1 00:00:04,880 --> 00:00:08,240 Speaker 1: Welcome back to another episode of Brown Ambition. Today, it's 2 00:00:08,280 --> 00:00:11,119 Speaker 1: time for the BAQA. This is the question and answer 3 00:00:11,200 --> 00:00:13,720 Speaker 1: show where I take your questions and I give you 4 00:00:13,960 --> 00:00:18,599 Speaker 1: my best answers lowercase A. Please don't sue me. I 5 00:00:18,640 --> 00:00:21,520 Speaker 1: ain't got it. You're gonna be very disappointed. I am 6 00:00:21,560 --> 00:00:24,040 Speaker 1: the friend and your head. I am a longtime personal 7 00:00:24,040 --> 00:00:27,240 Speaker 1: finance expert journalist. You know, the credits go on and 8 00:00:27,280 --> 00:00:28,840 Speaker 1: on and on. At the end of the day, I 9 00:00:28,880 --> 00:00:31,880 Speaker 1: am not your personal financial advisor. I don't know anything 10 00:00:31,920 --> 00:00:34,680 Speaker 1: about y'all really other than what you tell me. But 11 00:00:34,800 --> 00:00:37,120 Speaker 1: hopefully what I give you can be used to just 12 00:00:37,479 --> 00:00:40,600 Speaker 1: you know, inform whatever choices you make. It's a little infotainment. 13 00:00:40,720 --> 00:00:45,040 Speaker 1: But again, don't sue me. Did I cover that? Got it? Okay? Cool, 14 00:00:45,120 --> 00:00:47,240 Speaker 1: let's move on. I have a really good question from 15 00:00:47,280 --> 00:00:50,920 Speaker 1: a longtime listener girl, Courtney. I love getting your dms. 16 00:00:51,000 --> 00:00:54,040 Speaker 1: You are always sharing so much positivity with me, and 17 00:00:54,080 --> 00:00:56,279 Speaker 1: I had the pleasure I think of meeting you at 18 00:00:56,320 --> 00:01:00,400 Speaker 1: one of my our only live show and a half 19 00:01:00,440 --> 00:01:03,280 Speaker 1: ago or so. So Hey, Courtney, it's so nice to 20 00:01:03,280 --> 00:01:05,160 Speaker 1: hear from you, and you actually had a great question. 21 00:01:05,640 --> 00:01:10,000 Speaker 1: Courtney sent me this reel from IG which tuckles something 22 00:01:10,000 --> 00:01:12,839 Speaker 1: that we've never really talked about on Brown Ambition, which 23 00:01:12,880 --> 00:01:16,360 Speaker 1: is how employers verify where you have previously worked and 24 00:01:16,480 --> 00:01:19,559 Speaker 1: what data actually they are collecting. So let me play 25 00:01:19,600 --> 00:01:21,960 Speaker 1: this for y'all and then I will answer Courtney's question. 26 00:01:22,560 --> 00:01:24,679 Speaker 2: Okay, So yesterday I shared a story about a Rise 27 00:01:24,680 --> 00:01:27,240 Speaker 2: member who got a verbal job offer after going down 28 00:01:27,280 --> 00:01:30,319 Speaker 2: the path of multiple interviews. The final person extended a 29 00:01:30,480 --> 00:01:32,560 Speaker 2: verbal offer and was like, you're going to hear it 30 00:01:32,600 --> 00:01:34,200 Speaker 2: from us in a couple of days. We're just putting 31 00:01:34,200 --> 00:01:37,360 Speaker 2: everything together. Keep an eye out for a formal email, 32 00:01:37,400 --> 00:01:39,880 Speaker 2: formal offer. A couple days later, she gets a phone 33 00:01:39,920 --> 00:01:42,080 Speaker 2: call from that same person that said, actually, we are 34 00:01:42,120 --> 00:01:44,240 Speaker 2: not going to offer you this job. The CEO doesn't 35 00:01:44,280 --> 00:01:47,440 Speaker 2: feel comfortable hiring somebody that hasn't had full time employment 36 00:01:47,440 --> 00:01:50,960 Speaker 2: in ten months. Obviously, got a lot of comments this 37 00:01:51,120 --> 00:01:53,720 Speaker 2: is happening to many people in the job market right now. 38 00:01:53,720 --> 00:01:55,680 Speaker 2: But a lot of comments are like, who's the company, 39 00:01:55,680 --> 00:01:59,120 Speaker 2: what's going on? How are companies and CEOs so out 40 00:01:59,160 --> 00:02:01,320 Speaker 2: of touch but allowed to treat people this way? And 41 00:02:01,400 --> 00:02:03,520 Speaker 2: one comment really stuck out to me. It was this 42 00:02:03,600 --> 00:02:06,960 Speaker 2: one always lie and freeze your the work number account. Now, 43 00:02:07,000 --> 00:02:08,320 Speaker 2: for those of you who don't know what the work 44 00:02:08,360 --> 00:02:11,200 Speaker 2: number account is, it's essentially the place that employers go 45 00:02:11,280 --> 00:02:15,040 Speaker 2: to verify that what you put on your resume is true. Right. 