1 00:00:04,440 --> 00:00:12,080 Speaker 1: Text technology with tech Stuff from half stuff works dot com. 2 00:00:12,119 --> 00:00:15,320 Speaker 1: Hey there, and welcome to tech Stuff. I'm Jonathan Strickland, 3 00:00:15,320 --> 00:00:18,000 Speaker 1: an executive producer here at how stuff Works, and I 4 00:00:18,160 --> 00:00:22,320 Speaker 1: love all things tech, and today we're going to take 5 00:00:22,360 --> 00:00:25,119 Speaker 1: a ride with Uber. Actually, this is going to be 6 00:00:25,120 --> 00:00:28,440 Speaker 1: a two part episode because even though Uber as a 7 00:00:28,480 --> 00:00:32,880 Speaker 1: company is only about a decade old, the story is 8 00:00:32,920 --> 00:00:35,199 Speaker 1: a really complicated one and it has a lot of 9 00:00:35,240 --> 00:00:38,960 Speaker 1: consequences that are rippled into other areas of the text 10 00:00:39,000 --> 00:00:42,559 Speaker 1: space and beyond. And the Uber story isn't just a 11 00:00:42,680 --> 00:00:45,760 Speaker 1: tale about a startup that hit the big time, although 12 00:00:46,320 --> 00:00:48,920 Speaker 1: it is that in part, but it's also a story 13 00:00:48,960 --> 00:00:54,520 Speaker 1: about disruption, automation, corporate culture, and controversy. So this first 14 00:00:54,520 --> 00:00:57,080 Speaker 1: episode is really going to be about the founding of 15 00:00:57,120 --> 00:01:00,880 Speaker 1: the company and the challenges that it faced getting started, 16 00:01:01,080 --> 00:01:03,920 Speaker 1: as well as it's early rise to prominence in the 17 00:01:03,960 --> 00:01:07,080 Speaker 1: text sphere. In the second part will take a closer 18 00:01:07,120 --> 00:01:10,240 Speaker 1: look at what the company has been up to over 19 00:01:10,280 --> 00:01:15,600 Speaker 1: the past few years, but mainly throughout seventeen because that 20 00:01:15,720 --> 00:01:21,320 Speaker 1: was a truly tumultuous year in Uber's history. But I 21 00:01:21,319 --> 00:01:23,880 Speaker 1: thought it would be helpful to begin by looking at 22 00:01:23,920 --> 00:01:28,200 Speaker 1: the co founder of Uber, whose behavior at times seemed 23 00:01:28,200 --> 00:01:30,720 Speaker 1: to be closely aligned with some of the more criticized 24 00:01:30,720 --> 00:01:34,120 Speaker 1: elements of the company's overall culture. This is a guy 25 00:01:34,240 --> 00:01:38,400 Speaker 1: who has received a lot of attention, both positive and 26 00:01:38,560 --> 00:01:43,160 Speaker 1: negative throughout the years, and that co founder is Travis 27 00:01:43,240 --> 00:01:48,600 Speaker 1: clanic Uh. He is a bit of a character. I mean, 28 00:01:48,640 --> 00:01:53,440 Speaker 1: he definitely has earned himself a reputation among the Silicon 29 00:01:53,600 --> 00:01:59,040 Speaker 1: Valley as someone who is really aggressive and really visionary 30 00:01:59,120 --> 00:02:02,680 Speaker 1: in many ways. But who is he? Where did he 31 00:02:02,760 --> 00:02:06,400 Speaker 1: come from? And how did the idea of Uber come about? Well, 32 00:02:07,160 --> 00:02:10,680 Speaker 1: spoiler alert, the story I'm about to tell you is 33 00:02:10,680 --> 00:02:16,080 Speaker 1: only half the tail. This is the official story of Uber, 34 00:02:16,160 --> 00:02:19,880 Speaker 1: the one that the company lists as its own history, 35 00:02:20,200 --> 00:02:24,200 Speaker 1: and it traces everything back to a cold winter's evening 36 00:02:24,360 --> 00:02:27,120 Speaker 1: in France in two thousand and eight. But the truth 37 00:02:27,840 --> 00:02:30,880 Speaker 1: ends up being a little more complicated. But let's start 38 00:02:30,880 --> 00:02:35,079 Speaker 1: with Klanic. So he attended the University of California, Los Angeles. 39 00:02:35,080 --> 00:02:39,040 Speaker 1: He majored in computer engineering, but he never graduated. He 40 00:02:39,320 --> 00:02:43,600 Speaker 1: dropped out just a few months away from graduating in 41 00:02:43,600 --> 00:02:47,520 Speaker 1: that final year in nineteen and he went on to 42 00:02:47,639 --> 00:02:50,280 Speaker 1: go work as part of the original team behind a 43 00:02:50,400 --> 00:02:55,480 Speaker 1: business called Scour s c O. You are. Now. That 44 00:02:55,680 --> 00:02:58,640 Speaker 1: might not sound familiar to you, and that would not 45 00:02:58,800 --> 00:03:01,799 Speaker 1: be a big surprise because it didn't last that long. 46 00:03:01,880 --> 00:03:05,119 Speaker 1: Within a few years of its founding, it was obliterated 47 00:03:05,200 --> 00:03:09,800 Speaker 1: out of existence. But I'll explain. Scour was a peer 48 00:03:09,840 --> 00:03:13,080 Speaker 1: to peer file sharing service. Now, that means you could 49 00:03:13,080 --> 00:03:16,320 Speaker 1: download some software onto your computer and that would allow 50 00:03:16,360 --> 00:03:19,760 Speaker 1: you to designate specific folders on your computer's hard drive 51 00:03:19,919 --> 00:03:22,880 Speaker 1: as shared folders, which would be shared with the rest 52 00:03:22,919 --> 00:03:25,480 Speaker 1: of the network. So other people who had also downloaded 53 00:03:25,520 --> 00:03:30,240 Speaker 1: that same software would have access to those shared folders, 54 00:03:30,280 --> 00:03:33,440 Speaker 1: and you would have access to the stuff they put 55 00:03:33,480 --> 00:03:36,480 Speaker 1: in their own shared folders, so you could download files 56 00:03:36,520 --> 00:03:40,960 Speaker 1: stored in other people's computers. You would launch the app 57 00:03:41,080 --> 00:03:44,040 Speaker 1: and let's say you're looking for something specific. You you 58 00:03:44,080 --> 00:03:46,200 Speaker 1: start to use a search engine to look for a 59 00:03:46,320 --> 00:03:49,080 Speaker 1: very particular file. And let's say it was a piece 60 00:03:49,120 --> 00:03:53,240 Speaker 1: of freeware that someone had created but had no easy 61 00:03:53,280 --> 00:03:56,320 Speaker 1: way to distribute. It's a really big file. They don't 62 00:03:56,320 --> 00:03:57,960 Speaker 1: want to pay for the hosting fees to put it 63 00:03:58,040 --> 00:04:00,800 Speaker 1: up on a website and have to deal with all 64 00:04:00,840 --> 00:04:04,480 Speaker 1: that bandwidth, so instead they've put it on a shared folder, 65 00:04:04,560 --> 00:04:07,760 Speaker 1: and they've made it accessible by a peer to peer network. 66 00:04:08,120 --> 00:04:12,320 Speaker 1: You could download that file to your folder, and if 67 00:04:12,320 --> 00:04:15,560 Speaker 1: you kept it in your shared folder, it would mean 68 00:04:15,600 --> 00:04:18,000 Speaker 1: the next person to download the file would have an 69 00:04:18,040 --> 00:04:20,680 Speaker 1: extra source to pull from. They could pull some of 70 00:04:20,720 --> 00:04:23,080 Speaker 1: the data from the original source and some of the 71 00:04:23,160 --> 00:04:25,560 Speaker 1: data from you, and this would actually make the process faster. 72 00:04:25,880 --> 00:04:29,880 Speaker 1: So the more people sharing a particular file, the less 73 00:04:29,920 --> 00:04:32,520 Speaker 1: time it would take to download that file in general, 74 00:04:32,720 --> 00:04:36,000 Speaker 1: so it would become much faster the more people got 75 00:04:36,040 --> 00:04:38,320 Speaker 1: access to it. It was a really effective way to 76 00:04:38,360 --> 00:04:42,200 Speaker 1: distribute large files across a network of computers. Now, that 77 00:04:42,240 --> 00:04:44,800 Speaker 1: in itself is not a problem. In fact, it's a 78 00:04:44,839 --> 00:04:48,640 Speaker 1: pretty great solution for large file distribution, particularly in the 79 00:04:48,720 --> 00:04:53,640 Speaker 1: era before broadband speed's really got fast. The problem comes 80 00:04:53,800 --> 00:04:57,920 Speaker 1: when you start asking yourself what types of files are 81 00:04:58,320 --> 00:05:03,560 Speaker 1: particularly laur because a few things that fall into that category, 82 00:05:03,600 --> 00:05:07,920 Speaker 1: like movies or TV series or computer games or other 83 00:05:07,920 --> 00:05:12,040 Speaker 1: types of software, tend to be the property of very large, 84 00:05:12,200 --> 00:05:16,960 Speaker 1: very powerful corporations. And here's a spoiler alert. These corporations 85 00:05:17,120 --> 00:05:21,000 Speaker 1: understandably aren't too keen on people getting their grubby little 86 00:05:21,040 --> 00:05:24,360 Speaker 1: hands on the products without paying for them, so we're 87 00:05:24,360 --> 00:05:27,680 Speaker 1: talking about piracy. In other words, Now, I got to 88 00:05:27,720 --> 00:05:31,520 Speaker 1: be clear, there is nothing inherent in peer to peer 89 00:05:31,560 --> 00:05:36,000 Speaker 1: networking that suggests it is meant for piracy, But a 90 00:05:36,040 --> 00:05:38,960 Speaker 1: lot of people used it for that purpose, enough of 91 00:05:39,040 --> 00:05:42,080 Speaker 1: them to get the wrath of various big studios involved 92 00:05:42,080 --> 00:05:47,800 Speaker 1: in a massive lawsuit against Scour. How massive, well, they 93 00:05:47,920 --> 00:05:53,240 Speaker 1: claimed damages to the tune of one hundred thousand dollars 94 00:05:53,279 --> 00:05:56,600 Speaker 1: per file. So if you added up all the files 95 00:05:56,640 --> 00:05:59,880 Speaker 1: on the system that fell into the proprietary nature that 96 00:06:00,040 --> 00:06:02,960 Speaker 1: belong to one of these studios, it amounted to about 97 00:06:03,040 --> 00:06:08,719 Speaker 1: two hundred and fifty billion dollars. Now, the lawsuits scared 98 00:06:08,760 --> 00:06:13,760 Speaker 1: away scours financial backers, including their majority shareholder who was 99 00:06:13,839 --> 00:06:18,080 Speaker 1: a former Disney president, Michael Ovits, and it became clear 100 00:06:18,120 --> 00:06:21,440 Speaker 1: that the Hollywood studios would put the screws to anyone 101 00:06:21,480 --> 00:06:23,880 Speaker 1: who tried to swoop in to fill the void left 102 00:06:23,880 --> 00:06:29,080 Speaker 1: by the previous investors. Essentially, it was like the mafia saying, hey, 103 00:06:29,120 --> 00:06:32,159 Speaker 1: if you support these guys, we're gonna come after you. 104 00:06:32,800 --> 00:06:36,280 Speaker 1: So this left Scour without any real financial support and 105 00:06:36,320 --> 00:06:39,480 Speaker 1: the company had to file for Chapter eleven bankruptcy protection 106 00:06:39,880 --> 00:06:42,240 Speaker 1: by the end of two thousand. It was no more. 107 00:06:42,640 --> 00:06:45,480 Speaker 1: Its assets were auctioned off to a company called Center 108 00:06:45,560 --> 00:06:49,320 Speaker 1: Span Communications, and Scour was a thing of the past. 109 00:06:50,040 --> 00:06:54,200 Speaker 1: Now klan I took the whole thing as a learning experience. 