex landscape between, you know, being under preneur and and doing business and using technology. 560 00:44:29,080 --> 00:44:35,040 And on the other hand, we all heard about, like, how the all those technologies are affecting their environment. 561 00:44:35,040 --> 00:44:42,240 And, you know, especially with, I know, massive data centers, there's a water park cooling the power for powering all that think 562 00:44:42,920 --> 00:44:45,360 tell me like what's your what's your take. 563 00:44:45,360 --> 00:44:51,840 Because, you know, it's a little bit counterintuitive if you're coming from this environmental angle. 564 00:44:51,840 --> 00:44:57,160 And, and here's you're you're doing like a business here, which is obviously like everybody needs to live and do their business. 565 00:44:57,160 --> 00:44:58,680 So that's a genuine question. 566 00:44:58,680 --> 00:45:06,240 How you navigate that landscape both in a, in a, you know, practical matters and also in your, in your mind. 567 00:45:06,480 --> 00:45:08,120 Well, I think, 568 00:45:09,360 --> 00:45:10,760 let me take one step backwards. 569 00:45:10,760 --> 00:45:16,760 And we're talking about AI, but it takes 5000l of water to make a pair of jeans. 570 00:45:17,520 --> 00:45:18,880 Think about that. 571 00:45:18,880 --> 00:45:20,600 I mean, in, in Canada we have some of that. 572 00:45:20,600 --> 00:45:24,400 We have the largest, probably the largest reserve of freshwater. 573 00:45:24,400 --> 00:45:29,120 But first, lots of First Nations people live in this country without without access to, 574 00:45:29,120 --> 00:45:31,800 to clean potable water, as you and I would have access to it. 575 00:45:31,800 --> 00:45:33,240 Sure, they can drink water out of the lake 576 00:45:33,240 --> 00:45:39,240 or the river, but most neither you nor I would generally, you know, go down to the lake and get a bucket of water. 577 00:45:39,360 --> 00:45:47,320 So this, this, this idea of, of, of extraordinary resource usage is, is all around us. 578 00:45:47,320 --> 00:45:54,320 It's not just in AI, it's literally in the pants that you wear, like 5000l of water to make a pair of jeans seems seems excessive. 579 00:45:54,320 --> 00:45:56,160 Not to mention the fact that ships 580 00:45:56,160 --> 00:46:02,600 are traveling around the world because a pair of jeans is assembled in one place, but all the bits and pieces come from everywhere else. 581 00:46:02,880 --> 00:46:07,720 And then it comes on on a giant ship fueled by some of the worst diesel fuel for steel. 582 00:46:07,720 --> 00:46:09,440 You know, fuel you can imagine. 583 00:46:09,440 --> 00:46:15,840 So I, I heard I heard that the some, some of the factories are not built in 584 00:46:15,840 --> 00:46:20,160 certain areas because water is too bad and that water is a drinking water. 585 00:46:20,160 --> 00:46:24,840 But the industrial factories and stuff need the better, better quality of the water. 586 00:46:24,840 --> 00:46:28,680 The other one was the to make like a, like a chips, the amount of like, 587 00:46:29,920 --> 00:46:36,320 thousands upon tens of thousands of cubic liters of water every second using those things. 588 00:46:36,320 --> 00:46:42,120 It's just madness. It's, it's it's crazy. Like it's crazy talk like the the cloud. 589 00:46:42,120 --> 00:46:42,680 The cloud. 590 00:46:42,680 --> 00:46:48,680 This is about a year and a half ago now, the cloud at that time, you used more electricity than Japan. 591 00:46:48,720 --> 00:46:53,320 So, so, so how do you square those kinds of things? 592 00:46:53,320 --> 00:47:00,640 We have enormous problems and large language models, speaking specifically of AI are able to solve very, very complex problems. 593 00:47:00,640 --> 00:47:05,120 So if you think of the think of a protein and think of think of the drugs. 594 00:47:05,120 --> 00:47:07,520 Drugs are very expensive to make there. 595 00:47:07,520 --> 00:47:14,280 And and it it involves an incredible expenditure of time, energy and money and time. 596 00:47:14,280 --> 00:47:18,560 Energy and money translates into enormous resource usage. 597 00:47:18,560 --> 00:47:21,360 Like I'm talking about electricity and heating and all those kinds of things. 598 00:47:21,360 --> 00:47:24,720 But but proteins are very complicated. 599 00:47:24,720 --> 00:47:31,560 And there's about a billion different ways, at least for, for a protein to, to wrap itself into a shape and it's basically a key. 600 00:47:31,800 --> 00:47:36,000 And a drug basically is a mat is, is is a synthetic. It's a synthetic. 601 00:47:36,000 --> 00:47:38,920 So think of the protein natural as a lock. 602 00:47:38,920 --> 00:47:43,600 And a drug basically is a key to the lock. So they have to match perfectly. 