46 00:02:15,320 --> 00:02:16,880 Speaker 2: They want to make sure that you are who you 47 00:02:16,919 --> 00:02:19,120 Speaker 2: said you are, you have the experience you said, you 48 00:02:19,160 --> 00:02:22,360 Speaker 2: have references. And this also it takes into account like 49 00:02:22,440 --> 00:02:25,919 Speaker 2: your actual employment contract, and I'm like, you can freeze 50 00:02:25,960 --> 00:02:28,200 Speaker 2: that account. I have control over that. I thought it 51 00:02:28,240 --> 00:02:31,400 Speaker 2: was just like whatever information they have about me out 52 00:02:31,440 --> 00:02:34,200 Speaker 2: there from the jobs, right, Like you have an employment contract, 53 00:02:34,200 --> 00:02:35,960 Speaker 2: you put your Social Security number in. I'm like, all 54 00:02:36,040 --> 00:02:38,840 Speaker 2: this stuff is probably out there somewhere and people can 55 00:02:39,000 --> 00:02:42,440 Speaker 2: verify that it's real. I went online today and I 56 00:02:42,480 --> 00:02:45,560 Speaker 2: found my own work number account, signed up, got the 57 00:02:45,600 --> 00:02:49,600 Speaker 2: account downloaded it. One whole job that I had that 58 00:02:49,639 --> 00:02:51,480 Speaker 2: it was part a big part of my career is 59 00:02:51,520 --> 00:02:54,200 Speaker 2: not on it. So a job that I worked at 60 00:02:54,240 --> 00:02:57,560 Speaker 2: for over a year that I have on my resume 61 00:02:57,680 --> 00:03:00,360 Speaker 2: on my LinkedIn as something that did shape my career 62 00:03:00,400 --> 00:03:03,360 Speaker 2: and unfortunately I was laid off because of COVID is 63 00:03:03,440 --> 00:03:07,040 Speaker 2: not on there. But like jobs that I've had at restaurants, 64 00:03:07,160 --> 00:03:08,480 Speaker 2: jobs that I had at a gym when I was 65 00:03:08,480 --> 00:03:11,160 Speaker 2: a personal trainer years ago. That's on my work number account, 66 00:03:11,200 --> 00:03:14,240 Speaker 2: but a job that I would consider important in the 67 00:03:14,280 --> 00:03:17,360 Speaker 2: process of me looking for work these multiple times I 68 00:03:17,400 --> 00:03:20,040 Speaker 2: have been laid off, wasn't there. So I'm like, did 69 00:03:20,200 --> 00:03:22,360 Speaker 2: I get go through interviews and then not hear from people? 70 00:03:22,400 --> 00:03:24,640 Speaker 2: Did I go down processes with companies and then they 71 00:03:24,720 --> 00:03:28,040 Speaker 2: go look at my work number account and something's not 72 00:03:28,080 --> 00:03:29,560 Speaker 2: there and they're like, this doesn't line up. We don't 73 00:03:29,560 --> 00:03:31,320 Speaker 2: want to move forward with her. And nobody said anything 74 00:03:31,320 --> 00:03:34,320 Speaker 2: to me like I need to know from hiring managers 75 00:03:34,360 --> 00:03:37,080 Speaker 2: and recruiters, like how you use this work number account. 76 00:03:37,120 --> 00:03:40,040 Speaker 2: But also I would if I was you looking for 77 00:03:40,080 --> 00:03:42,840 Speaker 2: any job, unemployed, employed, whatever it is, I would go 78 00:03:42,880 --> 00:03:45,840 Speaker 2: online to your work number account verify that the things 79 00:03:45,880 --> 00:03:48,400 Speaker 2: that are on there are actually true about you. This 80 00:03:48,480 --> 00:03:52,880 Speaker 2: person commented a few other comments underneath this same comment 81 00:03:52,960 --> 00:03:55,240 Speaker 2: about what to do and how to handle it, and 82 00:03:55,320 --> 00:03:57,320 Speaker 2: I thought it was super helpful. So you can freeze 83 00:03:57,360 --> 00:04:00,200 Speaker 2: your information, you can also like pick and choose what 84 00:04:00,240 --> 00:04:02,640 Speaker 2: they can see. This might make it harder for a 85 00:04:02,680 --> 00:04:05,440 Speaker 2: company to quickly verify what's going on there. You might 86 00:04:05,480 --> 00:04:07,760 Speaker 2: have to provide references you might have to provide other 87 00:04:07,880 --> 00:04:10,640 Speaker 2: proof like W two's pay stuffs, those kinds of things, 88 00:04:10,640 --> 00:04:13,160 Speaker 2: but at least you're in control of the information that 89 00:04:13,280 --> 00:04:14,960 Speaker 2: they are looking up about you. 90 00:04:15,600 --> 00:04:17,560 Speaker 1: I'm mind blown, all right, So I do want to 91 00:04:17,600 --> 00:04:22,080 Speaker 1: credit that account. That's Giovanna Ventola from Instagram. All right. 