110 00:06:54,240 --> 00:06:59,280 Speaker 1: His contemporaries would describe him as being incredibly intelligent, ambitious, 111 00:06:59,520 --> 00:07:02,400 Speaker 1: and a restive and they say things like he's a 112 00:07:02,400 --> 00:07:06,039 Speaker 1: big thinker and he's relentless, which can be both a 113 00:07:06,120 --> 00:07:10,400 Speaker 1: good and a bad thing. His move after the Scour 114 00:07:10,520 --> 00:07:13,440 Speaker 1: disaster was to create what he would describe in a 115 00:07:13,560 --> 00:07:18,960 Speaker 1: talk as a quote revenge business end quote. So what 116 00:07:19,000 --> 00:07:23,920 Speaker 1: does that mean? It sounds really ominous. Well, in business terms, 117 00:07:23,960 --> 00:07:27,240 Speaker 1: it was pretty clever. It wasn't so dark as what 118 00:07:27,360 --> 00:07:29,960 Speaker 1: it might sound like. What he meant was that he 119 00:07:30,000 --> 00:07:33,120 Speaker 1: was determined to create a business that would appeal to 120 00:07:33,160 --> 00:07:37,280 Speaker 1: the very entities that had sued Scour out of existence. 121 00:07:38,160 --> 00:07:40,560 Speaker 1: So he wanted to take the people who had filed 122 00:07:40,640 --> 00:07:45,640 Speaker 1: lawsuits against him and turned them into customers, effectively taking 123 00:07:45,680 --> 00:07:49,520 Speaker 1: money from them, which you know now that I say 124 00:07:49,520 --> 00:07:53,440 Speaker 1: it does sound a little mafia esque, but pretty pretty 125 00:07:53,440 --> 00:07:56,560 Speaker 1: clever and completely legal. Obviously, you have to create the 126 00:07:56,600 --> 00:07:59,200 Speaker 1: business and you have to convince people that it's worth 127 00:08:00,160 --> 00:08:02,240 Speaker 1: using the business. So it's not like it was a 128 00:08:02,280 --> 00:08:05,320 Speaker 1: done deal from the beginning, And in fact his idea 129 00:08:05,440 --> 00:08:09,400 Speaker 1: was not a big departure from scour. Actually he wanted 130 00:08:09,440 --> 00:08:12,160 Speaker 1: to take that peer to peer technology and turn it 131 00:08:12,200 --> 00:08:16,080 Speaker 1: into an enterprise software package. So the idea would be 132 00:08:16,120 --> 00:08:20,200 Speaker 1: that big businesses like movie studios often need to move 133 00:08:20,320 --> 00:08:24,040 Speaker 1: large files around in house, right Like, there might be 134 00:08:24,320 --> 00:08:27,160 Speaker 1: one department that has a very large digital file and 135 00:08:27,200 --> 00:08:30,239 Speaker 1: they need to transfer it to another department. But even 136 00:08:30,360 --> 00:08:32,760 Speaker 1: within a company, there wasn't always an easy way to 137 00:08:32,800 --> 00:08:35,800 Speaker 1: do this. Using the peer to peer network, which would 138 00:08:35,840 --> 00:08:38,719 Speaker 1: be locked to a particular studio or company, they could 139 00:08:38,760 --> 00:08:41,480 Speaker 1: do that much more quickly than with other methods. So, 140 00:08:41,520 --> 00:08:43,840 Speaker 1: in other words, instead of downloading a piece of software 141 00:08:44,160 --> 00:08:46,360 Speaker 1: that would give you access to all the shared files 142 00:08:46,360 --> 00:08:48,920 Speaker 1: in the network, each one would be its own little, 143 00:08:48,920 --> 00:08:53,760 Speaker 1: self contained island of computers, its own intra net, and 144 00:08:53,840 --> 00:08:55,680 Speaker 1: you could use the peer to peer network to move 145 00:08:55,679 --> 00:08:58,880 Speaker 1: files around that way, but no one from outside the 146 00:08:58,920 --> 00:09:02,200 Speaker 1: company would have access to it. So he created this 147 00:09:02,240 --> 00:09:05,080 Speaker 1: new company and he called it Red Swoosh, and this 148 00:09:05,200 --> 00:09:09,240 Speaker 1: all started in two thousand one. But he also had 149 00:09:09,320 --> 00:09:12,440 Speaker 1: some pretty hefty obstacles in his way, and a lot 150 00:09:12,480 --> 00:09:15,400 Speaker 1: of it came down to timing. For one thing, this 151 00:09:15,520 --> 00:09:18,560 Speaker 1: was just around the time that broadband prices were starting 152 00:09:18,559 --> 00:09:22,880 Speaker 1: to come down, which meant that other options for companies 153 00:09:22,920 --> 00:09:25,320 Speaker 1: that needed to share large amounts of data across multiple 154 00:09:25,360 --> 00:09:29,160 Speaker 1: machines were opening up. Another problem for him was that 155 00:09:29,240 --> 00:09:32,600 Speaker 1: the dot com bubble had burst and the Internet startup 156 00:09:32,640 --> 00:09:36,959 Speaker 1: world was totally upside down as a result. You can 157 00:09:37,040 --> 00:09:39,600 Speaker 1: listen to episodes of tech Stuff where I talked about 158 00:09:39,679 --> 00:09:44,440 Speaker 1: the Internet dot com bubble. It was spectacular and it 159 00:09:44,520 --> 00:09:48,960 Speaker 1: had really an incredible effect across the industry for years 160 00:09:48,960 --> 00:09:51,440 Speaker 1: and years, and no one at this time was really 161 00:09:51,520 --> 00:09:55,000 Speaker 1: bullish about getting into startup companies because so many had 162 00:09:55,080 --> 00:09:56,959 Speaker 1: just gone belly up over the course of about a 163 00:09:57,040 --> 00:09:58,920 Speaker 1: year and a half. So it was really hard to 164 00:09:58,920 --> 00:10:02,520 Speaker 1: find financial back. According to a Fast Company article I read, 165 00:10:02,679 --> 00:10:06,760 Speaker 1: at one point, red Swosh got down to just two employees. 166 00:10:07,480 --> 00:10:10,560 Speaker 1: You had Klanic and you had an engineer, and Clinic 167 00:10:10,640 --> 00:10:13,000 Speaker 1: himself had to move back in with his parents, and 168 00:10:13,080 --> 00:10:17,559 Speaker 1: eventually his one engineer left the company too, so it 169 00:10:17,600 --> 00:10:20,800 Speaker 1: became a one man operation. But he didn't give up. 170 00:10:21,160 --> 00:10:24,480 Speaker 1: He kept plugging away, He kept looking for investors and 171 00:10:24,520 --> 00:10:28,920 Speaker 1: eventually he found one in Mark Cuban. Cubans investment allowed 172 00:10:29,000 --> 00:10:31,959 Speaker 1: Clinic to get red Swush on track, hiring a new team, 173 00:10:32,120 --> 00:10:36,520 Speaker 1: although a small one, and landing a client named Echo Star, 174 00:10:36,640 --> 00:10:39,960 Speaker 1: which is a satellite TV service provider, And this was 175 00:10:40,120 --> 00:10:44,520 Speaker 1: enough to make red Swoosh and attractive property. And in 176 00:10:44,600 --> 00:10:48,720 Speaker 1: two thousand seven, another company called akam I made an 177 00:10:48,760 --> 00:10:52,559 Speaker 1: acquisition offer to that which Clinic accepted. He said sure. 178 00:10:52,679 --> 00:10:54,640 Speaker 1: He sold his company for an amount that has been 179 00:10:54,679 --> 00:10:58,720 Speaker 1: reported to be between fifteen and eighteen million dollars, which 180 00:10:58,760 --> 00:11:00,600 Speaker 1: is not a bad chunk of chain age, though by 181 00:11:00,600 --> 00:11:03,520 Speaker 1: no means the enormous amount of money represented by other 182 00:11:03,559 --> 00:11:07,280 Speaker 1: acquisitions we've seen in the text space. Still, this experience 183 00:11:07,320 --> 00:11:11,920 Speaker 1: reinforced Calantics confidence in himself and his ideas. He bought 184 00:11:11,920 --> 00:11:14,960 Speaker 1: a home in San Francisco and became kind of an 185 00:11:14,960 --> 00:11:17,640 Speaker 1: angel investor, and he would invite lots of younger people 186 00:11:17,679 --> 00:11:19,960 Speaker 1: to come by and pitch ideas to him for various 187 00:11:20,000 --> 00:11:24,160 Speaker 1: businesses because he loved that part of the experience. He 188 00:11:24,240 --> 00:11:26,400 Speaker 1: seems to be the kind of guy who just really 189 00:11:26,559 --> 00:11:30,880 Speaker 1: enjoys innovative ideas and disruptive ideas, whether they come from 190 00:11:30,880 --> 00:11:33,040 Speaker 1: other people or he can take an idea that he 191 00:11:33,080 --> 00:11:35,520 Speaker 1: thinks is maybe seventy of the way there, and help 192 00:11:35,600 --> 00:11:38,439 Speaker 1: try and get it all the way there. Sometimes he 193 00:11:38,440 --> 00:11:41,320 Speaker 1: would just argue with people