1 00:00:00,120 --> 00:00:02,560 Speaker 1: Guess what, mango? What's that? Will? So I don't want 2 00:00:02,560 --> 00:00:07,160 Speaker 1: to stereotype, but that's right, stereotype alert. Now. I don't 3 00:00:07,200 --> 00:00:09,240 Speaker 1: know if you've noticed this, but the writers we've hired 4 00:00:09,280 --> 00:00:12,840 Speaker 1: who grew up on farms always have this amazing work ethic, 5 00:00:13,000 --> 00:00:15,159 Speaker 1: Like they all seem to get up early and just 6 00:00:15,240 --> 00:00:19,439 Speaker 1: crank out work, whatever the circumstance. They don't miss deadline. Yeah, 7 00:00:19,480 --> 00:00:21,600 Speaker 1: it's true. One of my favorite teachers in high school 8 00:00:21,600 --> 00:00:23,079 Speaker 1: grow up on a farm too, and he used to 9 00:00:23,079 --> 00:00:25,640 Speaker 1: sing the virtues of what farming teaches you growing up, 10 00:00:25,760 --> 00:00:27,400 Speaker 1: and he was the same way. He was like off 11 00:00:27,440 --> 00:00:30,040 Speaker 1: at a crack of dawn and just so focused. Yes. 12 00:00:30,080 --> 00:00:31,880 Speaker 1: So I was looking this up and there's actually this 13 00:00:31,920 --> 00:00:34,920 Speaker 1: great story from Iowa about the origin of Highway six 14 00:00:35,040 --> 00:00:37,840 Speaker 1: or whether it's predecessor, called the River to River Road, 15 00:00:38,200 --> 00:00:41,040 Speaker 1: and it went across the state. Now, apparently, on June 16 00:00:41,760 --> 00:00:46,120 Speaker 1: nineteen ten, ten thousand farmers and some volunteers started working 17 00:00:46,159 --> 00:00:48,360 Speaker 1: on building this road at nine am. Do you know 18 00:00:48,440 --> 00:00:50,199 Speaker 1: how long it took him to finish? I don't know, 19 00:00:50,280 --> 00:00:54,280 Speaker 1: like a month, one hour. It took the farmers one hour. 20 00:00:54,720 --> 00:00:57,800 Speaker 1: By ten am they were completely done. It almost feels 21 00:00:57,840 --> 00:00:59,960 Speaker 1: like that movie Dave. Do you remember this? So there's 22 00:01:00,040 --> 00:01:02,040 Speaker 1: this scene where they give the job of balancing the 23 00:01:02,080 --> 00:01:05,399 Speaker 1: congressional budget to a hard working, honest accountant and he 24 00:01:05,480 --> 00:01:09,120 Speaker 1: balances the budget in one night. It's that level. If 25 00:01:09,160 --> 00:01:11,319 Speaker 1: you ask a ragtag group of farmers to build you 26 00:01:11,360 --> 00:01:14,000 Speaker 1: a highway the width of the entire US state, they'll 27 00:01:14,000 --> 00:01:17,679 Speaker 1: have it done in an hours. I know, and I realized. 28 00:01:17,720 --> 00:01:20,679 Speaker 1: I got this story from the Root six Tourists Association website, 29 00:01:21,200 --> 00:01:23,560 Speaker 1: and it may be apocryphal, but it made me wonder. 30 00:01:23,880 --> 00:01:26,160 Speaker 1: If farmers work as hard as they're known to, and 31 00:01:26,200 --> 00:01:29,039 Speaker 1: if the science of farming is only getting better, then 32 00:01:29,080 --> 00:01:31,800 Speaker 1: why are people across the globe still going hungry? And 33 00:01:31,840 --> 00:01:34,360 Speaker 1: what will it take to actually feed the world. That's 34 00:01:34,360 --> 00:01:56,240 Speaker 1: our big question today. Yeah, hey, their podcast listeners, welcome 35 00:01:56,280 --> 00:01:58,559 Speaker 1: to Part Time Genius. I'm Will Pearson and as always 36 00:01:58,560 --> 00:02:01,000 Speaker 1: I'm joined by my good friend Man Guesh Ticketer. In 37 00:02:01,040 --> 00:02:03,320 Speaker 1: today's show, we're talking about what it will take to 38 00:02:03,480 --> 00:02:06,200 Speaker 1: feed the world, scientists playing by the year of two 39 00:02:06,200 --> 00:02:09,840 Speaker 1: thousand and fifty, the population will be at ten billion people. 40 00:02:10,320 --> 00:02:12,600 Speaker 1: That's a ton of people and a lot of hungry 41 00:02:12,600 --> 00:02:14,600 Speaker 1: mouths to feed. So we're going to try to answer 42 00:02:14,680 --> 00:02:16,560 Speaker 1: that big question, and along the way, we've got an 43 00:02:16,600 --> 00:02:20,399 Speaker 1: incredible guest, William McCaskill, a professor of philosophy at Oxford 44 00:02:20,400 --> 00:02:23,800 Speaker 1: and the founder of Effective Altruism. Yeah, he's amazing. He 45 00:02:23,880 --> 00:02:27,160 Speaker 1: essentially invented moneyball for charity, which sounds like a marriage 46 00:02:27,160 --> 00:02:29,040 Speaker 1: of two things that aren't supposed to go together. It's 47 00:02:29,080 --> 00:02:30,520 Speaker 1: like one of those pitches you hear from an off 48 00:02:30,560 --> 00:02:32,760 Speaker 1: brand shark tank and you know it's it's like uber 49 00:02:32,960 --> 00:02:36,640 Speaker 1: but for gymnastics. But his work is really awesome. And 50 00:02:36,639 --> 00:02:39,000 Speaker 1: we've got another nerd hero on today as well. Right, Yeah, 51 00:02:39,000 --> 00:02:41,200 Speaker 1: that's right. We've got Josh Miller from farm Shots and 52 00:02:41,240 --> 00:02:45,640 Speaker 1: he invented this program in college and it's pretty incredible, wonderful. So, Mango, 53 00:02:45,680 --> 00:02:47,080 Speaker 1: I've got to tell you, I'm going to start with 54 00:02:47,080 --> 00:02:50,000 Speaker 1: the fact that's going to disappoint you. Oh yeah, what's that? Well, 55 00:02:50,040 --> 00:02:52,160 Speaker 1: because today's big question is about how we're going to 56 00:02:52,200 --> 00:02:54,200 Speaker 1: feed the world. One of the first things I looked 57 00:02:54,240 --> 00:02:56,119 Speaker 1: up was what we can do to be more responsible 58 00:02:56,120 --> 00:02:58,600 Speaker 1: with our food choices. I do not like where this 59 00:02:58,680 --> 00:03:01,480 Speaker 1: guy I know and scientists have this list of eleven 60 00:03:01,520 --> 00:03:04,720 Speaker 1: things we should rethink eating. The usual suspects are all 61 00:03:04,800 --> 00:03:07,120 Speaker 1: on there, like beef, which always gets knocked because of 62 00:03:07,120 --> 00:03:10,280 Speaker 1: the amount of land and water that goes into raising cattle. Sure, 63 00:03:10,360 --> 00:03:12,600 Speaker 1: like that's a big vegetarian battle cry, how the land 64 00:03:12,600 --> 00:03:14,400 Speaker 1: could be better used to grow other things, and that 65 00:03:14,880 --> 00:03:17,880 Speaker 1: a kilogram of beef takes like twenty times more water 66 00:03:17,919 --> 00:03:20,440 Speaker 1: than growing grains, which is sort of true. It takes 67 00:03:20,480 --> 00:03:23,160 Speaker 1: three times more water to grow beef than raising chickens, 68 00:03:23,520 --> 00:03:25,760 Speaker 1: and according to new scientists, you could provide ten to 69 00:03:25,840 --> 00:03:28,360 Speaker 1: twenty times the protein if that land was used to 70 00:03:28,400 --> 00:03:31,760 Speaker 1: plant legumes. But that isn't what's interesting. Beef is at 71 00:03:31,760 --> 00:03:33,320 Speaker 1: the top of the list. Then there are things like 72 00:03:33,440 --> 00:03:35,600 Speaker 1: nuts and chocolate because they suck up a lot of 73 00:03:35,600 --> 00:03:39,200 Speaker 1: water and resource. But additionally, there are two things I 74 00:03:39,240 --> 00:03:43,160 Speaker 1: know you love. What's that coffee and you're ready for it? 75 00:03:43,400 --> 00:03:47,560 Speaker 1: Fry French fries. Yeah, French fries shouldn't be on that list. 76 00:03:47,640 --> 00:03:49,240 Speaker 1: I knew you were going to be happy about this. 77 00:03:49,320 --> 00:03:51,800 Speaker 1: For you listeners out there, Mango as a vegetarian in college, 78 00:03:51,800 --> 00:03:54,800 Speaker 1: which pretty much meant about eight of his diet was fries. 79 00:03:55,800 --> 00:03:57,400 Speaker 1: I really want to say it was because there weren't 80 00:03:57,440 --> 00:04:00,000 Speaker 1: enough vegetarian options. But the truth is I just really 81 00:04:00,160 --> 00:04:02,800 Speaker 1: love fries. They're delicious. I don't know if I ever 82 00:04:02,800 --> 00:04:04,520 Speaker 1: told you this, but when I was ten or eleven, 83 00:04:04,600 --> 00:04:06,360 Speaker 1: we had to do one of those exercises in math 84 00:04:06,400 --> 00:04:08,160 Speaker 1: class where we did a budget for when we were 85 00:04:08,160 --> 00:04:10,920 Speaker 1: grown up, and so we were handed out salaries, I 86 00:04:10,920 --> 00:04:13,520 Speaker 1: mean hunted for apartments, and we budgeted for things like 87 00:04:13,560 --> 00:04:17,440 Speaker 1: toilet paper and household supplies using coupons, and we also 88 00:04:17,480 --> 00:04:19,599 Speaker 1: had to plan out a menu, and I remember thinking 89 00:04:19,720 --> 00:04:22,240 Speaker 1: food is a great place to save. So I just 90 00:04:22,279 --> 00:04:24,720 Speaker 1: decided to stock my fridge with French fries and frozen 91 00:04:24,720 --> 00:04:28,680 Speaker 1: burritos and pizzas from Sam's Club getting hungry. And the 92 00:04:28,760 --> 00:04:30,719 Speaker 1: whole idea was just to spend like a hundred fifty 93 00:04:30,720 --> 00:04:33,640 Speaker 1: dollars a month on food. And when my teacher inspected 94 00:04:33,680 --> 00:04:35,279 Speaker 1: it and asked me if I wanted to revise it, 95 00:04:35,360 --> 00:04:39,120 Speaker 1: I was like, nah, I'm good. I was just supremely 96 00:04:39,160 --> 00:04:41,320 Speaker 1: confident that a plate of fries for dinner every night 97 00:04:41,600 --> 00:04:44,720 Speaker 1: wasn't just tasty, it was sensible. Makes sense to me. 98 00:04:45,120 --> 00:04:46,599 Speaker 1: I mean, can you imagine if we had to commit 99 00:04:46,640 --> 00:04:49,040 Speaker 1: to our clothing and food choices for life at age 100 00:04:49,080 --> 00:04:52,000 Speaker 1: and about how terrible we'd look and feel. We're probably 101 00:04:52,040 --> 00:04:54,560 Speaker 1: wearing umbros and hyper colored shirts to work every day 102 00:04:54,560 --> 00:04:57,000 Speaker 1: and eating nothing but bags of gummy bears. I know, 103 00:04:57,160 --> 00:04:59,080 Speaker 1: but I still don't get what French fries are so 104 00:04:59,120 --> 00:05:01,240 Speaker 1: bad for the earth? I mean, and coffee, I can 105 00:05:01,279 --> 00:05:03,080 Speaker 1: see that. Like a while back, I read this thing 106 00:05:03,160 --> 00:05:05,719 Speaker 1: that growing tea takes up more land, but coffee is 107 00:05:05,720 --> 00:05:08,279 Speaker 1: a much more difficult crop to rays. That's right. For 108 00:05:08,320 --> 00:05:10,559 Speaker 1: every single cup of coffee you drink, it takes five 109 00:05:10,640 --> 00:05:13,280 Speaker 1: hundred and fifty cups of water. Can you believe that? 110 00:05:13,320 --> 00:05:15,760 Speaker 1: I can't, which is why I only drink diet mountain dew. 111 00:05:15,760 --> 00:05:18,080 Speaker 1: It's a very principal decision I made a long time ago. 112 00:05:18,720 --> 00:05:20,880 Speaker 1: But fries around the list because of food waste. As 113 00:05:20,880 --> 00:05:23,080 Speaker 1: a French fried connoisseur, you probably already know this, but 114 00:05:23,120 --> 00:05:26,400 Speaker 1: apparently French fries don't taste good when they're cold. Yeah. 115 00:05:26,480 --> 00:05:28,000 Speaker 1: My wife and I do this thing where we guess 116 00:05:28,040 --> 00:05:30,159 Speaker 1: how long it will take for a fast food fry 117 00:05:30,279 --> 00:05:32,800 Speaker 1: to go from like hot and crispy and totally delicious 118 00:05:32,839 --> 00:05:36,160 Speaker 1: to completely limb. And it's stunning how fast it can 119 00:05:36,160 --> 00:05:39,159 Speaker 1: transform into something totally unappealing. I like that, this is 120 00:05:39,160 --> 00:05:42,440 Speaker 1: the thing you guys actively do. It's also crazy how 121 00:05:42,440 --> 00:05:44,560 Speaker 1: many fries are thrown out because they aren't good after 122 00:05:44,640 --> 00:05:47,520 Speaker 1: ten to fifteen minutes. So in the UK, New Scientists 123 00:05:47,520 --> 00:05:50,400 Speaker 1: reports that fries or chips as they call them, account 124 00:05:50,440 --> 00:05:53,599 Speaker 1: for ten percent of all food waste, but the potatoes 125 00:05:53,640 --> 00:05:56,120 Speaker 1: are only part of it. Fried foods in general are 126 00:05:56,120 --> 00:05:58,680 Speaker 1: considered wasteful because of all the oils and fats that 127 00:05:58,720 --> 00:06:01,560 Speaker 1: go into frying up all the deliciousness. So if we 128 00:06:01,680 --> 00:06:03,880 Speaker 1: use the land for veggies instead, it would be a 129 00:06:03,920 --> 00:06:06,479 Speaker 1: better source of calories for the population, Which is like 130 00:06:06,520 --> 00:06:09,200 Speaker 1: a total Sophie's choice for me, choosing between eating French 131 00:06:09,240 --> 00:06:11,800 Speaker 1: fries and saving the world. You can't do that to me. Well, 132 00:06:12,040 --> 00:06:14,800 Speaker 1: I'm so sorry, But let's back up for a second. 133 00:06:15,080 --> 00:06:17,320 Speaker 1: What actually is the state of world hunger? I mean, 134 00:06:17,400 --> 00:06:19,720 Speaker 1: there's so many different things written up about this that's 135 00:06:19,800 --> 00:06:21,760 Speaker 1: kind of hard to keep up. And part of what's 136 00:06:21,760 --> 00:06:24,360 Speaker 1: confusing to me is that I recently read we currently 137 00:06:24,400 --> 00:06:27,080 Speaker 1: produce enough food to feed everyone in the world. Well, 138 00:06:27,080 --> 00:06:29,960 Speaker 1: those things aren't mutually exclusive. So close to a billion 139 00:06:30,000 --> 00:06:33,039 Speaker 1: people go to sleep hungry every night, which is heartbreaking, 140 00:06:33,440 --> 00:06:35,840 Speaker 1: And in two thousand fifteen, the Food and Agriculture Arm 141 00:06:35,880 --> 00:06:37,760 Speaker 1: of the u N showed that there were seven hundred 142 00:06:37,920 --> 00:06:41,600 Speaker 1: nine million under nourished people in the world. And while 143 00:06:41,640 --> 00:06:43,880 Speaker 1: over the past couple of decades we've started to see 144 00:06:43,920 --> 00:06:46,599 Speaker 1: the numbers drop on that, you have to imagine that 145 00:06:46,680 --> 00:06:48,560 Speaker 1: this could get worse if we don't start to get 146 00:06:48,600 --> 00:06:51,160 Speaker 1: a real handle on this. But you're right, there actually 147 00:06:51,200 --> 00:06:54,640 Speaker 1: is enough food to feed everyone. How's that. Well. Gordon Conway, 148 00:06:54,680 --> 00:06:56,880 Speaker 1: who's a fellow at the Royal Society and this heavily 149 00:06:56,920 --> 00:07:01,600 Speaker 1: respected agriculture ecologists, points out in his book One Billion Hungry, 150 00:07:01,720 --> 00:07:03,680 Speaker 1: if we were to add up all the world's production 151 00:07:03,680 --> 00:07:06,640 Speaker 1: of food and then divide it equally among the world's population, 152 00:07:07,279 --> 00:07:10,400 Speaker 1: every man, woman, and child would receive a daily average 153 00:07:10,400 --> 00:07:14,160 Speaker 1: of over twenty hundred calories. That's enough for a healthy lifestyle, 154 00:07:14,360 --> 00:07:16,680 Speaker 1: which is amazing. But on the other hand, it's not 155 00:07:16,720 --> 00:07:20,000 Speaker 1: like humans are great at sharing, Like, we're not vampire bats. 156 00:07:20,920 --> 00:07:25,160 Speaker 1: Vampire bats, Yeah they sound so blood thirsty, Well they 157 00:07:25,160 --> 00:07:28,960 Speaker 1: are blood, but they're also super considerate. Like if a 158 00:07:29,040 --> 00:07:31,320 Speaker 1: vampire bat has a couple of bad nights of feeding, 159 00:07:31,440 --> 00:07:34,440 Speaker 1: it can actually starve to death because the creatures roost 160 00:07:34,480 --> 00:07:37,680 Speaker 1: together if one bat notices that another is hungry, it'll 161 00:07:37,720 --> 00:07:42,560 Speaker 1: be a good roostmatee and regurgitate some food for it. Roostmates. 162 00:07:42,600 --> 00:07:44,760 Speaker 1: Such a great word. I like the idea of a 163 00:07:44,800 --> 00:07:47,720 Speaker 1: little bad advertising on Craigslist looking for three hundred other 164 00:07:47,800 --> 00:07:51,560 Speaker 1: roostmates to share one bedroom in Bushwick. So the vampire 165 00:07:51,600 --> 00:07:54,560 Speaker 1: bats aren't the only ones. I mean, humans are empathetic too, 166 00:07:54,600 --> 00:07:57,680 Speaker 1: and they do share food. There was that wonderful story 167 00:07:57,680 --> 00:07:59,640 Speaker 1: of the man in Saudi Arabia who put a fridge 168 00:07:59,640 --> 00:08:01,960 Speaker 1: out on a sidewalk and then filled it with leftovers 169 00:08:02,000 --> 00:08:04,800 Speaker 1: for anyone to take. And that trend started to spread 170 00:08:04,800 --> 00:08:07,400 Speaker 1: across the Middle East of people stocking fridges on the 171 00:08:07,440 --> 00:08:10,520 Speaker 1: street with fresh water and food for anyone in need. 172 00:08:10,960 --> 00:08:13,080 Speaker 1: And there are those little food pantries that have popped 173 00:08:13,120 --> 00:08:15,880 Speaker 1: up in America and across the world. You know, people 174 00:08:15,960 --> 00:08:18,520 Speaker 1: do care. It's just that a lot of little food 175 00:08:18,560 --> 00:08:20,680 Speaker 1: pantries aren't going to add up to feeding a billion 176 00:08:20,760 --> 00:08:24,400 Speaker 1: hungry people. Sure, so being more thoughtful about how and 177 00:08:24,440 --> 00:08:26,480 Speaker 1: what we will be part of the solution, as we'll 178 00:08:26,520 --> 00:08:29,520 Speaker 1: be figuring out a better food distribution mechanism. But part 179 00:08:29,520 --> 00:08:32,040 Speaker 1: of the question too is what is it that's keeping 180 00:08:32,080 --> 00:08:34,360 Speaker 1: people hungry. And I think I have an answer for you. 181 00:08:35,000 --> 00:08:38,360 Speaker 1: So I've read some amazing research from Marthea Sen and 182 00:08:38,400 --> 00:08:41,800 Speaker 1: you know sends this Nobel Prize winning economists, and he 183 00:08:41,840 --> 00:08:44,679 Speaker 1: showed how famines aren't really caused by droughts or widespread 184 00:08:44,679 --> 00:08:47,720 Speaker 1: food shortages so much as the rooted in poverty. So 185 00:08:47,800 --> 00:08:49,720 Speaker 1: how so Well, when I first read that, I thought, 186 00:08:49,760 --> 00:08:51,920 Speaker 1: how can that be? I mean, a famine has to 187 00:08:51,920 --> 00:08:55,040 Speaker 1: be caused by droughts and crop devastation. But his point 188 00:08:55,080 --> 00:08:57,960 Speaker 1: is that statistically, if you look at these food crises, 189 00:08:58,240 --> 00:09:00,480 Speaker 1: there's little or no decline in the we're all food 190 00:09:00,520 --> 00:09:03,520 Speaker 1: supply in the greater region. Like he analyzed the famine 191 00:09:03,559 --> 00:09:06,960 Speaker 1: from nineteen three in Ethiopia where weather patterns caused a 192 00:09:07,000 --> 00:09:10,280 Speaker 1: small region of the country, this province called Wallow to 193 00:09:10,360 --> 00:09:14,480 Speaker 1: suffer and because the population was impoverished, their ability to 194 00:09:14,520 --> 00:09:17,520 Speaker 1: grow and purchase food was severely affected, but the overall 195 00:09:17,559 --> 00:09:20,920 Speaker 1: food production in the country wasn't substantially different from years before. 