92 00:04:22,120 --> 00:04:24,600 Speaker 1: So Courtney shared this with me. She said, Hey, Mandy, 93 00:04:24,640 --> 00:04:26,640 Speaker 1: it's been a while. I came across this video and 94 00:04:26,680 --> 00:04:29,840 Speaker 1: I wondered if you could do an episode on this topic. 95 00:04:30,240 --> 00:04:32,840 Speaker 1: Thank you so much, Courtney. Again, I have loved and just 96 00:04:32,920 --> 00:04:36,440 Speaker 1: so appreciated your support over the years. Let's get into it. Okay, 97 00:04:36,480 --> 00:04:39,880 Speaker 1: so work market? What even is work market? What is 98 00:04:39,920 --> 00:04:42,599 Speaker 1: your work market account? Why have we never heard about this? 99 00:04:43,120 --> 00:04:46,159 Speaker 1: I think all of us by now understands that big 100 00:04:46,240 --> 00:04:49,040 Speaker 1: data is a thing that no matter what we do, 101 00:04:49,279 --> 00:04:52,400 Speaker 1: every time you try to go to the grocery store 102 00:04:52,920 --> 00:04:55,240 Speaker 1: or sign up for I mean this morning, while I 103 00:04:55,320 --> 00:04:57,320 Speaker 1: was paying for parking at the train station, it was 104 00:04:57,360 --> 00:04:59,799 Speaker 1: like check this box, and I'm sure that the agreement 105 00:04:59,800 --> 00:05:03,200 Speaker 1: I signing up for said we going to take your data, girl, 106 00:05:03,240 --> 00:05:05,360 Speaker 1: and we're gonna do whatever we want with it. Big 107 00:05:05,440 --> 00:05:08,680 Speaker 1: data is a thing, and this data that they collect 108 00:05:08,800 --> 00:05:12,520 Speaker 1: on consumers is bundled up and it's sold in many 109 00:05:12,560 --> 00:05:15,919 Speaker 1: different ways. So in this case, when you're a big employer, 110 00:05:16,120 --> 00:05:18,000 Speaker 1: you know, and this typically is used by a big 111 00:05:18,040 --> 00:05:21,920 Speaker 1: employer who needs to needs to process a lot of 112 00:05:22,160 --> 00:05:26,000 Speaker 1: you know, new employees, new hires, do background checks. And 113 00:05:26,080 --> 00:05:28,320 Speaker 1: the way that they can do this at scale is 114 00:05:28,360 --> 00:05:31,760 Speaker 1: to partner or pay for something like the work market. 115 00:05:31,800 --> 00:05:35,200 Speaker 1: There's also one called true work on one word. That's 116 00:05:35,240 --> 00:05:38,320 Speaker 1: another big one that big employers can use. And what 117 00:05:38,360 --> 00:05:42,120 Speaker 1: these companies do is they have your data. They know 118 00:05:42,640 --> 00:05:45,280 Speaker 1: where you've lived, they know the types of companies that 119 00:05:45,320 --> 00:05:48,880 Speaker 1: you've worked for. They've got your sometimes your social Security, 120 00:05:48,960 --> 00:05:52,159 Speaker 1: your date of birth, like past addresses. It's a lot 121 00:05:52,440 --> 00:05:55,360 Speaker 1: like and I believe the work number is actually owned 122 00:05:55,360 --> 00:05:58,360 Speaker 1: by Equifax, which is one of the major credit reporting 123 00:05:58,520 --> 00:06:01,839 Speaker 1: reporting bureaus. Right, a lot like the credit reporting bureaus 124 00:06:02,200 --> 00:06:05,960 Speaker 1: have all your info, so do these companies. And it's 125 00:06:06,120 --> 00:06:09,520 Speaker 1: fairly innocuous, right when an employer wants to verify where 126 00:06:09,560 --> 00:06:12,279 Speaker 1: you've worked before, they're not going to use that data 127 00:06:12,360 --> 00:06:14,960 Speaker 1: in like a malignant way. They're genuinely just wanting to 128 00:06:14,960 --> 00:06:17,159 Speaker 1: be sure that this person is who they say they are, 129 00:06:17,520 --> 00:06:20,640 Speaker 1: and that the record of their employment lines up with 130 00:06:20,680 --> 00:06:23,680 Speaker 1: their resume, with their LinkedIn whatever it is that you 131 00:06:23,760 --> 00:06:28,240 Speaker 1: have submitted. As a former hiring manager myself, I didn't 132 00:06:28,520 --> 00:06:30,440 Speaker 1: work for a company that used a service like this. 133 00:06:30,600 --> 00:06:34,720 Speaker 1: We did our background check and verification