1 00:00:04,240 --> 00:00:07,240 Speaker 1: Welcome to Text Stuff, a production of I Heart Radios 2 00:00:07,320 --> 00:00:14,120 Speaker 1: How Stuff Works. Hey there, and welcome to text Stuff. 3 00:00:14,160 --> 00:00:16,959 Speaker 1: I'm your host job in Strickland. I'm an executive producer 4 00:00:16,960 --> 00:00:18,880 Speaker 1: with iHeart Radio and a lot of all things tech. 5 00:00:18,920 --> 00:00:22,800 Speaker 1: And boy feels good to say those words, because you know, 6 00:00:23,000 --> 00:00:26,599 Speaker 1: I've been running around traveling doing lots of stuff for 7 00:00:26,760 --> 00:00:31,800 Speaker 1: another show called The Restless Ones, which you may have heard, uh, 8 00:00:31,840 --> 00:00:35,199 Speaker 1: And it means that I've had a lot of time 9 00:00:35,240 --> 00:00:38,280 Speaker 1: away from the studio. But I'm back today, and it's 10 00:00:38,320 --> 00:00:41,200 Speaker 1: that time of year when I take a look back 11 00:00:41,240 --> 00:00:44,519 Speaker 1: at the previous twelve months and consider some of the 12 00:00:44,520 --> 00:00:48,040 Speaker 1: biggest text stories to come out over the course of 13 00:00:48,080 --> 00:00:52,000 Speaker 1: the year. Now, this year, twenty nineteen, it was a 14 00:00:52,120 --> 00:00:55,280 Speaker 1: pretty darn packed one when it comes to news, and 15 00:00:55,320 --> 00:00:57,560 Speaker 1: things changed so quickly, and there are so many high 16 00:00:57,640 --> 00:00:59,800 Speaker 1: level stories that it can actually be pretty easy to 17 00:01:00,040 --> 00:01:02,880 Speaker 1: good stuff that happened earlier in the year. So I'm 18 00:01:02,880 --> 00:01:05,520 Speaker 1: gonna walk us through some of the big themes of 19 00:01:05,560 --> 00:01:08,200 Speaker 1: the year and some of the stories that center on 20 00:01:08,280 --> 00:01:11,399 Speaker 1: those themes. And there are so many things to talk 21 00:01:11,440 --> 00:01:13,840 Speaker 1: about that I'm actually gonna have to do two episodes 22 00:01:13,880 --> 00:01:15,679 Speaker 1: about it. I originally was going to really try and 23 00:01:15,720 --> 00:01:19,640 Speaker 1: cram it into one, but that just wasn't very practical. 24 00:01:19,680 --> 00:01:22,840 Speaker 1: I would just be rattling off headlines, and what good 25 00:01:22,920 --> 00:01:24,760 Speaker 1: is that. So this one's going to be filled with 26 00:01:24,760 --> 00:01:28,000 Speaker 1: a lot of stories about mistakes and things going wrong 27 00:01:28,040 --> 00:01:30,640 Speaker 1: in the world of tech. So I'm calling this episode 28 00:01:30,680 --> 00:01:35,360 Speaker 1: the Bummers of twenty nineteen. But um, here's the bad news. 29 00:01:35,360 --> 00:01:38,039 Speaker 1: There were a lot of bummer stories, So some of 30 00:01:38,040 --> 00:01:40,720 Speaker 1: those are gonna probably spill into the next episode two, 31 00:01:41,319 --> 00:01:44,880 Speaker 1: but I'll do my best to to to lighten the 32 00:01:44,920 --> 00:01:48,120 Speaker 1: mood of it in the next one occasionally. Now, one 33 00:01:48,160 --> 00:01:51,400 Speaker 1: of the big themes has actually become a pretty common 34 00:01:51,400 --> 00:01:55,200 Speaker 1: one over the last several years is the theme of 35 00:01:55,360 --> 00:01:59,840 Speaker 1: data breaches. Like I have previously called earlier years like 36 00:02:00,080 --> 00:02:02,960 Speaker 1: the Year of the Data Breach, but I think the 37 00:02:03,000 --> 00:02:05,640 Speaker 1: same thing can be said of twenty nineteen. So a 38 00:02:05,640 --> 00:02:09,840 Speaker 1: couple of years ago, the credit reporting company Equifax dealt 39 00:02:09,880 --> 00:02:13,680 Speaker 1: with a massive data breach that resulted in a host 40 00:02:13,840 --> 00:02:17,080 Speaker 1: of investigations in the United States both the state and 41 00:02:17,160 --> 00:02:21,280 Speaker 1: federal levels, and the company ultimately agreed to pay out 42 00:02:21,320 --> 00:02:26,840 Speaker 1: somewhere between five and seven hundred million dollars as a 43 00:02:26,919 --> 00:02:31,160 Speaker 1: result in fines. They were also giving people the opportunity 44 00:02:31,200 --> 00:02:34,760 Speaker 1: to lay a claim for at least some sort of 45 00:02:34,800 --> 00:02:38,919 Speaker 1: compensation for this data breach. People were invited to apply 46 00:02:39,000 --> 00:02:42,760 Speaker 1: for a payout of one hundred twenty five dollars, not 47 00:02:42,960 --> 00:02:47,040 Speaker 1: exactly a princely sum when you consider having your personal 48 00:02:47,080 --> 00:02:51,640 Speaker 1: information rated due to insufficient protections on a corporate level. 49 00:02:52,120 --> 00:02:56,079 Speaker 1: In September two tho nineteen, Equifax announced that people claiming 50 00:02:56,120 --> 00:02:58,720 Speaker 1: a payout would need to provide proof that they had 51 00:02:58,800 --> 00:03:03,600 Speaker 1: also enrolled in a credit monitoring service by October, because 52 00:03:03,639 --> 00:03:06,799 Speaker 1: that would show that the people had concern about their 53 00:03:06,800 --> 00:03:09,560 Speaker 1: own credit rating and their own personal information, that they 54 00:03:09,600 --> 00:03:12,520 Speaker 1: weren't just looking for money to get money, but that 55 00:03:12,600 --> 00:03:16,559 Speaker 1: they actually were actively trying to keep track of this stuff, 56 00:03:16,880 --> 00:03:20,119 Speaker 1: or else the claim could be denied, and the FTC 57 00:03:20,360 --> 00:03:24,200 Speaker 1: had previously already warned that due to the number of claims, 58 00:03:24,240 --> 00:03:26,360 Speaker 1: people were likely to get far less than a hundred 59 00:03:26,400 --> 00:03:29,440 Speaker 1: twenty five dollars because there was only a pool of 60 00:03:29,480 --> 00:03:32,400 Speaker 1: around thirty one million dollars that had been set aside 61 00:03:32,600 --> 00:03:35,520 Speaker 1: for these payouts. You know that five d seventy five 62 00:03:35,600 --> 00:03:38,720 Speaker 1: to seven million dollars that wasn't set aside for payouts. 63 00:03:38,880 --> 00:03:41,760 Speaker 1: Only thirty one million was set aside for payouts. And 64 00:03:41,800 --> 00:03:44,240 Speaker 1: I know it's crazy to say only thirty one million, 65 00:03:44,280 --> 00:03:47,520 Speaker 1: but when you look at the scale of this data breach, 66 00:03:48,120 --> 00:03:51,080 Speaker 1: you realize that that means if everyone who was affected 67 00:03:51,800 --> 00:03:54,840 Speaker 1: lays claim to a payout, you don't get very much. 68 00:03:56,000 --> 00:03:59,600 Speaker 1: But this whole mess has prompted more conversations about data 69 00:03:59,640 --> 00:04:03,160 Speaker 1: secure and corporate accountability, which is a good thing. It's 70 00:04:03,200 --> 00:04:06,320 Speaker 1: sad that it comes at the expense of this terrible mistake, 71 00:04:07,000 --> 00:04:10,160 Speaker 1: but at least people are talking more seriously about this. 72 00:04:10,320 --> 00:04:13,880 Speaker 1: Hopefully something will actually happen because of it. Now, we've 73 00:04:13,920 --> 00:04:17,039 Speaker 1: seen lots of these stories over the last several years, 74 00:04:17,320 --> 00:04:19,720 Speaker 1: and they really do show no sign of slowing down 75 00:04:19,839 --> 00:04:22,880 Speaker 1: right now, which is unfortunate. In twenty nineteen, there were 76 00:04:22,920 --> 00:04:26,960 Speaker 1: some truly notable examples across different industries. I pulled data 77 00:04:27,120 --> 00:04:30,400 Speaker 1: from Norton, the information security company to look at some 78 00:04:30,480 --> 00:04:33,400 Speaker 1: of the big ones. One of those would be Capital One, 79 00:04:34,320 --> 00:04:38,520 Speaker 1: the financial company, reported that hackers were able to access 80 00:04:39,080 --> 00:04:43,280 Speaker 1: a large amount of data, affecting one hundred six million 81 00:04:43,560 --> 00:04:47,400 Speaker 1: records in the company's files. Most of those records were 82 00:04:47,440 --> 00:04:51,240 Speaker 1: for a credit card applications rather than established accounts. So 83 00:04:51,320 --> 00:04:54,160 Speaker 1: it wasn't like the hackers necessarily got a lot of 84 00:04:54,200 --> 00:04:57,479 Speaker 1: credit card info, but they got a lot of application information. 85 00:04:57,480 --> 00:04:59,560 Speaker 1: And when you think about the info you need to 86 00:04:59,640 --> 00:05:03,680 Speaker 1: provide hide when you apply for a credit card, it 87 00:05:03,720 --> 00:05:09,200 Speaker 1: includes stuff like, you know, personal information that is really 88 00:05:09,279 --> 00:05:13,039 Speaker 1: important to you. And it might be mundane stuff like 89 00:05:13,080 --> 00:05:15,520 Speaker 1: your name, which, hey, you know, no big deal, someone 90 00:05:15,560 --> 00:05:19,080 Speaker 1: knows your name, okay, But it might include your email, 91 00:05:19,520 --> 00:05:23,640 Speaker 1: which again maybe that's more frustrating or or irritating. But 92 00:05:23,720 --> 00:05:27,000 Speaker 1: then there's also your physical address, which gets a little 93 00:05:27,000 --> 00:05:32,960 Speaker 1: more spooky scary, your credit score, your income, maybe your 94 00:05:33,000 --> 00:05:36,479 Speaker 1: Social Security number, essentially all the stuff it would take 95 00:05:36,480 --> 00:05:38,800 Speaker 1: for someone to steal your identity and sell it off 96 00:05:38,839 --> 00:05:41,560 Speaker 1: on the dark web, which is not very cool. Capital 97 00:05:41,600 --> 00:05:45,960 Speaker 1: one hacker named Page Thompson targeted a third party cloud 98 00:05:46,040 --> 00:05:50,360 Speaker 1: computing company that Capital One had relied upon to host 99 00:05:50,480 --> 00:05:54,800 Speaker 1: the credit application services. She exploited a vulnerability in a 100 00:05:54,839 --> 00:05:57,839 Speaker 1: web at firewall to get illegal access to the data. 101 00:05:58,080 --> 00:06:00,720 Speaker 1: She was arrested for the data intrusion, and then she 102 00:06:00,839 --> 00:06:05,760 Speaker 1: was held in a men's detention center. Uh, she's transgender, 103 00:06:05,760 --> 00:06:08,280 Speaker 1: and this gets into a whole thing with criminal