603 00:47:43,600 --> 00:47:49,480 And that's that's very simplistically, sort of how, how that works. 604 00:47:49,480 --> 00:47:56,400 But it's almost impossible for a human to come up with the billions and billions of combinations to that particular lock. 605 00:47:57,000 --> 00:47:58,920 I does it in an hour. 606 00:47:58,920 --> 00:48:05,520 So we will see advances in, in, in technologies that have to deal with chronic degenerative diseases 607 00:48:05,840 --> 00:48:13,080 like cancer, like Alzheimer's, that are drug related, that we would have taken basically decades, if not centuries to solve that. 608 00:48:13,080 --> 00:48:20,280 I can do, in, in, in an unbelievably short amount of time because it can just, you know, create all these, these, these combinations. 609 00:48:20,320 --> 00:48:24,120 It basically in a heartbeat. So there's tremendous upside. 610 00:48:24,120 --> 00:48:27,680 And if you look at, okay, you have to have a huge data center to read it. 611 00:48:27,680 --> 00:48:37,240 But imagine it takes you ten years of, of of a 500 people in a, in a, in a building that have to live, work, feed to do the whole thing. 612 00:48:37,440 --> 00:48:44,880 Think of the cost of that to, to to come up with one drug as opposed to an hour of AI doing it to come up with the combination. 613 00:48:44,880 --> 00:48:49,880 And I'm sort of just scrubbing off all the other bits and pieces that go into getting a drug into market, 614 00:48:49,880 --> 00:48:55,520 but just discovering what might work, you know, you think of them, think of the poor white mice you have to kill in the lab. 615 00:48:55,520 --> 00:48:56,640 Right. 616 00:48:56,640 --> 00:49:00,920 So there's that's the other side of the coin, right? There's this tremendous amount of energy we're using. 617 00:49:00,920 --> 00:49:05,320 But then if you spread that out over, say, 5 or 10 years, what it would take to make a drug, 618 00:49:05,320 --> 00:49:09,440 then suddenly the equation seems to be a little bit more balanced. 619 00:49:09,440 --> 00:49:13,480 So in terms of for me how I so that's one way I look at it. 620 00:49:13,480 --> 00:49:16,800 Basically resource usage across on, on a big scale. 621 00:49:16,800 --> 00:49:22,120 Because if I'm going to talk about how much it costs to run a data center, then I'm going to then okay, let's talk about 622 00:49:22,120 --> 00:49:29,040 let's talk about producing, you know, 500,000 pairs of jeans in a month, how much, you know, what kind of energy goes into that. 623 00:49:29,040 --> 00:49:31,680 But we wear jeans all the time and don't think anything of it. 624 00:49:31,680 --> 00:49:37,200 So I look at it from that's from firstly from that scale, but on a smaller scale as it pertains to me. 625 00:49:37,200 --> 00:49:41,400 My father was a small businessman. He and I grew up in a small town. 626 00:49:41,400 --> 00:49:43,320 Small businesses, really hard. 627 00:49:43,320 --> 00:49:46,080 Small business lies at the heart of basically innovation. 628 00:49:46,080 --> 00:49:50,160 It lies at the heart of people being employed. It lies at the heart of of every economy. 629 00:49:50,160 --> 00:49:54,120 Because without small business, like 90% of businesses, basically. 630 00:49:54,120 --> 00:49:57,600 Well, I shouldn't say 90%, but certainly the majority of business is small business 631 00:49:58,880 --> 00:50:00,600 and they struggle with basically the same thing. 632 00:50:00,600 --> 00:50:03,760 And what I have been able to do is relieve some of those problems, 633 00:50:03,760 --> 00:50:10,080 like for example, when when you buy something today, you go online and ask the question, you know, who should I give my money to? 634 00:50:10,840 --> 00:50:16,880 We used to go into, you know, the hardware store and ask a guy, you know, what kind of washing machine should I buy? 635 00:50:16,920 --> 00:50:18,480 But we don't do that anymore. 636 00:50:18,480 --> 00:50:20,080 That happens online, 637 00:50:20,080 --> 00:50:25,880 and it happens in the context of a small A because most most businesses, small business, it happens in the context of small business. 638 00:50:25,880 --> 00:50:32,400 So if you can if I can in some way, shape or form help those small business people or small business persons 639 00:50:33,000 --> 00:50:38,120 get in the conversation when their customers are saying, who do I buy from? Then I think I've done something good. 640 00:50:38,120 --> 00:50:44,160 So and I use and we can use AI to, to make sure that, the footprint of that business is large enough 641 00:50:44,160 --> 00:50:48,120 that they can be found online because it's a, it's a the playing field is not level. 