internally, and a 134 00:06:34,760 --> 00:06:37,120 Speaker 1: lot of companies, do you know, that's when they call up, 135 00:06:37,400 --> 00:06:40,800 Speaker 1: you know, a former employer, or they call up a 136 00:06:41,040 --> 00:06:44,919 Speaker 1: university you know, enrollment office or admissions office to be 137 00:06:44,960 --> 00:06:47,800 Speaker 1: sure that you completed the degree that you said you did. 138 00:06:47,839 --> 00:06:51,520 Speaker 1: We did that manually. And yeah, there was a one 139 00:06:51,600 --> 00:06:54,720 Speaker 1: time where a new employee of mine lied about having 140 00:06:54,720 --> 00:06:57,960 Speaker 1: a master's I believe in finance or journalism or something, 141 00:06:58,440 --> 00:07:00,680 Speaker 1: and ended up missing out on the road because when 142 00:07:00,680 --> 00:07:04,800 Speaker 1: we did our verification, she lied, which sucked because if 143 00:07:04,839 --> 00:07:06,560 Speaker 1: she had just told the truth, she probably still would 144 00:07:06,560 --> 00:07:09,800 Speaker 1: have got the job, because degrees are okay, but they're 145 00:07:09,800 --> 00:07:13,040 Speaker 1: not the end all be all, so fairly innocuous like 146 00:07:13,080 --> 00:07:16,200 Speaker 1: the reason that they're doing it. So would I be 147 00:07:16,560 --> 00:07:18,800 Speaker 1: super worried? And am I going to stay up late 148 00:07:18,840 --> 00:07:21,760 Speaker 1: tonight because my information is on one of these you know, 149 00:07:21,920 --> 00:07:27,120 Speaker 1: job verification websites like the work Number or true Work No. 150 00:07:27,840 --> 00:07:30,040 Speaker 1: I know the same way that whenever I get an 151 00:07:30,080 --> 00:07:32,560 Speaker 1: alert that the password I'm using has been leaked in 152 00:07:32,600 --> 00:07:34,880 Speaker 1: one of these a million jillion leaks out there, I'm 153 00:07:34,960 --> 00:07:38,119 Speaker 1: just like, let go and let God. At a certain point, 154 00:07:38,200 --> 00:07:40,640 Speaker 1: like I can't come up with any I don't got it. 155 00:07:40,680 --> 00:07:42,960 Speaker 1: I don't have enough brain cells to come up with 156 00:07:43,000 --> 00:07:45,880 Speaker 1: another password and keep tabs on it, like if you 157 00:07:45,880 --> 00:07:48,200 Speaker 1: want it, come and get it, Like what what are 158 00:07:48,200 --> 00:07:49,560 Speaker 1: you going to get at the end, at the end 159 00:07:49,560 --> 00:07:52,320 Speaker 1: of the day. So I have that, you know, sort 160 00:07:52,360 --> 00:07:55,560 Speaker 1: of attitude about it. You may be different, maybe a 161 00:07:55,560 --> 00:07:58,040 Speaker 1: bit more paranoid. So I do think it's something worth 162 00:07:58,280 --> 00:08:02,440 Speaker 1: talking to, especially in this example, and that real In 163 00:08:02,440 --> 00:08:06,680 Speaker 1: that example she gives saying that this this worker, potential 164 00:08:07,120 --> 00:08:11,600 Speaker 1: job candidate was declined because when they completed her job 165 00:08:11,720 --> 00:08:15,720 Speaker 1: verification through the work number that the CEO of the 166 00:08:15,760 --> 00:08:18,440 Speaker 1: company was like, oh, they've been unemployed for ten months. 167 00:08:18,720 --> 00:08:21,880 Speaker 1: That's a red flag. I'm not hiring that person now. 168 00:08:21,960 --> 00:08:25,360 Speaker 1: That's within the CEO's rights. Does it make him or 169 00:08:25,360 --> 00:08:28,360 Speaker 1: her an asshole? Yes, because that is some bullshit, especially 170 00:08:28,400 --> 00:08:31,720 Speaker 1: in this economy where the average person who the average 171 00:08:31,760 --> 00:08:34,400 Speaker 1: time that unemployed people are looking for work right now, 172 00:08:34,400 --> 00:08:37,480 Speaker 1: according to the Bureau of Labor Statistics is six months. Okay, 173 00:08:37,800 --> 00:08:39,680 Speaker 1: So you're not going to make me feel bad for 174 00:08:39,880 --> 00:08:42,080 Speaker 1: being out here for ten months, okay, because it is 175 00:08:42,120 --> 00:08:47,360 Speaker 1: not unheard of. Times are wild, so again, asshole. Yes, 176 00:08:48,040 --> 00:08:51,199 Speaker 1: my concern would be what if that's not true? And 177 00:08:51,480 --> 00:08:55,000 Speaker 1: I do feel like there is power in us