justice 104 00:06:08,279 --> 00:06:11,279 Speaker 1: systems and the treatment of people who are transgender, which 105 00:06:11,520 --> 00:06:14,159 Speaker 1: honestly goes way beyond the scope of this podcast. But 106 00:06:14,200 --> 00:06:15,719 Speaker 1: I'll just say that when I read that she was 107 00:06:15,720 --> 00:06:19,120 Speaker 1: held in a men's detention center, that really upset me. Now, 108 00:06:19,160 --> 00:06:23,040 Speaker 1: I don't disagree with her being detained she broke the law, 109 00:06:23,360 --> 00:06:28,039 Speaker 1: or allegedly broke the law. She denies this. I more 110 00:06:28,080 --> 00:06:32,440 Speaker 1: object that it wasn't in a more appropriate setting. Anyway, 111 00:06:32,520 --> 00:06:35,440 Speaker 1: She's awaiting trial for the case. That trial is scheduled 112 00:06:35,520 --> 00:06:39,719 Speaker 1: right now for March twenty. She has pled not guilty 113 00:06:39,800 --> 00:06:43,719 Speaker 1: to the charges. Another company to experience a data breach 114 00:06:43,880 --> 00:06:47,640 Speaker 1: was door Dash, the food delivery service. The company experienced 115 00:06:47,640 --> 00:06:51,480 Speaker 1: the breach in May, but didn't disclose it until September 116 00:06:51,560 --> 00:06:55,320 Speaker 1: twenty nineteen. A third party access the information of nearly 117 00:06:55,400 --> 00:06:59,960 Speaker 1: five million drivers and customers without permission. The information they 118 00:07:00,040 --> 00:07:03,000 Speaker 1: were able to access included personal information, including the last 119 00:07:03,000 --> 00:07:06,080 Speaker 1: few digits of credit card and bank account numbers, but 120 00:07:06,160 --> 00:07:09,960 Speaker 1: not the whole number. It was just that last little string. 121 00:07:10,800 --> 00:07:14,680 Speaker 1: It also included the hashed passwords of many account holders, 122 00:07:14,760 --> 00:07:17,760 Speaker 1: so it's always good to change your password if you 123 00:07:17,840 --> 00:07:22,040 Speaker 1: make use of services that later reveal that they've been hacked, 124 00:07:22,320 --> 00:07:25,800 Speaker 1: it's always a good idea to change that information. And also, well, 125 00:07:25,840 --> 00:07:28,640 Speaker 1: I'll get to it, but don't use the same password everywhere. 126 00:07:29,040 --> 00:07:32,520 Speaker 1: It's a little spoiler alert for a future discussion. So 127 00:07:33,760 --> 00:07:36,720 Speaker 1: early in the year, the service Evite had a data 128 00:07:36,800 --> 00:07:40,880 Speaker 1: breach that affected one hundred million records, again exposing customer 129 00:07:40,880 --> 00:07:44,920 Speaker 1: information like names, addresses, phone numbers, and the password that 130 00:07:44,960 --> 00:07:48,000 Speaker 1: they used for the account. And again the exposure of 131 00:07:48,000 --> 00:07:52,320 Speaker 1: passwords drives home that importance right use unique passwords with 132 00:07:52,400 --> 00:07:55,880 Speaker 1: different services. That way, if one service is compromised, you 133 00:07:55,880 --> 00:07:58,960 Speaker 1: don't have to worry about the hackers accessing everything else 134 00:07:59,040 --> 00:08:02,120 Speaker 1: you use using the same password. If you're using one 135 00:08:02,160 --> 00:08:04,880 Speaker 1: password for everything, then you're essentially opening up the door. 136 00:08:05,520 --> 00:08:08,960 Speaker 1: As soon as one breach is effective, all of your 137 00:08:09,000 --> 00:08:13,360 Speaker 1: services have been breached. So don't use the same password 138 00:08:13,400 --> 00:08:16,880 Speaker 1: for everything. Use a password vault, UH, use stuff like 139 00:08:16,920 --> 00:08:20,560 Speaker 1: two factor authentication. All of that will help minimize your risk. 140 00:08:20,640 --> 00:08:24,480 Speaker 1: It doesn't eliminate it, but it minimizes it. And if 141 00:08:24,480 --> 00:08:26,880 Speaker 1: you find out one of the services you use was compromised, 142 00:08:26,960 --> 00:08:29,640 Speaker 1: change all that log and information right away. Now. The 143 00:08:29,640 --> 00:08:32,760 Speaker 1: medical industry also saw its share of data breaches the 144 00:08:32,800 --> 00:08:36,880 Speaker 1: American Medical Collection Agency, which is a company that collects 145 00:08:36,920 --> 00:08:40,719 Speaker 1: overdue payments for various medical labs. So essentially, these are 146 00:08:40,720 --> 00:08:42,600 Speaker 1: the folks who come after you if you haven't paid 147 00:08:42,640 --> 00:08:47,000 Speaker 1: certain medical bills. They also had a breach. Hackers access 148 00:08:47,080 --> 00:08:50,120 Speaker 1: more than twenty million records, and the information included not 149 00:08:50,200 --> 00:08:54,000 Speaker 1: just personal information, but even stuff like credit card information. 150 00:08:54,440 --> 00:08:57,199 Speaker 1: The actual breach began back in the summer of eighteen, 151 00:08:57,320 --> 00:09:02,080 Speaker 1: but the vulnerability remain unpatched until Arch twenty nineteen. In 152 00:09:02,160 --> 00:09:04,800 Speaker 1: June of this year, the company filed for bankruptcy protection. 153 00:09:05,120 --> 00:09:08,960 Speaker 1: So you know, things are just going great for them. 154 00:09:09,040 --> 00:09:12,280 Speaker 1: And close to home, Georgia Tech suffered a data breach 155 00:09:12,360 --> 00:09:16,040 Speaker 1: when some third party gained access to a university owned database. 156 00:09:16,320 --> 00:09:19,560 Speaker 1: The database had tons of personal information on current and 157 00:09:19,679 --> 00:09:23,320 Speaker 1: former students, as well as staff and faculty at the college, 158 00:09:23,520 --> 00:09:27,800 Speaker 1: including things like social security numbers. In total, one point 159 00:09:27,840 --> 00:09:32,240 Speaker 1: to six five million people were affected by that data breach. 160 00:09:32,720 --> 00:09:35,400 Speaker 1: The college is reaching out to offer credit monitoring and 161 00:09:35,520 --> 00:09:39,040 Speaker 1: identity theft protection services for those affected by it, but 162 00:09:39,120 --> 00:09:42,600 Speaker 1: still yikes. The U. S Government also was not immune 163 00:09:42,600 --> 00:09:47,040 Speaker 1: to data breaches. The Federal Emergency Management Agency, or FEMA 164 00:09:47,160 --> 00:09:50,280 Speaker 1: had a data breach, not because some hacker broke into 165 00:09:50,280 --> 00:09:54,960 Speaker 1: the system, but because the agency accidentally released files containing 166 00:09:54,960 --> 00:09:58,120 Speaker 1: sensitive information, such as the personal info of more than 167 00:09:58,160 --> 00:10:03,040 Speaker 1: two million people. So ad trombone noise insert here now. 168 00:10:03,120 --> 00:10:07,160 Speaker 1: According to the US Inspector General, FEMA violated the Privacy 169 00:10:07,200 --> 00:10:10,440 Speaker 1: Act of nineteen seventy four by releasing this data to 170 00:10:10,520 --> 00:10:14,080 Speaker 1: a third party contractor. The contractor was in charge of 171 00:10:14,120 --> 00:10:18,080 Speaker 1: securing temporary lodging for people who are affected by emergencies 172 00:10:18,120 --> 00:10:21,840 Speaker 1: and disasters, so like a fire or a flood. But 173 00:10:22,040 --> 00:10:26,200 Speaker 1: the data FEMA provided was far more extensive than what 174 00:10:26,320 --> 00:10:29,079 Speaker 1: was actually needed for this contractor to do its job, 175 00:10:29,880 --> 00:10:33,280 Speaker 1: and so that data included stuff like banking information and 176 00:10:33,320 --> 00:10:36,920 Speaker 1: bank transit numbers and stuff like that, stuff that did 177 00:10:36,960 --> 00:10:39,679 Speaker 1: not need to be shared. Now, considering that this breach 178 00:10:39,720 --> 00:10:43,920 Speaker 1: affected people who are already dealing with emergency situations that 179 00:10:43,960 --> 00:10:47,400 Speaker 1: were bad enough to necessitate a relocation, that's a that's 180 00:10:47,400 --> 00:10:51,840 Speaker 1: a big, big ouch. Making matters worse is that even 181 00:10:51,880 --> 00:10:54,920 Speaker 1: some of the companies that are dedicated towards security and 182 00:10:55,000 --> 00:10:59,120 Speaker 1: privacy have had data breaches in twenty nineteen. Take nord 183 00:10:59,240 --> 00:11:02,280 Speaker 1: VPN for example. That was a service that I've used 184 00:11:02,280 --> 00:11:05,400 Speaker 1: in the past. A VPN is a virtual private network, 185 00:11:05,440 --> 00:11:07,280 Speaker 1: and the purpose of a VPN is to allow a 186 00:11:07,360 --> 00:11:10,280 Speaker 1: user to log into a remote server and then use 187 00:11:10,360 --> 00:11:13,480 Speaker 1: various internet services so that they can't be traced back 188 00:11:13,640 --> 00:11:16,640 Speaker 1: to the end user. Now, at first glance, that might 189 00:11:16,679 --> 00:11:19,600 Speaker 1: sound like it's shady, but it's actually a really useful service. 190 00:11:19,920 --> 00:11:22,560 Speaker 1: If you're concerned about your own data security, you can 191 00:11:22,640 --> 00:11:24,760 Speaker 1: use a VPN when you're in areas where you can't 192 00:11:24,800 --> 00:11:27,079 Speaker 1: be certain of the security of the network, and that 193 00:11:27,200 --> 00:11:31,839 Speaker 1: helps improve your own security. But then this year, word 194 00:11:31,880 --> 00:11:35,120 Speaker 1: came out that nord vpn had an internal private key 195 00:11:35,160 --> 00:11:39,400 Speaker 1: exposed back in which created the possibility for hackers to 196 00:11:39,440 --> 00:11:42,960 Speaker 1: create a server and host it on the nord vpn 197 00:11:43,040 --> 00:11:47,199 Speaker 1: service as if it were a valid Nord VPN server. Now, 198 00:11:47,240 --> 00:11:51,079 Speaker 1: that would mean that an end user who was relying 199 00:11:51,080 --> 00:11:54,200 Speaker 1: on nord vpn might end up logging into one of 200 00:11:54,200 --> 00:11:57,880 Speaker 1: the hackers computers thinking it was a secure VPN server, 201 00:11:58,320 --> 00:12:00,319 Speaker 1: and the hacker we get to see all the traffic 202 00:12:00,520 --> 00:12:04,200 Speaker 1: coming through that computer. Nord vpn has stated that since 203 00:12:04,240 --> 00:12:07,120 Speaker 1: the breach, the company has patched this problem and that 204 00:12:07,160 --> 00:12:10,319 Speaker 1: the company doesn't keep a log of any user activity, 205 00:12:10,360 --> 00:12:13,400 Speaker 1: So hackers would only capture any traffic that happened on 206 00:12:13,440 --> 00:12:16,160 Speaker 1: their own server during that breach. They wouldn't have gotten 207 00:12:16,440 --> 00:12:20,240 Speaker 1: traffic information from any other servers on the nord VPN network. 