642 00:50:48,120 --> 00:50:48,480 You don't 643 00:50:48,480 --> 00:50:50,640 you can be really, really good at what you do, but you could 644 00:50:50,640 --> 00:50:54,600 that doesn't mean that necessarily you're going to be found on YouTube where you're going to be found on Instagram 645 00:50:54,600 --> 00:50:59,840 or LinkedIn or Google or whatever search engine, you know, whatever search algorithm you have to be engaged with. 646 00:50:59,840 --> 00:51:06,840 So being good at being good at your job and actually being found online are two different things, but all your customers are online. 647 00:51:06,840 --> 00:51:11,200 So you've got to square those two things. And AI is a is a really, really good way to do it. 648 00:51:11,200 --> 00:51:14,680 You spoke with entrepreneurs. That was you're in there. Partner yourself. 649 00:51:14,680 --> 00:51:19,200 Like in your experience what is their most convinced? 650 00:51:19,200 --> 00:51:21,400 Like what is the way to convince 651 00:51:22,360 --> 00:51:23,760 decision makers in the 652 00:51:23,760 --> 00:51:29,760 businesses to make like environmentally conscious decisions? 653 00:51:30,080 --> 00:51:32,680 What is like, but you know, how to talk to them? 654 00:51:32,680 --> 00:51:37,720 Well, I think the most important thing is like every business person is concerned with culture. 655 00:51:37,720 --> 00:51:42,320 So if you have a culture in your business that's dysfunctional, the business itself is dysfunctional. 656 00:51:42,320 --> 00:51:45,680 And if the business is is dysfunctional, you never going to make it. 657 00:51:45,680 --> 00:51:50,680 So. In this day and age, you have to be a well, I shouldn't say in this day and age it's always been that way. 658 00:51:50,680 --> 00:51:54,480 If you want to attract really good people to come work with you, then you have to have a really 659 00:51:54,480 --> 00:51:57,800 there has to be a reason for them to come work with you beyond just paying, 660 00:51:57,800 --> 00:52:03,760 because people don't just respond to money, they respond to things that are well outside just getting paid. 661 00:52:03,760 --> 00:52:11,280 Because after after our basic needs are met basically, and all are primarily in the culture that we live in, all our needs are met. 662 00:52:11,320 --> 00:52:14,280 We live like kings, basically compared to the rest of the world. 663 00:52:14,280 --> 00:52:16,000 Certainly in a historical context. 664 00:52:16,000 --> 00:52:20,880 So it's hard to say that, you know, in general that our needs aren't, aren't being met. 665 00:52:20,880 --> 00:52:23,640 But beyond that, there's other things that humans respond to. 666 00:52:23,640 --> 00:52:29,760 Like, we have a people respond, to the to things, then of course, of course, 667 00:52:29,800 --> 00:52:35,800 that they're passionate about, but they respond to things that they are morally that they feel morally aligned with. 668 00:52:36,360 --> 00:52:42,240 So they respond to, you know, things that are pointed up as appointed as opposed to pointed down. 669 00:52:42,240 --> 00:52:46,440 So if your culture in your business is pointed up, you're doing good things in the community, you're doing 670 00:52:46,440 --> 00:52:52,840 good things when it comes to, stewardship in the environment, it means that you're engaged in volunteering and those kinds of things. 671 00:52:52,840 --> 00:52:56,440 And that draws people beyond, beyond just the fact that you're paying them. 672 00:52:56,440 --> 00:53:02,000 So for entrepreneurs, I would say focus on the culture in your business and make sure that the culture that you're that 673 00:53:02,000 --> 00:53:06,280 you're what you're actually cultivating is good stewardship for the environment. 674 00:53:06,280 --> 00:53:12,280 And, you know, even if you're even if you're doing something like making jeans, that doesn't mean you can't be planting trees. 675 00:53:12,520 --> 00:53:18,640 That doesn't mean that you can't be, that you can't be engaged in providing clean water to to those to those communities 676 00:53:18,640 --> 00:53:20,680 that don't necessarily have access to it. 677 00:53:20,680 --> 00:53:31,520 That doesn't it doesn't mean that you can't be out in in your community ensuring that people have access to, to good, safe food, safe being. 678 00:53:31,520 --> 00:53:34,760 It's not full of it's not laden with, you know, with, with chemicals. 679 00:53:34,760 --> 00:53:38,160 And of course, that's a huge problem in the culture that we live in. 680 00:53:38,160 --> 00:53:44,160 You can be in to that's that's this stewardship and the and the ecosystem that you're actually in. 681 00:53:44,200 --> 00:53:49,160 You can but you can also be engaged and in volunteering like there's nothing there's nothing more powerful. 