and say, your idea just 194 00:11:41,360 --> 00:11:43,079 Speaker 1: doesn't make sense, it's not a it's not a big 195 00:11:43,160 --> 00:11:46,160 Speaker 1: enough idea for a business. And he would have these 196 00:11:46,160 --> 00:11:48,720 Speaker 1: discussions on a regular basis and invited a lot of 197 00:11:48,720 --> 00:11:51,400 Speaker 1: people over to be part of them. And he seems 198 00:11:51,400 --> 00:11:55,000 Speaker 1: to have the instincts really necessary to go from practically 199 00:11:55,000 --> 00:12:00,240 Speaker 1: nothing to something and in an accelerated amount of time. Well, 200 00:12:00,280 --> 00:12:03,960 Speaker 1: in December two thousand eight, Clinic attended a conference in 201 00:12:03,960 --> 00:12:09,640 Speaker 1: Paris called loeweb I Love the French. During his stay there, 202 00:12:09,840 --> 00:12:13,680 Speaker 1: it snowed, which is a pretty rare event in Paris actually, 203 00:12:13,760 --> 00:12:15,600 Speaker 1: and the snow was sticking to the ground, which is 204 00:12:15,880 --> 00:12:19,200 Speaker 1: even more rare, And he found himself in need of 205 00:12:19,240 --> 00:12:22,199 Speaker 1: a taxi cab and he was frustrated that he couldn't 206 00:12:22,280 --> 00:12:26,040 Speaker 1: find one. He happened to be with another attendee. That 207 00:12:26,080 --> 00:12:29,720 Speaker 1: guy was named Garrett camp who is the other co 208 00:12:29,880 --> 00:12:33,439 Speaker 1: founder of Uber. And it was this experience of being 209 00:12:33,520 --> 00:12:37,199 Speaker 1: stuck in snowy Paris near the Eiffel Tower with no 210 00:12:37,400 --> 00:12:40,679 Speaker 1: cab in sight that inspired the two to dream up 211 00:12:40,720 --> 00:12:44,880 Speaker 1: the service that would become known as Uber, or so 212 00:12:45,000 --> 00:12:49,559 Speaker 1: the official story goes. The real one, Well, let's talk 213 00:12:49,600 --> 00:12:52,320 Speaker 1: about Garrett Camp for a little bit. He was born 214 00:12:52,320 --> 00:12:56,120 Speaker 1: in Canada, and while attending the University of Calgary's graduate 215 00:12:56,200 --> 00:12:59,800 Speaker 1: school program, he and a friend named Jeff Smith founded 216 00:12:59,840 --> 00:13:04,080 Speaker 1: a service called stumble Upon. Now, this was a recommendation 217 00:13:04,240 --> 00:13:07,719 Speaker 1: engine and discovery platform. In other words, stumble Upon was 218 00:13:07,760 --> 00:13:10,200 Speaker 1: a service that let people share the cool things they 219 00:13:10,200 --> 00:13:12,920 Speaker 1: came across on the web with their friends. Now keep 220 00:13:12,920 --> 00:13:15,679 Speaker 1: in mind, this is before you have stuff like Facebook 221 00:13:15,800 --> 00:13:18,480 Speaker 1: or Twitter. This was a way for you to say, Hey, 222 00:13:18,920 --> 00:13:22,160 Speaker 1: I just happened to find this really great web comic 223 00:13:22,280 --> 00:13:24,520 Speaker 1: that hasn't really taken off yet, and I think you 224 00:13:24,520 --> 00:13:26,520 Speaker 1: need to know about it. You can use stumble Upon 225 00:13:26,640 --> 00:13:29,640 Speaker 1: to help your friends discover this stuff. It was one 226 00:13:29,640 --> 00:13:31,880 Speaker 1: of the first services to hit upon this formula, and 227 00:13:31,880 --> 00:13:35,280 Speaker 1: it became very successful. By the mid two thousands, Camp 228 00:13:35,320 --> 00:13:39,000 Speaker 1: and his team had to relocate to San Francisco, largely 229 00:13:39,040 --> 00:13:41,640 Speaker 1: because that's where the investment money was coming from. So 230 00:13:41,880 --> 00:13:44,640 Speaker 1: they actually left Canada and moved to San Francisco, and 231 00:13:44,640 --> 00:13:48,680 Speaker 1: stumble Upon grew into an enormous endeavor. In two thousand seven, 232 00:13:48,800 --> 00:13:52,800 Speaker 1: eBay acquired the company for seventy five million dollars, making 233 00:13:52,840 --> 00:13:55,960 Speaker 1: Camp a wealthy guy. Camp would continue to work with 234 00:13:56,000 --> 00:13:59,240 Speaker 1: the company as an eBay employee. A couple of years later, 235 00:13:59,480 --> 00:14:02,240 Speaker 1: eBay would spin out stumble Upon so that it would 236 00:14:02,240 --> 00:14:05,880 Speaker 1: once again be an independent company, and Camp was CEO 237 00:14:06,040 --> 00:14:08,760 Speaker 1: until two thousand twelve, when he moved off to pursue 238 00:14:08,840 --> 00:14:11,920 Speaker 1: other interests, and by two thousand fifteen, stumble Upon was 239 00:14:11,960 --> 00:14:15,679 Speaker 1: in trouble, but Camp came back and reacquired the company 240 00:14:15,720 --> 00:14:18,880 Speaker 1: because he didn't want to just see his baby go 241 00:14:18,960 --> 00:14:22,680 Speaker 1: away anyway. During those years when Camp first moved to 242 00:14:22,720 --> 00:14:25,720 Speaker 1: San Francisco, he found getting around in the city to 243 00:14:25,800 --> 00:14:28,480 Speaker 1: be a bit of a challenge. He was never really 244 00:14:28,520 --> 00:14:32,400 Speaker 1: a driver in Calgary, and he hadn't really planned on 245 00:14:32,480 --> 00:14:35,280 Speaker 1: becoming a driver in San Francisco. He had been vexed 246 00:14:35,280 --> 00:14:37,440 Speaker 1: by the problems he saw on the taxi cab industry 247 00:14:37,520 --> 00:14:39,960 Speaker 1: for a while, and he saw that there were too 248 00:14:40,000 --> 00:14:43,960 Speaker 1: few cars servicing too many people who needed to go somewhere. 249 00:14:44,440 --> 00:14:47,760 Speaker 1: He had actually bought himself a really expensive sports car 250 00:14:48,080 --> 00:14:50,360 Speaker 1: once eBay came in, but he found driving in San 251 00:14:50,360 --> 00:14:54,520 Speaker 1: Francisco was way too stressful, and if you've never driven 252 00:14:54,520 --> 00:14:56,680 Speaker 1: in San Francisco, the first time you come to an 253 00:14:56,720 --> 00:15:00,600 Speaker 1: intersection at the top of an extremely steep hill, you'll 254 00:15:00,600 --> 00:15:03,920 Speaker 1: start exploring lots of philosophical and religious concepts and the 255 00:15:03,960 --> 00:15:06,160 Speaker 1: hopes that you can make it through the light once 256 00:15:06,200 --> 00:15:10,520 Speaker 1: it changes. But options outside of personal transportation were pretty 257 00:15:10,600 --> 00:15:15,560 Speaker 1: limited or lackluster. Public transportation in San Francisco has often 258 00:15:15,680 --> 00:15:21,040 Speaker 1: been the subject of consternation, let's say, so, Camp began 259 00:15:21,160 --> 00:15:24,840 Speaker 1: using what The Guardian called in an article the gypsy 260 00:15:25,040 --> 00:15:28,760 Speaker 1: cab fleet of San Francisco. Now I'm not a big 261 00:15:28,800 --> 00:15:31,760 Speaker 1: fan of the word gypsy, I mean, it's essentially a slur, 262 00:15:32,240 --> 00:15:34,800 Speaker 1: but what the paper meant by this was that there 263 00:15:34,840 --> 00:15:37,520 Speaker 1: were people trying to earn extra money by driving black 264 00:15:37,560 --> 00:15:40,920 Speaker 1: sedans and transporting people to various places in the city. 265 00:15:41,680 --> 00:15:44,720 Speaker 1: Most of this was unofficial stuff, and they might be 266 00:15:44,880 --> 00:15:47,880 Speaker 1: livery drivers, but they might be doing this on their 267 00:15:47,880 --> 00:15:50,800 Speaker 1: own time, not on company time, So essentially it was 268 00:15:50,880 --> 00:15:54,080 Speaker 1: kind of like a black market for taxi services. And 269 00:15:54,160 --> 00:15:56,680 Speaker 1: Camp found that many of the drivers were reliable and 270 00:15:56,760 --> 00:16:00,360 Speaker 1: friendly and they weren't overcharging him, so he began to 271 00:16:00,360 --> 00:16:03,240 Speaker 1: collect phone numbers of the drivers he liked so that 272 00:16:03,280 --> 00:16:06,160 Speaker 1: he could use them instead of the official taxi service, 273 00:16:06,640 --> 00:16:09,320 Speaker 1: and that led Camp to envision an app that would 274 00:16:09,320 --> 00:16:12,280 Speaker 1: allow you to hail a ride at any time. It 275 00:16:12,320 --> 00:16:14,880 Speaker 1: would also keep you informed of where your driver was, 276 00:16:15,040 --> 00:16:17,240 Speaker 1: how long it would take the car to reach you, 277 00:16:17,440 --> 00:16:20,200 Speaker 1: and when you could expect to arrive at your destination. 278 00:16:20,800 --> 00:16:23,440 Speaker 1: Now this was all just in the concept phase, but 279 00:16:23,640 --> 00:16:26,440 Speaker 1: sometime in early two thousand and eight, Camp wrote down 280 00:16:26,440 --> 00:16:29,360 Speaker 1: an idea for the services name. He called it Uber, 281 00:16:30,120 --> 00:16:32,760 Speaker 1: but he actually put an umble out over the you, 282 00:16:33,000 --> 00:16:38,160 Speaker 1: which I, I guess means you would call it Uber anyway. 283 00:16:38,240 --> 00:16:41,680 Speaker 1: Camp decided he would call the service uber Cab. He 284 00:16:41,720 --> 00:16:45,480 Speaker 1: registered uber cab dot com in August two thousand, eight 285 00:16:45,840 --> 00:16:49,280 Speaker 1: months before he would have that snowy meeting with Clanic 286 00:16:49,360 --> 00:16:53,120 Speaker 1: in Paris. Now that same summer, Apple had launched the 287 00:16:53,160 --> 00:16:56,320 Speaker 1: App Store for iPhones, which opened up the opportunity to 288 00:16:56,400 --> 00:16:59,520 Speaker 1: create a smartphone app that could do exactly what Camp 289 00:16:59,560 --> 00:17:02,720 Speaker 1: had been imagining. So that things were falling into place. 