208 00:12:20,840 --> 00:12:23,520 Speaker 1: They wouldn't be able to look at historic data because 209 00:12:23,960 --> 00:12:27,160 Speaker 1: the company doesn't keep any Still, that might come as 210 00:12:27,160 --> 00:12:29,959 Speaker 1: a little comfort to a community of users who presumably 211 00:12:30,040 --> 00:12:32,240 Speaker 1: have subscribed to the service out of a desire to 212 00:12:32,280 --> 00:12:36,240 Speaker 1: maintain privacy and security. Now, these stories are pretty discouraging, 213 00:12:36,559 --> 00:12:39,679 Speaker 1: and to be honest, it's just the tip of a 214 00:12:39,760 --> 00:12:43,880 Speaker 1: huge iceberg. According to a report from Javelin Strategy and Research, 215 00:12:44,280 --> 00:12:48,199 Speaker 1: there were five thousand, one hundred eighty three reported data 216 00:12:48,240 --> 00:12:52,360 Speaker 1: breaches in the first nine months of two thousand nineteen alone. 217 00:12:52,960 --> 00:12:57,439 Speaker 1: Now keep in mind those are reported data breaches. There 218 00:12:57,440 --> 00:13:01,760 Speaker 1: are likely many more that have either gone discovered or unreported. 219 00:13:02,120 --> 00:13:07,640 Speaker 1: Now those breaches represent nearly eight billion records exposed. The 220 00:13:07,760 --> 00:13:11,240 Speaker 1: rate shows a thirty three increase in breaches compared to 221 00:13:11,240 --> 00:13:15,000 Speaker 1: two thousand eighteen. Most of those breaches happened to companies 222 00:13:15,000 --> 00:13:18,320 Speaker 1: with fewer than one employees, so these weren't like the 223 00:13:18,440 --> 00:13:21,439 Speaker 1: big big news items like Capital One or door Dash. 224 00:13:21,800 --> 00:13:24,520 Speaker 1: There were some good news items in the report. However, 225 00:13:24,920 --> 00:13:28,679 Speaker 1: not everything was dour. Credit Card security has improved thanks 226 00:13:28,679 --> 00:13:32,080 Speaker 1: to chip technology, so there was actually a decline in 227 00:13:32,160 --> 00:13:35,679 Speaker 1: credit card frauds. That's something to be thankful for. Now. 228 00:13:35,760 --> 00:13:38,800 Speaker 1: It can be a hassle just to practice good secure 229 00:13:38,920 --> 00:13:42,240 Speaker 1: internet habits, as I've covered in previous episodes of tech Stuff. 230 00:13:42,520 --> 00:13:46,240 Speaker 1: As users, we all have a responsibility to protect our 231 00:13:46,320 --> 00:13:49,080 Speaker 1: data as best we can, But if we want to 232 00:13:49,080 --> 00:13:53,080 Speaker 1: do useful stuff with that data, ultimately we eventually have 233 00:13:53,240 --> 00:13:56,120 Speaker 1: to hand it over to other entities, and when these 234 00:13:56,200 --> 00:14:00,119 Speaker 1: other entities have data breaches, it's also a breach of trust. 235 00:14:00,520 --> 00:14:04,800 Speaker 1: If we don't trust in the systems, things fall apart. Now, 236 00:14:04,880 --> 00:14:07,480 Speaker 1: I think it highly unlikely that we're going to see 237 00:14:07,640 --> 00:14:11,200 Speaker 1: fewer attempts at data breaches as time goes on. It 238 00:14:11,280 --> 00:14:13,760 Speaker 1: only makes sense we're gonna keep seeing them and probably 239 00:14:13,840 --> 00:14:17,640 Speaker 1: see efforts increase over time. So hopefully we'll have more 240 00:14:17,679 --> 00:14:22,040 Speaker 1: success stories revolving around foiling a data breach. But the 241 00:14:22,080 --> 00:14:25,240 Speaker 1: world of information security is typically a see saw type 242 00:14:25,240 --> 00:14:28,120 Speaker 1: of thing. The hackers get better at cracking systems and 243 00:14:28,160 --> 00:14:32,480 Speaker 1: exploiting vulnerabilities, companies get better at patching the holes, but 244 00:14:32,520 --> 00:14:35,520 Speaker 1: then the hackers look for different holes, and the entire 245 00:14:35,560 --> 00:14:39,440 Speaker 1: cycle repeats itself. Meanwhile, people like you and me get 246 00:14:39,480 --> 00:14:42,520 Speaker 1: caught up with our data potentially at risk, which is 247 00:14:42,600 --> 00:14:46,280 Speaker 1: kind of gross. Well, let's stick with some more bummers. 248 00:14:46,440 --> 00:14:50,160 Speaker 1: Um I figured if I frontload the episodes with bummers, 249 00:14:50,160 --> 00:14:52,600 Speaker 1: then I can make some space in the back half 250 00:14:52,760 --> 00:14:54,960 Speaker 1: for some more fun stuff. But first, let's talk about 251 00:14:55,000 --> 00:14:58,800 Speaker 1: financial performance. So two thousand nineteen saw some pretty rough 252 00:14:58,880 --> 00:15:02,320 Speaker 1: quarters for a you companies. One of those was Uber. 253 00:15:02,400 --> 00:15:04,840 Speaker 1: Now I mentioned this in an earlier episode this year 254 00:15:04,880 --> 00:15:07,560 Speaker 1: about fake it until you Make it, but Uber leads 255 00:15:07,600 --> 00:15:10,640 Speaker 1: the way among ride hailing companies in a category you 256 00:15:10,760 --> 00:15:13,400 Speaker 1: don't want to appear in, which is the most money 257 00:15:13,560 --> 00:15:17,160 Speaker 1: lost per quarter. Now, to be clear, all ride hailing 258 00:15:17,200 --> 00:15:20,760 Speaker 1: companies are losing money. None of them are profitable. No 259 00:15:20,800 --> 00:15:23,520 Speaker 1: one has figured out how to make a business model 260 00:15:23,720 --> 00:15:27,000 Speaker 1: that has a profitable side as of yet. But Uber 261 00:15:27,120 --> 00:15:30,240 Speaker 1: is losing money on a scale that's pretty monumental. During 262 00:15:30,240 --> 00:15:33,080 Speaker 1: the second quarter of twenty nineteen, the company posted revenues 263 00:15:33,080 --> 00:15:36,480 Speaker 1: of three billion dollars, which, come on, that's that's a 264 00:15:36,520 --> 00:15:41,960 Speaker 1: lot of chadder, But they posted losses of five billion dollars. 265 00:15:42,480 --> 00:15:46,480 Speaker 1: Wolf Uber CEO stated that a large part of those 266 00:15:46,520 --> 00:15:49,400 Speaker 1: losses came from the I P O process that Uber 267 00:15:49,440 --> 00:15:52,640 Speaker 1: went through the initial public offering. The company had bought 268 00:15:52,680 --> 00:15:56,520 Speaker 1: back shares that belonged to employees, which posted in the 269 00:15:56,520 --> 00:15:59,280 Speaker 1: company records as an expense, but that was a one 270 00:15:59,320 --> 00:16:02,400 Speaker 1: time expen Uber won't be buying back shares again in 271 00:16:02,400 --> 00:16:06,120 Speaker 1: the future. Still, analysts say that even taking into account 272 00:16:06,240 --> 00:16:09,320 Speaker 1: the stock compensation cost, Uber would have lost more than 273 00:16:09,360 --> 00:16:12,760 Speaker 1: a billion dollars. And that's just one quarter. That's not 274 00:16:12,800 --> 00:16:15,400 Speaker 1: all of twenty nineteen, So if my math is right, 275 00:16:15,800 --> 00:16:18,960 Speaker 1: there are four quarters every year. So the question is, 276 00:16:19,080 --> 00:16:21,840 Speaker 1: can Uber find a way to be profitable in the 277 00:16:21,960 --> 00:16:25,120 Speaker 1: right hailing and related businesses or will it have to 278 00:16:25,160 --> 00:16:28,480 Speaker 1: bank on investors bailing the company out again. I'm worried 279 00:16:28,520 --> 00:16:31,040 Speaker 1: we're looking at another bubble that's just about to burst. 280 00:16:31,240 --> 00:16:34,200 Speaker 1: But I hold out hope that companies like Uber Left 281 00:16:34,240 --> 00:16:36,720 Speaker 1: and other right hailing services are able to turn things 282 00:16:36,800 --> 00:16:40,760 Speaker 1: around preferably while also treating their employees well and ensuring 283 00:16:40,800 --> 00:16:44,560 Speaker 1: the safety of their customers, which are also ongoing issues 284 00:16:44,600 --> 00:16:47,680 Speaker 1: with many of these right hailing companies. More to say 285 00:16:47,720 --> 00:16:49,480 Speaker 1: about that in just a moment, but first let's take 286 00:16:49,760 --> 00:17:00,480 Speaker 1: a quick break now. Speaking of safety and right inhaling, 287 00:17:00,560 --> 00:17:03,440 Speaker 1: it's also important to hold up Lift to the magnifying 288 00:17:03,480 --> 00:17:07,000 Speaker 1: glass and not give that company a free pass while 289 00:17:07,240 --> 00:17:11,159 Speaker 1: raking Uber over the coals. Numerous women have come forward 290 00:17:11,200 --> 00:17:14,400 Speaker 1: in lawsuits against Lift, stating that they were the victims 291 00:17:14,400 --> 00:17:17,199 Speaker 1: of assault. They also say the company did nothing to 292 00:17:17,240 --> 00:17:20,159 Speaker 1: prevent those assaults, and they didn't do enough to ensure 293 00:17:20,200 --> 00:17:23,800 Speaker 1: passengers safety. And on top of all that, they say 294 00:17:23,840 --> 00:17:28,080 Speaker 1: that Lift ignored complaints filed after the assaults took place 295 00:17:28,440 --> 00:17:32,080 Speaker 1: and then downplayed the events to the media. One lawyer 296 00:17:32,160 --> 00:17:36,360 Speaker 1: states that there's evidence that Lift purposefully withheld cooperation from 297 00:17:36,400 --> 00:17:40,520 Speaker 1: law enforcement officers who are investigating these claims. Now Lift 298 00:17:40,600 --> 00:17:43,000 Speaker 1: is not the only right hailing company to come under 299 00:17:43,000 --> 00:17:46,560 Speaker 1: scrutiny due to safety concerns and reports of assault, and 300 00:17:46,600 --> 00:17:49,639 Speaker 1: there are also cases in which drivers have been assaulted 301 00:17:49,680 --> 00:17:53,439 Speaker 1: by passengers. This is an ongoing story, and there are 302 00:17:53,440 --> 00:17:56,320 Speaker 1: a lot of discussions about measures that could help protect 303 00:17:56,359 --> 