682 00:53:49,160 --> 00:53:56,160 There's nothing, nothing that gets people working for you more excited than then volunteering in the community in a way that they themselves 683 00:53:56,160 --> 00:53:59,960 think is important. So simply ask the people that are working for you what is it you'd like to do in the community? 684 00:53:59,960 --> 00:54:05,120 What would make you feel good about about yourself today? And you'll get fantastic ideas. 685 00:54:05,120 --> 00:54:09,360 And the companies that do those sorts of things are wildly successful because people want to work. 686 00:54:09,360 --> 00:54:10,680 They're they're excited. 687 00:54:10,680 --> 00:54:15,600 They think that they're they think they're doing something really good, not just for themselves but for other people. 688 00:54:15,600 --> 00:54:16,880 And that's incredibly motivating. 689 00:54:16,880 --> 00:54:24,560 So you can you can incentivize your, your workforce, not just by paying them, but by, by creating a, a culture that's engaged 690 00:54:24,920 --> 00:54:31,440 with good policy that does good and that can start that can start locally, that can start exactly where you are. 691 00:54:31,880 --> 00:54:35,280 And then then of course, you'll have a voice if you do that, and you can use that voice 692 00:54:35,280 --> 00:54:41,280 then to, to lever the people who are supposed to be making policy decisions by writing to them as a group, 693 00:54:41,480 --> 00:54:45,760 saying, okay, here, there's a letter here that's signed by everybody that works for us, 694 00:54:45,760 --> 00:54:50,080 and we're unhappy about what you're doing because we think what you're doing sounds good but isn't doing any good. 695 00:54:50,080 --> 00:54:54,840 And here's why. And you should probably rethink that. That's a that's a very good answer. 696 00:54:54,840 --> 00:55:00,960 And that actually answered my other question that I had, because sometimes you have those, you know, 697 00:55:01,080 --> 00:55:05,040 but you have those initiatives that are sounds good, like I'm going to use your words. 698 00:55:05,040 --> 00:55:07,600 They sounds good, but they are not doing any good. 699 00:55:07,600 --> 00:55:09,880 And, you know, like I also like I'm wondering, 700 00:55:09,880 --> 00:55:15,880 like how to engage with those things because on the other hand, you know, like I my day job isn't it. 701 00:55:15,960 --> 00:55:17,520 It isn't a tech. 702 00:55:17,520 --> 00:55:21,600 And I, for example, listen about the authors who are just boasting where like, 703 00:55:21,600 --> 00:55:27,920 oh, you know, we this many percent powered by renewable energy and we, you know, do all those things. 704 00:55:27,920 --> 00:55:33,960 And this is like it sounds like it is pointing up and people say, oh, this is great, right? 705 00:55:34,240 --> 00:55:38,600 But then you are approaching that from the environmental perspective. And it's like, okay, so how does it work? 706 00:55:38,600 --> 00:55:46,080 Is that through subsidy companies, the subsidy companies are be buying peat bog, which is carbon sink and should be left alone. 707 00:55:46,280 --> 00:55:49,960 And they're building big frickin, wind farms 708 00:55:49,960 --> 00:55:57,040 on those peat bogs, and they're becoming net carbon emitters because of the service roads needed to build those things. 709 00:55:57,040 --> 00:56:00,560 And so on and so forth and all that is. 710 00:56:00,560 --> 00:56:08,160 So you can then say from the stage that like, oh, we like this, this many percent, you know, renewable energy. 711 00:56:08,160 --> 00:56:13,040 But the damage you've done to the environment to say this. So, you know, we call it greenwashing. 712 00:56:13,040 --> 00:56:15,600 And so this is one part that I'm saying. 713 00:56:15,600 --> 00:56:21,600 But then there's another angle that I was like, well, they gotta start somewhere 714 00:56:22,680 --> 00:56:28,120 for like for so many decades that was not even in the picture. 715 00:56:28,120 --> 00:56:33,440 So now this is in the picture. Is it not good that this is in the picture because they got gotta start somewhere. 716 00:56:33,440 --> 00:56:35,320 You know, I, I don't know if you have that. 717 00:56:35,320 --> 00:56:40,200 I'm sure you have some comments on this, but I'm just wondering this, you know, like how to engage with this. 718 00:56:40,200 --> 00:56:46,560 Like on one hand call them out on just blatant greenwashing and then on the other hand, like, 719 00:56:46,760 --> 00:56:53,560 well, maybe actually the more productive approach is just as support or like engage positively with this 720 00:56:53,920 --> 00:56:57,680 because this is a start with might be a start of something actually positive. 