196 00:09:21,840 --> 00:09:24,120 Speaker 1: And he showed this over and over in other places, 197 00:09:24,160 --> 00:09:27,280 Speaker 1: including in Bengal and other countries where the diminished purchasing 198 00:09:27,280 --> 00:09:29,920 Speaker 1: power of wages was the root cause of starvation, not 199 00:09:30,080 --> 00:09:33,440 Speaker 1: overall food supply. In fact, there's this wonderful series called 200 00:09:33,600 --> 00:09:36,680 Speaker 1: Hungry Hungry Humans. Actually, do you remember the magazine Meat Paper, 201 00:09:36,800 --> 00:09:40,160 Speaker 1: Meat Paper, of course, so that beautiful indie magazine with 202 00:09:40,200 --> 00:09:42,679 Speaker 1: all those photographs of meat from a few years back, right, 203 00:09:42,880 --> 00:09:44,880 Speaker 1: I know, it's so good. I don't even like me 204 00:09:45,000 --> 00:09:47,240 Speaker 1: that much, but I loved looking through it. But one 205 00:09:47,240 --> 00:09:50,080 Speaker 1: of the former editors there, this Berkeley journalism professor named 206 00:09:50,120 --> 00:09:53,560 Speaker 1: Nathaniel Johnson. He spent six months investigating the food crisis 207 00:09:53,640 --> 00:09:55,959 Speaker 1: in a series called Hungry, Hungry Humans. And one of 208 00:09:56,000 --> 00:09:58,640 Speaker 1: the things he pointed out that Marthea Sen also says 209 00:09:58,960 --> 00:10:01,040 Speaker 1: is that one thing that can help curb of potential 210 00:10:01,080 --> 00:10:04,360 Speaker 1: famine is free press. And it's simply because in democracies, 211 00:10:04,360 --> 00:10:07,440 Speaker 1: politicians have to get reelected, and as long as someone 212 00:10:07,480 --> 00:10:10,040 Speaker 1: is shedding light on a food or economic problem is 213 00:10:10,040 --> 00:10:12,360 Speaker 1: going to get addressed before it becomes a total crisis. 214 00:10:12,520 --> 00:10:14,480 Speaker 1: But you have to imagine the internet and the spread 215 00:10:14,480 --> 00:10:17,080 Speaker 1: of mobile phones is also great for spreading that knowledge. 216 00:10:17,120 --> 00:10:19,560 Speaker 1: And you know, currently there's some amazing apps trying to 217 00:10:19,559 --> 00:10:22,760 Speaker 1: address the problem by connecting food donors with those in need. 218 00:10:23,240 --> 00:10:25,320 Speaker 1: But part of what's interesting to me is that a 219 00:10:25,320 --> 00:10:28,600 Speaker 1: little investment in infrastructure might also solve some of these problems. 220 00:10:29,559 --> 00:10:31,800 Speaker 1: We don't think about this, but roads and access to 221 00:10:31,920 --> 00:10:34,800 Speaker 1: villages and town centers actually play a big part in 222 00:10:34,840 --> 00:10:38,080 Speaker 1: bringing people out of poverty. Like Johnson interviewed a farmer 223 00:10:38,120 --> 00:10:41,160 Speaker 1: from Ethiopia who told him it takes her four hours 224 00:10:41,200 --> 00:10:43,360 Speaker 1: just to walk from her farm to the nearest town. 225 00:10:43,880 --> 00:10:45,520 Speaker 1: And his point is, can you imagine if you have 226 00:10:45,559 --> 00:10:47,880 Speaker 1: to walk four hours every time you need to get 227 00:10:47,920 --> 00:10:51,720 Speaker 1: seeds or fertilizer or anything to raise your crops. And 228 00:10:51,760 --> 00:10:54,520 Speaker 1: that's not even taking into account getting your food to market. 229 00:10:55,000 --> 00:10:57,920 Speaker 1: Just imagine how much time she's losing. So a good 230 00:10:57,920 --> 00:11:00,440 Speaker 1: paved road would ease her situation and helped her have 231 00:11:00,520 --> 00:11:03,520 Speaker 1: more of a successful farm. And there's hard evidence that 232 00:11:03,559 --> 00:11:06,280 Speaker 1: shows this bears out economically, Like there was a study 233 00:11:06,280 --> 00:11:08,880 Speaker 1: in India in the nineteen nineties that showed for every 234 00:11:08,920 --> 00:11:11,520 Speaker 1: million rupees that was spent on a road, which at 235 00:11:11,559 --> 00:11:15,000 Speaker 1: the time was like fifty dollars, eight hundred and eighty 236 00:11:15,040 --> 00:11:17,520 Speaker 1: one people were lifted out of poverty. And that's not 237 00:11:17,600 --> 00:11:20,800 Speaker 1: just them but their future generations. So what you're saying 238 00:11:20,920 --> 00:11:23,360 Speaker 1: is we just need to get like ten thousand farmers 239 00:11:23,360 --> 00:11:26,520 Speaker 1: from Iowa over to these remote locations across the globe 240 00:11:26,760 --> 00:11:29,160 Speaker 1: and get a few roads built in under an hour. Exactly. 241 00:11:29,160 --> 00:11:31,880 Speaker 1: It's that simple. But before we charter some planes and 242 00:11:31,960 --> 00:11:34,760 Speaker 1: launch our farmers without borders who adopt a highway program, 243 00:11:34,760 --> 00:11:36,640 Speaker 1: why don't we break for a quiz? Sounds good to 244 00:11:36,679 --> 00:11:45,120 Speaker 1: me for a quiz. Today, we've got Josh Miller on 245 00:11:45,160 --> 00:11:47,560 Speaker 1: the line, and Josh is a fascinating guy because he 246 00:11:47,600 --> 00:11:50,240 Speaker 1: created a company called farm Shots right out of his 247 00:11:50,320 --> 00:11:53,560 Speaker 1: dorm room. Josh, welcome to part time Genius. Hey, thanks 248 00:11:53,559 --> 00:11:56,160 Speaker 1: for having me. Now, Josh, you graduated in two thousand 249 00:11:56,160 --> 00:11:59,079 Speaker 1: and sixteen, so you're pretty fresh out of college. Tell 250 00:11:59,160 --> 00:12:01,400 Speaker 1: us a little bit about farm Shots and what inspired 251 00:12:01,440 --> 00:12:03,880 Speaker 1: you to create it. Yeah, so we got started. It 252 00:12:03,880 --> 00:12:08,000 Speaker 1: would have been the sophomore year I had at Duke, 253 00:12:08,240 --> 00:12:10,120 Speaker 1: So it's kind of I had of this love for 254 00:12:10,200 --> 00:12:13,599 Speaker 1: agriculture and I was studying engineering at the time. I 255 00:12:13,679 --> 00:12:15,640 Speaker 1: really wanted to find a way to put the two together, 256 00:12:15,720 --> 00:12:18,080 Speaker 1: and there wasn't really anything out there that kind of 257 00:12:18,320 --> 00:12:22,520 Speaker 1: did that, except for making tractors, which wasn't very exciting 258 00:12:23,920 --> 00:12:27,240 Speaker 1: and so and so, I uh, I went back and 259 00:12:27,240 --> 00:12:29,040 Speaker 1: I did some research and it turned out in the 260 00:12:29,160 --> 00:12:33,280 Speaker 1: sixties and seventies, there was a lot of research into 261 00:12:33,600 --> 00:12:38,360 Speaker 1: sensing vegetation, uh from half a days, particularly for finding 262 00:12:38,360 --> 00:12:40,520 Speaker 1: areas where there might be a disease or a bug 263 00:12:40,600 --> 00:12:43,560 Speaker 1: out of the farm. The problem was, back in the 264 00:12:43,679 --> 00:12:46,720 Speaker 1: sixties and seventies, there weren't really ano satellites for that 265 00:12:46,800 --> 00:12:49,679 Speaker 1: to be useful. Right, you got an imagine it was 266 00:12:49,760 --> 00:12:53,240 Speaker 1: really low resolution, maybe once a month. So if you 267 00:12:53,320 --> 00:12:56,040 Speaker 1: passed forward to when I was about to start the 268 00:12:56,040 --> 00:12:58,880 Speaker 1: company would have been around two thousand and fourteen. There 269 00:12:58,920 --> 00:13:00,920 Speaker 1: were all these kind thing is coming out of a 270 00:13:00,920 --> 00:13:04,559 Speaker 1: woodwork that you know, aboard Elon Musk's rockets, and all 271 00:13:04,559 --> 00:13:07,040 Speaker 1: these tiny rockets that we're going up to space. We're 272 00:13:07,080 --> 00:13:09,719 Speaker 1: putting these tiny, tiny satellites that are about as big 273 00:13:09,760 --> 00:13:13,920 Speaker 1: as your forearm in space. So all that research back 274 00:13:13,960 --> 00:13:16,960 Speaker 1: in the sixties and seventies and then be applied to 275 00:13:17,040 --> 00:13:20,439 Speaker 1: these hundreds and and almost a thousand new satellites have 276 00:13:20,520 --> 00:13:25,160 Speaker 1: gone into space since that research had happened. And so 277 00:13:25,200 --> 00:13:27,160 Speaker 1: I went out and I said, okay, you know, can 278 00:13:27,280 --> 00:13:30,480 Speaker 1: can we turn this Neohle product that actually helps farmers 279 00:13:30,600 --> 00:13:32,719 Speaker 1: um And it turned out we could, And I went 280 00:13:32,720 --> 00:13:36,240 Speaker 1: ahead and I built the first version of the software. Uh, 281 00:13:36,320 --> 00:13:40,240 Speaker 1: and I'm a terrible engineer, and so it was probably 282 00:13:40,240 --> 00:13:43,680 Speaker 1: the most awful, like you, piece of software exemplified. But 283 00:13:43,760 --> 00:13:46,599 Speaker 1: but these guys loved it, right, it made sense and 284 00:13:46,640 --> 00:13:49,200 Speaker 1: it was something that they wanted to buy. Um. And 285 00:13:49,240 --> 00:13:51,360 Speaker 1: if you fast forward to where we are today, you know, 286 00:13:51,600 --> 00:13:55,840 Speaker 1: three years later, Uh, the company's operating about thirty different countries. 287 00:13:56,600 --> 00:14:01,520 Speaker 1: We're on about ten million acres internationally, very significantly. That's 288 00:14:01,640 --> 00:14:04,480 Speaker 1: very cool. So so, Joshua, what keeps you optimistic about 289 00:14:04,480 --> 00:14:06,920 Speaker 1: the future and growing enough to to feed the world 290 00:14:06,920 --> 00:14:10,280 Speaker 1: as we're talking about today? Yeah, you know, it's it's 291 00:14:10,360 --> 00:14:12,679 Speaker 1: kind of funny because we talked about there's a good 292 00:14:12,679 --> 00:14:15,760 Speaker 1: amount of urban growth going on in places like the US, 293 00:14:16,480 --> 00:14:19,080 Speaker 1: where you have cities kind of expanding outwards and outwards, 294 00:14:19,280 --> 00:14:22,720 Speaker 1: which means more people. And at the same time, you know, 295 00:14:23,120 --> 00:14:25,320 Speaker 1: a lot of what's getting converted to this kind of 296 00:14:25,440 --> 00:14:29,320 Speaker 1: used land is farm land. Um. So the question is 297 00:14:29,640 --> 00:14:32,800 Speaker 1: you've got more people causing less farm land. How do 298 00:14:32,960 --> 00:14:34,800 Speaker 1: how do you kind of feed those sorts of people? 299 00:14:35,280 --> 00:14:38,640 Speaker 1: And so I think that's an ever pressing problem that's 300 00:14:38,640 --> 00:14:41,600 Speaker 1: going to go on for hundreds of years. Any ideas 301 00:14:41,920 --> 00:14:44,560 Speaker 1: you know, we've got to take a shrinking amount of 302 00:14:44,640 --> 00:14:47,840 Speaker 1: acridge and turn that into more food. And the homely 303 00:14:47,840 --> 00:14:49,640 Speaker 1: way you're gonna be able to really do something like 304 00:14:49,680 --> 00:14:54,640 Speaker 1: that is through applications of technology. M hm. We certainly 305 00:14:54,640 --> 00:14:57,400 Speaker 1: appreciate what you're doing with the business, and congratulations again 306 00:14:57,480 --> 00:15:01,320 Speaker 1: on on its success. So um, so, something equally important 307 00:15:02,560 --> 00:15:05,840 Speaker 1: is the quiz that we're playing today. Uh, Matt, mango. 