Court filing
Exhibit 1 to the Mura Declaration - Public Version of ECF No.… — Brooks v. Thomson Reuters Corporation (Dkt. 148.1)
Filed December 14, 2022 in Brooks v. Thomson Reuters Corporation; one of 127 filings from this case.
Record facts
| Court | U.S. District Court for the Northern District of California |
|---|---|
| Filed | 2022-12-14 |
U.S. District Court for the Northern District of California · No. 3:21-cv-01418-EMC · Doc. 148-1 · 2022-12-14 · Docket on CourtListener
Full text
EXHIBIT 1
(Redacted)
Case 3:21-cv-01418-EMC Document 148-1 Filed 12/14/22 Page 1 of 49
CONFIDENTIAL - STEVEN FOX
Golkow Litigation Services
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UNITED STATES DISTRICT COURT FOR THE
2
NORTHERN DISTRICT OF CALIFORNIA
3
SAN FRANCISCO DIVISION
4
* * * * * * * * * * * * * * *
5
CAT BROOKS and RASHEED SHABAZZ, individually
and on behalf of all others similarly situated,
6
Plaintiffs,
7
vs. Case No. 3:21-cv-1418-EMC
8
THOMSON REUTERS CORPORATION,
9
Defendant.
10
* * * * * * * * * * * * * * *
11
***** CONFIDENTIAL *****
12
13
REMOTE VIDEOTAPED DEPOSITION OF STEVEN FOX
14
May 16, 2022
15
10:02 a.m. to 5:36 p.m.
16
REPORTED BY ANITA KORNBURGER
REGISTERED PROFESSIONAL REPORTER
17
18
***** CONFIDENTIAL *****
19
20
* * * * * * * * * * * * * * *
21
22
23
24
25
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CONFIDENTIAL - STEVEN FOX
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A P P E A R A N C E S
2
GIBBS LAW GROUP LLP, by
Mr. Ezekiel S. Wald
3
1111 Broadway, Suite 2100
Oakland, California 94607
4
510-350-9700
zsw@classlawgroup.com
5
Appearing by videoconference on behalf of the
Plaintiffs.
6
SURVEILLANCE TECHNOLOGY
7
OVERSIGHT PROJECT, by
Mr. Albert Fox Cahn (pro hac vice)
8
Mr. Evan Enzer
Mr. David Siffert
9
40 Rector Street, 9th Floor
New York, NY 10006
10
albert@stopspying.org
Appearing by videoconference on behalf of the
11
Plaintiffs.
12
PERKINS COIE LLP, by
Ms. Nicola Menaldo
13
Ms. Erin Earl
Ms. Susan Fahringer
14
1201 Third Avenue, Suite 4900
Seattle, Washington 98101-3099
15
nmenaldo@perkinscoie.com
Appearing by videoconference on behalf of the
16
Defendant.
17
ALSO PRESENT: Jon Olson - Thomson Reuters
18
I N D E X
19
20
Examination by Page
21
Mr. Fox Cahn. . . . . . . . . . . . . . 6
22
23
24
25
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the question?
2
BY MR. FOX CAHN:
3
Q. How did Thomson Reuters acquire CLEAR?
4
A. Thomson Reuters acquired CLEAR when one
5
of our competitors acquired a company called Choice
6
Point, and the CLEAR product was something that had
7
to be divested before that acquisition would be
8
approved.
9
Q. And this was due to antitrust concerns?
10
A. I believe that's the case, yes.
11
Q. And how did CLEAR -- strike that.
12
At the time that CLEAR was acquired,
13
how did it compare to the products that CLEAR
14
offers today?
15
MS. MENALDO: Objection, form.
16
THE WITNESS: Yeah, I'm not -- I'm not
17
very familiar with what CLEAR looked like or did at
18
the time it was acquired.
19
BY MR. FOX CAHN:
20
Q. In the time you've been working with
21
CLEAR, how has it changed?
22
A. In the time that I've been working with
23
it, again, since approximately 2010, it has become
24
a research tool used more than by government
25
entities and law enforcement, and has expanded
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into, say, a corporate segment and, as such, new
2
features and new data has been added for those
3
additional use cases.
4
Q. What data has been added for those use
5
cases?
6
A. There's a lot of data that has been added
7
in the last twelve years. I'm not going to
8
remember all of them. But as examples, we have
9
increased our data sets containing phone numbers,
10
containing e-mail addresses, containing information
11
that would identify relationships between a
12
research subject and an employer, as well as other
13
files that meet certain regulatory needs, such as
14
data that would identify people or businesses that
15
are in the marijuana industry, and additional data
16
sources that helps identify research subjects that
17
might not be represented in the credit bureau
18
files, so consumers with early -- early to the
19
banking market consumers, younger consumers or
20
individuals that don't have the best credit.