721 00:56:57,680 --> 00:57:02,880 Yeah, I think that's exactly the way to look at it is still the with the ways to look at it that they're on, they're on the path. 722 00:57:02,880 --> 00:57:04,400 At least they're pointed up. 723 00:57:04,400 --> 00:57:10,080 So firstly they have to invest money and the infrastructure into into making a change. 724 00:57:10,080 --> 00:57:11,800 And, and that's a very big deal right. 725 00:57:11,800 --> 00:57:16,840 Because you know, big companies are you know, imagine Amazon has to somehow change direction. Right. 726 00:57:16,840 --> 00:57:23,280 Or they think of the things that machinations of, of a company that big that has to that has to move 727 00:57:23,760 --> 00:57:27,280 because the inertia behind it is, is, is, is, is enormous. 728 00:57:27,280 --> 00:57:33,600 So once they start to move like that's the hard part is getting them to move then now the problem is to accelerate that. 729 00:57:33,800 --> 00:57:34,600 So okay, okay. 730 00:57:34,600 --> 00:57:37,360 You've, you've you've moved in in a positive direction. 731 00:57:37,360 --> 00:57:40,920 But that isn't enough. Right. Because wind farms aren't the answer. 732 00:57:40,920 --> 00:57:44,480 Solar isn't the answer. The energy density is just not enough to power the, 733 00:57:45,480 --> 00:57:50,680 the demand that we have for for energy, the demand that we have for energy is going up exponentially. 734 00:57:50,680 --> 00:57:54,120 And we need we need very, very, very we need very, very, 735 00:57:54,120 --> 00:58:00,120 power dense solutions to providing the energy that we're going to that with, that we're going to need. 736 00:58:00,880 --> 00:58:06,120 And, solar and wind is, is, is basically gets everybody moving in the right direction. 737 00:58:06,120 --> 00:58:08,240 But it's not the solution. 738 00:58:08,240 --> 00:58:11,040 There isn't, you know, the solution to power 739 00:58:11,040 --> 00:58:17,040 the cloud, for example, is not to cover the a landmass the size of the United States with with windmills. 740 00:58:17,520 --> 00:58:20,440 That's that's not a good solution. 741 00:58:20,440 --> 00:58:21,920 It is a solution. 742 00:58:21,920 --> 00:58:23,280 But it's not a good solution. 743 00:58:23,280 --> 00:58:29,560 It sounds good, like you say, because it's green, but it doesn't doesn't do good, but it's moving in the right direction. 744 00:58:29,560 --> 00:58:35,440 So once once the change happens and then the responsibility is to accelerate that and ask some what's next? 745 00:58:35,440 --> 00:58:36,960 What's next, what's next. 746 00:58:36,960 --> 00:58:42,840 Because clearly, clearly this is now taking something in your case, something that was carbon neutral, that was a carbon sink to now 747 00:58:42,840 --> 00:58:46,440 that's it's not no longer carbon neutral. It's carbon positive. 748 00:58:46,440 --> 00:58:48,600 It's it's emitter. It's a carbon emitter. Right. 749 00:58:48,600 --> 00:58:51,720 So it's not it's not taking such scrubbing carbon. 750 00:58:51,720 --> 00:58:55,000 It's actually it's like dumping it producing it. 751 00:58:55,000 --> 00:58:58,720 So you need to accelerate that change because now they're moving in the right direction. 752 00:58:58,720 --> 00:59:01,680 And the hard part is actually to get the moving which is why they're celebrating. 753 00:59:01,680 --> 00:59:05,280 Look at us. You know, we've made this big change okay. That's great. 754 00:59:05,280 --> 00:59:09,200 It isn't enough. Like you got to go just a little bit farther, but you're moving in the right direction. 755 00:59:09,200 --> 00:59:12,480 They need to be celebrated in that regard for making that change. 756 00:59:12,480 --> 00:59:17,280 But then they you can't take that. You can't take your foot off the gas and let them off the hook. 757 00:59:17,280 --> 00:59:23,880 Well, maybe letting them off the hook is not the right way to say it, but you just can't take your foot off the gas to to to encourage them 758 00:59:23,880 --> 00:59:30,520 to continue down that path in an accelerating manner, to keep up with it, with the demands that they're actually, 759 00:59:30,520 --> 00:59:34,160 with the demands that their own industry, their own companies are going to be creating. 760 00:59:34,160 --> 00:59:35,160 Yeah, thanks for that. 761 00:59:35,160 --> 00:59:36,440 This is this is a good point. 762 00:59:36,440 --> 00:59:40,560 And, you know, like we always like the message in this podcast is always, like I said 763 00:59:40,560 --> 00:59:47,640 at the top of the show, just engage in the positive way and the and the and the mutual understanding, rather than, than fighting. 