00:17:59,639 Speaker 1: passengers and drivers alike. But the rollout is likely to 304 00:17:59,640 --> 00:18:03,479 Speaker 1: be re regional and staggered over weeks or months, so 305 00:18:03,520 --> 00:18:07,840 Speaker 1: it's not exactly the super fast response you would hope for. Necessarily, 306 00:18:08,200 --> 00:18:10,520 Speaker 1: all right, let's keep that bummer train of moving. In 307 00:18:10,680 --> 00:18:15,639 Speaker 1: January two thousand, nineteen, the utility company Pacific Gas and 308 00:18:15,720 --> 00:18:19,840 Speaker 1: Electric or pg n E, declared bankruptcy. Now, this company 309 00:18:19,920 --> 00:18:23,160 Speaker 1: serves customers along the West Coast, and in twenty seventeen, 310 00:18:23,520 --> 00:18:27,000 Speaker 1: it was found guilty of starting a series of wildfires 311 00:18:27,040 --> 00:18:31,400 Speaker 1: in California, which then put the company thirty billion dollars 312 00:18:31,600 --> 00:18:34,800 Speaker 1: in debt. That's billion with a b P. G n 313 00:18:34,880 --> 00:18:38,800 Speaker 1: E emerged from bankruptcy in September twenty nineteen after agreeing 314 00:18:38,880 --> 00:18:43,240 Speaker 1: on an eleven billion dollar settlement with insurance companies. Now, 315 00:18:43,240 --> 00:18:45,960 Speaker 1: this is the same utility company that would shut down 316 00:18:46,000 --> 00:18:49,879 Speaker 1: power to California residents in a series of planned blackouts 317 00:18:49,960 --> 00:18:53,119 Speaker 1: during a particularly windy season in order to avoid a 318 00:18:53,200 --> 00:18:56,840 Speaker 1: similar situation and which perhaps a broken power line might 319 00:18:56,960 --> 00:19:00,359 Speaker 1: start a wildfire. The blackouts affected more than half a 320 00:19:00,359 --> 00:19:03,919 Speaker 1: million people in the San Francisco region. So that was 321 00:19:03,960 --> 00:19:07,760 Speaker 1: not a great story, and the tech sector obviously covered 322 00:19:07,760 --> 00:19:10,520 Speaker 1: it quite a bit, with so many tech companies located 323 00:19:10,560 --> 00:19:13,879 Speaker 1: in the Bay Area. Now, at least seven coal mining 324 00:19:13,920 --> 00:19:17,520 Speaker 1: companies in the United States have declared bankruptcy in twenty nineteen, 325 00:19:17,680 --> 00:19:20,639 Speaker 1: which marked the first year in which more US citizens 326 00:19:20,680 --> 00:19:24,480 Speaker 1: got electricity from renewable sources than from coal powered plants. 327 00:19:25,119 --> 00:19:28,160 Speaker 1: At least thirty three oil and gas producers have gone 328 00:19:28,160 --> 00:19:31,520 Speaker 1: bankrupt as well, and the Zoo might imagine this has 329 00:19:31,560 --> 00:19:35,000 Speaker 1: made lots of folks in the coal and oil industries upset. 330 00:19:35,400 --> 00:19:37,760 Speaker 1: And while I definitely don't want to see people face 331 00:19:37,840 --> 00:19:40,400 Speaker 1: hardship as companies closed down, I don't want to see 332 00:19:40,440 --> 00:19:43,359 Speaker 1: people out of work. I also think the move away 333 00:19:43,400 --> 00:19:47,000 Speaker 1: from fossil fuels is a necessity. So it's my hope 334 00:19:47,480 --> 00:19:50,159 Speaker 1: that employees of these companies can find work in the 335 00:19:50,240 --> 00:19:54,000 Speaker 1: renewable energy sector. I think it's imperative we rid ourselves 336 00:19:54,000 --> 00:19:56,280 Speaker 1: of our dependence upon fossil fuels. But we also have 337 00:19:56,320 --> 00:19:59,480 Speaker 1: to make sure that the people who were employed by 338 00:19:59,520 --> 00:20:03,040 Speaker 1: that into tree can find good work elsewhere and they're 339 00:20:03,040 --> 00:20:05,640 Speaker 1: not just left in the lurch. We have to make 340 00:20:05,680 --> 00:20:08,440 Speaker 1: sure that whatever plans we have to transition away from 341 00:20:08,480 --> 00:20:12,800 Speaker 1: fossil fuels also take into account the people whose livelihoods 342 00:20:12,800 --> 00:20:16,840 Speaker 1: depend upon those industries. Now, speaking of going elsewhere, what 343 00:20:16,880 --> 00:20:19,840 Speaker 1: do you do when your company is in financial crisis 344 00:20:20,200 --> 00:20:23,119 Speaker 1: and the company's main product is renting out office space 345 00:20:23,200 --> 00:20:26,480 Speaker 1: to tech startups. That's the question that we Work has 346 00:20:26,520 --> 00:20:29,600 Speaker 1: been trying to answer for much of twenty nineteen. So 347 00:20:29,640 --> 00:20:33,480 Speaker 1: we Work was launched back in. The company leases out 348 00:20:33,600 --> 00:20:36,919 Speaker 1: office space to tenants and markets around the globe, So 349 00:20:37,000 --> 00:20:41,159 Speaker 1: essentially at leases out space and buildings and then sublets 350 00:20:41,240 --> 00:20:44,280 Speaker 1: that space to smaller companies. And in that regard, it's 351 00:20:44,320 --> 00:20:48,200 Speaker 1: not really a tech company in of itself, but it's 352 00:20:48,320 --> 00:20:52,800 Speaker 1: clients are in largely the startup tech space. It's kind 353 00:20:52,800 --> 00:20:57,119 Speaker 1: of the market that we Work targets. Specifically, we Work 354 00:20:57,160 --> 00:20:59,720 Speaker 1: offices tend to have amenities that you might find in 355 00:20:59,760 --> 00:21:02,080 Speaker 1: a art up that has a lot of venture capital 356 00:21:02,080 --> 00:21:04,439 Speaker 1: and angel investors behind it. So, you know, a lot 357 00:21:04,440 --> 00:21:08,280 Speaker 1: of tech journals have covered the company's rather tumultuous twenty nineteen. 358 00:21:08,840 --> 00:21:12,199 Speaker 1: We Work initially planned to hold an initial public offering 359 00:21:12,240 --> 00:21:15,520 Speaker 1: in September twenty nineteen, when it would become a publicly 360 00:21:15,560 --> 00:21:17,920 Speaker 1: traded company on the stock market. Only things did not 361 00:21:18,119 --> 00:21:22,240 Speaker 1: go quite as planned. First, something that would have made 362 00:21:22,280 --> 00:21:25,840 Speaker 1: my eyebrows go up was that the founder or co founder, 363 00:21:25,880 --> 00:21:30,320 Speaker 1: Adam Newman, liquidated around seven hundred million dollars worth of 364 00:21:30,359 --> 00:21:35,320 Speaker 1: we Work stock before it went into its initial public offering. Now, 365 00:21:35,800 --> 00:21:40,359 Speaker 1: that does not necessarily mean that Newman lacked confidence about 366 00:21:40,400 --> 00:21:43,280 Speaker 1: how the stock market would treat his company, but a 367 00:21:43,320 --> 00:21:46,720 Speaker 1: lot of folks tend to interpret those types of moves 368 00:21:47,160 --> 00:21:50,320 Speaker 1: as kind of a message that the founder doesn't think 369 00:21:50,440 --> 00:21:53,720 Speaker 1: things are gonna go well, so they're cashing out before 370 00:21:53,840 --> 00:21:57,399 Speaker 1: the value of their stock tanks. Now, when the I 371 00:21:57,520 --> 00:22:01,439 Speaker 1: p O paperwork became public in August twenty nineteen, journalists 372 00:22:01,480 --> 00:22:04,240 Speaker 1: pointed out that the company had been experiencing some pretty 373 00:22:04,280 --> 00:22:08,240 Speaker 1: massive losses, not unlike the right hailing businesses I talked 374 00:22:08,280 --> 00:22:11,760 Speaker 1: about earlier in this episode, there were questions about whether 375 00:22:11,840 --> 00:22:15,480 Speaker 1: or not we Work would ever be profitable, so also 376 00:22:15,760 --> 00:22:17,800 Speaker 1: like the right hailing services. In fact, I think there 377 00:22:17,840 --> 00:22:20,400 Speaker 1: are a lot of parallels between the two. There's also 378 00:22:20,440 --> 00:22:22,919 Speaker 1: a report that in some we Work offices the company 379 00:22:22,920 --> 00:22:26,000 Speaker 1: had included stuff like these little phone cubbies or phone 380 00:22:26,000 --> 00:22:29,879 Speaker 1: booths that had equipment in them that was emitting for 381 00:22:30,000 --> 00:22:33,760 Speaker 1: malde hyde fumes, which isn't a great thing either. We 382 00:22:33,800 --> 00:22:36,119 Speaker 1: Work ended up scuttling its plans for an I p 383 00:22:36,240 --> 00:22:41,200 Speaker 1: O and postponed those plans UH to late twenty nineteen, which, 384 00:22:41,240 --> 00:22:44,800 Speaker 1: as far as this recording is concerned, UH still hasn't 385 00:22:44,840 --> 00:22:48,000 Speaker 1: happened those those I p O plans. Newman actually would 386 00:22:48,000 --> 00:22:51,320 Speaker 1: step down as CEO shortly thereafter. He reportedly got a 387 00:22:51,400 --> 00:22:56,000 Speaker 1: one point seven billion dollar buyout from soft Bank, which 388 00:22:56,280 --> 00:23:00,160 Speaker 1: effectively controls we Work. Now, we Work began to all 389 00:23:00,160 --> 00:23:03,560 Speaker 1: off some other companies it had acquired over recent years, 390 00:23:03,880 --> 00:23:07,240 Speaker 1: and it also laid off about twenty percent of its workforce. 391 00:23:07,560 --> 00:23:10,280 Speaker 1: Reporters noted that the company had also started to explore 392 00:23:10,280 --> 00:23:14,080 Speaker 1: ways it might back out of some leases in various regions, 393 00:23:14,440 --> 00:23:21,000 Speaker 1: while simultaneously announcing plans about opening news space in different cities. Also, 394 00:23:21,200 --> 00:23:25,160 Speaker 1: just here's a personal note to soft Bank. You can 395 00:23:25,200 --> 00:23:28,479 Speaker 1: pay me a billion dollars and I won't even settle 396 00:23:28,560 --> 00:23:32,119 Speaker 1: you with a company that has no known pathway to profitability. 397 00:23:32,359 --> 00:23:36,440 Speaker 1: It's a bargain. Just show me the money now. Not 398 00:23:36,480 --> 00:23:39,120 Speaker 1: to get too sidetracked by all this, but I feel 399 00:23:39,160 --> 00:23:42,440 Speaker 1: like we Work and the ride hailing services really fall 400 00:23:42,480 --> 00:23:44,600 Speaker 1: into that fake it until you make it category I 401 00:23:44,640 --> 00:23:46,639 Speaker 1: covered on a recent episode of Tech Stuff, you know, 402 00:23:46,680 --> 00:23:49,040 Speaker 1: the one where I ranted for like forty five minutes. 