290 00:17:03,680 --> 00:17:05,640 Speaker 1: On the other side of the equation where the drivers, 291 00:17:05,920 --> 00:17:08,000 Speaker 1: Camp had figured out that a lot of those drivers 292 00:17:08,040 --> 00:17:11,800 Speaker 1: were spending a huge amount of time not transporting anyone 293 00:17:11,840 --> 00:17:15,080 Speaker 1: at all, They were just waiting for a potential fair, 294 00:17:15,119 --> 00:17:18,480 Speaker 1: maybe at an airport or at out front of a hotel. 295 00:17:18,880 --> 00:17:21,920 Speaker 1: They would just park in these areas and wait, which 296 00:17:21,960 --> 00:17:25,119 Speaker 1: was wasted time. Camp knew that the driver's side of 297 00:17:25,160 --> 00:17:28,000 Speaker 1: such an app could help them maximize their time and 298 00:17:28,000 --> 00:17:31,439 Speaker 1: their fares, which meant everyone would benefit. Cars would be 299 00:17:31,440 --> 00:17:33,880 Speaker 1: able to move throughout the city going to where they 300 00:17:33,880 --> 00:17:37,200 Speaker 1: were needed, and drivers would have less downtime and therefore 301 00:17:37,280 --> 00:17:40,640 Speaker 1: make more money while they were actually working for this 302 00:17:40,840 --> 00:17:45,439 Speaker 1: app service. Camp registered uber Cab as a limited liability 303 00:17:45,480 --> 00:17:48,760 Speaker 1: company on November two thousand and eight, still a month 304 00:17:48,800 --> 00:17:51,520 Speaker 1: before he has that meeting in Paris. He was trying 305 00:17:51,560 --> 00:17:54,199 Speaker 1: to decide if it would make sense to purchase several 306 00:17:54,280 --> 00:17:56,560 Speaker 1: cars so that a small group of people he knew 307 00:17:56,680 --> 00:17:59,920 Speaker 1: could become the first drivers in the service. He talked 308 00:18:00,000 --> 00:18:03,600 Speaker 1: of an engineer named Oscar Salazar about developing the app 309 00:18:03,640 --> 00:18:06,280 Speaker 1: side of the business. Now, Salazar was in the United 310 00:18:06,280 --> 00:18:09,480 Speaker 1: States on a student visa, and as such he could 311 00:18:09,480 --> 00:18:14,359 Speaker 1: not accept cash as payments, so instead Camp offered Salazar 312 00:18:14,480 --> 00:18:17,520 Speaker 1: some ownership of the company. If it paid off, Salazar 313 00:18:17,520 --> 00:18:20,400 Speaker 1: would make a profit. As it turned out, Salazar would 314 00:18:20,400 --> 00:18:24,960 Speaker 1: make hundreds of millions of dollars. As for Camp, he 315 00:18:25,119 --> 00:18:28,359 Speaker 1: took a little trip to Paris in December two thousand eight, where, 316 00:18:28,400 --> 00:18:31,240 Speaker 1: through a mutual friend, he was put into contact with 317 00:18:31,280 --> 00:18:34,359 Speaker 1: a certain Travis Kellenic. And while the story goes that 318 00:18:34,400 --> 00:18:36,879 Speaker 1: the two started coming up with Uber while trying to 319 00:18:36,880 --> 00:18:40,520 Speaker 1: get a cab on that snowy Parisian night, the truth 320 00:18:40,560 --> 00:18:43,639 Speaker 1: of the matter is that Camp and Kalanic had been 321 00:18:43,680 --> 00:18:47,880 Speaker 1: talking about it all week, and you had two different 322 00:18:47,960 --> 00:18:52,040 Speaker 1: arguments here. Kalin Nick wanted to create a startup that 323 00:18:52,160 --> 00:18:54,840 Speaker 1: was a lot like what Airbnb would turn into. He 324 00:18:54,880 --> 00:18:58,040 Speaker 1: was thinking of a sort of a luxury apartment kind 325 00:18:58,040 --> 00:19:01,120 Speaker 1: of business that you could book using an app, whereas 326 00:19:01,160 --> 00:19:04,359 Speaker 1: Camp was advocating for the idea that would become Uber. 327 00:19:04,720 --> 00:19:09,439 Speaker 1: And eventually they decided to go with Camp's idea. So 328 00:19:09,480 --> 00:19:13,640 Speaker 1: what happens next, Well, I'll tell you, but first let's 329 00:19:13,680 --> 00:19:23,280 Speaker 1: take a quick break to thank our sponsor. So Clinic 330 00:19:23,480 --> 00:19:26,760 Speaker 1: and Camp get to talking at LOWBB in Paris and 331 00:19:26,800 --> 00:19:31,360 Speaker 1: they decided to work together on Camp's Uber cab idea. Immediately, 332 00:19:32,119 --> 00:19:35,760 Speaker 1: the two founders were at a disagreement, so Camp wanted 333 00:19:35,760 --> 00:19:39,800 Speaker 1: the business to purchase several Mercedes luxury cars and own 334 00:19:39,920 --> 00:19:43,600 Speaker 1: the cars outright and just hire the drivers. Clinic felt 335 00:19:43,640 --> 00:19:45,800 Speaker 1: that this was a mistake and that the business should 336 00:19:45,800 --> 00:19:49,360 Speaker 1: instead rely on drivers supplying their own cars in return 337 00:19:49,440 --> 00:19:53,640 Speaker 1: for access to the app, and eventually Clinic convinced Camp 338 00:19:53,680 --> 00:19:55,919 Speaker 1: to try it his way, and Camp backed off of 339 00:19:56,000 --> 00:20:00,720 Speaker 1: making the purchase. At the beginning, uber Cab focused on 340 00:20:00,840 --> 00:20:04,879 Speaker 1: contacting limo drivers only. It was a black car service, 341 00:20:04,920 --> 00:20:08,560 Speaker 1: so a bit posh and definitely not something that relied 342 00:20:08,600 --> 00:20:10,720 Speaker 1: on the average automobile. That would come a couple of 343 00:20:10,760 --> 00:20:14,520 Speaker 1: years later. Camp got to work with Oscar Salazar, the 344 00:20:14,720 --> 00:20:19,280 Speaker 1: engineer who was working on the promise of equity in 345 00:20:19,280 --> 00:20:22,399 Speaker 1: the company, and they started to build out the uber 346 00:20:22,440 --> 00:20:25,960 Speaker 1: Cab app for real zs. He also reached out to 347 00:20:26,000 --> 00:20:29,439 Speaker 1: a friend of his named Conrad Wheland. Now, Wheland had 348 00:20:29,480 --> 00:20:33,000 Speaker 1: worked for a Canadian company called excel Aware, and he 349 00:20:33,040 --> 00:20:35,520 Speaker 1: had cashed out of that and he wasn't exactly looking 350 00:20:35,560 --> 00:20:37,800 Speaker 1: for a new job at the time, but Camp called 351 00:20:37,840 --> 00:20:40,280 Speaker 1: him up, or he called up Camp, and Camp was 352 00:20:40,320 --> 00:20:42,320 Speaker 1: able to convince him to come on over and join 353 00:20:42,400 --> 00:20:47,280 Speaker 1: the uber Cab team as the first official software engineer 354 00:20:47,359 --> 00:20:51,159 Speaker 1: for the company. Now in a piece in Fortune, Whelan 355 00:20:51,280 --> 00:20:54,840 Speaker 1: revealed that when he joined the Uber Cab apps development 356 00:20:55,520 --> 00:20:58,320 Speaker 1: it was in its earliest stages. It allowed a user 357 00:20:58,359 --> 00:21:00,919 Speaker 1: to order a car, but there was no link to 358 00:21:00,960 --> 00:21:04,680 Speaker 1: create an account or associate a payment method with the service, 359 00:21:04,840 --> 00:21:07,560 Speaker 1: so you would have to pay in some other method. Now, 360 00:21:07,600 --> 00:21:10,600 Speaker 1: this was all in the development phase. Nothing was rolled 361 00:21:10,600 --> 00:21:13,000 Speaker 1: out to the public at this stage, but it was 362 00:21:13,040 --> 00:21:16,800 Speaker 1: still pretty primitive. Wheland got to work building out the 363 00:21:16,880 --> 00:21:19,040 Speaker 1: various aspects of the app that would allow you to 364 00:21:19,080 --> 00:21:22,360 Speaker 1: create an account and associate a credit card or PayPal 365 00:21:22,400 --> 00:21:24,880 Speaker 1: account with it, so that that way you could pay 366 00:21:24,920 --> 00:21:28,840 Speaker 1: for everything seamlessly. It was an idea that would appeal 367 00:21:28,880 --> 00:21:33,520 Speaker 1: both to writers and to drivers, and he also wanted 368 00:21:33,560 --> 00:21:36,800 Speaker 1: to guarantee that Uber would get a cut of the action. 369 00:21:37,400 --> 00:21:39,199 Speaker 1: You had to have some sort of way for the 370 00:21:39,240 --> 00:21:44,000 Speaker 1: company to earn some money from every transaction. Whelan also 371 00:21:44,080 --> 00:21:47,680 Speaker 1: worked on creating algorithms for the dispatch side of the service. 372 00:21:48,080 --> 00:21:49,960 Speaker 1: So when you look at what Uber does from a 373 00:21:50,040 --> 00:21:54,200 Speaker 1: macro level, it's pretty fascinating. On the one hand, it's 374 00:21:54,200 --> 00:21:56,440 Speaker 1: an app that allows you to send out a message 375 00:21:56,480 --> 00:21:59,840 Speaker 1: to nearby drivers, and that message essentially says, I need 376 00:21:59,840 --> 00:22:02,359 Speaker 1: a car to drive me somewhere the app connects to 377 00:22:02,359 --> 00:22:05,080 Speaker 1: an account and payment method so that no cash is 378 00:22:05,119 --> 00:22:08,080 Speaker 1: needed to change hands, which is pretty useful as more 379 00:22:08,080 --> 00:22:10,320 Speaker 1: and more people are going cashless in their day to 380 00:22:10,400 --> 00:22:12,679 Speaker 1: day lives. But on the other side of that app 381 00:22:13,320 --> 00:22:16,360 Speaker 1: is the management system that decides things such as which 382 00:22:16,440 --> 00:22:19,960 Speaker 1: drivers will get contacted for specific jobs. So it's both 383 00:22:20,000 --> 00:22:23,240 Speaker 1: proximity based and takes into account what sort of service 384 00:22:23,359 --> 00:22:26,080 Speaker 1: is being requested and whether or not the Uber drivers 385 00:22:26,080 --> 00:22:29,359 Speaker 1: in the area are currently engaged in another job. So 386 00:22:29,400 --> 00:22:31,280 Speaker 1: the goal on the corporate side of things is to 387 00:22:31,320 --> 00:22:33,840 Speaker 1: do two things. Cut down on the idle time a 388 00:22:33,960 --> 00:22:36,800 Speaker 1: driver experiences between dropping someone off and picking up the 389 00:22:36,840 --> 00:22:39,639 Speaker 1: next fair because whenever they're idle, they're not making money 390 00:22:39,720 --> 00:22:42,520 Speaker 1: for themselves or for the company. And the second thing 391 00:22:42,600 --> 00:22:44,400 Speaker 1: is to cut down the wait time for someone who 392 00:22:44,400 --> 00:22:47,040 Speaker 1: needs to get a ride, because if the wait times 393 00:22:47,040 --> 00:22:49,400 Speaker 1: are really crazy, no one's going to use your service. 