308 00:15:05,920 --> 00:15:07,920 Speaker 1: What's what's our game that we're playing with Josh today? 309 00:15:08,240 --> 00:15:11,400 Speaker 1: It's called farm Raised where all the answers are people 310 00:15:11,520 --> 00:15:16,680 Speaker 1: or characters who grew up on farms. And what is 311 00:15:16,800 --> 00:15:20,320 Speaker 1: Josh playing for? As always our listeners playing for a 312 00:15:20,360 --> 00:15:22,440 Speaker 1: chance to win a handwritten note from us to his 313 00:15:22,560 --> 00:15:27,160 Speaker 1: mom or his boss, singing his praises. All right, so 314 00:15:27,200 --> 00:15:28,920 Speaker 1: this should be easy. What we will do is we 315 00:15:28,920 --> 00:15:31,280 Speaker 1: will give you a bit of pop culture and you 316 00:15:31,320 --> 00:15:34,640 Speaker 1: tell us which farm boy or girl we're talking about. Okay, 317 00:15:34,720 --> 00:15:39,680 Speaker 1: we've got five questions for you. The steaks are very high. Okay, 318 00:15:40,400 --> 00:15:42,720 Speaker 1: how many do I have to get? Right? Well, we'll see, 319 00:15:43,520 --> 00:15:45,800 Speaker 1: we'll see. We'll have to turn to the judges in 320 00:15:45,840 --> 00:15:49,520 Speaker 1: a bit. So um they are I'll go ahead and 321 00:15:49,520 --> 00:15:53,480 Speaker 1: warn you they are incredibly difficult questions. So let's see 322 00:15:53,480 --> 00:15:57,200 Speaker 1: what we can do, all right. Question number one. This 323 00:15:57,280 --> 00:15:59,720 Speaker 1: superhero grew up on a farm in the town of 324 00:16:00,040 --> 00:16:03,240 Speaker 1: Malville and was raised by his adopted parents, Ma and 325 00:16:03,360 --> 00:16:07,000 Speaker 1: Paw Kent, who kept him away from Kryptonite. Who would 326 00:16:07,000 --> 00:16:12,520 Speaker 1: this be, Well, Superman, it's Clark Kent, alright, one for one. 327 00:16:12,640 --> 00:16:18,200 Speaker 1: Question number two. We'll see, we'll see. They may get harder, 328 00:16:18,320 --> 00:16:22,080 Speaker 1: so we're not alright, So here we go. This pop 329 00:16:22,160 --> 00:16:24,400 Speaker 1: star behind Shake It Off famously grew up on a 330 00:16:24,520 --> 00:16:27,920 Speaker 1: Christmas tree farm in Pennsylvania. Also, at the two thousand 331 00:16:28,000 --> 00:16:31,960 Speaker 1: ten Grammy Awards, she won more Grammys four than Elvis 332 00:16:32,000 --> 00:16:37,200 Speaker 1: would ever win. Being three. Who was this artist Taylor Swift? Wow? 333 00:16:37,640 --> 00:16:41,720 Speaker 1: So smart? Alright? Question number three? This Civil War general 334 00:16:41,760 --> 00:16:44,560 Speaker 1: who later became president went into the military because he 335 00:16:44,680 --> 00:16:47,960 Speaker 1: was a terrible farmer. Also, he once got a speeding 336 00:16:48,000 --> 00:16:51,520 Speaker 1: ticket for traveling too fast on his horse. Who would 337 00:16:51,520 --> 00:16:59,280 Speaker 1: this be? Oh? Wow, um wow, Yes, I have a 338 00:16:59,320 --> 00:17:00,760 Speaker 1: feeling he knew that when it was just kind of 339 00:17:00,800 --> 00:17:05,600 Speaker 1: pausing for dramatic effects. I think that's right. Well, I 340 00:17:05,600 --> 00:17:07,840 Speaker 1: almost said Abraham Lincoln, and then I was like, oh wait, 341 00:17:08,040 --> 00:17:13,399 Speaker 1: that's question number four. This Star Wars hero grew up 342 00:17:13,440 --> 00:17:16,760 Speaker 1: separate from his twin sister on a moisture farm in Tattooing. 343 00:17:17,200 --> 00:17:20,239 Speaker 1: This was years before he would train with Yoda. Who 344 00:17:20,320 --> 00:17:26,159 Speaker 1: are we talking? Oh this is Skywalker. Yes for the 345 00:17:26,240 --> 00:17:34,439 Speaker 1: final question, you know, take your satellites to that. All right, 346 00:17:34,480 --> 00:17:37,800 Speaker 1: here we go question number five. This rancher's daughter grew 347 00:17:37,880 --> 00:17:39,840 Speaker 1: up to be the first woman on the U. S. 348 00:17:39,880 --> 00:17:43,000 Speaker 1: Supreme Court. While serving on the court, she used to 349 00:17:43,080 --> 00:17:45,880 Speaker 1: run a jazzer size class in the building for clerks. 350 00:17:46,040 --> 00:17:49,520 Speaker 1: Who was this? Oh? Wow, do I get like a lifeline? 351 00:17:49,720 --> 00:17:53,000 Speaker 1: Can he go? Five for five? First woman on the U. S. 352 00:17:53,040 --> 00:17:59,640 Speaker 1: Supreme Court? The first woman on the U Supreme Court? Uh? 353 00:18:00,240 --> 00:18:02,159 Speaker 1: Do I get that? So? I'm no life? Can't call 354 00:18:02,240 --> 00:18:07,840 Speaker 1: my mom? Uh? So the middle name would be the 355 00:18:07,960 --> 00:18:16,359 Speaker 1: opposite of night Daddy O'Connor. So tell tell us what 356 00:18:16,720 --> 00:18:19,040 Speaker 1: tell us what he wanted today, Mango, Because Joshua an 357 00:18:19,080 --> 00:18:21,760 Speaker 1: astounding five for five. In addition to this hen written 358 00:18:21,800 --> 00:18:23,959 Speaker 1: note we're sending him, we're also going to send him 359 00:18:23,960 --> 00:18:26,680 Speaker 1: a sender day O'Connor finger puppet, which is a collector's 360 00:18:26,720 --> 00:18:29,520 Speaker 1: item because it's the only sender day O'Connor finger puppet 361 00:18:29,600 --> 00:18:33,399 Speaker 1: we could find online. So congratulations Josh so much for 362 00:18:33,480 --> 00:18:50,680 Speaker 1: playing Gosh. Thank you. So before we get back to 363 00:18:50,760 --> 00:18:52,760 Speaker 1: this question of how to feed the world, I want 364 00:18:52,800 --> 00:18:56,879 Speaker 1: to talk about carrots mango, specifically baby carrot. Okay, so 365 00:18:57,040 --> 00:18:59,159 Speaker 1: here's the thing. You and I have basically grown up 366 00:18:59,200 --> 00:19:02,320 Speaker 1: with baby carrots, right, They've always been around and offered 367 00:19:02,359 --> 00:19:05,720 Speaker 1: as this nutritious option with lunches and whatever. But the 368 00:19:05,800 --> 00:19:08,920 Speaker 1: truth is there a pretty recent invention. According to the 369 00:19:09,040 --> 00:19:11,119 Speaker 1: Carrot Museum, which, as you know, is my go to 370 00:19:11,320 --> 00:19:15,520 Speaker 1: for all carrot related knowledge, this California farmer, Mike Eurosic 371 00:19:16,000 --> 00:19:18,240 Speaker 1: was throwing out a ton of his carrot crop because 372 00:19:18,280 --> 00:19:21,240 Speaker 1: they looked deformed. They were perfectly good, but because consumers 373 00:19:21,280 --> 00:19:23,760 Speaker 1: don't want to buy a gnarled carrot, farmers in the 374 00:19:23,840 --> 00:19:26,680 Speaker 1: eighties would regularly toss out about a third of their crop. 375 00:19:27,160 --> 00:19:30,119 Speaker 1: So Eurosi decided why not try to remarket this thing. 376 00:19:30,520 --> 00:19:32,560 Speaker 1: He took a peeler and trimmed down the carrots and 377 00:19:32,640 --> 00:19:36,400 Speaker 1: came up with two varieties, baby carrots, which obviously took off, 378 00:19:37,000 --> 00:19:40,439 Speaker 1: and bunny balls, which did not. Yeah, I think they 379 00:19:40,480 --> 00:19:42,879 Speaker 1: were supposed to look like cheese balls, but I pretty 380 00:19:42,880 --> 00:19:44,920 Speaker 1: sure they could have used the different name. And while 381 00:19:44,960 --> 00:19:46,920 Speaker 1: this took place in the eighties, my point is this 382 00:19:47,200 --> 00:19:50,359 Speaker 1: their innovations, both big and small, which can create less 383 00:19:50,440 --> 00:19:53,600 Speaker 1: food waste. Carving a cute character two out of a bigger, 384 00:19:53,720 --> 00:19:56,600 Speaker 1: uglier carrot is certainly one thing. But here's something that's 385 00:19:56,640 --> 00:20:00,320 Speaker 1: even stranger. Scientists in Virginia Tech have figure down a 386 00:20:00,400 --> 00:20:02,680 Speaker 1: process to make the cob part of the corn on 387 00:20:02,760 --> 00:20:06,520 Speaker 1: the cob edible. Basically would turn all of that undigestible 388 00:20:06,600 --> 00:20:09,760 Speaker 1: cellulos into good starch, which would have the potential to 389 00:20:09,840 --> 00:20:13,160 Speaker 1: feed millions more people. That's so insane. Do you think 390 00:20:13,200 --> 00:20:15,440 Speaker 1: future generations will still eat corn the same way and 391 00:20:15,520 --> 00:20:18,280 Speaker 1: hold cobs horizontally like at a tradition or do you 392 00:20:18,320 --> 00:20:20,480 Speaker 1: think they'll start attacking it more like a banana. That's 393 00:20:20,520 --> 00:20:25,200 Speaker 1: a good question. Who knows. But here's another innovation. Apparently 394 00:20:25,280 --> 00:20:27,359 Speaker 1: scientists that Texas A and M figured out a way 395 00:20:27,440 --> 00:20:30,280 Speaker 1: to make cotton seed, which are currently poisonous, into an 396 00:20:30,440 --> 00:20:34,040 Speaker 1: edible product. And according to Scientific American, the proteins and 397 00:20:34,080 --> 00:20:36,640 Speaker 1: the cotton seed that are already being harvested every year 398 00:20:37,000 --> 00:20:41,200 Speaker 1: would be enough to feed five hundred million people. That's 399 00:20:41,400 --> 00:20:44,000 Speaker 1: that's just insane. So of the one billion people out 400 00:20:44,000 --> 00:20:46,520 Speaker 1: there going hungry right now, some crazy corn and cotton 401 00:20:46,560 --> 00:20:48,520 Speaker 1: seed could actually feed half of them. I mean, that's 402 00:20:48,560 --> 00:20:50,920 Speaker 1: assuming chefs can sell people on the taste. Yeah, I 403 00:20:50,960 --> 00:20:53,320 Speaker 1: guess that's true. Like how the US government taught people 404 00:20:53,400 --> 00:20:57,080 Speaker 1: to eat calamari, right right, Like back in the nineties, 405 00:20:57,160 --> 00:20:59,240 Speaker 1: the government was worried about over fishing off things like 406 00:20:59,320 --> 00:21:01,560 Speaker 1: cod and had dick, so they asked chefs and restaurants 407 00:21:01,600 --> 00:21:04,040 Speaker 1: to use squid as a replacement. And before then squid 408 00:21:04,160 --> 00:21:06,440 Speaker 1: was really only used for bait. And this is great 409 00:21:06,480 --> 00:21:08,600 Speaker 1: salon piece on this from two thousand fourteen, but the 410 00:21:08,680 --> 00:21:12,400 Speaker 1: government basically sent out approved test recipes and even encouraged 411 00:21:12,440 --> 00:21:14,560 Speaker 1: the use of the word calamari because it sounded so 412 00:21:14,680 --> 00:21:17,600 Speaker 1: much fancier and more exotic. But the funny thing is, 413 00:21:17,920 --> 00:21:21,280 Speaker 1: because restaurant owners didn't want to overwhelm customers, they only 414 00:21:21,359 --> 00:21:24,280 Speaker 1: serve the squid and appetizer form and that's mostly where 415 00:21:24,320 --> 00:21:26,359 Speaker 1: it stayed on menus. Well, they'll be surprised if you 416 00:21:26,400 --> 00:21:28,560 Speaker 1: see all you can eat cotton seed appetizers at your 417 00:21:28,600 --> 00:21:31,520 Speaker 1: local olive garden soon. But let's get back to farming, 418 00:21:31,800 --> 00:21:34,320 Speaker 1: because I think there's some interesting stuff we should talk about. 