764 00:59:47,760 --> 00:59:54,240 Are you like overall are you an optimist into, you know, like if you look at your crystal ball and you look, you know, 765 00:59:54,320 --> 00:59:58,640 what's going to happen to the environment in the next ten, 20, 50, maybe 100 years. 766 00:59:58,640 --> 00:59:59,560 What do you see? 767 00:59:59,560 --> 01:00:01,080 Are you a do you see the good picture? 768 01:00:01,080 --> 01:00:05,600 You see a bad picture? Do you think we are just as good as done or do we have a chance? 769 01:00:05,600 --> 01:00:07,920 Oh, I think I'm very positive to be. 770 01:00:07,920 --> 01:00:12,760 To be frank, the humans are very, very good at adapting, but we're terrible at mitigating. 771 01:00:12,760 --> 01:00:20,200 So one of the ways to to differentiate good and bad policy is to is understand the difference between mitigation and adaptation. 772 01:00:20,680 --> 01:00:23,280 And we have, like, you know, First Nations here. 773 01:00:23,280 --> 01:00:25,840 I mentioned them a couple times in this country because we live quite close 774 01:00:25,840 --> 01:00:31,840 to Aboriginal peoples in terms of, proximity, but one but then in terms of temporal, temporal. 775 01:00:32,440 --> 01:00:37,800 Basically you have pre-industrial age cultures, you know, clashing with industrial age cultures and that that's, 776 01:00:37,800 --> 01:00:42,480 you know, whenever there's whenever there's a boundary, you obviously have friction. That's where everything happens. 777 01:00:42,480 --> 01:00:49,080 So they have a this marvelous history of, that goes back 10,000 years of, of adapting. 778 01:00:49,400 --> 01:00:54,160 So think of people living, the Inuit people living in Greenland or all across in the Arctic, 779 01:00:54,160 --> 01:01:00,920 all the Arctic from, you know, Russia, all around Canada, you know, Denmark, Iceland, maybe. 780 01:01:00,920 --> 01:01:03,160 That's certainly Iceland, I suppose. 781 01:01:03,160 --> 01:01:06,600 And the people that have been living there have adapted to that environment. 782 01:01:06,600 --> 01:01:11,280 It's probably one of the harshest environments in the world to live in, but they're beautifully adapted to living there. 783 01:01:11,280 --> 01:01:15,440 And they did it with tools that you and I wouldn't look at a tool like a thorn. 784 01:01:15,440 --> 01:01:19,440 Can you imagine sewing deer clothing with a thorn? 785 01:01:19,440 --> 01:01:25,080 And you're sewing through seal hide in moose hide and al-Qaida and caribou and wolf and everything under the sun. 786 01:01:25,080 --> 01:01:27,080 But their clothing is unbelievably good. 787 01:01:27,080 --> 01:01:33,000 It's it's so they're they're they're really good at we're really good at adaptation. Look at the Dutch people 788 01:01:34,200 --> 01:01:36,440 building, you know, building their I can there. 789 01:01:36,440 --> 01:01:40,920 No one has. There's no one out there telling the North Sea to stop rising like that's happening. 790 01:01:40,920 --> 01:01:48,360 They're not going to mitigate, you know, rainfall into the ocean by, by by seeding clouds or whatever the case, they are seeding clouds. 791 01:01:48,360 --> 01:01:49,960 I suppose. It's such a word. 792 01:01:49,960 --> 01:01:54,040 They're going it's going to build, they're going to raise the dike a little bit, which is mitigation, rising sea levels. 793 01:01:54,040 --> 01:01:57,840 Who knows why we're not going to worry about that. We're going to raise the dike. 794 01:01:57,840 --> 01:01:59,480 So we're good at mitigating. 795 01:01:59,480 --> 01:02:05,480 So one way to to to differentiate policy is mitigation versus adaptation. 796 01:02:05,560 --> 01:02:11,720 But as we go forward where our ability to mitigate improves, it improves with with with technology. 797 01:02:12,040 --> 01:02:15,400 So you can feed large language models, very complex problems. 798 01:02:15,400 --> 01:02:21,720 And they'll come up with really good answers in ways that, that we couldn't imagine and at a, at a pace at which we couldn't imagine. 799 01:02:22,080 --> 01:02:22,920 So I think we'll see. 800 01:02:22,920 --> 01:02:24,280 I solve problems that we 801 01:02:24,280 --> 01:02:30,760 that we would not be able to solve ourselves in the future, not all good, of course, because there's always two sides to every coin. 802 01:02:31,240 --> 01:02:38,320 But I think that our ability to mitigate is going to it's going to, it's going to outpace our, 803 01:02:38,760 --> 01:02:42,120 by a very large margin, our ability to destroy things. 