394 00:22:49,840 --> 00:22:52,800 Speaker 1: Wheeland worked on that technology to improve the experience for 395 00:22:52,840 --> 00:22:56,720 Speaker 1: both sides, both drivers and riders. Now, according to that 396 00:22:56,800 --> 00:23:00,440 Speaker 1: same piece and Fortune, Uber's second engineer are was a 397 00:23:00,440 --> 00:23:04,040 Speaker 1: guy named Ryan McKillen who found things in a pretty 398 00:23:04,119 --> 00:23:08,600 Speaker 1: unusual state for a startup in San Francisco. At that time, 399 00:23:08,720 --> 00:23:11,119 Speaker 1: Uber was using a small space in the office of 400 00:23:11,160 --> 00:23:15,399 Speaker 1: another company called Zozie. The story of Zozie is also 401 00:23:15,480 --> 00:23:18,960 Speaker 1: filled with lots of ups and downs and tons of drama. 402 00:23:19,240 --> 00:23:23,480 Speaker 1: It was acquired in seen by another company called Peak. Anyway, 403 00:23:23,520 --> 00:23:25,800 Speaker 1: that's a story for another time. The important thing here 404 00:23:25,960 --> 00:23:28,919 Speaker 1: is that this is before Uber having any sort of 405 00:23:28,960 --> 00:23:31,919 Speaker 1: headquarters of its very own. It was just cohabitating with 406 00:23:32,000 --> 00:23:35,760 Speaker 1: another company. So McKillen comes in and he walks into 407 00:23:35,800 --> 00:23:39,280 Speaker 1: the conference room that's serving as Uber's offices and sees 408 00:23:39,320 --> 00:23:43,080 Speaker 1: on the table there that there's a bunch of books 409 00:23:43,400 --> 00:23:46,520 Speaker 1: and most of them are on coding and database management 410 00:23:46,520 --> 00:23:49,439 Speaker 1: and computer science, but none of them looked like they 411 00:23:49,480 --> 00:23:52,240 Speaker 1: had really been used very much. But there was one 412 00:23:52,280 --> 00:23:55,280 Speaker 1: book that obviously had seen a lot of use, and 413 00:23:55,320 --> 00:23:56,760 Speaker 1: so he takes a look at it and he sees 414 00:23:56,760 --> 00:24:00,680 Speaker 1: that it's a Spanish to English dictionary. So why was 415 00:24:00,720 --> 00:24:04,879 Speaker 1: it there? Because Salazar, who had done that initial coding 416 00:24:04,920 --> 00:24:07,520 Speaker 1: on the app, was from Mexico, and he coded in 417 00:24:07,600 --> 00:24:10,600 Speaker 1: his native language. And so the engineers who were building 418 00:24:10,600 --> 00:24:13,480 Speaker 1: out the early functionality of Uber, we're doing so on 419 00:24:13,520 --> 00:24:17,280 Speaker 1: a foundation written in another language. So they needed that 420 00:24:17,359 --> 00:24:20,120 Speaker 1: dictionary there on top of all the coding books. Now. 421 00:24:20,160 --> 00:24:23,600 Speaker 1: In August two thousand nine, Garrett Camp and Travis Kellanic 422 00:24:23,760 --> 00:24:28,160 Speaker 1: invested two thousand dollars of their own money into the company, 423 00:24:28,280 --> 00:24:32,440 Speaker 1: and at this time, Uber the service still didn't exist. 424 00:24:32,520 --> 00:24:35,919 Speaker 1: The company existed, but they hadn't had anything that was 425 00:24:35,960 --> 00:24:39,320 Speaker 1: public facing yet, so there were rumors about it. There 426 00:24:39,440 --> 00:24:41,480 Speaker 1: was a lot of buzz in the tech space, but 427 00:24:41,560 --> 00:24:43,240 Speaker 1: there was no way for you to actually use the 428 00:24:43,280 --> 00:24:46,760 Speaker 1: service yet. The engineers had to build out the technology 429 00:24:46,800 --> 00:24:49,679 Speaker 1: that would make everything work. So while Uber the company 430 00:24:49,720 --> 00:24:52,320 Speaker 1: was rolling along in two thousand nine, it would not 431 00:24:52,480 --> 00:24:57,399 Speaker 1: be until mid that Uber would officially start taking customers 432 00:24:57,440 --> 00:25:00,720 Speaker 1: for rides in San Francisco, and it wouldn't be until 433 00:25:00,800 --> 00:25:03,879 Speaker 1: October twenty that the company would receive a round of 434 00:25:03,920 --> 00:25:07,960 Speaker 1: funding from angel investors. There would be twenty nine angel 435 00:25:08,040 --> 00:25:10,639 Speaker 1: investors in that round and they contributed a total of 436 00:25:10,680 --> 00:25:14,640 Speaker 1: one point three million dollars of first round capital. Sticking 437 00:25:14,640 --> 00:25:17,560 Speaker 1: with investments for a second before we get back on 438 00:25:17,680 --> 00:25:20,880 Speaker 1: track with Uber rolling out its first rides. The company 439 00:25:20,920 --> 00:25:24,760 Speaker 1: has had several rounds of funding and debt financing throughout 440 00:25:24,760 --> 00:25:29,359 Speaker 1: its history. By August, Uber had raised more than four 441 00:25:29,440 --> 00:25:33,200 Speaker 1: hundred million dollars in various rounds of funding. The most 442 00:25:33,359 --> 00:25:38,320 Speaker 1: recent round, which happened in December, was for one point 443 00:25:38,440 --> 00:25:42,520 Speaker 1: three billion dollars. So if you total it all up, 444 00:25:42,680 --> 00:25:45,640 Speaker 1: the company has raised at least ten point seven billion 445 00:25:45,640 --> 00:25:49,520 Speaker 1: dollars in various series funding rounds and private equity rounds. 446 00:25:50,280 --> 00:25:52,160 Speaker 1: There are other ones that we could talk about two, 447 00:25:52,280 --> 00:25:57,280 Speaker 1: but the point is it was a crapload of money. Okay. 448 00:25:57,280 --> 00:26:00,840 Speaker 1: Back to those early days of Uber, in Jenue wary ten, 449 00:26:00,960 --> 00:26:04,400 Speaker 1: Travis Clanic needed to find someone to oversee the business 450 00:26:04,440 --> 00:26:10,159 Speaker 1: side of Uber, so he sent out a tweet, because 451 00:26:10,160 --> 00:26:12,760 Speaker 1: that's how things work at these levels. I guess the 452 00:26:12,760 --> 00:26:19,600 Speaker 1: tweet read looking for that's the number for darn Twitter 453 00:26:19,920 --> 00:26:25,520 Speaker 1: limitations entrepreneurial product manager slash business developer killer for a 454 00:26:25,560 --> 00:26:31,720 Speaker 1: location based service pre launch, big equity, big peeps involved 455 00:26:32,119 --> 00:26:36,200 Speaker 1: any tips wells. Tweet got a response from a guy 456 00:26:36,280 --> 00:26:39,760 Speaker 1: named Ryan Graves. Graves would be brought on to act 457 00:26:39,840 --> 00:26:43,600 Speaker 1: as the general manager for Uber before eventually becoming the 458 00:26:43,640 --> 00:26:46,280 Speaker 1: CEO of the company. For a short while, he took 459 00:26:46,359 --> 00:26:50,240 Speaker 1: over that role from Clanic, but then in December he 460 00:26:50,240 --> 00:26:53,560 Speaker 1: would step aside and Clanic would become CEO again. Graves 461 00:26:53,560 --> 00:26:57,359 Speaker 1: would also serve as present for a while before taking 462 00:26:57,359 --> 00:27:00,800 Speaker 1: on the role of senior vice president of Global Operations. 463 00:27:01,359 --> 00:27:04,480 Speaker 1: His first day on the job was March first. According 464 00:27:04,480 --> 00:27:07,359 Speaker 1: to Klanic, I found some sources that would refer to 465 00:27:07,440 --> 00:27:11,159 Speaker 1: him as quote the first Uber employee end quote. But 466 00:27:11,240 --> 00:27:14,400 Speaker 1: based off my knowledge of the engineers, that seems a 467 00:27:14,440 --> 00:27:18,359 Speaker 1: tiny bit misleading. But maybe there's some particulars I'm not 468 00:27:18,400 --> 00:27:21,840 Speaker 1: aware of. Actually, there are probably many particulars I'm not 469 00:27:21,880 --> 00:27:26,200 Speaker 1: aware of. Anyway. Graves would stay on with Uber until seventeen, 470 00:27:26,240 --> 00:27:28,440 Speaker 1: when he would step down from the company, and I'll 471 00:27:28,440 --> 00:27:31,280 Speaker 1: talk about that more in the next episode. In the 472 00:27:31,320 --> 00:27:35,840 Speaker 1: summer of Uber still known as Uber Cab at this point, 473 00:27:36,080 --> 00:27:38,880 Speaker 1: launched its app in the iPhone store and began connecting 474 00:27:38,960 --> 00:27:42,159 Speaker 1: drivers with writers, but only in San Francisco. It was 475 00:27:42,200 --> 00:27:45,120 Speaker 1: the only city where they were active at that time. Now, 476 00:27:45,119 --> 00:27:48,080 Speaker 1: when they did this, a ride cost about one and 477 00:27:48,119 --> 00:27:51,600 Speaker 1: a half times more than it would cost in a cab, 478 00:27:52,359 --> 00:27:54,199 Speaker 1: But the whole point was it was really hard to 479 00:27:54,240 --> 00:27:57,159 Speaker 1: get a cab in San Francisco, depending upon the time 480 00:27:57,200 --> 00:28:01,600 Speaker 1: and place. Uber, on the other hand, was user friendly 481 00:28:01,800 --> 00:28:04,320 Speaker 1: and gave writers a sense of what was actually happening 482 00:28:04,320 --> 00:28:06,919 Speaker 1: when they were looking for a ride, unless like the 483 00:28:07,320 --> 00:28:10,960 Speaker 1: less tech savvy cab services that were operating in San 484 00:28:10,960 --> 00:28:14,080 Speaker 1: Francisco at that time. Now I've covered how this works 485 00:28:14,080 --> 00:28:16,960 Speaker 1: a little bit just in the earlier section. The app 486 00:28:17,000 --> 00:28:21,160 Speaker 1: consults your phones location data, such as your GPS coordinates, 487 00:28:21,200 --> 00:28:23,840 Speaker 1: and uses that to help guide drivers to your location. 