419 00:21:34,560 --> 00:21:36,280 Speaker 1: So one thing we should mention is that while food 420 00:21:36,320 --> 00:21:39,080 Speaker 1: waste and wealthy countries is mostly about people tossing out 421 00:21:39,200 --> 00:21:43,960 Speaker 1: leftovers and developing nations, it's mostly about food spoilage. Again, 422 00:21:44,040 --> 00:21:46,600 Speaker 1: this is something Nathaniel Johnson talks about, but he reports 423 00:21:46,640 --> 00:21:49,720 Speaker 1: that between thirty and forty percent of food grown around 424 00:21:49,760 --> 00:21:53,280 Speaker 1: the world is lost annually, whether that's spoilage from not 425 00:21:53,359 --> 00:21:57,000 Speaker 1: being sealed in airtight containers or being refrigerated properly, or 426 00:21:57,040 --> 00:21:59,600 Speaker 1: even things like vermin. And his point is if farmers 427 00:21:59,680 --> 00:22:02,399 Speaker 1: could deserve even a fraction of this food better, that 428 00:22:02,480 --> 00:22:06,240 Speaker 1: could actually lift their economic prospects, meaning hopefully less famine, 429 00:22:06,280 --> 00:22:08,720 Speaker 1: but also address some of the hunger issues. Well, I 430 00:22:08,840 --> 00:22:11,359 Speaker 1: know that's an area of study that's getting attention. Actually, 431 00:22:11,400 --> 00:22:14,200 Speaker 1: there's a super simple invention from the guy Mohammed bah 432 00:22:14,280 --> 00:22:17,400 Speaker 1: ah Bah of Nigeria, and it's one of my favorite things. 433 00:22:17,800 --> 00:22:19,880 Speaker 1: So you can guess that food spoilage is a particularly 434 00:22:19,920 --> 00:22:22,520 Speaker 1: big problem in tropical and desert regions where fruits and 435 00:22:22,600 --> 00:22:26,119 Speaker 1: vegetables can go bad quickly. But his non electric refrigerator 436 00:22:26,320 --> 00:22:29,560 Speaker 1: is so simple it's incredible. He basically showed that if 437 00:22:29,560 --> 00:22:31,880 Speaker 1: you take two earthen pots, and you fill the outer 438 00:22:32,000 --> 00:22:34,200 Speaker 1: pot with wet sand, and then put your food in 439 00:22:34,240 --> 00:22:36,280 Speaker 1: the inner pot, and you cover the system with a 440 00:22:36,320 --> 00:22:39,320 Speaker 1: wet cloth. Well, the evaporation from that wet sand will 441 00:22:39,400 --> 00:22:41,120 Speaker 1: suck the heat out of the inner pot and keep 442 00:22:41,160 --> 00:22:44,240 Speaker 1: the food chilled as low as four degrees fahrenheit. Yeah. 443 00:22:44,320 --> 00:22:47,680 Speaker 1: So Baba has given away hundreds of thousands of earthen 444 00:22:47,720 --> 00:22:50,240 Speaker 1: pots in the last decade or so to increase food security. 445 00:22:50,440 --> 00:22:52,320 Speaker 1: That is so cool. I believe he actually want a 446 00:22:52,400 --> 00:22:55,560 Speaker 1: Rolex Design Award for this simple yet elegant design. But 447 00:22:55,800 --> 00:22:58,679 Speaker 1: speaking of design, let's talk about the future of farming. Now, 448 00:22:58,760 --> 00:23:01,960 Speaker 1: let's skip over the robot pickers and driverless tractors and 449 00:23:02,119 --> 00:23:06,520 Speaker 1: get directly to vertical farms. I love vertical farms just 450 00:23:06,560 --> 00:23:09,200 Speaker 1: because they look so cool. And Jetson's like, I mean, 451 00:23:09,359 --> 00:23:12,199 Speaker 1: instead of doing your farming horizontally, why not just rotated 452 00:23:12,240 --> 00:23:15,560 Speaker 1: by ninety degrees. I love this idea too, so, especially 453 00:23:15,600 --> 00:23:18,240 Speaker 1: because it makes eating farm to table meals easier in 454 00:23:18,359 --> 00:23:21,119 Speaker 1: cities where there aren't large patches of green to farm on. 455 00:23:21,520 --> 00:23:23,240 Speaker 1: But what's interesting is that there are a lot of 456 00:23:23,320 --> 00:23:26,440 Speaker 1: people criticizing the idea. They see vertical farming as a 457 00:23:26,480 --> 00:23:29,240 Speaker 1: gimmick because to actually give each plant light and water 458 00:23:29,359 --> 00:23:32,239 Speaker 1: them indoors, you have to use electricity, which means you're 459 00:23:32,280 --> 00:23:34,919 Speaker 1: not taking advantage of all the natural resources that outdoor 460 00:23:35,000 --> 00:23:38,520 Speaker 1: farming does. So what's the solution. I know, they're floating farms, 461 00:23:38,600 --> 00:23:41,800 Speaker 1: where they're basically farming done on barges and man made islands, 462 00:23:41,880 --> 00:23:45,080 Speaker 1: but again I've read that's just a supplemented region's food security. 463 00:23:45,240 --> 00:23:46,760 Speaker 1: It couldn't be done in a big enough way to 464 00:23:46,920 --> 00:23:50,160 Speaker 1: really address hunger issues. Well, floating farms are definitely interesting, 465 00:23:50,280 --> 00:23:53,400 Speaker 1: but my favorite of the futuristic farms is the floating 466 00:23:53,600 --> 00:23:57,320 Speaker 1: vertical farms. Floating and vertical, best of both worlds. Yeah, 467 00:23:57,320 --> 00:23:59,840 Speaker 1: I mean these things are so theoretical, but they're beautiful. 468 00:24:00,040 --> 00:24:03,000 Speaker 1: And the outdoor floating vertical farm basically takes advantage of 469 00:24:03,080 --> 00:24:06,080 Speaker 1: the sun and rainwater, it doesn't need land to work, 470 00:24:06,160 --> 00:24:08,640 Speaker 1: and its shaped like a giant roller coaster loop, which 471 00:24:08,680 --> 00:24:11,520 Speaker 1: not only looks really cool, but avoids casting shadows on 472 00:24:11,640 --> 00:24:14,400 Speaker 1: the crops on the inside so they can get sunlight equally, 473 00:24:14,480 --> 00:24:17,560 Speaker 1: which is pretty cool. I mean, if we're talking pure theory, 474 00:24:17,680 --> 00:24:20,680 Speaker 1: and this isn't Jetson's futurism here, but it is idealistic. 475 00:24:21,000 --> 00:24:23,040 Speaker 1: The thing that totally blew me away was that if 476 00:24:23,080 --> 00:24:25,680 Speaker 1: we could use the available land in the Congo, that 477 00:24:25,720 --> 00:24:29,040 Speaker 1: could essentially feed all of Africa. Wait what, I know, 478 00:24:29,200 --> 00:24:31,520 Speaker 1: it sounded insane to me too, But according to the 479 00:24:31,640 --> 00:24:34,840 Speaker 1: u n's Food and Agricultural Organization, climate change is going 480 00:24:34,880 --> 00:24:37,960 Speaker 1: to aggravate food charges on the continent. But the Democratic 481 00:24:38,000 --> 00:24:41,280 Speaker 1: Republic of Congo is in this unique position. It has 482 00:24:41,359 --> 00:24:44,880 Speaker 1: giant territories on both sides of the equator. Basically, there's 483 00:24:44,920 --> 00:24:47,359 Speaker 1: always a rainy season in the country and only a 484 00:24:47,440 --> 00:24:49,960 Speaker 1: fraction of the arable land is being used. I mean, 485 00:24:50,080 --> 00:24:53,119 Speaker 1: apparently there are over eighty million hectares of land that 486 00:24:53,160 --> 00:24:55,960 Speaker 1: would be great for farms. And of course the DRC 487 00:24:56,080 --> 00:24:58,800 Speaker 1: has been rife with horrible wars and political issues that 488 00:24:58,880 --> 00:25:02,320 Speaker 1: have prevented that di element. But according to a UN representative, 489 00:25:02,520 --> 00:25:05,800 Speaker 1: the region has the potential defeat up to two billion people, 490 00:25:06,080 --> 00:25:09,840 Speaker 1: which if we're targeting, maybe that's enough time for the 491 00:25:09,880 --> 00:25:12,760 Speaker 1: country to solve its internal conflicts. Plus it only takes 492 00:25:12,800 --> 00:25:15,880 Speaker 1: our Iowa farm core like an hour on roads. Yeah, 493 00:25:15,960 --> 00:25:18,200 Speaker 1: making peace in the Congo and settling the land does 494 00:25:18,280 --> 00:25:20,960 Speaker 1: sound optimistic, but so do's trying to get the entire 495 00:25:21,000 --> 00:25:24,000 Speaker 1: world to go vegetarian, which we'll talk about after this break. 496 00:25:34,240 --> 00:25:36,480 Speaker 1: Over the past fifteen to twenty years, we've witnessed the 497 00:25:36,520 --> 00:25:39,840 Speaker 1: emergence of data and carefully gathered information being applied to 498 00:25:39,920 --> 00:25:42,480 Speaker 1: several different fields to make people more effective at what 499 00:25:42,640 --> 00:25:45,240 Speaker 1: they do and how they process the world around them, 500 00:25:45,560 --> 00:25:48,720 Speaker 1: whether that's recognized through stories like Moneyball and Baseball or 501 00:25:48,800 --> 00:25:51,359 Speaker 1: Nate Silver's five twenty nine. In the world of politics 502 00:25:51,440 --> 00:25:55,200 Speaker 1: and sports are through so many interesting works and behavioral economics. 