getting, 178 00:08:55,040 --> 00:08:56,880 Speaker 1: you know, logging into one of these accounts and just 179 00:08:56,920 --> 00:09:00,000 Speaker 1: making sure that the information that they have there is accurate, 180 00:09:00,360 --> 00:09:03,840 Speaker 1: because if we're going to get judged for being unemployed 181 00:09:03,880 --> 00:09:06,480 Speaker 1: quote unquote for ten months, like, let's make sure it 182 00:09:06,559 --> 00:09:09,880 Speaker 1: was actually true and accurate. It also leads me to 183 00:09:09,960 --> 00:09:14,840 Speaker 1: question like, if companies like this particular leader is relying 184 00:09:14,920 --> 00:09:19,080 Speaker 1: so heavily on these third party data big data collectors, 185 00:09:19,480 --> 00:09:22,640 Speaker 1: they're missing the nuance that you can really explain yourself 186 00:09:22,720 --> 00:09:24,599 Speaker 1: if you had a phone screen with a recruiter, or 187 00:09:24,640 --> 00:09:27,200 Speaker 1: if you had a phone call with the hiring manager, 188 00:09:27,440 --> 00:09:29,840 Speaker 1: you could say, okay, sure on paper, I haven't been 189 00:09:29,960 --> 00:09:32,320 Speaker 1: a W two employee for the past ten months, but 190 00:09:32,400 --> 00:09:35,520 Speaker 1: I have been consulting, I've been freelancing, I've been over 191 00:09:35,559 --> 00:09:38,679 Speaker 1: here getting a certificate or you know, enrolling in some 192 00:09:38,760 --> 00:09:42,199 Speaker 1: kind of skills based program. I think it's completely short 193 00:09:42,240 --> 00:09:45,400 Speaker 1: sighted to just judge someone based on a career gap. 194 00:09:45,760 --> 00:09:48,680 Speaker 1: You know that one of these these big data firms 195 00:09:48,720 --> 00:09:50,880 Speaker 1: may be showing on their end because it won't be 196 00:09:50,920 --> 00:09:54,560 Speaker 1: telling you the full picture. So here's how these companies work. 197 00:09:54,640 --> 00:09:59,000 Speaker 1: So these sites, your employer will actually send payroll sometimes 198 00:09:59,160 --> 00:10:01,600 Speaker 1: HR data like your job title, the dates you've worked, 199 00:10:02,080 --> 00:10:05,600 Speaker 1: your job status, sometimes salary, not always to a third 200 00:10:05,640 --> 00:10:08,839 Speaker 1: party like the work number or a platform that may 201 00:10:08,960 --> 00:10:12,520 Speaker 1: use true work. And this isn't just employers, but also 202 00:10:12,679 --> 00:10:17,040 Speaker 1: like landlords, potential like credit lenders, or in this case, 203 00:10:17,120 --> 00:10:20,400 Speaker 1: another employer. If they need to verify you and your details, 204 00:10:20,760 --> 00:10:23,840 Speaker 1: they can log into these sites as a verifier and 205 00:10:23,880 --> 00:10:27,640 Speaker 1: they can certify that they have a permissible purpose basically 206 00:10:27,679 --> 00:10:31,679 Speaker 1: that they are looking you up for just cause under 207 00:10:32,679 --> 00:10:35,640 Speaker 1: a regulation called the Fair Credit Reporting Act, and that 208 00:10:35,720 --> 00:10:38,760 Speaker 1: they have your consent. So again, this consent comes from 209 00:10:38,880 --> 00:10:41,760 Speaker 1: checking that box on a loan agreement, checking that box 210 00:10:41,760 --> 00:10:46,120 Speaker 1: on a lease application. And some setups can email you 211 00:10:46,200 --> 00:10:49,679 Speaker 1: so that you can explicitly approve or deny that request. 212 00:10:49,800 --> 00:10:54,000 Speaker 1: But a lot of times it's happening really without our knowledge. 213 00:10:54,840 --> 00:10:57,520 Speaker 1: Hey BAFAM, we got to take a quick break. Pay 214 00:10:57,559 --> 00:11:00,640 Speaker 1: some bills. And we'll be right back. So here's what 215 00:11:00,679 --> 00:11:03,640 Speaker 1: you can be mindful of, ba Fan that again, you 216 00:11:03,720 --> 00:11:06,680 Speaker 1: make consent to this kind of data collection without realizing it. 217 00:11:06,720 --> 00:11:09,079 Speaker 1: When you sign a loan, a credit card, a lease application, 218 00:11:09,760 --> 00:11:13,560 Speaker 1: there's almost always language there that authorizes that creditor to 219 00:11:13,679 --> 00:11:17,720 Speaker 1: verify your employment and income information, which they can do 220 00:11:17,760 --> 00:11:22,280 Speaker 1: repeatedly for ongoing quote unquote account review. And that when 221 00:11:22,320 --> 00:11:25,479 Speaker 1: that data is collected, it's sitting in a big database. 