488 00:28:24,600 --> 00:28:27,119 Speaker 1: A later building the app would add in the feature 489 00:28:27,160 --> 00:28:30,400 Speaker 1: where you could designate a specific pickup spot. You would 490 00:28:30,400 --> 00:28:33,359 Speaker 1: put a little virtual pin on a map that would 491 00:28:33,359 --> 00:28:36,520 Speaker 1: designate where you wanted the driver to meet you, and 492 00:28:36,640 --> 00:28:39,040 Speaker 1: once a driver accepts a job, the writer will see 493 00:28:39,040 --> 00:28:41,880 Speaker 1: the driver's car appear on the map with an estimated 494 00:28:41,960 --> 00:28:44,200 Speaker 1: arrival time for pickups. So you can actually follow the 495 00:28:44,200 --> 00:28:46,880 Speaker 1: little graphic and watch the drivers slowly make their way 496 00:28:46,920 --> 00:28:49,840 Speaker 1: to your location, which I have done on numerous occasions. 497 00:28:50,600 --> 00:28:55,280 Speaker 1: The initial response from customers in San Francisco was largely positive, 498 00:28:55,920 --> 00:28:59,600 Speaker 1: but a couple of big organizations were not nearly as 499 00:28:59,680 --> 00:29:03,800 Speaker 1: happy be about Uber Cabs operations. They were the San 500 00:29:03,840 --> 00:29:10,440 Speaker 1: Francisco Metro Transit Authority and the Public Utilities Commission of California. 501 00:29:10,560 --> 00:29:13,040 Speaker 1: The two sent a message to Uber Cab, which was 502 00:29:13,560 --> 00:29:18,840 Speaker 1: cease and desist all ride hailing services or face hefty fines. 503 00:29:19,720 --> 00:29:23,080 Speaker 1: Uber cabs response was, quote, we believe that the service 504 00:29:23,160 --> 00:29:27,400 Speaker 1: we offer is in compliance with the cited regulations end quote. 505 00:29:28,640 --> 00:29:31,640 Speaker 1: The taxi business in San Francisco was in an uproar 506 00:29:31,960 --> 00:29:35,080 Speaker 1: about Uber Cab, and this would become a familiar story 507 00:29:35,120 --> 00:29:37,600 Speaker 1: to the company over the following years. In fact, it 508 00:29:37,640 --> 00:29:41,760 Speaker 1: would play out repeatedly in city after city around the world. 509 00:29:42,160 --> 00:29:44,960 Speaker 1: Sometimes Uber would make a quick, solid case for this 510 00:29:45,240 --> 00:29:47,880 Speaker 1: business and the taxi cab companies had to grit their 511 00:29:47,920 --> 00:29:50,560 Speaker 1: teeth and just accept it. But other times things went 512 00:29:50,600 --> 00:29:53,160 Speaker 1: a little further, and I'll cover a few of those 513 00:29:53,160 --> 00:29:56,680 Speaker 1: in the next episode. The taxi cab companies said their 514 00:29:56,720 --> 00:30:01,120 Speaker 1: concerns were prompted by the following issues. Uber Cab was 515 00:30:01,160 --> 00:30:04,080 Speaker 1: operating much like a cab company, but did not have 516 00:30:04,160 --> 00:30:08,080 Speaker 1: a taxi license. Its cars did not have the insurance 517 00:30:08,120 --> 00:30:13,680 Speaker 1: equivalent to taxis insurance. Uber cab would possibly threatened taxi 518 00:30:13,760 --> 00:30:17,480 Speaker 1: dispatchers ways of earning a living, and limos in the 519 00:30:17,520 --> 00:30:22,560 Speaker 1: United States have to have a pre book period, usually 520 00:30:22,600 --> 00:30:26,760 Speaker 1: about an hour in advance by law, While only licensed 521 00:30:26,760 --> 00:30:29,200 Speaker 1: taxis would be allowed to pick someone up right away 522 00:30:29,280 --> 00:30:32,320 Speaker 1: for example, when they were being hailed. However, Uber Cab 523 00:30:32,720 --> 00:30:36,040 Speaker 1: was operating as a limousine service but behaving like a 524 00:30:36,080 --> 00:30:40,720 Speaker 1: taxi service and without a taxi license. Now, one of 525 00:30:40,880 --> 00:30:45,360 Speaker 1: uber CAB's responses to this complaint was to drop cab 526 00:30:45,720 --> 00:30:49,200 Speaker 1: from its name, so it became Uber, the one we 527 00:30:49,200 --> 00:30:53,200 Speaker 1: talked about today. What's in the name? Though a cab 528 00:30:53,240 --> 00:30:57,320 Speaker 1: by any other name would smell as well, Let's let's 529 00:30:57,360 --> 00:30:59,040 Speaker 1: not think about what a cab may or may not 530 00:30:59,120 --> 00:31:02,000 Speaker 1: smell like. The point is that changing the company's name, 531 00:31:02,120 --> 00:31:05,360 Speaker 1: while a prudent step, might not have been seen as 532 00:31:05,680 --> 00:31:09,600 Speaker 1: significant enough to escape legal troubles. So what did the 533 00:31:09,640 --> 00:31:13,920 Speaker 1: company do in the face of this resistance, Well, it 534 00:31:14,040 --> 00:31:17,600 Speaker 1: kept going as if nothing had happened. Ryan Graves, who 535 00:31:17,680 --> 00:31:20,480 Speaker 1: was the CEO at that time, said that the company 536 00:31:20,560 --> 00:31:23,600 Speaker 1: was working with s F M t A to fix 537 00:31:23,680 --> 00:31:28,160 Speaker 1: the problems that the organization said Uber was causing, and 538 00:31:28,200 --> 00:31:31,640 Speaker 1: the taxi cab industry was still quite upset. But why 539 00:31:31,760 --> 00:31:37,920 Speaker 1: is that. Well, to understand the taxicab industry's concerns, it 540 00:31:38,160 --> 00:31:40,680 Speaker 1: helps to know how they work in general, as well 541 00:31:40,680 --> 00:31:43,160 Speaker 1: as get a kind of brief overview of the history 542 00:31:43,240 --> 00:31:46,800 Speaker 1: of regulations in that industry. So we'll get to that 543 00:31:46,960 --> 00:31:50,960 Speaker 1: in just a moment, but first let's take another quick 544 00:31:50,960 --> 00:32:01,720 Speaker 1: break to thank our sponsor of King. So you got 545 00:32:01,720 --> 00:32:07,320 Speaker 1: the taxicab industry. Clearly, Uber services and all ride hailing 546 00:32:07,440 --> 00:32:11,400 Speaker 1: services for that matter, pose a competitive threat to establish 547 00:32:11,480 --> 00:32:15,120 Speaker 1: taxicab companies. But competition is healthy, right, I mean it 548 00:32:15,480 --> 00:32:18,760 Speaker 1: pushes companies to create more compelling products and are for 549 00:32:18,840 --> 00:32:22,920 Speaker 1: more competitive rates than their rivals, which ultimately benefits the consumer. Right, 550 00:32:23,320 --> 00:32:27,760 Speaker 1: So what exactly is the issue? Well, one big issue 551 00:32:27,920 --> 00:32:31,320 Speaker 1: is that taxicab drivers have specific rules they have to 552 00:32:31,400 --> 00:32:35,480 Speaker 1: follow taxicab companies to Actually, these are rules that Uber 553 00:32:35,560 --> 00:32:39,200 Speaker 1: drivers didn't necessarily need to observe. So you could argue 554 00:32:39,200 --> 00:32:42,440 Speaker 1: that Uber is more convenient than a taxi, but the 555 00:32:42,440 --> 00:32:45,720 Speaker 1: taxi industry said that was largely because Uber could ignore 556 00:32:45,760 --> 00:32:48,120 Speaker 1: the protections that were in place to keep the taxicab 557 00:32:48,200 --> 00:32:53,440 Speaker 1: industry from causing big problems. The history of taxicab regulation 558 00:32:53,920 --> 00:32:56,560 Speaker 1: dates back in the United States to the Great Depression. 559 00:32:57,120 --> 00:32:59,960 Speaker 1: During that era, many people found themselves out of work, 560 00:33:00,280 --> 00:33:03,800 Speaker 1: so some people in big cities like New York City 561 00:33:03,840 --> 00:33:09,120 Speaker 1: became entrepreneurs by offering unlicensed taxi cab service. This led 562 00:33:09,120 --> 00:33:11,920 Speaker 1: to an increase in accidents with more drivers on the 563 00:33:12,000 --> 00:33:14,680 Speaker 1: roads competing for fairs, and that in turn had a 564 00:33:14,760 --> 00:33:19,120 Speaker 1: ripple effect and created new traffic woes which impacted everybody. 565 00:33:19,160 --> 00:33:21,040 Speaker 1: And then there was the fact that many people didn't 566 00:33:21,040 --> 00:33:25,480 Speaker 1: have very good insurance coverage, which minimustate could become very costly. 567 00:33:25,880 --> 00:33:28,080 Speaker 1: It could be difficult to figure out who could pay 568 00:33:28,120 --> 00:33:31,160 Speaker 1: for what if someone was injured in the process. That 569 00:33:31,200 --> 00:33:33,840 Speaker 1: made things even more difficult to figure out, and this 570 00:33:33,920 --> 00:33:37,760 Speaker 1: affected people who are already in a vulnerable financial position. 