503 00:25:55,280 --> 00:25:57,920 Speaker 1: It's been interesting to watch as scholars help us approach 504 00:25:58,000 --> 00:26:01,040 Speaker 1: these fields with careful reasoning and not just what our 505 00:26:01,080 --> 00:26:03,760 Speaker 1: gut tells us. And today's guest is helping the world 506 00:26:03,800 --> 00:26:06,720 Speaker 1: apply this kind of information gathering and careful reasoning to 507 00:26:06,800 --> 00:26:09,480 Speaker 1: the world of altruism. In fact, he's the founder of 508 00:26:09,520 --> 00:26:13,760 Speaker 1: a fascinating organization called Effective Altruism. Will mccaske all, welcome 509 00:26:13,800 --> 00:26:15,879 Speaker 1: to Part Time Genius. Thank you for having me on. 510 00:26:16,240 --> 00:26:17,720 Speaker 1: So we'll tell us a little bit about how you 511 00:26:17,840 --> 00:26:20,800 Speaker 1: got into this field and decided to start Effective Altruism. 512 00:26:21,440 --> 00:26:24,480 Speaker 1: I got into this field because I was deeply concerned 513 00:26:24,480 --> 00:26:27,240 Speaker 1: about a problem of global poverty. It seemed to me 514 00:26:27,440 --> 00:26:30,960 Speaker 1: that given that I was, you know, from the middle 515 00:26:31,000 --> 00:26:34,040 Speaker 1: class family of a well lost country, and there were 516 00:26:34,200 --> 00:26:37,359 Speaker 1: a billion people living on the time less than a 517 00:26:37,440 --> 00:26:41,320 Speaker 1: dollar a day, I just thought, well, why shouldn't I 518 00:26:41,440 --> 00:26:44,920 Speaker 1: be doing this? And I made a decision to give 519 00:26:44,920 --> 00:26:47,840 Speaker 1: away most of my income over the course of my life, 520 00:26:47,960 --> 00:26:50,960 Speaker 1: to set a cap at what's now about twenty five 521 00:26:51,400 --> 00:26:57,240 Speaker 1: pounds a year it's dollars, and give away everything above that. 522 00:26:57,840 --> 00:26:59,640 Speaker 1: Now I'm not going to be super rich, but I'm 523 00:26:59,640 --> 00:27:02,680 Speaker 1: going to have an okay income as an academic h 524 00:27:02,760 --> 00:27:04,680 Speaker 1: and so over the course of my life that would 525 00:27:04,720 --> 00:27:08,760 Speaker 1: be between one and two million dollars. And having made 526 00:27:08,800 --> 00:27:11,000 Speaker 1: that decision, I thought, well, this is now a pretty 527 00:27:11,040 --> 00:27:14,359 Speaker 1: big decision that I'm making in terms of trying to 528 00:27:14,440 --> 00:27:16,680 Speaker 1: help other people. And so I thought, well's what's absolutely 529 00:27:16,720 --> 00:27:20,000 Speaker 1: crucial is to figure out not just can I use 530 00:27:20,080 --> 00:27:22,280 Speaker 1: this money well or not or will it not be wasted? 531 00:27:22,600 --> 00:27:24,680 Speaker 1: But actually, how can I use this money to have 532 00:27:24,760 --> 00:27:28,639 Speaker 1: as big an impact as possible? And from that seeds 533 00:27:28,760 --> 00:27:32,280 Speaker 1: this general idea of asking the question, how can we 534 00:27:32,359 --> 00:27:35,080 Speaker 1: do as much good as possible with our time and money? 535 00:27:36,119 --> 00:27:39,240 Speaker 1: That could who game what's known as the effective answers. 536 00:27:39,680 --> 00:27:42,120 Speaker 1: How did your family react when you decided to catch 537 00:27:42,160 --> 00:27:45,360 Speaker 1: your salary and give the rest of it to charity. Honestly, 538 00:27:45,720 --> 00:27:50,320 Speaker 1: my mom said that's unethical. They took a while getting 539 00:27:50,359 --> 00:27:54,480 Speaker 1: into it, but now I think they're um supportive. It 540 00:27:54,640 --> 00:27:58,119 Speaker 1: was definitely, Yeah, I'd imagine that's that's such a big decision. 541 00:27:58,320 --> 00:28:00,960 Speaker 1: It's kind of incredible. Yeah, And so, well, what are 542 00:28:00,960 --> 00:28:03,240 Speaker 1: the biggest mistakes we tend to make in giving the charities? 543 00:28:03,600 --> 00:28:06,200 Speaker 1: I think one major mistake that we make is to 544 00:28:06,280 --> 00:28:10,160 Speaker 1: look at overheads costs. So that's where as a way 545 00:28:10,160 --> 00:28:13,800 Speaker 1: of assessing the efficiency of the charity, you look at 546 00:28:14,880 --> 00:28:18,159 Speaker 1: how much money does this charity spend on administration and 547 00:28:18,359 --> 00:28:21,280 Speaker 1: fund raising versus how much does it spend on the program. 548 00:28:22,040 --> 00:28:25,480 Speaker 1: And it's just a really bad way of assessing whether 549 00:28:25,520 --> 00:28:28,119 Speaker 1: the charity is good or not, because if the charity 550 00:28:28,200 --> 00:28:31,320 Speaker 1: is implementing some sort of lousy program, and there are 551 00:28:31,400 --> 00:28:34,120 Speaker 1: some programs that do nothing, some that are even harmful, 552 00:28:34,800 --> 00:28:38,280 Speaker 1: then no matter how low the overhead costs are, it's 553 00:28:38,320 --> 00:28:41,560 Speaker 1: still not going to be a good charity. Whereas you 554 00:28:41,600 --> 00:28:44,320 Speaker 1: could have a charity focused on a really effective program, 555 00:28:44,440 --> 00:28:46,480 Speaker 1: but it just needs to spend say a third of 556 00:28:46,560 --> 00:28:50,320 Speaker 1: its finances working out what are the most effective ways 557 00:28:50,360 --> 00:28:53,160 Speaker 1: to help. So, in general, what we should be thinking 558 00:28:53,200 --> 00:28:56,440 Speaker 1: about is how much money is going in and what's 559 00:28:56,480 --> 00:28:59,120 Speaker 1: the good outcomes that are coming out. And this is 560 00:28:59,200 --> 00:29:01,760 Speaker 1: just completely normal and how we think about perch in 561 00:29:01,840 --> 00:29:04,920 Speaker 1: goods in general. If you were deciding between buying a 562 00:29:05,040 --> 00:29:07,960 Speaker 1: mac work or buying a PC, you wouldn't ask yourself 563 00:29:08,080 --> 00:29:10,000 Speaker 1: or how much does tin cook get paid or how 564 00:29:10,080 --> 00:29:12,520 Speaker 1: much are they spending on the administration. You just care 565 00:29:12,560 --> 00:29:14,880 Speaker 1: about the quality of the product and how much that 566 00:29:14,960 --> 00:29:18,000 Speaker 1: product cost m So how does someone as an outsider 567 00:29:18,160 --> 00:29:21,240 Speaker 1: figure this out? You know, like if the standard person 568 00:29:21,320 --> 00:29:22,960 Speaker 1: at home trying to figure out, like I I know 569 00:29:23,080 --> 00:29:24,640 Speaker 1: I want to give a little bit of money to charity, 570 00:29:24,720 --> 00:29:27,880 Speaker 1: what's the best way to make sure it is effective? Yeah? 571 00:29:28,000 --> 00:29:30,440 Speaker 1: I think the key thing to bear in mind is 572 00:29:30,640 --> 00:29:33,040 Speaker 1: just in the same way as you know, most people 573 00:29:33,120 --> 00:29:35,600 Speaker 1: shouldn't find invest on their own because it's just too 574 00:29:35,680 --> 00:29:38,080 Speaker 1: hard and you're going to end up getting burned. In 575 00:29:38,160 --> 00:29:40,200 Speaker 1: the same way when it comes to charities, I think 576 00:29:40,240 --> 00:29:42,920 Speaker 1: the best thing to do is just to find some 577 00:29:43,080 --> 00:29:46,880 Speaker 1: experts really trust and then go on the basis of 578 00:29:46,960 --> 00:29:52,960 Speaker 1: their recommendations, and the two places that I recommend most highly. 579 00:29:53,080 --> 00:29:56,920 Speaker 1: One is give Well that Give Wealth, the organ which 580 00:29:57,760 --> 00:30:05,640 Speaker 1: makes recommendations charvities that do more quantifiable UM interventions working 581 00:30:05,680 --> 00:30:08,880 Speaker 1: in the developing world to improve bubal health and development, 582 00:30:09,360 --> 00:30:12,520 Speaker 1: such as the Against Malaria Foundation that I mentioned. And 583 00:30:13,160 --> 00:30:17,920 Speaker 1: then the alternative is at my own organization. On the 584 00:30:17,960 --> 00:30:21,160 Speaker 1: website effective Altism dot org. You can go to donate 585 00:30:21,200 --> 00:30:25,400 Speaker 1: effectively and you can choose one of three different cause areas, 586 00:30:25,480 --> 00:30:28,640 Speaker 1: so global health and development is one, but also farm 587 00:30:28,680 --> 00:30:33,640 Speaker 1: animal welfare and programs to have a positive impact on 588 00:30:33,680 --> 00:30:39,320 Speaker 1: the very long run future of human civilization and which 589 00:30:39,360 --> 00:30:43,640 Speaker 1: we have identified as particularly neglected and high priority causes UM. 590 00:30:43,960 --> 00:30:47,000 Speaker 1: And then an expert will return one of the most 591 00:30:47,040 --> 00:30:49,560 Speaker 1: effective chravities to be giving to in these areas and 592 00:30:49,640 --> 00:30:52,360 Speaker 1: then donate. So you might not get quite the same 593 00:30:52,520 --> 00:30:56,440 Speaker 1: kind of warm glow or warm fuzzy feelings from donating 594 00:30:56,480 --> 00:30:59,440 Speaker 1: through this, but you will have pens or hundreds of 595 00:30:59,480 --> 00:31:02,280 Speaker 1: times when potentially well, thank you so much for giving 596 00:31:02,320 --> 00:31:04,600 Speaker 1: us so much to uh to think about. And as 597 00:31:04,640 --> 00:31:07,480 Speaker 1: our way of saying thank you, we want to we 598 00:31:07,560 --> 00:31:09,400 Speaker 1: want to give you one of our quizzes that we 599 00:31:09,520 --> 00:31:12,760 Speaker 1: have and in every episode, so h so, so mango? 600 00:31:12,840 --> 00:31:14,760 Speaker 1: What game are we playing with Will today? This is 601 00:31:14,800 --> 00:31:17,680 Speaker 1: a game called Who Is the World? And it's pretty simple. Basically, 602 00:31:17,680 --> 00:31:19,040 Speaker 1: we're going to give you a clue about one of 603 00:31:19,120 --> 00:31:22,040 Speaker 1: the many many musicians who participated in We Are the World, 604 00:31:22,160 --> 00:31:23,880 Speaker 1: and you have to guess who it is. So We 605 00:31:24,000 --> 00:31:26,480 Speaker 1: Are the World was the epic nineteen eighties supergroup song 606 00:31:26,600 --> 00:31:29,720 Speaker 1: that raised over sixty one million dollars for humanitarian aid 607 00:31:29,760 --> 00:31:32,640 Speaker 1: in Africa, and there were a lot of famous people singing. 