804 01:02:42,120 --> 01:02:47,000 So so let me give you an example. Let's talk about, very briefly, industrial agriculture. 805 01:02:47,000 --> 01:02:50,880 One of the ways that we're able to feed the world is because we've become very, very good 806 01:02:50,880 --> 01:02:56,880 at producing, at producing on a set piece of land, at increasing production. 807 01:02:57,280 --> 01:03:05,520 Now, the problem with that is that we've been using, you know, we've been using fossil based fossil, fossil based fertilizers to do that. 808 01:03:06,240 --> 01:03:08,200 I can solve that problem for us. 809 01:03:08,200 --> 01:03:10,400 It'll solve the problem of of us, 810 01:03:10,400 --> 01:03:16,800 being able to increase industrial production, food production, which will which we'll have to do if we're going to feed the world. 811 01:03:16,800 --> 01:03:21,120 But we can do that in a way that's not nearly so damaging to the environment. 812 01:03:21,120 --> 01:03:23,960 One of the ways that one of the ways that happens here in Canada, 813 01:03:23,960 --> 01:03:31,280 in a, in a sort of simplistic way, is that everything that's that's every every piece of farming equipment has a GPS on it. 814 01:03:31,960 --> 01:03:32,880 And that G.P.S. 815 01:03:32,880 --> 01:03:40,040 tracker tells that, that tells that farmer exactly how much seeds should, should be going into this part, into this part of his 816 01:03:40,400 --> 01:03:44,400 part of his field, because it knows what the moisture content is, because it's being measured. 817 01:03:44,400 --> 01:03:48,960 It knows that this part of the field needs a little bit more fertilizer than the the other part of the field. 818 01:03:48,960 --> 01:03:49,520 It knows. 819 01:03:49,520 --> 01:03:54,960 It knows historically what the yield was last year, in the year before that, in the year before that, and that likely that's going to 820 01:03:54,960 --> 01:03:58,080 maybe that trend is going to continue or it's going to do something else. 821 01:03:58,080 --> 01:04:01,240 So that's an incredible amount of data on a tractor. 822 01:04:01,240 --> 01:04:06,160 And that tractors being every, every meter that tractor moves across that field is being tracked. 823 01:04:06,160 --> 01:04:14,960 So there's a, a way to think of simplistic AI helping that farmer be far more efficient in the use of fertilizers and chemicals, be 824 01:04:14,960 --> 01:04:22,320 far more efficient in the use of seeds, be far more efficient in the use of fuels, everything to increase yield, which is incredibly important. 825 01:04:22,560 --> 01:04:27,240 So I think yields on in North America have increased almost tenfold over the last. 826 01:04:27,240 --> 01:04:33,840 Well, I mean, ever since they've been farming industrially, which is a massive increase, like ten times the amount of 827 01:04:34,280 --> 01:04:38,400 if you can produce ten times the amount of fuel over the same piece of ground, then that's a big win. 828 01:04:38,400 --> 01:04:40,680 And if you can increase that again, 829 01:04:40,680 --> 01:04:46,920 and there's no reason to think that that can't happen because you can be far more efficient and you can be far better at what you're doing. 830 01:04:46,920 --> 01:04:51,480 So if you can increase that again but but reduce the environmental impact, that's a huge win. 831 01:04:51,480 --> 01:04:53,600 And so I'm optimistic about things like that. 832 01:04:53,600 --> 01:05:01,000 I'm optimistic about about using large language models to to come up with better policies around fishing. 833 01:05:01,000 --> 01:05:04,760 So I'm a I love to fish, love to fly fish actually. So 834 01:05:06,000 --> 01:05:11,400 and I don't think I don't remember the last time ever I've eaten a fish I've ever caught because, anyway. 835 01:05:11,400 --> 01:05:13,160 But I love to fish, so I'm. 836 01:05:13,160 --> 01:05:19,200 I'm always on the river, and I that one thing that drives me crazy are, is the lack of enforcement like you were describing. 837 01:05:19,280 --> 01:05:25,840 For people who are fishing, there's lack of enforcement, but there's a there's a fisherman, by and large, tend to be at least there. 838 01:05:25,840 --> 01:05:30,080 At least it's a vocal voice because people that like fly fishermen are they're 839 01:05:30,080 --> 01:05:38,760 they're making huge strides and turning rivers into catch and release only they're making huge strides into helping, fish come back to, 840 01:05:38,760 --> 01:05:46,200 fish populations to increase by encouraging governments to create waters that are controlled or classified, which which reduces impact. 