403 00:23:49,480 --> 00:23:52,680 Speaker 1: I find it perplexing that the motivating factor for investment 404 00:23:53,280 --> 00:23:57,760 Speaker 1: isn't profitability but just company growth, as in, a company 405 00:23:57,800 --> 00:24:00,760 Speaker 1: doesn't need to show it can be profitable if it 406 00:24:00,840 --> 00:24:05,000 Speaker 1: can continue to expand rapidly. But in my mind, that 407 00:24:05,119 --> 00:24:08,920 Speaker 1: just means that now instead of a small, unprofitable company, 408 00:24:09,040 --> 00:24:13,199 Speaker 1: you've got a large, more complex, unprofitable company. And I 409 00:24:13,240 --> 00:24:16,240 Speaker 1: suppose the hope is that you will eventually quote unquote 410 00:24:16,320 --> 00:24:19,560 Speaker 1: make it up in volume, meaning that whenever you achieve 411 00:24:20,200 --> 00:24:25,520 Speaker 1: some predetermined magical scale, your operations will become profitable. But 412 00:24:25,600 --> 00:24:29,280 Speaker 1: from my perspective, it seems that that very rarely happens, 413 00:24:29,320 --> 00:24:32,280 Speaker 1: and that you're more likely to find yourself pouring money 414 00:24:32,359 --> 00:24:35,560 Speaker 1: into a sinking ship, and then people like Newman get 415 00:24:35,600 --> 00:24:39,879 Speaker 1: the benefit of a lifeboat that's loaded down with cash. Anyway, 416 00:24:39,920 --> 00:24:42,920 Speaker 1: I'm not an expert in corporate finance, so it's entirely 417 00:24:42,960 --> 00:24:46,480 Speaker 1: possible that I'm overlooking something obvious. It's just to me, 418 00:24:47,240 --> 00:24:51,320 Speaker 1: this model doesn't make much sense. I get the desire 419 00:24:51,400 --> 00:24:55,200 Speaker 1: to grow year over year, although I'm not crazy about it, 420 00:24:55,240 --> 00:24:59,960 Speaker 1: but without the profitability part in there, and growth is unsustained, 421 00:25:00,080 --> 00:25:03,080 Speaker 1: bowl you'll eventually collapse in on yourself because no one's 422 00:25:03,080 --> 00:25:06,639 Speaker 1: gonna keep giving you money just to grow. All right, 423 00:25:06,680 --> 00:25:09,800 Speaker 1: how about we chat a bit about everyone's favorite social 424 00:25:09,840 --> 00:25:13,640 Speaker 1: media platform that continues to play an increasingly pivotal role 425 00:25:13,720 --> 00:25:17,600 Speaker 1: in how we access information and misinformation. So it's time 426 00:25:17,600 --> 00:25:19,919 Speaker 1: to check in on what Facebook was up to in 427 00:25:19,960 --> 00:25:23,280 Speaker 1: twenty nineteen. And boy howdy, there was a lot going on. 428 00:25:23,560 --> 00:25:25,840 Speaker 1: I'm not even going to cover all of it, because 429 00:25:26,000 --> 00:25:28,800 Speaker 1: you could do a full episode on just the shenanigans 430 00:25:28,800 --> 00:25:32,360 Speaker 1: Facebook got up to in nineteen, But anyway, let's look 431 00:25:32,400 --> 00:25:34,399 Speaker 1: at some of the big ones. For one thing, the 432 00:25:34,440 --> 00:25:37,920 Speaker 1: company received a hefty fine for the Cambridge Analytica scandal, 433 00:25:38,119 --> 00:25:41,560 Speaker 1: in which Facebook's app permissions allowed a data collection company 434 00:25:41,600 --> 00:25:44,720 Speaker 1: to access not just the information of people who downloaded 435 00:25:44,880 --> 00:25:48,080 Speaker 1: the app or who installed the app, but also the 436 00:25:48,200 --> 00:25:52,080 Speaker 1: data of all of their contacts on Facebook who did 437 00:25:52,119 --> 00:25:55,920 Speaker 1: not opt in. The fine was five billion dollars of 438 00:25:56,040 --> 00:25:59,600 Speaker 1: princely some no doubt about it, But there are critics 439 00:25:59,640 --> 00:26:03,440 Speaker 1: who said that's not nearly severe enough of a penalty 440 00:26:03,520 --> 00:26:07,159 Speaker 1: considering the scope of the betrayal of trust and user information. 441 00:26:07,400 --> 00:26:11,520 Speaker 1: After all, Facebook as a company earned twenty two billion 442 00:26:11,600 --> 00:26:15,360 Speaker 1: dollars in revenue in so yeah, five billions a lot 443 00:26:15,400 --> 00:26:17,640 Speaker 1: of cash, But when you're looking at numbers like twenty 444 00:26:17,640 --> 00:26:21,000 Speaker 1: two billion dollars in revenue, a five billion dollar fine 445 00:26:21,080 --> 00:26:23,879 Speaker 1: might not be enough to make Facebook actually take greater 446 00:26:23,960 --> 00:26:28,119 Speaker 1: steps towards ensuring user security. In June two thousand nineteen, 447 00:26:28,560 --> 00:26:33,560 Speaker 1: Facebook announced the launch of Libra, the cryptocurrency project. Facebook 448 00:26:33,600 --> 00:26:37,520 Speaker 1: also announced the Libra Association, a consortium of twenty eight 449 00:26:37,560 --> 00:26:41,119 Speaker 1: companies that would form the initial group responsible for bringing 450 00:26:41,119 --> 00:26:45,560 Speaker 1: this cryptocurrency into reality, with a promise that more companies 451 00:26:45,560 --> 00:26:48,879 Speaker 1: would soon follow to join the consortium. So think of 452 00:26:48,880 --> 00:26:52,399 Speaker 1: it as a digital currency, not too different from something 453 00:26:52,440 --> 00:26:56,919 Speaker 1: like bitcoin, although the Libra cryptocurrency would be based on 454 00:26:57,040 --> 00:27:00,920 Speaker 1: real world assets and not just its own own uh 455 00:27:01,240 --> 00:27:06,360 Speaker 1: sense of value among the community. However, this announcement Facebook 456 00:27:06,359 --> 00:27:09,040 Speaker 1: made was met with scrutiny, particularly on the part of 457 00:27:09,119 --> 00:27:11,800 Speaker 1: various governmental agencies around the world, and to be fair, 458 00:27:12,560 --> 00:27:16,159 Speaker 1: it's more accurate to say Facebook is the leading voice 459 00:27:16,800 --> 00:27:21,399 Speaker 1: in this project UH and is not the only entity 460 00:27:21,480 --> 00:27:24,920 Speaker 1: behind it, but for the purposes of most reporting, people 461 00:27:24,960 --> 00:27:28,480 Speaker 1: tend to simplify it by saying Facebook now. Governments began 462 00:27:28,520 --> 00:27:31,879 Speaker 1: to call for regulations and rules to guide any sort 463 00:27:31,920 --> 00:27:35,320 Speaker 1: of cryptocurrency effort, particularly in the wake of some high 464 00:27:35,400 --> 00:27:39,560 Speaker 1: profile missteps by Facebook, like the aforementioned Cambridge Analytica scandal. 465 00:27:40,280 --> 00:27:44,600 Speaker 1: By October twenty nineteen, more than of those original companies 466 00:27:44,640 --> 00:27:48,359 Speaker 1: had walked away from the Libra consortium. The first to 467 00:27:48,440 --> 00:27:52,000 Speaker 1: leave was PayPal, and in an interview with Forbes, PayPal 468 00:27:52,080 --> 00:27:55,240 Speaker 1: CEO Dan Shulman said that when they were able to 469 00:27:55,280 --> 00:27:57,920 Speaker 1: see how far the project needed to go before it 470 00:27:57,960 --> 00:28:01,000 Speaker 1: could roll out, and they heard that with the amount 471 00:28:01,000 --> 00:28:03,160 Speaker 1: of work that PayPal needed to do to meet its 472 00:28:03,160 --> 00:28:07,280 Speaker 1: own internal goals that were not related to Libra, they said, oh, well, 473 00:28:07,400 --> 00:28:09,240 Speaker 1: just it makes sense for us to be part of 474 00:28:09,280 --> 00:28:13,040 Speaker 1: the consortium. We needed to focus on us first. Now, 475 00:28:13,040 --> 00:28:16,600 Speaker 1: whether that was the same justification for the other companies 476 00:28:16,600 --> 00:28:20,000 Speaker 1: that bailed on the Libra association, I can't say, but 477 00:28:20,280 --> 00:28:25,560 Speaker 1: companies like Visa, Stripe, MasterCard, and eBay also left the association. 478 00:28:26,000 --> 00:28:29,479 Speaker 1: With the increased interest among various governments to create rules 479 00:28:29,480 --> 00:28:32,280 Speaker 1: to minimize the risk of something like a new cryptocurrency, 480 00:28:32,560 --> 00:28:34,600 Speaker 1: it seems like Libra has a long way to go 481 00:28:34,960 --> 00:28:38,640 Speaker 1: before it becomes a practical currency, if it ever does. 482 00:28:39,600 --> 00:28:42,840 Speaker 1: Another big Facebook story revolves around these social media platforms 483 00:28:42,960 --> 00:28:47,520 Speaker 1: role in disseminating information and misinformation. This was a big 484 00:28:47,560 --> 00:28:50,920 Speaker 1: theme throughout twenty nineteen, Mark Zuckerberg stated before the US 485 00:28:50,960 --> 00:28:54,120 Speaker 1: government that he feels Facebook shouldn't play a role in 486 00:28:54,200 --> 00:28:58,400 Speaker 1: fact checking stuff like political ads. So if a politician 487 00:28:58,440 --> 00:29:01,160 Speaker 1: wanted to post an ad to face Book that contained 488 00:29:01,440 --> 00:29:05,800 Speaker 1: incorrect or outright false information, they could do that and 489 00:29:05,880 --> 00:29:09,600 Speaker 1: Facebook would not intervene. As the company continues to deal 490 00:29:09,640 --> 00:29:13,200 Speaker 1: with accusations that it is profiting from efforts of political 491 00:29:13,240 --> 00:29:17,360 Speaker 1: manipulation and deception, this has been an area of focus 492 00:29:17,400 --> 00:29:22,120 Speaker 1: for a lot of folks. Moreover, Facebook's algorithm favors posts 493 00:29:22,120 --> 00:29:27,160 Speaker 1: that drive a lot of engagement, so likes, shares comments 494 00:29:27,200 --> 00:29:30,040 Speaker 1: that kind of thing. Now, in turn, that generates more 495 00:29:30,080 --> 00:29:33,680 Speaker 1: screen time for Facebook and us more revenue for the company. 