608 00:31:33,000 --> 00:31:34,920 Speaker 1: So we're going to give you a weird clue about 609 00:31:34,960 --> 00:31:37,040 Speaker 1: one of the singers and you just have to guess 610 00:31:37,080 --> 00:31:39,120 Speaker 1: who it is. Are you ready to play Who Was 611 00:31:39,200 --> 00:31:44,240 Speaker 1: the World? Okay, here we go, alright? Question question number 612 00:31:44,280 --> 00:31:46,800 Speaker 1: one this We Are the World. Singer used to be 613 00:31:46,880 --> 00:31:49,760 Speaker 1: in a band with Art Garfunkle, where his hit song Mrs. 614 00:31:49,880 --> 00:31:55,360 Speaker 1: Robinson was originally titled Mrs Roosevelt? Who are we talking about? Simon? 615 00:31:55,560 --> 00:31:58,280 Speaker 1: You got it? Exactually the song was originally about Eleanor 616 00:31:58,400 --> 00:32:01,040 Speaker 1: Roosevelt before the lyrics were changed. All right, he's one 617 00:32:01,160 --> 00:32:04,960 Speaker 1: for one. Question number two, This We Are the World 618 00:32:05,040 --> 00:32:08,000 Speaker 1: folk singer and recent award winner of a Nobel Prize 619 00:32:08,040 --> 00:32:12,720 Speaker 1: in Literature famously introduced the Beatles to pot He also 620 00:32:12,840 --> 00:32:15,760 Speaker 1: took a week long vow of silence when Elvis Presley 621 00:32:15,840 --> 00:32:18,920 Speaker 1: passed away. Who are we talking about? I didn't know 622 00:32:19,040 --> 00:32:24,200 Speaker 1: those facts. It sounds like Bob Dylan. Al Right, he's 623 00:32:24,240 --> 00:32:27,560 Speaker 1: two for two, three left, Here we go. Before his death, 624 00:32:27,720 --> 00:32:29,800 Speaker 1: This We Are the World singer was trying to build 625 00:32:29,840 --> 00:32:33,240 Speaker 1: a fifty foot robot replica of himself that would wander 626 00:32:33,320 --> 00:32:37,000 Speaker 1: the Las Vegas desert with giant laser lights. You might 627 00:32:37,120 --> 00:32:42,760 Speaker 1: know him better as the King of Pop. Oh, good guests, 628 00:32:42,960 --> 00:32:45,600 Speaker 1: but this was actually who was at Mango? Michael Jackson. 629 00:32:45,800 --> 00:32:49,840 Speaker 1: Michael Jackson, Michael Jackson cool? Alright's okay, here we go, 630 00:32:50,680 --> 00:32:53,120 Speaker 1: This we are the World. R and B Legend claimed 631 00:32:53,160 --> 00:32:56,600 Speaker 1: that Mick Jagger stole a number of her moves when 632 00:32:56,680 --> 00:32:59,840 Speaker 1: she and her former husband Ike opened for the Stones 633 00:33:00,040 --> 00:33:03,200 Speaker 1: in the nineteen sixties. Who do you think this is? 634 00:33:03,800 --> 00:33:06,320 Speaker 1: She has the most famous legs and show business. According 635 00:33:06,360 --> 00:33:17,400 Speaker 1: to George W. Bush, you know I was born you 636 00:33:17,480 --> 00:33:21,160 Speaker 1: were born in nine seven. This is unbelievable what you've accomplished. 637 00:33:21,200 --> 00:33:24,160 Speaker 1: That had no idea? Okay, this was who was this? 638 00:33:24,280 --> 00:33:29,560 Speaker 1: Mango it's Tina Turner. Tina Turner. Alright, so this last one, 639 00:33:29,680 --> 00:33:32,680 Speaker 1: here we go, this we are the World Star was 640 00:33:32,720 --> 00:33:36,080 Speaker 1: actually a Bible salesman before he became a country star. 641 00:33:36,640 --> 00:33:43,040 Speaker 1: You might know him better as the red Headed Stranger. Yes, 642 00:33:43,480 --> 00:33:46,440 Speaker 1: Willie Nelson, exactly Nelson. All right, So how did we'll 643 00:33:46,520 --> 00:33:50,320 Speaker 1: do today? Mango? Will went three for five, which still 644 00:33:50,480 --> 00:33:55,920 Speaker 1: entitles him for our biggest prize, our total admirations. Congratulations. Well, 645 00:33:57,040 --> 00:33:59,920 Speaker 1: thank you, so I hope everyone will check out effect 646 00:34:00,000 --> 00:34:02,320 Speaker 1: Altruism will Thank you again for all the work that 647 00:34:02,400 --> 00:34:04,360 Speaker 1: you're doing and for really giving us a lot to 648 00:34:04,440 --> 00:34:06,600 Speaker 1: think about. Okay, well, thank you for having me on. 649 00:34:20,800 --> 00:34:23,520 Speaker 1: So let's talk about vegetarianism, which is often touted as 650 00:34:23,600 --> 00:34:25,920 Speaker 1: one way to help be the world. You were vegetarian 651 00:34:25,960 --> 00:34:28,680 Speaker 1: for a while. Why did you fall off the wagon? Yeah? 652 00:34:28,840 --> 00:34:31,239 Speaker 1: I was a vegining from about age twelve until I 653 00:34:31,320 --> 00:34:33,560 Speaker 1: was twenty two, I think, and then I moved to Alabama. 654 00:34:33,880 --> 00:34:36,880 Speaker 1: That's right. I do have to say when you finally 655 00:34:36,920 --> 00:34:39,160 Speaker 1: decided to eat meat, and we went to dream Land 656 00:34:39,200 --> 00:34:42,400 Speaker 1: barbecue that only serves ribs and watched you eat that 657 00:34:42,560 --> 00:34:45,719 Speaker 1: single rib slowly, just kind of licking at it. That 658 00:34:45,920 --> 00:34:48,680 Speaker 1: has to be one of the weirdest things I've ever watched. 659 00:34:49,200 --> 00:34:51,719 Speaker 1: But that's exactly the problem. Like, we made that pilgrimage, 660 00:34:51,800 --> 00:34:54,600 Speaker 1: which was so amazing because it's just a shack in Tuscaloosa, 661 00:34:54,960 --> 00:34:56,680 Speaker 1: but when we got there, the only things on the 662 00:34:56,760 --> 00:34:58,960 Speaker 1: menu were a rack and a half rack. I mean, 663 00:34:59,040 --> 00:35:02,960 Speaker 1: the half rack is the vegetarian option. Also, the T 664 00:35:03,080 --> 00:35:05,439 Speaker 1: shirts are just amazing because there's just you know, there's 665 00:35:05,480 --> 00:35:07,480 Speaker 1: like the white shirt with the hand Dan's just like 666 00:35:08,400 --> 00:35:12,640 Speaker 1: pulling across the shirts so groty good. I love it. 667 00:35:13,080 --> 00:35:16,240 Speaker 1: But let's not talk about my inability to commit to vegetarianism. 668 00:35:16,360 --> 00:35:19,759 Speaker 1: Let's talk about the world's inability to commit to vegetarianism. Yeah, 669 00:35:19,840 --> 00:35:22,080 Speaker 1: so this is how our power researcher Gabe explained it 670 00:35:22,120 --> 00:35:24,520 Speaker 1: to me. Basically, the world would be better off if 671 00:35:24,600 --> 00:35:27,600 Speaker 1: we were vegetarian. The meat industry is responsible for about 672 00:35:27,680 --> 00:35:30,600 Speaker 1: fifteen percent of the world's greenhouse gas emissions, and all 673 00:35:30,680 --> 00:35:33,280 Speaker 1: that grazing land, which if you added up, is about 674 00:35:33,360 --> 00:35:36,120 Speaker 1: the size of Africa, could be better used for growing 675 00:35:36,200 --> 00:35:39,560 Speaker 1: other foods. But the problem with everyone going cold Turkey 676 00:35:39,680 --> 00:35:41,640 Speaker 1: vegetarian is that there are a lot of people who 677 00:35:41,719 --> 00:35:44,880 Speaker 1: make their livelihood off the production and sale of animal products. 678 00:35:45,200 --> 00:35:48,360 Speaker 1: In fact, it's over a billion people, and the majority 679 00:35:48,400 --> 00:35:51,320 Speaker 1: are small scale farmers in developing nations. So if the 680 00:35:51,360 --> 00:35:54,359 Speaker 1: world just switched to being vegetarian overnight, not only would 681 00:35:54,400 --> 00:35:56,680 Speaker 1: jobs be lost, but good meat would be wasted and 682 00:35:56,760 --> 00:35:59,560 Speaker 1: people would starve. But if we made a slow switch, 683 00:35:59,719 --> 00:36:01,520 Speaker 1: any eased then to it kind of like dipping your 684 00:36:01,520 --> 00:36:04,480 Speaker 1: toe into pool. But doesn't that feel impractical too. I 685 00:36:04,520 --> 00:36:07,040 Speaker 1: can't imagine convincing any of my state loving friends that 686 00:36:07,040 --> 00:36:09,759 Speaker 1: they should go vegetarian. Yeah, it's certainly going against the grain. 687 00:36:09,840 --> 00:36:11,880 Speaker 1: I mean, four to five percent of the population in 688 00:36:11,920 --> 00:36:14,799 Speaker 1: the US is vegetarian right now, and when the money 689 00:36:14,840 --> 00:36:17,680 Speaker 1: flows into places like India and China, the populations that 690 00:36:17,840 --> 00:36:21,000 Speaker 1: gain wealth are actually using that money to eat more meat. 691 00:36:21,760 --> 00:36:23,759 Speaker 1: Of course, one glimmer of hope here is that meat 692 00:36:23,840 --> 00:36:26,960 Speaker 1: substitutes are getting better and better. Their seaweed that was 693 00:36:27,000 --> 00:36:29,719 Speaker 1: recently discovered that tastes like bacon. I'll believe it when 694 00:36:29,760 --> 00:36:32,640 Speaker 1: I taste it, which is certainly a start. Their new 695 00:36:32,719 --> 00:36:35,680 Speaker 1: plant based products like beyond meat and the impossible burger 696 00:36:35,760 --> 00:36:39,040 Speaker 1: that supposedly taste like beef, and even ooze fats was 697 00:36:39,360 --> 00:36:42,719 Speaker 1: squeezed on a drill, and their cultured meats or test 698 00:36:42,760 --> 00:36:45,040 Speaker 1: tube meets, which are still a decade or so away, 699 00:36:45,520 --> 00:36:47,799 Speaker 1: will basically grow meat in a lab without ever having 700 00:36:47,840 --> 00:36:50,640 Speaker 1: an animal involved, which is all awesome, but let's get 701 00:36:50,680 --> 00:36:52,800 Speaker 1: back to the original question, what will it take to 702 00:36:52,880 --> 00:36:55,879 Speaker 1: feed the world. I mean, clearly it's complicated and there's 703 00:36:55,920 --> 00:36:59,640 Speaker 1: no silver bullet solution, so people are trying everything. There's 704 00:36:59,680 --> 00:37:03,719 Speaker 1: talk of flour made from insects, there's precision agriculture, which 705 00:37:03,719 --> 00:37:07,240 Speaker 1: could use technology to monitor crop health and increase crop yields. 706 00:37:07,719 --> 00:37:10,960 Speaker 1: There's so many potential solutions for slivers of the problem. 