21
Q. And has that additional focus on
22
consumers that are early to banking included
23
minors?
24
A. No.
25
Q. So there has not been any minors whose
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BY MR. FOX CAHN:
2
Q. So there are occasions when a minor's
3
data is available on CLEAR?
4
A. There are occasions where a minor's name
5
might show up in a record with no other identifying
6
information that would indicate that it's a minor
7
or the name of a person that's a minor.
8
Q. You mentioned increasing the number of
9
e-mail addresses and phone numbers that are
10
available in CLEAR during the time you've worked on
11
the product.
12
Whose e-mail addresses and phone
13
numbers have been included?
14
A. Basically consumers'.
15
Q. So -- sorry. Go ahead, please.
16
A. I mean, it's a very broad question. I
17
can't, you know, obviously produce a list of names,
18
but these files attempt to identify e-mail
19
addresses and phone numbers of -- and the owners of
20
those e-mail addresses and phone numbers, and that
21
can be -- they can be very large files.
22
Q. Would it be fair to say that there are
23
millions of additional individuals whose e-mails
24
and phone numbers have been added to CLEAR during
25
the time you worked with the product?
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A. In the last twelve years, I think that's
2
a safe bet that it would number in the millions for
3
each phones and e-mails.
4
Q. And this has included millions of
5
additional consumers who previously weren't in the
6
database?
7
A. No. The vast majority of base -- based
8
on our testing, as we're testing these files, it's
9
actually pretty rare that a brand-new consumer will
10
show up in the CLEAR database as a result of an
11
e-mail or phone-centric file. The subject is
12
usually already there, but these files may produce
13
different phone numbers or e-mail addresses for
14
that consumer.
15
Q. Why is that?
16
A. Can you clarify the question?
17
Q. Would you say it's fair to say that CLEAR
18
contains profiles for most consumers?
19
A. Yes, that's fair.
20
MS. MENALDO: Objection, form.
21
BY MR. FOX CAHN:
22
Q. I'm sorry, Mr. Fox, could you repeat your
23
answer?
24
A. I said yes, that's fair.
25
Q. Would you say that CLEAR likely has
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profiles for more than 75 percent of consumers in
2
the United States?
3
A. Based on our analysis, I think that is a
4
correct statement.
5
Q. Would you say it's fair to say that CLEAR
6
has profiles on more than 90 percent of consumers
7
in the United States?
8
A. I would say once you get to that number,
9
then I don't have -- I can't speak -- I can't
10
confirm that that is true or false.
11
Q. Is it possible that you have that many
12
consumer profiles?
13
A. In my opinion, it's possible, but I don't
14
know that for sure.
15
Q. Do you believe it's likely?
16
A. I think it's possible.
17
Q. Would you say that CLEAR has records on
18
the vast majority of consumers in the United
19
States?
20
A. If by "vast majority" that number
21
coincides with 90 percent, then I would say that
22
sounds right. But I think it depends on your
23
definition of vast majority.
24
Q. Of course. And how many profiles do you
25
have on consumers outside the United States?
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A. I don't know the answer to that question.
2
Q. Would you say you have profiles for a
3
smaller percentage of consumers outside of the
4
United States than you do for those inside the
5
United States?
6
A. Can you clarify whether you mean all
7
consumers, international and US based?
8
Q. So is the -- sorry. Strike that.
9
Is the percentage of US consumers that
10
have CLEAR profiles higher than the percentage of
11
consumers that have CLEAR profiles outside of the
12
United States?
13
A. I think I keep on missing the distinction
14
here. US consumers in both instances?
15
Q. No. I'm comparing consumers within the
16
United States, American consumers, and those in
17
countries outside of the United States. So the
18
rest of the world apart from the United States.
19
A. Okay. CLEAR contains predominantly US
20
consumers in the database. There are instances,
21
but it's -- it's virtually all US consumers.
22
Q. So it's virtually all US consumers in the
23
CLEAR database?
24
A. That is correct.
25
Q. All right. Could you tell us what the
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use cases?
2
A. No. We would also be able to obtain it,
3
but we would not be allowed to allow certain
4
customers or certain use cases. We would not be
5
allowed to use those data elements in research or a
6
report for certain customers or certain use cases.
7
Q. All right. So, you know, some CLEAR
8
customers are able to access more data than others;
9
is that correct?
10
A. Every CLEAR end user has to declare a
11
permissible use under GLB, DPPA, and certain
12
voters' laws every time they sign into the product.
13
So for the most part, all of the data that's
14
included is -- meets those use cases under those
15
regulatory frameworks.