222 00:11:25,520 --> 00:11:29,439 Speaker 1: So privacy advocates, of course, they worry about what can 223 00:11:29,480 --> 00:11:34,240 Speaker 1: happen when this information is breached in a leak or 224 00:11:34,280 --> 00:11:39,440 Speaker 1: it's misused. Once they live in a big centralized system. Honestly, 225 00:11:39,480 --> 00:11:42,200 Speaker 1: in this day and age, we know everything eventually gets leaked, 226 00:11:42,360 --> 00:11:45,640 Speaker 1: so there is some concern there. There's also the scope 227 00:11:45,679 --> 00:11:49,040 Speaker 1: of the info we can understand. So at minimum, most 228 00:11:49,120 --> 00:11:52,320 Speaker 1: verifications they can include your name, the employer you worked for, 229 00:11:52,840 --> 00:11:58,240 Speaker 1: job title, dates you work, their pay, which can be 230 00:11:58,320 --> 00:12:01,679 Speaker 1: you know, pretty sensitive, especially if you're bargaining for you 231 00:12:02,080 --> 00:12:05,360 Speaker 1: if you're negotiating your salary. I don't think it is. 232 00:12:06,120 --> 00:12:08,760 Speaker 1: It's a little chilling to know that maybe the employer 233 00:12:08,800 --> 00:12:11,480 Speaker 1: has access to data that could potentially tell them the 234 00:12:11,640 --> 00:12:14,120 Speaker 1: range that you've been earning before. I don't mean to 235 00:12:14,120 --> 00:12:17,079 Speaker 1: be alarmist at all. Again, not every company uses these sites, 236 00:12:17,120 --> 00:12:20,040 Speaker 1: but if it's out there, then you know that could 237 00:12:20,040 --> 00:12:25,080 Speaker 1: potentially make it difficult for you to negotiate. The key 238 00:12:25,240 --> 00:12:27,400 Speaker 1: is not anyone off the street can sign up to 239 00:12:27,440 --> 00:12:30,800 Speaker 1: be a verifier on these sites. So only credentialed verifiers 240 00:12:30,960 --> 00:12:34,760 Speaker 1: who have again that permissible use case are supposed to 241 00:12:34,760 --> 00:12:36,880 Speaker 1: be able to get in, and they themselves are audited, 242 00:12:37,360 --> 00:12:40,200 Speaker 1: So you know that can give you some comfort. The 243 00:12:40,280 --> 00:12:43,360 Speaker 1: question from Courtney is can you opt out or can 244 00:12:43,400 --> 00:12:46,559 Speaker 1: you stop yourself from being tracked? I remember years and 245 00:12:46,640 --> 00:12:50,640 Speaker 1: years ago doing multiple articles on and writing multiple stories 246 00:12:50,679 --> 00:12:52,960 Speaker 1: about big data and how our data is being tracked 247 00:12:52,960 --> 00:12:55,560 Speaker 1: and a lot of time being sold for marketing purposes. 248 00:12:55,600 --> 00:12:58,240 Speaker 1: I mean, this is the reason why you talk about 249 00:12:58,600 --> 00:13:01,200 Speaker 1: wanting a new watch, you know, on the phone, and 250 00:13:01,200 --> 00:13:03,320 Speaker 1: the next thing you know, you're being served ads for it, 251 00:13:03,400 --> 00:13:06,800 Speaker 1: because that information is being packaged and sold to companies 252 00:13:06,840 --> 00:13:08,559 Speaker 1: you want to be able to market to you, right, 253 00:13:09,280 --> 00:13:13,719 Speaker 1: And it's really like so widespread that I don't think 254 00:13:13,760 --> 00:13:16,600 Speaker 1: it's possible for any of us to fully stop our 255 00:13:16,720 --> 00:13:20,600 Speaker 1: information from being bought and sold in this way. With 256 00:13:20,720 --> 00:13:23,560 Speaker 1: many employers, you can't fully stop them from using one 257 00:13:23,600 --> 00:13:27,359 Speaker 1: of these services, like the work number for basic employment verification, 258 00:13:27,480 --> 00:13:31,040 Speaker 1: it's actually just part of their HR operations. In some 259 00:13:31,200 --> 00:13:35,320 Speaker 1: cases you can ask for blocking or extra restrictions like 260 00:13:35,720 --> 00:13:38,600 Speaker 1: putting a block or security freeze flag on your file, 261 00:13:38,920 --> 00:13:43,360 Speaker 1: so automated income sharing is limited and extra steps are 262 00:13:43,400 --> 00:13:46,360 Speaker 1: needed before they're able to pull that info. But this 263 00:13:46,600 --> 00:13:50,720 Speaker 1: is really policy specific, and if everything is kosher, you 264 00:13:50,720 --> 00:13:54,840 Speaker 1: could actually be delaying your eventual hire and slow down 265 00:13:55,160 --> 00:13:58,720 Speaker 1: like legitimate verification. And in this job market, who wants 266 00:13:58,720 --> 00:14:00,520 Speaker 1: to get in their own way and it comes to 267 00:14:00,600 --> 00:14:03,760 Speaker 1: just ticking a final background check and getting that job right. 