496 00:29:33,760 --> 00:29:37,280 Speaker 1: So the company has a financial incentive to give a 497 00:29:37,360 --> 00:29:40,840 Speaker 1: platform for stuff that gets people riled up, which in 498 00:29:40,920 --> 00:29:44,920 Speaker 1: turn contributes to things like political extremism, which I'll talk 499 00:29:44,960 --> 00:29:49,160 Speaker 1: more about in our next episode. It's a pretty ugly situation, 500 00:29:49,280 --> 00:29:52,320 Speaker 1: and Zuckerberg so far seems to be intent on absolving 501 00:29:52,400 --> 00:29:55,840 Speaker 1: himself of any responsibility for creating a platform that can 502 00:29:55,880 --> 00:29:59,800 Speaker 1: be gamed in this way, and the platform itself benefits 503 00:30:00,200 --> 00:30:05,080 Speaker 1: from this. I can't stress that enough. Facebook makes money 504 00:30:05,280 --> 00:30:09,880 Speaker 1: by having these sorts of posts on it because it 505 00:30:09,920 --> 00:30:13,920 Speaker 1: generates a lot of activity, and that activity translates into 506 00:30:14,000 --> 00:30:17,120 Speaker 1: more screen time, which translates into more money for Facebook, 507 00:30:17,480 --> 00:30:20,720 Speaker 1: so they have a financial incentive to keep things going 508 00:30:20,720 --> 00:30:23,520 Speaker 1: the way they are. Towards the end of twenty nineteen, 509 00:30:23,880 --> 00:30:26,320 Speaker 1: the Federal Trade Commission in the United States began to 510 00:30:26,360 --> 00:30:29,480 Speaker 1: take a closer look at Facebook's proposed plan to integrating 511 00:30:29,520 --> 00:30:34,280 Speaker 1: its various properties together, uh those being Facebook, Messenger, WhatsApp, 512 00:30:34,440 --> 00:30:37,240 Speaker 1: and Instagram. So while Facebook is trying to do this, 513 00:30:37,480 --> 00:30:40,280 Speaker 1: it is also under investigation by the US government in 514 00:30:40,320 --> 00:30:44,720 Speaker 1: an antitrust case. A tighter integration between the different platforms 515 00:30:44,720 --> 00:30:47,480 Speaker 1: would make it more difficult to separate down the line, 516 00:30:47,760 --> 00:30:50,320 Speaker 1: and it's possible that the US government will demand Facebook 517 00:30:50,360 --> 00:30:52,800 Speaker 1: to break up its various properties and spin them off 518 00:30:52,840 --> 00:30:55,880 Speaker 1: as independent companies. So there's a chance that by the 519 00:30:55,880 --> 00:30:58,200 Speaker 1: time you hear this, the FTC will have filed an 520 00:30:58,240 --> 00:31:02,840 Speaker 1: injunction against Facebook from integrating these services further. And the 521 00:31:02,920 --> 00:31:07,240 Speaker 1: hits just keep on coming. Between when I started making 522 00:31:07,320 --> 00:31:10,320 Speaker 1: notes for this episode and when I actually sat down 523 00:31:10,360 --> 00:31:13,000 Speaker 1: in the studio to record it right now, you had 524 00:31:13,040 --> 00:31:16,760 Speaker 1: another story about Facebook broke in mid December Facebook sent 525 00:31:16,880 --> 00:31:19,800 Speaker 1: a letter to the United States Senate. The letter revealed 526 00:31:19,840 --> 00:31:22,640 Speaker 1: that the company could locate users even if they had 527 00:31:22,680 --> 00:31:26,880 Speaker 1: opted out of being tracked with location data. Now, I 528 00:31:26,920 --> 00:31:30,440 Speaker 1: would argue that this isn't as big a news story 529 00:31:30,560 --> 00:31:33,320 Speaker 1: as it was made out to be because Facebook stated 530 00:31:33,360 --> 00:31:36,240 Speaker 1: that they could use meta data, such as tagged photos 531 00:31:36,280 --> 00:31:39,160 Speaker 1: that indicated a location and time, as well as who 532 00:31:39,240 --> 00:31:43,280 Speaker 1: was in the tagged photo. But that seems pretty intuitive 533 00:31:43,320 --> 00:31:45,200 Speaker 1: to me. If I go to a party and I 534 00:31:45,280 --> 00:31:47,240 Speaker 1: take a photo of you, you're at the party two, 535 00:31:47,400 --> 00:31:50,200 Speaker 1: and then I post from the party and I tagged 536 00:31:50,320 --> 00:31:53,600 Speaker 1: the location of the party and I tag you, then 537 00:31:53,600 --> 00:31:56,880 Speaker 1: Facebook has data on where I am, where you are, 538 00:31:57,280 --> 00:32:00,160 Speaker 1: what time we were there, and all of that that. 539 00:32:00,520 --> 00:32:03,800 Speaker 1: It's all there in Facebook's data even if we don't 540 00:32:03,800 --> 00:32:08,000 Speaker 1: have location information turned on regularly. Other ways Facebook could 541 00:32:08,160 --> 00:32:11,440 Speaker 1: make guesses as to where people are depend less on 542 00:32:11,560 --> 00:32:15,000 Speaker 1: direct user input and more and stuff like I P addresses, 543 00:32:15,320 --> 00:32:19,440 Speaker 1: which aren't as exact. They can give you a general idea, 544 00:32:19,720 --> 00:32:22,880 Speaker 1: but they're not full proof. Now, Facebook defended its policies 545 00:32:22,920 --> 00:32:27,680 Speaker 1: by stating that it could detect suspicious logins using this approach, 546 00:32:27,960 --> 00:32:29,920 Speaker 1: such as if a person in one part of the 547 00:32:29,960 --> 00:32:32,600 Speaker 1: country were to suddenly appear as though they were trying 548 00:32:32,680 --> 00:32:36,440 Speaker 1: to log into Facebook, but from an IP address located 549 00:32:36,520 --> 00:32:38,800 Speaker 1: on the other side of the world. That would indicate 550 00:32:38,840 --> 00:32:41,160 Speaker 1: that maybe somebody else had gotten hold of some log 551 00:32:41,200 --> 00:32:45,360 Speaker 1: in information and they were trying to steal someone's Facebook account. 552 00:32:45,600 --> 00:32:49,800 Speaker 1: Of course, stuff like VPNs could also create this scenario. 553 00:32:50,080 --> 00:32:53,040 Speaker 1: You could be using a VPN to log into Facebook 554 00:32:53,200 --> 00:32:56,440 Speaker 1: from the other side of the world for various reasons, 555 00:32:56,480 --> 00:32:58,400 Speaker 1: and that could raise a false flag. But I do 556 00:32:58,480 --> 00:33:01,280 Speaker 1: see what Facebook was trying to say. Now, one last 557 00:33:01,280 --> 00:33:04,760 Speaker 1: Facebook story before I take another break. In mid November, 558 00:33:05,160 --> 00:33:08,640 Speaker 1: a thief stole several hard drives from the car of 559 00:33:08,680 --> 00:33:13,400 Speaker 1: a Facebook employee, and those hard drives included unencrypted payroll 560 00:33:13,560 --> 00:33:17,760 Speaker 1: data for thousands of Facebook employees. The data covered about 561 00:33:17,800 --> 00:33:21,959 Speaker 1: twenty nine thousand people who are working for Facebook, so 562 00:33:22,000 --> 00:33:26,479 Speaker 1: some of those folks presumably no longer work for the company. Now, 563 00:33:26,520 --> 00:33:29,880 Speaker 1: in this case, we're talking about physical hardware taken from 564 00:33:29,880 --> 00:33:32,080 Speaker 1: a car, so this was not a data breach in 565 00:33:32,080 --> 00:33:35,760 Speaker 1: the traditional sense. Now I'm surprised the data was unencrypted. 566 00:33:36,080 --> 00:33:38,320 Speaker 1: I would imagine that in most cases you would want 567 00:33:38,320 --> 00:33:41,240 Speaker 1: to encrypt that information, even on just a physical hard drive, 568 00:33:41,960 --> 00:33:45,360 Speaker 1: but presumably it wasn't because no one ever assumed the 569 00:33:45,360 --> 00:33:49,640 Speaker 1: hard drives would leave the possession of Facebook. Still, yikes, 570 00:33:50,840 --> 00:33:53,240 Speaker 1: we got a few more bummers to go, but before 571 00:33:53,240 --> 00:34:03,000 Speaker 1: we do, let's take another quick break. So a big 572 00:34:03,040 --> 00:34:05,640 Speaker 1: story to play out over the course of twenty nineteen 573 00:34:06,240 --> 00:34:10,160 Speaker 1: was the world's response to the Chinese telecom company Huawei, 574 00:34:10,400 --> 00:34:13,120 Speaker 1: which I've also covered in a previous episode of tech Stuff. 575 00:34:13,400 --> 00:34:16,440 Speaker 1: The company isn't that old, but it already stands to 576 00:34:16,440 --> 00:34:18,880 Speaker 1: be one of the major players in rolling out the 577 00:34:18,920 --> 00:34:22,920 Speaker 1: technology that will enable five G wireless connectivity around the world. 578 00:34:23,320 --> 00:34:26,560 Speaker 1: In fact, with the outstanding orders the company already has 579 00:34:26,640 --> 00:34:29,600 Speaker 1: in Europe, it leads the pack in terms of five 580 00:34:29,680 --> 00:34:34,080 Speaker 1: G equipment sales. This is despite some hefty restrictions placed 581 00:34:34,120 --> 00:34:38,560 Speaker 1: upon Huawei, mostly from the United States. In mid December 582 00:34:38,640 --> 00:34:42,000 Speaker 1: twenty nineteen, it was revealed that Chinese officials had leveraged 583 00:34:42,120 --> 00:34:46,600 Speaker 1: tremendous pressure on European countries to sign contracts to purchase 584 00:34:46,680 --> 00:34:51,160 Speaker 1: five G equipment from Huawei or face consequences such as 585 00:34:51,239 --> 00:34:56,120 Speaker 1: canceled trade agreements. You know, wider trade agreements throughout China. 586 00:34:56,520 --> 00:34:59,000 Speaker 1: Now at the heart of the dispute is a concern 587 00:34:59,080 --> 00:35:02,239 Speaker 1: that Huawei has close ties with the Chinese government and 588 00:35:02,360 --> 00:35:07,040 Speaker 1: that as a provider of telecommunications equipment, it's possible the 589 00:35:07,040 --> 00:35:10,320 Speaker 1: company could potentially build in back doors and other features 590 00:35:10,360 --> 00:35:14,840 Speaker 1: that would allow China to access vital communications channels across 591 00:35:14,920 --> 00:35:18,680 Speaker 1: the globe. In fact, such back doors had previously been found, 592 00:35:18,680 --> 00:35:23,160 Speaker 1: although they could have been vulnerabilities not intentionally placed there, 593 00:35:23,520 --> 00:35:28,560 Speaker 1: but still it raises some eyebrows. Huawei argues that it's 594 00:35:28,560 --> 00:35:31,440 Speaker 1: actually a private company and it doesn't have any direction 595 00:35:31,480 --> 00:35:35,080 Speaker 1: from the Chinese government, and that such fears are unfounded. 596 00:35:35,640 --> 00:35:38,120 Speaker 1: But it hasn't stopped countries like the United States from 597 00:35:38,120 --> 00:35:42,279 Speaker 1: eyeing Huawei with suspicion, And to be fair, China is 598 00:35:42,719 --> 00:35:46,840 Speaker 1: putting some pressure on various countries that are you know, 599 00:35:46,960 --> 00:35:51,200 Speaker 1: conflicted about using Huawei, and that seems to send a 600 00:35:51,239 --> 00:35:57,239 Speaker 1: message that China's kind of deeply integrated with the company's 601 00:35:57,760 --> 00:36:02,200 Speaker 1: you know, day to day operations. Although Huawei says, no, no, no, 602 00:36:02,239 --> 00:36:05,080 Speaker 1: this is just a government looking out for a company 603 00:36:05,120 --> 00:36:09,160 Speaker 1: that exists within its borders. That's it. It's not a 604 00:36:09,280 --> 00:36:13,160 Speaker 1: sign that it's a Chinese government operation. So it's a 605 00:36:13,200 --> 00:36:16,920 Speaker 1: complicated thing, and it all depends upon whose perspective you believe. 