707 00:37:11,360 --> 00:37:14,040 Speaker 1: Plus all the things that we talked about, new styles 708 00:37:14,080 --> 00:37:17,600 Speaker 1: of farming edible cotton seeds, reducing food waste and developing 709 00:37:17,719 --> 00:37:21,360 Speaker 1: nations a reduction and how much meat wheat, oh and 710 00:37:21,480 --> 00:37:24,919 Speaker 1: possibly farming the congo to All of those things would 711 00:37:24,960 --> 00:37:27,200 Speaker 1: get us there, and also just trying to help lift 712 00:37:27,280 --> 00:37:29,399 Speaker 1: the poorest to the poor out of poverty by giving 713 00:37:29,440 --> 00:37:32,680 Speaker 1: them better roads and access to information. But all of 714 00:37:32,760 --> 00:37:35,759 Speaker 1: that would take real, unified commitment from a number of 715 00:37:35,840 --> 00:37:39,320 Speaker 1: big countries and that's a difficult path. But the interesting 716 00:37:39,400 --> 00:37:42,240 Speaker 1: thing is there are a lot of positive indicators. For instance, 717 00:37:42,280 --> 00:37:44,759 Speaker 1: in two thousand fifteen, the UN announced there were nearly 718 00:37:44,840 --> 00:37:47,879 Speaker 1: eight hundred million under nourished people in the world, which 719 00:37:48,000 --> 00:37:50,399 Speaker 1: is a lot, but that number was actually down two 720 00:37:50,920 --> 00:37:54,160 Speaker 1: million from the nineteen nineties, despite there being two billion 721 00:37:54,200 --> 00:37:56,520 Speaker 1: more people living on the planet now. So a lot 722 00:37:56,560 --> 00:37:59,200 Speaker 1: of economists and journalists are actually hopeful, which is a 723 00:37:59,239 --> 00:38:01,400 Speaker 1: good thing. That is a good thing. And speaking of 724 00:38:01,480 --> 00:38:03,160 Speaker 1: good things, what do you say we indulge in a 725 00:38:03,360 --> 00:38:17,160 Speaker 1: friendly little fact off? M m m. It sounds so 726 00:38:17,239 --> 00:38:19,719 Speaker 1: much more menacing when you put it though, but let's 727 00:38:19,760 --> 00:38:21,239 Speaker 1: do it all right. Here's a sweet one to kick 728 00:38:21,239 --> 00:38:23,120 Speaker 1: it off. Did you know that if we switch from 729 00:38:23,160 --> 00:38:26,040 Speaker 1: using sugarcane is the source of sugar to sugar beets, 730 00:38:26,400 --> 00:38:29,080 Speaker 1: we would save over two hundred thousand gallons of water 731 00:38:29,280 --> 00:38:32,000 Speaker 1: per ton of sugar produced, which could be channeled into 732 00:38:32,080 --> 00:38:35,080 Speaker 1: growing bananas or something else. I guess no, I think 733 00:38:35,160 --> 00:38:38,920 Speaker 1: it has to be bananas. Did you know in Congress 734 00:38:39,000 --> 00:38:42,400 Speaker 1: nearly passed an American hippo bill? Didn't The idea was 735 00:38:42,480 --> 00:38:45,080 Speaker 1: to bring hippos to the Bayou to eat invasive plants 736 00:38:45,280 --> 00:38:48,160 Speaker 1: while using them as a new meat source, and editorial 737 00:38:48,239 --> 00:38:50,440 Speaker 1: pages of the time praised the idea and called Hippo's 738 00:38:50,880 --> 00:38:54,960 Speaker 1: Lake Cow Bacon Lake bake it all right. So I'm 739 00:38:55,000 --> 00:38:57,360 Speaker 1: feering off course here because you used the hippo facts 740 00:38:57,520 --> 00:39:00,799 Speaker 1: and I'm going to match you with another hippo. Did 741 00:39:00,880 --> 00:39:03,239 Speaker 1: you know that the eighteen fifties England went through an 742 00:39:03,280 --> 00:39:06,120 Speaker 1: intense phase of hippo mania when the first one, named 743 00:39:06,160 --> 00:39:09,520 Speaker 1: o Bas was brought to the London Zoo. So thousands 744 00:39:09,560 --> 00:39:12,640 Speaker 1: of visitors each day crowded and to see him. Novelty 745 00:39:12,719 --> 00:39:15,440 Speaker 1: hippos were sold, and there was even a popular polka 746 00:39:15,480 --> 00:39:18,160 Speaker 1: written for him. O Bach was so popular that Charles 747 00:39:18,239 --> 00:39:21,759 Speaker 1: Dickens was jealous of all the attention he received. That's 748 00:39:21,800 --> 00:39:24,880 Speaker 1: so good, you know, I can't top a Dickens hippo fact. 749 00:39:25,239 --> 00:39:27,200 Speaker 1: So I'm gonna bring it back state side. Do you 750 00:39:27,239 --> 00:39:29,560 Speaker 1: know that David Copperfield tried to launch a magic themed 751 00:39:29,600 --> 00:39:32,680 Speaker 1: restaurant in Times Square? According to the New York Times, 752 00:39:32,719 --> 00:39:35,680 Speaker 1: the restaurant was supposed to have seventy foot gargoyles, a 753 00:39:35,800 --> 00:39:38,160 Speaker 1: bar and banquette that looked like it was floating on air, 754 00:39:38,520 --> 00:39:41,240 Speaker 1: sections of tables that would disappear from view on occasion. 755 00:39:41,680 --> 00:39:44,120 Speaker 1: And this is the best part. Every hour, a giant 756 00:39:44,200 --> 00:39:46,359 Speaker 1: spinning saw would appear to cut a dinner guest into 757 00:39:46,520 --> 00:39:49,080 Speaker 1: how nice. That's a nice touch. Of course, the Time's 758 00:39:49,160 --> 00:39:51,319 Speaker 1: article claimed the greatest trick about the place was how 759 00:39:51,719 --> 00:39:54,680 Speaker 1: thirty four million dollars in investment magically disappeared in the 760 00:39:54,680 --> 00:39:57,520 Speaker 1: restaurant never came to be. It's quite the trick. That's 761 00:39:57,560 --> 00:40:00,440 Speaker 1: pretty brutal. All right, here's a strange one. According to 762 00:40:00,520 --> 00:40:04,480 Speaker 1: a two thousand fourteen study from Westminster University, hungry men 763 00:40:04,719 --> 00:40:07,919 Speaker 1: find heavier women more attractive, and it goes the same 764 00:40:08,000 --> 00:40:10,920 Speaker 1: way for women. They like their men huskier when they're hungry. 765 00:40:11,280 --> 00:40:14,080 Speaker 1: Apparently it takes about six hours of not eating for 766 00:40:14,200 --> 00:40:18,480 Speaker 1: your preferences to change. Um. So, Eric Carl's The Very 767 00:40:18,560 --> 00:40:22,400 Speaker 1: Hungry Caterpillar was originally about a bookworm named Willie. The 768 00:40:22,480 --> 00:40:24,759 Speaker 1: book changed when Eric and his editor realized there was 769 00:40:24,800 --> 00:40:27,120 Speaker 1: no transformation. At the end of the book, the bookworm 770 00:40:27,239 --> 00:40:29,400 Speaker 1: was just fatter instead of, you know, turning into a 771 00:40:29,400 --> 00:40:34,480 Speaker 1: beautiful biter pie. Alright, So at nine study on leeches 772 00:40:35,000 --> 00:40:39,560 Speaker 1: found that drinking beer makes leeches lazy and undisciplined. Yeah, 773 00:40:39,560 --> 00:40:41,960 Speaker 1: and apparently they're attracted to garlic, but if they eat 774 00:40:42,000 --> 00:40:44,480 Speaker 1: too much of it, it kills them just like vampires. 775 00:40:44,680 --> 00:40:46,719 Speaker 1: That's brilliant. I know. The authors of the study even 776 00:40:46,760 --> 00:40:49,399 Speaker 1: went on to win an Ignoble prize for their research. Well, 777 00:40:49,520 --> 00:40:51,840 Speaker 1: if feeding beer to leeches is good enough for the ignobles, 778 00:40:51,880 --> 00:40:53,839 Speaker 1: it's good enough for me. I think you win this round. 779 00:40:53,960 --> 00:40:56,600 Speaker 1: And speaking of prizes, who do you think we should 780 00:40:56,600 --> 00:40:58,480 Speaker 1: give today's award too? Well? I kind of want to 781 00:40:58,480 --> 00:41:00,279 Speaker 1: give it to whoever came up with the phrase late 782 00:41:00,360 --> 00:41:03,399 Speaker 1: cow bacon as a synonym for hippopotamus, But I think 783 00:41:03,440 --> 00:41:06,160 Speaker 1: a better winner might be the inventor Sarah Collins, who 784 00:41:06,239 --> 00:41:10,560 Speaker 1: invented the Wonder Bag. It's this amazing invention that's basically 785 00:41:10,600 --> 00:41:13,560 Speaker 1: a non electric slow cooker where you bring your ingredients 786 00:41:13,600 --> 00:41:15,759 Speaker 1: to a boil in a pan or a pot, then 787 00:41:15,840 --> 00:41:17,840 Speaker 1: wrap them in this bag and it keeps them cooking 788 00:41:17,920 --> 00:41:21,320 Speaker 1: for you. The amazing thing is that of staple foods 789 00:41:21,360 --> 00:41:24,239 Speaker 1: cooked in Africa end up burned because they're cooked on 790 00:41:24,320 --> 00:41:26,799 Speaker 1: an open fire. So this not only saves food from 791 00:41:26,840 --> 00:41:29,520 Speaker 1: being wasted, but it also saves a considerable amount of 792 00:41:29,560 --> 00:41:32,319 Speaker 1: money on energy and allows families to do other things 793 00:41:32,400 --> 00:41:35,200 Speaker 1: instead of spending so much time gathering firewood and tending 794 00:41:35,239 --> 00:41:38,399 Speaker 1: to fires. Plus it's got a great name, the wonder Bag. 795 00:41:38,760 --> 00:41:41,279 Speaker 1: Wonder Bag. I like it. Sarah Collins, you'll be getting 796 00:41:41,280 --> 00:41:43,120 Speaker 1: a certificate from us in the mail to put on 797 00:41:43,200 --> 00:41:45,480 Speaker 1: your fridge. And I think that's it for today's episode 798 00:41:45,480 --> 00:41:59,759 Speaker 1: of Part Time Genius. Thanks so much for listening, k 799 00:42:01,920 --> 00:42:04,120 Speaker 1: Thanks again for listening to Part Time Genius. Be sure 800 00:42:04,160 --> 00:42:06,560 Speaker 1: to subscribe wherever you listen to your podcast, And because 801 00:42:06,600 --> 00:42:08,880 Speaker 1: we're a brand new show, if you're feeling extra generous, 802 00:42:08,920 --> 00:42:10,239 Speaker 1: we'd love it if you'd give us a rating on 803 00:42:10,320 --> 00:42:13,279 Speaker 1: Apple Podcast. Part Time Genius is produced by some of 804 00:42:13,360 --> 00:42:16,600 Speaker 1: our favorite geniuses. It's edited by Tristan McNeil, theme song 805 00:42:16,680 --> 00:42:19,520 Speaker 1: and audio mixing by Noel Brown. Our executive producer is 806 00:42:19,600 --> 00:42:22,960 Speaker 1: Jerry Rowland. Our research team is Gabe Bluesier, Lucas Adams, 807 00:42:23,040 --> 00:42:26,800 Speaker 1: Autum white Field, Madronto, Austin Thompson and Meg Robbins. Jason 808 00:42:26,840 --> 00:42:28,040 Speaker 1: Hok is our chief cheer leader.