268 00:14:04,320 --> 00:14:07,120 Speaker 1: There is some practical advice for you. There'll be a family. 269 00:14:07,120 --> 00:14:09,439 Speaker 1: If you're really curious, you can sign up for your 270 00:14:09,440 --> 00:14:14,160 Speaker 1: own work number the work Number employee portal, so you 271 00:14:14,200 --> 00:14:15,920 Speaker 1: can sign up, create a log in, and you can 272 00:14:15,960 --> 00:14:18,280 Speaker 1: see what your record looks like. I might go in 273 00:14:18,280 --> 00:14:20,280 Speaker 1: there and see what mine looks like. It'll be interesting 274 00:14:20,320 --> 00:14:23,120 Speaker 1: since I haven't worked full like for as a W 275 00:14:23,360 --> 00:14:25,520 Speaker 1: two worker in about five years now, so I don't 276 00:14:25,560 --> 00:14:27,480 Speaker 1: know what they're going to have on there. I hope 277 00:14:27,480 --> 00:14:34,320 Speaker 1: they have just incredible badassory. She's a podcaster and consultant 278 00:14:34,440 --> 00:14:38,480 Speaker 1: and she's speaking and she's I got stuff. Okay. You 279 00:14:38,520 --> 00:14:41,480 Speaker 1: can also ask HR at the company that you're interviewing 280 00:14:41,520 --> 00:14:45,440 Speaker 1: with what their policy is for job verification. You can say, 281 00:14:45,480 --> 00:14:47,640 Speaker 1: you know, is there a particular third party service that 282 00:14:47,680 --> 00:14:51,120 Speaker 1: you use for employment verification? What fields are you looking for? 283 00:14:51,160 --> 00:14:52,840 Speaker 1: I mean, I think you can approach it like if 284 00:14:53,200 --> 00:14:55,720 Speaker 1: you're really concerned about it, just approach it, not in 285 00:14:55,760 --> 00:14:57,920 Speaker 1: a way that they think you have something to hide, 286 00:14:58,240 --> 00:15:00,480 Speaker 1: but just in like a way of curiosity, like, Hey, 287 00:15:00,520 --> 00:15:05,040 Speaker 1: I actually have heard that there's a job verification process 288 00:15:05,080 --> 00:15:07,880 Speaker 1: and I'm just curious you guys use any particular service 289 00:15:07,920 --> 00:15:11,160 Speaker 1: for that or are you doing that completing that internally? 290 00:15:11,200 --> 00:15:13,080 Speaker 1: I just want to be sure that all of my 291 00:15:13,160 --> 00:15:17,040 Speaker 1: information is up to date and super current. I'm concerned 292 00:15:17,080 --> 00:15:19,640 Speaker 1: that maybe there may be some gaps, and if that's 293 00:15:19,640 --> 00:15:22,960 Speaker 1: the case, then I think any reasonable rep from that 294 00:15:23,040 --> 00:15:26,040 Speaker 1: company would say, oh, well we use this or you know, 295 00:15:26,080 --> 00:15:29,000 Speaker 1: we're gonna do an internal review ourselves, and you know, 296 00:15:29,040 --> 00:15:33,680 Speaker 1: we'll make sure to run any potential gaps or make 297 00:15:33,720 --> 00:15:37,200 Speaker 1: sure any any confusion is cleared up before we move forward. 298 00:15:37,440 --> 00:15:40,280 Speaker 1: If you really want to be mindful about where your 299 00:15:40,360 --> 00:15:42,360 Speaker 1: data is ending up. I mean, you could read those 300 00:15:42,440 --> 00:15:44,520 Speaker 1: terms of use on everything that we sign up for, 301 00:15:44,760 --> 00:15:48,280 Speaker 1: and it's one of those situations where you know, if 302 00:15:48,320 --> 00:15:51,480 Speaker 1: you want to live in the woods and like be 303 00:15:51,640 --> 00:15:54,720 Speaker 1: off the grid, maybe that's cool for you. But just 304 00:15:54,800 --> 00:15:57,600 Speaker 1: the way things are set up these days, the data, 305 00:15:58,440 --> 00:16:00,840 Speaker 1: they don't need it. It's the it's pay to play, 306 00:16:00,880 --> 00:16:03,000 Speaker 1: and we pay with our info in a lot a 307 00:16:03,000 --> 00:16:05,040 Speaker 1: lot of ways. If you sign up for one of 308 00:16:05,080 --> 00:16:07,880 Speaker 1: these accounts and you do spot errors, you're well within 309 00:16:07,920 --> 00:16:10,560 Speaker 1: your right to get those errors corrected. So you should 310 00:16:10,560 --> 00:16:12,560 Speaker 1: be able to reach out to the company and request 311 00:16:12,720 --> 00:16:17,600 Speaker 1: that inaccurate information is fixed or taken off. So there 312 00:16:17,640 --> 00:16:19,560 Speaker 1: is some empowerment there. If you sign up for one 313 00:16:19,560 --> 00:16:22,840 Speaker 1: of these accounts and you see misinformation one hundred percent, 314 00:16:23,040 --> 00:16:26,480 Speaker 1: make sure that that is scrubbed. But the bottom line, BAFAM, 315 00:16:26,640 --> 00:16:30,600 Speaker 1: is that you probably cannot fully stop your employer, any employer, 316 00:16:30,920 --> 00:16:34,400 Speaker 1: from using these systems. You can, however, get to know 317 00:16:34,440 --> 00:16:37,960 Speaker 1: what's in your file and understand when and how you 318 00:16:38,000 --> 00:16:41,160 Speaker 1: are consenting to have your information collected in this ways, 319 00:16:41,680 --> 00:16:45,360 Speaker 1: and in some particular cases, maybe you're able to formally 320 00:16:45,400 --> 00:16:48,080 Speaker 1: approve those requests for information, but a lot of times 321 00:16:48,120 --> 00:16:50,520 Speaker 1: it's happening in the background and we may not be 322 00:16:51,000 --> 00:16:54,760 Speaker 1: fully aware unless you know, in situations like this, someone 323 00:16:54,920 --> 00:16:56,880 Speaker 1: lets someone know, Hey, I was screwed out of a 324 00:16:56,960 --> 00:16:59,480 Speaker 1: job because there was some misinformation or a gap on 325 00:16:59,560 --> 00:17:03,280 Speaker 1: my employment history and this company was trying to check it. 326 00:17:03,480 --> 00:17:06,080 Speaker 1: So I'm really really sorry for that person. At the 327 00:17:06,160 --> 00:17:07,520 Speaker 1: end of the day, though, I don't think you want 328 00:17:07,520 --> 00:17:10,080 Speaker 1: to work there anywhere. Girl, Like, if that CEO is 329 00:17:10,080 --> 00:17:12,280 Speaker 1: going to judge you for ten months of a career gap, like, 330 00:17:12,800 --> 00:17:14,680 Speaker 1: they can get to step and you're probably better off. 331 00:17:14,880 --> 00:17:18,200 Speaker 1: Let's just keep it one hundred, all right, Courtney, Thank 332 00:17:18,200 --> 00:17:20,520 Speaker 1: you so so much for your question, ba Fam. If 333 00:17:20,520 --> 00:17:22,200 Speaker 1: you want to submit a question to the show, you 334 00:17:22,280 --> 00:17:24,760 Speaker 1: know where to find me. It's Brown Ambition Podcast at 335 00:17:24,800 --> 00:17:28,040 Speaker 1: gmail dot com. Or you can send me a message 336 00:17:28,080 --> 00:17:31,800 Speaker 1: on ig slide into my DMS at Brown Ambition Podcast 337 00:17:32,000 --> 00:17:33,920 Speaker 1: if you want to write your question, amazing. If you 338 00:17:33,960 --> 00:17:36,680 Speaker 1: want to send me a voice note, even better. Love 339 00:17:36,720 --> 00:17:39,840 Speaker 1: hearing y'all's voices and playing that on the show. Until 340 00:17:39,920 --> 00:17:42,199 Speaker 1: next time, It's Mandy Money. Thank you so much for 341 00:17:42,240 --> 00:17:50,879 Speaker 1: listening to Brown Ambition by Bafam. And before I go, 342 00:17:51,000 --> 00:17:53,040 Speaker 1: BA Fam, I want to shout out the team that 343 00:17:53,119 --> 00:17:56,440 Speaker 1: helps make Brown Ambition possible. Huge thanks to my fam 344 00:17:56,480 --> 00:18:00,720 Speaker 1: at iHeartRadio, Katrina Norvel and Jenna Cagel, my worker bees 345 00:18:00,760 --> 00:18:04,960 Speaker 1: behind the scenes, booking Assistant Brittany Laier and virtual Assistant 346 00:18:04,960 --> 00:18:08,199 Speaker 1: Cameron McNair who keep me organized, and of course my 347 00:18:08,359 --> 00:18:11,680 Speaker 1: editor Courtney Dean. Thank y'all so much for supporting the show. 348 00:18:11,880 --> 00:18:14,520 Speaker 1: If you love Brown Ambition, share it with a friend, 349 00:18:14,680 --> 00:18:17,080 Speaker 1: tag us on social and don't forget to leave a 350 00:18:17,160 --> 00:18:20,199 Speaker 1: comment or review. Until next time. By BA Fam