16
There are very isolated instances
17
where CLEAR may have to restrict certain data
18
elements from certain use cases that might prevent
19
that data flowing to a specific end user with a
20
specific use case.
21
Q. So is it fair to say that when states
22
expand the definition of PII, they can prevent
23
CLEAR from showing the covered data to users in
24
response to queries made under certain use cases?
25
A. That is correct.
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BY MR. FOX CAHN:
2
Q. All right.
3
Well, Mr. Fox, moving back to the
4
prior line of questioning, looking at the users of
5
CLEAR, you mentioned that there was an increase in
6
commercial users during your time with the product;
7
is that correct?
8
A. I think I refer to them as corporate
9
users, but yes.
10
Q. And what percentage of CLEAR users are
11
corporate users?
12
A. Today?
13
Q. Correct.
14
A. I don't know an exact number, but I
15
believe it's about
16
17
18
19
20
Q. And what sort of government agencies use
21
CLEAR?
22
A. A variety of federal, state, and local
23
agencies that need investigative tools.
24
Q. And what percentage of those government
25
agencies are law enforcement agencies?
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A. I do not.
2
Q. How do you track what portion of
3
customers use each payment model?
4
A. I don't track that.
5
Q. Does Thomson Reuters track what portion
6
of users use each type of payment model?
7
A. I'm not sure if they track that or not.
8
Q. Do you know what type of payment model is
9
most common for CLEAR users?
10
A. To the best of my knowledge, most CLEAR
11
customers use a subscription model for CLEAR.
12
Q. And how does pricing work with a
13
subscription model?
14
A. I don't know.
15
Q. Are users charged a flat fee with a
16
subscription model?
17
A. I don't know.
18
Q. Does Thomson Reuters track what
19
percentage of revenue comes from each product?
20
A. Can you define "product"?
21
Q. Does Thomson Reuters keep track of what
22
percentage of its revenue comes from each use case
23
of CLEAR?
24
A. Not that I'm aware of.
25
Q. And does Thomson Reuters track what
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Q. Is SFTP secure file transfer protocol?
2
A. Correct.
3
Q. Does CLEAR also receive data from
4
licensors on physical media?
5
A. I don't know whether Thomson Reuters does
6
that anymore.
7
Q. Is there any documentation of how Thomson
8
Reuters receives data from licensors?
9
A. I'm not aware of any.
10
Q. Does Thomson Reuters have a standard SFTP
11
protocol for transferring data from a licensor?
12
A. No. It varies from vendor to vendor.
13
Q. How do you clean data you receive from
14
the vendors?
15
MS. MENALDO: Objection, form.
16
BY MR. FOX CAHN:
17
Q. Strike that.
18
Mr. Fox, do you know what I mean by
19
the term "clean data"?
20
A. I don't.
21
Q. Do you process data received from
22
licensors to make it -- strike that.
23
Do you process data once you receive
24
it from licensors?
25
A. Yes, we do.
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Q. Do you take steps to review that data and
2
conform it to the protocols used by the CLEAR
3
platform?
4
A. Our processing of inbound files from our
5
vendors varies from vendor to vendor and file to
6
file, but all of them will undergo some amount of
7
processing, yes.
8
Q. And what are the factors you consider in
9
determining how to process data?
10
A. As I said, all data is going to get
11
processed to some degree or another, and primarily
12
it is so that however the data came to us, it needs
13
to be able to be processed in a way that CLEAR
14
recognizes it and accepts it.
15
Q. I've just marked plaintiffs' Exhibit 5.
16
It is an e-mail chain with a Bates stamp ending in
17
the number 144207 on the bottom of the first page.
18
Can you confirm that that document is available to
19
you, Mr. Fox?
20
A. It is available to me.
21
Q. And can you confirm that Bates stamp is
22
visible on the bottom of the first page?
23
A. I can confirm that, yes.
24
Q. Please take a moment to review the
25
document.
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A. All right. I've read the document.
2
Q. Do you know what this document is?
3
A. Yes.
4
Q. What is it?
5
A. It's an e-mail between myself and Leah
6
Weikert. And there are other individuals in the
7
e-mail chain down below.
8
Q. Who's Leah Weikert?
9
A. She, at the time, was a senior -- senior
10
marketer in our marketing department.
11
Q. You state in the first full paragraph of
12
the e-mail sent on June 25, 2018, at 3:14 p.m.,
13
"Thomson Reuters is not the source of any of the
14
data in the" -- strike that.
15
You state, "Thomson Reuters is not the
16
source of any of the data in a CLEAR report. We
17
are simply the vehicle for facilitating the
18
compilation of unverified data for an
19
investigation." Did I read that correctly?