606 00:36:17,120 --> 00:36:20,440 Speaker 1: The truth is probably somewhere in the middle. Speaking of China, 607 00:36:20,960 --> 00:36:24,279 Speaker 1: the country's conflicts with Hong Kong have spilled over into 608 00:36:24,320 --> 00:36:27,400 Speaker 1: the tech space in various ways. A large number of 609 00:36:27,440 --> 00:36:31,680 Speaker 1: Hong Kong citizens mobilized against the Chinese government, initially protesting 610 00:36:31,680 --> 00:36:35,560 Speaker 1: a policy that would allow for extradition of Hong Kong 611 00:36:35,680 --> 00:36:39,279 Speaker 1: citizens accused of certain crimes and they would be extradited 612 00:36:39,320 --> 00:36:43,000 Speaker 1: to mainland China. Now, given China's reputation when it comes 613 00:36:43,000 --> 00:36:47,200 Speaker 1: to justice, the too long didn't read version of that is, 614 00:36:47,719 --> 00:36:52,759 Speaker 1: it's a very bad reputation. Many Hong Kong citizens protested 615 00:36:52,960 --> 00:36:56,520 Speaker 1: against this policy. They stated that it was undermining the 616 00:36:56,560 --> 00:36:59,920 Speaker 1: independence of Hong Kong, which was something China had previously 617 00:37:00,040 --> 00:37:03,719 Speaker 1: promised it wouldn't mess around with. While China would ultimately 618 00:37:03,760 --> 00:37:07,719 Speaker 1: withdraw the extradition bill, this was really the push that 619 00:37:07,840 --> 00:37:11,600 Speaker 1: got the ball rolling, and protests continue to this day 620 00:37:11,640 --> 00:37:14,200 Speaker 1: because they extend beyond that. You could think of that 621 00:37:14,200 --> 00:37:17,799 Speaker 1: as the straw that broke the camel's back. Now the 622 00:37:17,840 --> 00:37:21,160 Speaker 1: tech angle of all of this, there's the video game 623 00:37:21,160 --> 00:37:23,799 Speaker 1: company Blizzard that I recently covered on tech stuff. While 624 00:37:23,840 --> 00:37:28,120 Speaker 1: they make a digital card battle game called Hearthstone, and 625 00:37:28,239 --> 00:37:32,240 Speaker 1: during a Hearthstone tournament in Taiwan, a Hong Kong player 626 00:37:32,320 --> 00:37:36,960 Speaker 1: named why Chung or blitz Chung that's his gamer handle, 627 00:37:37,560 --> 00:37:41,600 Speaker 1: showed support for Hong Kong protesters on camera during an 628 00:37:41,640 --> 00:37:46,160 Speaker 1: interview Blizzard band blitz Chung from the tournament. The Blizzard 629 00:37:46,200 --> 00:37:50,040 Speaker 1: also banned the UH the people who were conducting the interview, 630 00:37:50,080 --> 00:37:52,719 Speaker 1: even though they were doing their best to try and 631 00:37:53,280 --> 00:37:57,759 Speaker 1: avoid appearing like they were enabling this UH and that 632 00:37:57,840 --> 00:38:00,080 Speaker 1: band of blitz Chung would prevent him from playing in 633 00:38:00,239 --> 00:38:02,799 Speaker 1: any grand Master tournament for a year, and he would 634 00:38:02,800 --> 00:38:05,759 Speaker 1: have to forfeit the prize money he had accumulated up 635 00:38:05,800 --> 00:38:09,240 Speaker 1: to that point in the tournament. When pressed to explain 636 00:38:09,440 --> 00:38:13,440 Speaker 1: why they leveled such a harsh ban, Blizzards stated that 637 00:38:13,480 --> 00:38:17,120 Speaker 1: blitz Chung had violated a policy that prohibited players from 638 00:38:17,160 --> 00:38:20,280 Speaker 1: doing anything that would tarnish the company's image or within 639 00:38:20,400 --> 00:38:24,560 Speaker 1: the public. Now, that raised a pretty strong counter objection 640 00:38:24,960 --> 00:38:29,440 Speaker 1: among the gaming community at large. Many people hypothesized that 641 00:38:29,520 --> 00:38:33,359 Speaker 1: blizzards response was largely motivated by the fact that ten Cent, 642 00:38:33,680 --> 00:38:38,080 Speaker 1: a Chinese company, owns a stake of ownership in Activision. 643 00:38:38,120 --> 00:38:41,279 Speaker 1: Blizzard they don't own the company outright, they just own 644 00:38:41,320 --> 00:38:46,040 Speaker 1: a percentage. There was also speculation that Blizzard didn't want 645 00:38:46,080 --> 00:38:50,360 Speaker 1: to endanger operations within the Chinese market. The Chinese market 646 00:38:50,400 --> 00:38:54,160 Speaker 1: represents billions of dollars of potential revenue, so they didn't 647 00:38:54,160 --> 00:38:57,040 Speaker 1: want to put that at risk. Critics also pointed out 648 00:38:57,080 --> 00:39:00,400 Speaker 1: that Blizzards punishments toward other gamers around the world in 649 00:39:00,480 --> 00:39:03,960 Speaker 1: response to vulgarity, you know, clear cut cases where someone 650 00:39:04,040 --> 00:39:08,200 Speaker 1: has violated that policy. They were rarely as severe as 651 00:39:08,239 --> 00:39:13,799 Speaker 1: what blitz Chung experienced. Blizzards subsequently walked back the punishment 652 00:39:13,880 --> 00:39:16,719 Speaker 1: a little bit. They returned the prize winnings to blitz Chung, 653 00:39:17,040 --> 00:39:19,799 Speaker 1: but they kept a ban in place for half a 654 00:39:19,880 --> 00:39:25,120 Speaker 1: year rather than a full year. Interestingly, Chinese companies, namely Tencent, 655 00:39:25,280 --> 00:39:29,160 Speaker 1: have partial ownership in other video game companies, not just Blizzard, 656 00:39:29,600 --> 00:39:32,400 Speaker 1: and some of these companies also produce games that have 657 00:39:32,560 --> 00:39:35,480 Speaker 1: a tournament circuit, and in some of those cases, there 658 00:39:35,480 --> 00:39:38,000 Speaker 1: seems to be no restriction on what players can say 659 00:39:38,040 --> 00:39:41,560 Speaker 1: about the situation in Hong Kong. So that raises questions 660 00:39:41,560 --> 00:39:45,279 Speaker 1: about whether Blizzard was being proactively responsive for fear of 661 00:39:45,400 --> 00:39:49,200 Speaker 1: upsetting the Apple cart or if possibly other companies have 662 00:39:49,360 --> 00:39:53,360 Speaker 1: seen the backlash that Blizzard faced and they're setting themselves 663 00:39:53,360 --> 00:39:56,960 Speaker 1: apart by taking a different approach. Oh and I should 664 00:39:56,960 --> 00:39:59,560 Speaker 1: also backtrack just a little bit. So remember how I 665 00:39:59,600 --> 00:40:02,319 Speaker 1: mentioned Whahwei is a leading company when it comes to 666 00:40:02,360 --> 00:40:05,560 Speaker 1: five G technologies. Well, that reminds me I should quickly 667 00:40:05,560 --> 00:40:08,280 Speaker 1: address that a T and T and the company's attempt 668 00:40:08,360 --> 00:40:10,600 Speaker 1: to leverage the concept of five G and how that 669 00:40:10,880 --> 00:40:14,040 Speaker 1: got a lot of scorn in the tech community. Okay, 670 00:40:14,080 --> 00:40:17,719 Speaker 1: so part of this story hinges on the fact that 671 00:40:17,880 --> 00:40:21,120 Speaker 1: five G isn't just a single technology or anything like that. 672 00:40:21,760 --> 00:40:26,200 Speaker 1: You can't just say five G relates to this specific implementation. 673 00:40:26,480 --> 00:40:29,720 Speaker 1: It's really more of a family of technologies and implementations 674 00:40:29,760 --> 00:40:34,759 Speaker 1: that enable wireless data throughput at really impressive levels. And 675 00:40:34,800 --> 00:40:38,200 Speaker 1: we typically describe it as speed, but the data is 676 00:40:38,239 --> 00:40:41,160 Speaker 1: not actually moving faster than it was before. It's just 677 00:40:41,200 --> 00:40:44,760 Speaker 1: that more data can travel all at once through a channel. 678 00:40:45,000 --> 00:40:48,080 Speaker 1: So instead of thinking of it as like a one 679 00:40:48,160 --> 00:40:50,479 Speaker 1: lane road where you can just somehow defy the laws 680 00:40:50,520 --> 00:40:53,120 Speaker 1: of physics and drive faster than the speed of light, 681 00:40:53,719 --> 00:40:56,920 Speaker 1: it's more like you have an ultra wide highway where 682 00:40:57,120 --> 00:40:59,600 Speaker 1: all the cars can travel at the speed of light 683 00:40:59,640 --> 00:41:03,239 Speaker 1: simul taneously, so you get more cars, more data, but 684 00:41:03,280 --> 00:41:05,759 Speaker 1: they're not traveling faster than they were before. There's just 685 00:41:05,920 --> 00:41:09,160 Speaker 1: more of them. The rollout of five G is taking 686 00:41:09,200 --> 00:41:13,160 Speaker 1: time because it requires new infrastructure. You can't just send 687 00:41:13,200 --> 00:41:16,520 Speaker 1: an update out to existing antenna's out there. You actually 688 00:41:16,560 --> 00:41:19,840 Speaker 1: have to go install new ones and make them in 689 00:41:19,880 --> 00:41:23,560 Speaker 1: a different density than older generations of wireless technology. You 690 00:41:23,600 --> 00:41:26,600 Speaker 1: also need to have phones and other devices that can 691 00:41:26,640 --> 00:41:29,520 Speaker 1: actually receive five G signals to take advantage of it. 692 00:41:29,560 --> 00:41:32,960 Speaker 1: They can't just do that with their standard stuff, so 693 00:41:33,000 --> 00:41:36,719 Speaker 1: it requires a whole lot of hardware upgrades across the board. Now, 694 00:41:36,760 --> 00:41:39,239 Speaker 1: A T and T decided to kind of, you know, 695 00:41:40,600 --> 00:41:44,120 Speaker 1: leap frog all of that. The company made a change 696 00:41:44,480 --> 00:41:47,239 Speaker 1: and they pushed out an update that would replace the 697 00:41:47,480 --> 00:41:51,960 Speaker 1: LTE indicator on certain A T and T smartphones with 698 00:41:52,120 --> 00:41:55,880 Speaker 1: a symbol saying five G E, and the E stands 699 00:41:55,920 --> 00:42:01,399 Speaker 1: for evolution, so is a five G evolution network device. Now. 700 00:42:01,400 --> 00:42:04,360 Speaker 1: Critics said that A T and T was purposefully confusing 701 00:42:04,400 --> 00:42:08,399 Speaker 1: the market, that it was positioning