841 01:05:47,200 --> 01:05:53,280 And I can help with that because it can it can it can take a large amount of data and then and then feed it 842 01:05:53,280 --> 01:06:00,520 into basically a global knowledge base to come up with better decisions on how best to, to manage or to classify or to control access. 843 01:06:00,520 --> 01:06:04,040 So I'm, I'm optimistic almost across the scale. 844 01:06:04,040 --> 01:06:06,920 But that doesn't mean that we're not going to have big problems. 845 01:06:06,920 --> 01:06:12,360 We will have big problems, but we have we'll be able to wield bigger and bigger hammers, as it were, to solve those problems. 846 01:06:12,360 --> 01:06:16,680 Well, thank you for that. And we need we need, positive messages, folks. 847 01:06:16,680 --> 01:06:25,320 Links to birds, personal website to website describing his adventures as well as his business are in the description of this show. 848 01:06:25,640 --> 01:06:28,440 So go in there and continue exploring. 849 01:06:28,440 --> 01:06:33,640 Bert, would you leave us and our listeners with that final message, like how? 850 01:06:33,640 --> 01:06:34,960 Like if you would like to 851 01:06:36,080 --> 01:06:37,920 leave us, like with one 852 01:06:37,920 --> 01:06:44,400 advice, you know, how to engage with the environment, with the policy, how to engage in a positive way 853 01:06:44,800 --> 01:06:50,800 that would make that brighter future that you describe a reality. 854 01:06:50,920 --> 01:06:52,440 What would that advice be? 855 01:06:52,440 --> 01:06:57,080 I've never been successful at anything in my life that I didn't have to persist at. 856 01:06:57,080 --> 01:07:01,120 So if you want to make if you want to be successful in business, you have to persist. 857 01:07:01,120 --> 01:07:03,720 You want to climb a mountain, you have to persist. You want to sail around the world. 858 01:07:03,720 --> 01:07:06,960 You got to persist, paddle across a continent. You got to persist. 859 01:07:06,960 --> 01:07:09,520 You got to think of, think of the strides that people made. 860 01:07:09,520 --> 01:07:16,480 Greenpeace in particular, I suppose, maybe, I mean, well, I would say Greenpeace in terms of, 861 01:07:16,480 --> 01:07:23,080 killing, literally killing the international, whale fishery like, that didn't happen overnight. 862 01:07:23,080 --> 01:07:29,080 There wasn't one person with a sign, you know, in front of some parliament building somewhere saying you know, stop killing whales. 863 01:07:29,400 --> 01:07:32,520 That took, took, you know, at least two decades. 864 01:07:33,600 --> 01:07:36,200 I'm not saying everything that you're going to do is going to take two decades. 865 01:07:36,200 --> 01:07:40,880 What I'm saying is that if you find something that that you're passionate about, you will have to persist. 866 01:07:40,880 --> 01:07:42,600 If you want to make a long life, think of it. 867 01:07:42,600 --> 01:07:47,480 If you want to make a long term change, then you're going to then you're going to have to engage over the long term. 868 01:07:47,480 --> 01:07:48,920 So we have big problems. 869 01:07:48,920 --> 01:07:57,360 They're all solvable if we're willing to persist in pursuing good solutions, solutions that don't just sound weird but do good. 870 01:07:57,680 --> 01:08:03,840 So when you when you I would say to those people who are listening, who are legitimately concerned and want to do something, 871 01:08:03,840 --> 01:08:06,240 then understand that you're this is a long game. 872 01:08:06,240 --> 01:08:10,800 This isn't this isn't nothing that nothing that we've talked about is going to change overnight. 873 01:08:10,800 --> 01:08:15,560 That's not a bad thing in any way, in any way, shape or form, because we all 874 01:08:15,560 --> 01:08:18,920 because we live in a pretty good space, by and large, in this country. 875 01:08:18,920 --> 01:08:23,280 And those things have come about because people have been playing the long game to make things good. 876 01:08:23,280 --> 01:08:26,160 And now we have to play the long things to make things better. 877 01:08:26,160 --> 01:08:31,040 It's as simple as that. So simply persist. That's all it takes. You don't have to be smart. You don't get to be good. 878 01:08:31,040 --> 01:08:34,920 You don't have to be rich. You just have to be willing to persist that desire. 879 01:08:34,920 --> 01:08:38,280 These are words of wisdom. Thank you so much. It's been pleasure. 880 01:08:38,280 --> 01:08:39,440 Yeah, it's been great timing. 881 01:08:39,440 --> 01:08:44,720 I, like I said, I knew I knew we'd have fun doing it, even though maybe some of the news is not as necessarily good. 882 01:08:44,720 --> 01:08:47,000 But it doesn't mean this isn't a good thing to talk about.