571 00:33:38,800 --> 00:33:42,640 Speaker 1: Cities around the United States responded by passing local laws 572 00:33:42,640 --> 00:33:46,480 Speaker 1: that were intended to improve safety and assign liability in 573 00:33:46,480 --> 00:33:49,440 Speaker 1: the event of an accident. They also looked to regulate 574 00:33:49,480 --> 00:33:53,040 Speaker 1: taxi cabs to make certain qualified drivers were the ones 575 00:33:53,080 --> 00:33:55,800 Speaker 1: picking people up and not just anyone who happens to 576 00:33:55,840 --> 00:33:59,160 Speaker 1: have access to a vehicle. Now. In the seventies and eighties, 577 00:33:59,520 --> 00:34:03,560 Speaker 1: some ease eased off on regulations because it was politically 578 00:34:03,600 --> 00:34:07,560 Speaker 1: advantageous to do so. The word regulation has often been 579 00:34:07,600 --> 00:34:12,680 Speaker 1: associated with negative consequences, such as stifling innovation and investment 580 00:34:12,800 --> 00:34:17,080 Speaker 1: in infrastructure. But when those cities eased up on regulations, 581 00:34:17,400 --> 00:34:21,480 Speaker 1: several things happened that made those cities question their decisions, 582 00:34:21,520 --> 00:34:25,359 Speaker 1: and those things probably will not surprise you. For one thing, 583 00:34:26,120 --> 00:34:30,960 Speaker 1: taxi prices went up. For another, without the regulations requiring 584 00:34:31,040 --> 00:34:35,400 Speaker 1: vehicles meet certain standards, the quality of vehicles decreased and 585 00:34:35,440 --> 00:34:39,719 Speaker 1: the average age of vehicles increased. Before there was a 586 00:34:39,760 --> 00:34:41,920 Speaker 1: limit on how old a car could be and still 587 00:34:41,960 --> 00:34:44,800 Speaker 1: be used for taxi cab service. With those regulations lifted, 588 00:34:45,160 --> 00:34:47,839 Speaker 1: suddenly you could use any old vehicle, didn't matter how 589 00:34:47,880 --> 00:34:52,720 Speaker 1: decrepit it was or badly maintained. There were less incentives 590 00:34:52,760 --> 00:34:55,680 Speaker 1: to keep cars in good shape and to phase out 591 00:34:55,719 --> 00:34:58,880 Speaker 1: older cars. Fares would become really complicated, with lots of 592 00:34:58,920 --> 00:35:01,719 Speaker 1: different variables that could affect the price, and most of 593 00:35:01,760 --> 00:35:05,200 Speaker 1: them were so convoluted that the average writer had no 594 00:35:05,280 --> 00:35:07,160 Speaker 1: clue how much a cab fair was going to be 595 00:35:07,200 --> 00:35:11,640 Speaker 1: in any given situation. Driver quality also would decrease because 596 00:35:11,680 --> 00:35:14,000 Speaker 1: those regulations no longer meant that you had to meet 597 00:35:14,040 --> 00:35:19,160 Speaker 1: certain criteria, and accidents increased. So in short, taxis were 598 00:35:19,200 --> 00:35:21,520 Speaker 1: causing a big mess, the same mess that we saw 599 00:35:21,520 --> 00:35:25,319 Speaker 1: in the Great Depression. So, of course, most of these 600 00:35:25,320 --> 00:35:29,120 Speaker 1: cities started to enact new regulations to address these problems, 601 00:35:29,120 --> 00:35:32,480 Speaker 1: saying whoop seedes are bad. Turns out, regulations in this 602 00:35:32,560 --> 00:35:37,359 Speaker 1: sense are totally realistic and important, and they are good 603 00:35:37,360 --> 00:35:39,000 Speaker 1: for the protection of not just the people but the 604 00:35:39,040 --> 00:35:43,480 Speaker 1: cities themselves, and therefore taxi cab companies had to follow 605 00:35:43,480 --> 00:35:46,960 Speaker 1: these rules in order to be licensed businesses. Part of 606 00:35:47,000 --> 00:35:50,160 Speaker 1: those regulations included a cap on how many drivers a 607 00:35:50,239 --> 00:35:53,960 Speaker 1: taxi company can employ at any given time. Now you 608 00:35:54,160 --> 00:35:57,240 Speaker 1: get in with ride hailing services like Uber, and suddenly 609 00:35:57,239 --> 00:35:59,520 Speaker 1: you've got a service as doing the same thing that 610 00:35:59,600 --> 00:36:02,560 Speaker 1: tax cabs do, picking up people and taking them to 611 00:36:02,600 --> 00:36:07,440 Speaker 1: a destination for a fee. But it was largely unregulated, 612 00:36:07,560 --> 00:36:10,120 Speaker 1: so no wonder there's been stiff resistance from the taxi 613 00:36:10,160 --> 00:36:13,960 Speaker 1: industry in various cities around the world. One regulation that 614 00:36:14,000 --> 00:36:17,720 Speaker 1: many cities require from taxi cab companies is that all 615 00:36:17,800 --> 00:36:22,400 Speaker 1: drivers submit fingerprint based background checks. Now this is not universal, 616 00:36:22,760 --> 00:36:25,040 Speaker 1: but in many cities in the United States it is 617 00:36:25,200 --> 00:36:30,080 Speaker 1: a prerequisite. These checks are administered, typically by the respective 618 00:36:30,120 --> 00:36:34,440 Speaker 1: state governments. Uber and other right hailing services claim they 619 00:36:34,440 --> 00:36:38,719 Speaker 1: do extensive background checks on perspective drivers themselves, and that 620 00:36:38,920 --> 00:36:42,400 Speaker 1: those background checks negate the need to file paperwork like 621 00:36:42,440 --> 00:36:45,000 Speaker 1: that with state agencies. They don't need to do this 622 00:36:45,160 --> 00:36:49,439 Speaker 1: fingerprint background check that taxi cab companies do, and some 623 00:36:49,560 --> 00:36:54,160 Speaker 1: cities have agreed to that exception. Others, such as Austin, Texas, 624 00:36:54,239 --> 00:36:56,600 Speaker 1: stood their ground. They held a referendum and the voters 625 00:36:56,600 --> 00:37:00,880 Speaker 1: said no, we want fingerprint fingerprint background checks to happen 626 00:37:01,000 --> 00:37:04,480 Speaker 1: for right hailing services. And they said that this would 627 00:37:04,520 --> 00:37:08,120 Speaker 1: otherwise create an unfair advantage for right hailing services over 628 00:37:08,200 --> 00:37:11,760 Speaker 1: other companies. And that's why services like Uber and Left 629 00:37:11,840 --> 00:37:16,160 Speaker 1: left Austin, Texas. But why put up a resistance? Why 630 00:37:16,360 --> 00:37:20,160 Speaker 1: would Uber or Lift or any right hailing companies say no, 631 00:37:20,440 --> 00:37:23,920 Speaker 1: we don't want to do fingerprint background checks. Well, this 632 00:37:24,000 --> 00:37:28,480 Speaker 1: comes down to a business reason more than a technological reason. 633 00:37:29,000 --> 00:37:33,759 Speaker 1: Uber drivers are considered contract workers in most states, not 634 00:37:34,080 --> 00:37:38,680 Speaker 1: employees of Uber. And this designation isn't just trivial. There 635 00:37:38,680 --> 00:37:41,719 Speaker 1: are lots of tax issues, there are benefits that can 636 00:37:41,719 --> 00:37:44,319 Speaker 1: come into play. There are a lot of things that 637 00:37:44,440 --> 00:37:48,520 Speaker 1: could affect Uber's bottom line if their staff, if their 638 00:37:48,600 --> 00:37:53,839 Speaker 1: drivers are considered employees rather than contract workers. So does 639 00:37:53,880 --> 00:37:56,279 Speaker 1: that have to do with fingerprinting. Well, the i r 640 00:37:56,440 --> 00:37:59,760 Speaker 1: S states that if a company exerts a certain amount 641 00:37:59,800 --> 00:38:03,719 Speaker 1: of quote control end quote over those who work for it. 642 00:38:04,160 --> 00:38:08,520 Speaker 1: Those people might be considered employees rather than contractors. So 643 00:38:08,560 --> 00:38:12,040 Speaker 1: in other words, if Uber can boss you around, Uber 644 00:38:12,120 --> 00:38:15,240 Speaker 1: is your boss, and there are certain obligations the company 645 00:38:15,280 --> 00:38:19,399 Speaker 1: has to meet if that's your relationship. Uber and other 646 00:38:19,560 --> 00:38:22,680 Speaker 1: ride hailing services don't want to go down that path 647 00:38:22,880 --> 00:38:26,040 Speaker 1: because it would mean a complete overhaul of their business model. 648 00:38:26,640 --> 00:38:29,759 Speaker 1: So there was this fear that if Uber were to 649 00:38:29,800 --> 00:38:34,360 Speaker 1: require fingerprinting, then the I R s would say that 650 00:38:34,400 --> 00:38:37,399 Speaker 1: seems like you have some control over your drivers, and 651 00:38:37,440 --> 00:38:39,360 Speaker 1: they could mean that drivers if they ever had a 652 00:38:39,440 --> 00:38:43,120 Speaker 1: labor dispute with Uber, could claim that they are employees, 653 00:38:43,400 --> 00:38:47,320 Speaker 1: not contractors, and therefore they have other protections in place. 654 00:38:47,680 --> 00:38:50,120 Speaker 1: The whole matter would likely have to be settled by 655 00:38:50,160 --> 00:38:52,600 Speaker 1: a court. But it all boils down to the fact 656 00:38:52,600 --> 00:38:55,600 Speaker 1: that Uber and Lift and other right hailing services would 657 00:38:55,760 --> 00:38:58,839 Speaker 1: much prefer to avoid that problem entirely, and thus they 658 00:38:58,880 --> 00:39:04,800 Speaker 1: resist any move to our choir companies to fingerprint their drivers. Unfortunately, 659 00:39:05,600 --> 00:39:08,600 Speaker 1: that opens up the possibility that the drivers that the 660 00:39:08,640 --> 00:39:12,719 Speaker 1: companies do employ could be problematic citizens, so in some 661 00:39:12,800 --> 00:39:16,920 Speaker 1: cases they might have criminal backgrounds. Typically, a new company 662 00:39:16,960 --> 00:39:20,239 Speaker 1: will partner with a third party provider to conduct background 663 00:39:20,320 --> 00:39:25,600 Speaker 1: checks on staff, and sometimes those background checks are cursory 664 00:39:25,920 --> 00:39:29,879 Speaker 1: and could easily miss important information. And this is not 665 00:39:30,120 --> 00:39:34,839 Speaker 1: just a hypothetical situation. In two thousand seventeen, state regulators 666 00:39:34,840 --> 00:39:37,880 Speaker 1: in Colorado went after Uber, saying that the company had 667 00:39:37,960 --> 00:39:41,920 Speaker 1: hired more than fifty drivers with criminal records or