these phones as if 702 00:42:08,440 --> 00:42:11,719 Speaker 1: they were already taking advantage of true five G networks, 703 00:42:11,760 --> 00:42:15,440 Speaker 1: and we're operating on actual five G technology, when in 704 00:42:15,560 --> 00:42:19,480 Speaker 1: fact they were actually relying on the older lt E 705 00:42:19,840 --> 00:42:24,000 Speaker 1: four G technology. Making matters more confusing was that A 706 00:42:24,080 --> 00:42:28,120 Speaker 1: T and T was actually rolling out legit five G infrastructure, 707 00:42:28,320 --> 00:42:31,080 Speaker 1: but it was only available in limited areas, and sometimes 708 00:42:31,080 --> 00:42:33,960 Speaker 1: that would just be a small area within an actual city. 709 00:42:34,040 --> 00:42:38,360 Speaker 1: For example, according to analytics company open Signal, the A 710 00:42:38,440 --> 00:42:41,799 Speaker 1: T and T five G E service did not outperform 711 00:42:41,920 --> 00:42:45,600 Speaker 1: either T Mobile or Verizons LTE service, and so the 712 00:42:45,640 --> 00:42:48,640 Speaker 1: general conclusion was that A T and T was trying 713 00:42:48,640 --> 00:42:51,719 Speaker 1: to take advantage of an emerging technology to make it 714 00:42:51,760 --> 00:42:55,879 Speaker 1: seem like their product, which according to tests wasn't superior 715 00:42:56,160 --> 00:42:59,720 Speaker 1: to the competition, was somehow more capable. It was dirty 716 00:42:59,760 --> 00:43:03,279 Speaker 1: pool wool, as go maz Adams would say. Now I 717 00:43:03,320 --> 00:43:05,880 Speaker 1: should also add that while it looks to me like 718 00:43:05,960 --> 00:43:09,360 Speaker 1: A T and T deliberately tried to fool folks with 719 00:43:09,400 --> 00:43:13,759 Speaker 1: this whole five G evolution network approach, the situation does 720 00:43:13,840 --> 00:43:18,560 Speaker 1: actually get pretty complicated because the generations of wireless connectivity 721 00:43:18,600 --> 00:43:22,080 Speaker 1: are kind of lucy goosey. You can't point to say 722 00:43:22,280 --> 00:43:25,440 Speaker 1: three G and give a set of firm specifications on 723 00:43:25,480 --> 00:43:28,120 Speaker 1: how much data could be sent over a network per 724 00:43:28,239 --> 00:43:32,200 Speaker 1: unit of time. The technologies within a generation evolve over 725 00:43:32,239 --> 00:43:34,879 Speaker 1: the course of that generation, and if a company can 726 00:43:35,000 --> 00:43:38,640 Speaker 1: upgrade hardware to take advantage of those evolutions, it can 727 00:43:38,680 --> 00:43:42,480 Speaker 1: see improved data rate. So, in other words, not all 728 00:43:42,560 --> 00:43:46,200 Speaker 1: four G networks or devices are equal. Some are capable 729 00:43:46,239 --> 00:43:49,879 Speaker 1: of much better data transfer rates than others. It's even 730 00:43:49,920 --> 00:43:53,280 Speaker 1: possible to have a really good network and a device 731 00:43:53,400 --> 00:43:58,359 Speaker 1: on an earlier generation outperform a later generation. Example, so 732 00:43:58,520 --> 00:44:00,520 Speaker 1: it's possible for you to have a really good four 733 00:44:00,560 --> 00:44:04,000 Speaker 1: G network and device outperform a five G device on 734 00:44:04,040 --> 00:44:10,279 Speaker 1: a five G network. Possibly it's that the Venn diagram 735 00:44:10,320 --> 00:44:12,839 Speaker 1: is narrow, but it can happen, so it's not as 736 00:44:12,880 --> 00:44:15,279 Speaker 1: simple as saying five G is faster than four G. 737 00:44:15,800 --> 00:44:19,319 Speaker 1: It's definitely true that the potential of five G far 738 00:44:19,400 --> 00:44:23,360 Speaker 1: outpaces that of four G. In other words, the best 739 00:44:23,400 --> 00:44:26,000 Speaker 1: implementation of five G is always going to be better 740 00:44:26,040 --> 00:44:28,359 Speaker 1: than the best implementation of four G as far as 741 00:44:28,480 --> 00:44:32,560 Speaker 1: data throughput is concerned. But potential and reality are two 742 00:44:32,560 --> 00:44:35,160 Speaker 1: different things, so it all depends on how it's implemented 743 00:44:35,200 --> 00:44:38,000 Speaker 1: in the area that you are in. And yes, I 744 00:44:38,120 --> 00:44:42,080 Speaker 1: find this all to be incredibly frustrating because as a consumer. 745 00:44:42,160 --> 00:44:45,000 Speaker 1: I just want my stuff to work really well and 746 00:44:45,080 --> 00:44:48,280 Speaker 1: for it to be really fast, and it's not always 747 00:44:48,360 --> 00:44:51,279 Speaker 1: an easy thing to determine. I'll wrap up with a 748 00:44:51,280 --> 00:44:55,120 Speaker 1: couple of short stories. One is the saga of these 749 00:44:55,120 --> 00:44:58,040 Speaker 1: seven thirty seven Macs, which I covered in a recent 750 00:44:58,120 --> 00:45:02,160 Speaker 1: tech Stuff episode. After two strop it crashes, governments around 751 00:45:02,200 --> 00:45:05,200 Speaker 1: the world ordered that Boeing's seven thirty seven Max aircraft 752 00:45:05,239 --> 00:45:08,160 Speaker 1: be grounded, pending a full investigation into what went wrong 753 00:45:08,320 --> 00:45:11,839 Speaker 1: and any adjustments that need to be made. Boeing subsequently 754 00:45:11,880 --> 00:45:15,120 Speaker 1: made changes to the aircraft's systems. The particular system at 755 00:45:15,120 --> 00:45:17,400 Speaker 1: fault was meant to be a safety feature, a system 756 00:45:17,400 --> 00:45:19,640 Speaker 1: that would kick in to counter this seven thirty seven 757 00:45:19,640 --> 00:45:24,200 Speaker 1: Max's tendency to tilt its nose upward. The problem was 758 00:45:24,440 --> 00:45:28,480 Speaker 1: that the safety feature could override pilot commands, and if 759 00:45:28,520 --> 00:45:32,960 Speaker 1: you had a single sensor failure sending incorrect information to 760 00:45:33,120 --> 00:45:37,440 Speaker 1: the safety system, that's what could cause tragedy. Now, as 761 00:45:37,520 --> 00:45:40,480 Speaker 1: of this recording, the fleet of aircraft is still grounded 762 00:45:40,520 --> 00:45:43,279 Speaker 1: and Boeing has suspended manufacturing any more of them for 763 00:45:43,320 --> 00:45:46,000 Speaker 1: the time being. The last story I wanted to mention 764 00:45:46,080 --> 00:45:48,839 Speaker 1: quickly is a follow up on a company that I've 765 00:45:48,880 --> 00:45:52,520 Speaker 1: covered in a past episode of Tech Stuff. That company is, 766 00:45:53,080 --> 00:45:57,279 Speaker 1: or rather was, movie Pass. So movie Pass aimed to 767 00:45:57,280 --> 00:46:00,920 Speaker 1: create a subscription based service in which stomers could purchase 768 00:46:01,000 --> 00:46:04,320 Speaker 1: a monthly pass to see first run movies in various 769 00:46:04,360 --> 00:46:09,160 Speaker 1: movie theaters. But movie theater chains weren't super keen on 770 00:46:09,160 --> 00:46:13,640 Speaker 1: this idea. Movie Pass had many notable ups and downs, 771 00:46:13,680 --> 00:46:16,800 Speaker 1: most of which I covered in my episode on the company, 772 00:46:16,840 --> 00:46:20,080 Speaker 1: but somehow managed to hang on longer than anyone really 773 00:46:20,120 --> 00:46:23,000 Speaker 1: thought was possible. This was despite the company having to 774 00:46:23,400 --> 00:46:26,399 Speaker 1: walk back it's unlimited movie Pass for a much more 775 00:46:26,520 --> 00:46:30,279 Speaker 1: modest offering, which I imagine must have led to a 776 00:46:30,320 --> 00:46:33,960 Speaker 1: pretty large number of customers canceling their subscriptions when suddenly 777 00:46:34,000 --> 00:46:37,160 Speaker 1: their unlimited movie Pass became no, you can see three 778 00:46:37,160 --> 00:46:41,600 Speaker 1: movies or you can get discounts on tickets. And thus 779 00:46:41,680 --> 00:46:44,640 Speaker 1: movie Pass had to secure loans from various sources just 780 00:46:44,719 --> 00:46:48,400 Speaker 1: to stay in business. Now, eventually the credits had to 781 00:46:48,520 --> 00:46:51,919 Speaker 1: roll on this company, and in September twenty nine, team 782 00:46:52,080 --> 00:46:56,040 Speaker 1: that's what happened. Movie Pass CEO Mitch Lowe released a 783 00:46:56,080 --> 00:47:00,920 Speaker 1: statement that the company would cease operations immediately, and uh it, 784 00:47:01,040 --> 00:47:04,160 Speaker 1: did you know? Movie Pass had failed to turn a 785 00:47:04,160 --> 00:47:07,719 Speaker 1: profit and the opposition it faced was considerable. While the 786 00:47:07,760 --> 00:47:10,480 Speaker 1: company tried lots of different approaches to right itself, those 787 00:47:10,520 --> 00:47:15,080 Speaker 1: choices ultimately either didn't work or actively worked against the company, 788 00:47:15,680 --> 00:47:19,520 Speaker 1: alienating the users and inviting various lawsuits to come in. 789 00:47:19,600 --> 00:47:24,000 Speaker 1: And it was pretty ugly stuff, all right. That wraps 790 00:47:24,080 --> 00:47:27,840 Speaker 1: up this episode, but in our next episode, I'll continue 791 00:47:27,880 --> 00:47:30,919 Speaker 1: to look back on technology in twenty nineteen. There's still 792 00:47:30,920 --> 00:47:34,080 Speaker 1: a lot of bummers left on that list, including some 793 00:47:34,239 --> 00:47:39,560 Speaker 1: they go beyond bummer too outright disastrous. But there are 794 00:47:39,560 --> 00:47:42,680 Speaker 1: a few cool things in there too, so we'll get 795 00:47:42,719 --> 00:47:45,840 Speaker 1: to those as well. So if you guys have suggestions 796 00:47:45,840 --> 00:47:47,960 Speaker 1: for future episodes of tech Stuff, reach out to me. 797 00:47:48,400 --> 00:47:51,799 Speaker 1: The best place to do so's on social media over 798 00:47:51,920 --> 00:47:54,239 Speaker 1: on Twitter and on Facebook. You can find us at 799 00:47:54,320 --> 00:47:57,719 Speaker 1: text stuff, H s W and I'll talk to you 800 00:47:57,760 --> 00:48:05,520 Speaker 1: again really soon. Text Stuff is a production of I 801 00:48:05,640 --> 00:48:08,600 Speaker 1: Heart Radio's How Stuff Works. For more podcasts from I 802 00:48:08,719 --> 00:48:12,319 Speaker 1: heart Radio, visit the i heart Radio app, Apple Podcasts, 803 00:48:12,440 --> 00:48:14,400 Speaker 1: or wherever you listen to your favorite shows.