serious 668 00:39:42,120 --> 00:39:46,640 Speaker 1: vehicle offenses in their backgrounds. The regulators find Uber eight 669 00:39:46,719 --> 00:39:51,000 Speaker 1: point nine million dollars. Now, according to the regulators, it 670 00:39:51,040 --> 00:39:54,080 Speaker 1: wasn't just that Uber had allowed these people to drive 671 00:39:54,120 --> 00:39:57,000 Speaker 1: for the service, It was also that the company was 672 00:39:57,040 --> 00:40:01,760 Speaker 1: aware of their backgrounds. New whose Week quoted Doug Dean, 673 00:40:01,960 --> 00:40:06,879 Speaker 1: director of Colorado's Public Utilities Commission, and he said, we 674 00:40:06,960 --> 00:40:10,800 Speaker 1: have determined that Uber had background check information that should 675 00:40:10,880 --> 00:40:15,120 Speaker 1: have disqualified these drivers under the law, but they were 676 00:40:15,160 --> 00:40:19,440 Speaker 1: allowed to drive anyway. These actions put the safety of 677 00:40:19,560 --> 00:40:25,520 Speaker 1: passengers in extreme jeopardy. Now, according to that same Newsweek article, 678 00:40:25,800 --> 00:40:29,520 Speaker 1: the list of drivers included twelve who had felony offenses 679 00:40:29,560 --> 00:40:32,920 Speaker 1: in their background. There were three who had drunk driving 680 00:40:32,960 --> 00:40:36,600 Speaker 1: convictions of recent nature, and there were a whopping sixty 681 00:40:36,719 --> 00:40:40,600 Speaker 1: three drivers on Uber's payroll in Colorado who had issues 682 00:40:40,640 --> 00:40:43,359 Speaker 1: with their driver's licenses. Some of them might have had 683 00:40:43,400 --> 00:40:47,000 Speaker 1: suspended license or driving with an expired license, that kind 684 00:40:47,000 --> 00:40:50,600 Speaker 1: of thing. Uber's response was that this was all just 685 00:40:50,719 --> 00:40:54,400 Speaker 1: a quote process error in the quote and not really 686 00:40:54,560 --> 00:40:56,680 Speaker 1: as big a deal as the story made it out 687 00:40:56,719 --> 00:41:00,680 Speaker 1: to be. That Rather, Uber's process was just in consistent 688 00:41:00,760 --> 00:41:04,440 Speaker 1: with Colorado's regulations for ride sharing, and this was all 689 00:41:04,520 --> 00:41:08,120 Speaker 1: an honest misunderstanding that could be adjusted by just changing 690 00:41:08,160 --> 00:41:10,959 Speaker 1: up that process a little bit. If that is the case, 691 00:41:11,000 --> 00:41:14,120 Speaker 1: it's not the only time it's ever happened. Uber had 692 00:41:14,160 --> 00:41:17,440 Speaker 1: earlier been accused of hiring drivers with criminal records in 693 00:41:17,520 --> 00:41:21,240 Speaker 1: Los Angeles and San Francisco, and there have been numerous 694 00:41:21,280 --> 00:41:25,400 Speaker 1: stories of drivers who made passengers uncomfortable or outright scared 695 00:41:25,680 --> 00:41:30,320 Speaker 1: during their experiences. But we should remember these problem drivers 696 00:41:30,520 --> 00:41:34,200 Speaker 1: are outliers. Most of the people driving for Uber and 697 00:41:34,320 --> 00:41:37,719 Speaker 1: other services like it do not have criminal backgrounds. They 698 00:41:37,760 --> 00:41:41,719 Speaker 1: are responsible adults. They're just doing a job. The instances 699 00:41:41,760 --> 00:41:45,960 Speaker 1: of Uber falling short of expectations should not reflect on 700 00:41:46,000 --> 00:41:49,520 Speaker 1: all the people who work hard for the service. Rather, 701 00:41:50,040 --> 00:41:53,080 Speaker 1: I would say this is a cautionary tale for investors 702 00:41:53,080 --> 00:41:55,520 Speaker 1: and customers, and it points out the issues that the 703 00:41:55,560 --> 00:41:58,799 Speaker 1: company should work to resolve rather than just attempt to 704 00:41:58,880 --> 00:42:03,239 Speaker 1: explain away. Now getting back to Uber's history, By two 705 00:42:03,239 --> 00:42:07,680 Speaker 1: thousand eleven, the company was looking to expand in numerous cities. 706 00:42:08,040 --> 00:42:11,600 Speaker 1: One big one, New York City, was a huge target. 707 00:42:12,040 --> 00:42:15,319 Speaker 1: Uber started operating there in May two thousand eleven. To 708 00:42:15,400 --> 00:42:19,959 Speaker 1: say things when smoothly would be incorrect. In other words, 709 00:42:20,040 --> 00:42:23,200 Speaker 1: Uber's operations in New York City have been really rocky, 710 00:42:23,440 --> 00:42:26,359 Speaker 1: but it didn't stop the company from expanding in New 711 00:42:26,400 --> 00:42:29,920 Speaker 1: York City and beyond. By the end of two thousand eleven, 712 00:42:30,160 --> 00:42:33,719 Speaker 1: Uber tested out service in its first country outside the 713 00:42:33,800 --> 00:42:37,399 Speaker 1: United States. And how fitting should it be that that 714 00:42:37,520 --> 00:42:40,640 Speaker 1: first place where Uber opened up operations outside of the 715 00:42:40,680 --> 00:42:45,000 Speaker 1: United States was in France, in Paris. For it to 716 00:42:45,080 --> 00:42:49,480 Speaker 1: be really specific, and as we learned, that city is 717 00:42:49,680 --> 00:42:52,799 Speaker 1: the city of Uber's origin according to the company's own 718 00:42:52,880 --> 00:42:55,800 Speaker 1: official history, if you ignore all the stuff that Camp 719 00:42:55,880 --> 00:42:58,800 Speaker 1: did before he went to the web. But yeah, according 720 00:42:58,840 --> 00:43:01,840 Speaker 1: to the official Uber story, Paris, France is where the 721 00:43:01,880 --> 00:43:05,920 Speaker 1: whole idea got started. Uber would face much more resistance 722 00:43:05,960 --> 00:43:10,680 Speaker 1: in multiple markets, including outright protests. In fact, in France 723 00:43:10,760 --> 00:43:14,319 Speaker 1: there were some extremely violent ones. I'll talk a bit 724 00:43:14,640 --> 00:43:17,600 Speaker 1: about some of those in our next episode, but my 725 00:43:17,680 --> 00:43:20,880 Speaker 1: real focus for part two of the Uber story is 726 00:43:20,880 --> 00:43:24,160 Speaker 1: going to be two thousand seventeen. Now, a lot did 727 00:43:24,239 --> 00:43:27,520 Speaker 1: happen between two thousand and eleven and two thousand seventeen, 728 00:43:27,920 --> 00:43:29,600 Speaker 1: but a lot of it can be summed up with 729 00:43:30,200 --> 00:43:33,600 Speaker 1: Uber made a bold move into a market, face resistance, 730 00:43:33,719 --> 00:43:36,960 Speaker 1: and either persisted or bailed. There are a few other 731 00:43:37,000 --> 00:43:39,440 Speaker 1: things will need to look at. There's some battles between 732 00:43:39,560 --> 00:43:43,759 Speaker 1: Uber and the competitor Lift that got really nasty and 733 00:43:43,840 --> 00:43:48,840 Speaker 1: involved some seriously shady behavior allegedly on both sides. But 734 00:43:48,920 --> 00:43:50,759 Speaker 1: as I said, most of the episode is going to 735 00:43:50,800 --> 00:43:54,280 Speaker 1: focus on the chaotic and tumultuous events of two thousand 736 00:43:54,400 --> 00:43:58,520 Speaker 1: seventeen and how Uber changed as a result of those events. 737 00:43:59,080 --> 00:44:02,040 Speaker 1: In the meantime, if you guys have suggestions for future 738 00:44:02,120 --> 00:44:05,200 Speaker 1: episodes of tech Stuff, maybe there's a company you would 739 00:44:05,239 --> 00:44:07,640 Speaker 1: like me to cover, or specific technology you would like 740 00:44:07,680 --> 00:44:10,840 Speaker 1: to learn more about, or a guest I should interview 741 00:44:10,840 --> 00:44:13,040 Speaker 1: on the show or have as a guest co host 742 00:44:13,080 --> 00:44:15,879 Speaker 1: for an episode. Let me know your thoughts. You can 743 00:44:15,920 --> 00:44:19,080 Speaker 1: send me a message. The email address is tech Stuff 744 00:44:19,239 --> 00:44:22,520 Speaker 1: at how stuff works dot com, or you can drop 745 00:44:22,560 --> 00:44:25,759 Speaker 1: me a line on Twitter or Facebook. The handle I 746 00:44:25,880 --> 00:44:28,160 Speaker 1: use for both of those. For this show is text 747 00:44:28,160 --> 00:44:32,239 Speaker 1: stuff hs W. Remember we have an Instagram account. You 748 00:44:32,239 --> 00:44:34,879 Speaker 1: can go follow all the antics going on over there 749 00:44:34,880 --> 00:44:38,520 Speaker 1: and see some interesting behind the scenes photographs that we 750 00:44:38,560 --> 00:44:41,040 Speaker 1: are taking on a regular basis, as well as other 751 00:44:41,040 --> 00:44:44,200 Speaker 1: stuff that Crystal is curating for us, which is awesome. 752 00:44:44,880 --> 00:44:49,840 Speaker 1: And I also live stream tech Stuff on Wednesdays and Fridays. 753 00:44:49,880 --> 00:44:52,920 Speaker 1: If you just go to twitch dot tv slash tech Stuff, 754 00:44:53,120 --> 00:44:55,080 Speaker 1: you'll see the schedule there. You can join in when 755 00:44:55,120 --> 00:44:57,680 Speaker 1: you can watch me record the show live. I have 756 00:44:57,680 --> 00:45:00,120 Speaker 1: a chat room there you can chat with me and 757 00:45:00,160 --> 00:45:03,879 Speaker 1: whenever I'm on a break, I'll chat back. Otherwise I'm 758 00:45:03,960 --> 00:45:07,319 Speaker 1: I'm kind of doing the show because that's that's how 759 00:45:07,400 --> 00:45:11,400 Speaker 1: That's how sausages made. All right. That wraps up this episode. 760 00:45:11,920 --> 00:45:21,080 Speaker 1: I'll talk to you again. Release soon for more on 761 00:45:21,200 --> 00:45:23,919 Speaker 1: this and thousands of other topics because it how stuff works. 762 00:45:23,960 --> 00:45:34,120 Speaker 1: Dot com