20
A. You did.
21
Q. What do you mean by "unverified data"?
22
A. Unverified data from an industry
23
standpoint indicates data that has not been
24
independently verified. It is simply as is from
25
the source.
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happens on a file, we analyze the different fields
2
within a document. And in certain instances, it's
3
fairly obvious when a data element is not accurate,
4
such as a zip code only containing four digits,
5
phone numbers that are -- have the incorrect number
6
of digits, Social Security numbers that start with
7
the number nine, like that.
8
Q. And in those cases does Thomson Reuters
9
provide that data to CLEAR customers?
10
A. Provide which data?
11
Q. The data you identified as having the
12
incorrect number of digits in a zip code or a phone
13
number beginning with nine, is that data provided
14
to customers?
15
A. It depends on the type of data.
16
17
18
19
20
21
Q. So are there times when Thomson Reuters
22
obtains data and, in the course of processing,
23
identifies that it has a zip code that has the
24
wrong number of digits and it will still be
25
provided to customers?
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A. Correct.
2
Q. And there are times when that data will
3
be removed?
4
A. There aren't -- there wouldn't be many
5
situations where data would be removed for
6
inaccuracy such as that. It would still be
7
presented to the user based on the other elements
8
that are contained within that document.
9
Q. Are there any cases where that data
10
wouldn't be presented to the user?
11
A. There are instances where data, when it's
12
being processed for inclusion into CLEAR, may not
13
be -- may not make it into the product and
14
therefore not presented to users, yes.
15
Q. So there are times when Thomson Reuters
16
receives data that doesn't make it into the
17
product?
18
A. Correct.
19
Q. In the paragraph I was previously reading
20
from, it says, "While our customers are trained on
21
CLEAR, and hopefully understand the unverified
22
nature of these reports, the general public, the
23
subjects of the investigations, does not." Did I
24
read that correctly?
25
A. Yes.
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Q. Why do you hope that customers understand
2
the unverified nature of these reports?
3
A. I hope that they understand the
4
unverified nature of the reports because that is
5
part of the initial training that is given to CLEAR
6
customers and CLEAR end users, that the data that's
7
included in a CLEAR report is unverified and
8
presented as is, and ultimately it's up to the end
9
user if they need to verify the data, that they do
10
so independently.
11
Q. Do you want customers to understand this
12
limitation with CLEAR data?
13
A. Yes.
14
Q. How do you think this understanding of
15
the limitation of CLEAR data impacts how customers
16
use the CLEAR product?
17
A. The way that it impacts the way users use
18
the product is when they perform an investigation
19
and run a CLEAR report, they will need to verify
20
any important pieces of information that's relevant
21
to their investigation.
22
Q. What percentage of customers do you think
23
understand that CLEAR reports are unverified?
24
MS. MENALDO: Objection, form.
25
THE WITNESS: I don't have an answer to
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LPR gateway delivers more than six billion
2
commercial results"; is that correct?
3
A. That is correct.
4
Q. What is a commercial result?
5
MS. MENALDO: Objection.
6
THE WITNESS: I'm not sure what a
7
commercial result is referring to as used by the
8
marketing department when they created this
9
document.
10
BY MR. FOX CAHN:
11
Q. Are you familiar with the LPR gateway?
12
A. I am familiar, yes.
13
Q. And are you familiar with the type of
14
search results it provides?
15
A. I am, yes.
16
Q. Given that, is there something you
17
believe that the number six billion could
18
accurately represent?
19
A. It could represent the number of records
20
within that data set.
21
Q. And by "record," do you mean photographs
22
of automotive license plates?
23
A. Among other data elements, yes.
24
Q. What other data elements would it
25
include?
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2
3
Q. So would the number six billion be larger
4
than the number of photos available?
5
A. No, the six billion represents the number
6
of records, but each record would contain those
7
data elements.
8
Q. And where it says, "New license plates
9
scans are being added at a rate of more than 150
10
million per month"; did I read that correctly?
11
A. Yes, you did.
12
Q. Does that reference new photographs of
13
license plates?
14
A. That does, yes.
15
Q. What are the sources of this data?
16
A. The source of this data, again, subject
17
to any confidentiality in the license agreement, is
18
Motorola.
19
Q. And does this include photographs taken
20
within California?
21
A. It does.
22
Q. Is this available to customers in
23
California?
24
A. That I am not sure of.
25
Q. Does CLEAR process LPR data prior to
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Did I read that correctly?
2
A. You did.
3
Q. And what is the ERD process?
4
A. The ERD is an internal process that we
5
have. The acronym refers to Entity Resolution
6
Database.
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Q. What is enough information to pin a
21
record to an individual?
22
A. Technically, I don't have an answer to
23
that question.
24
Q. I've just marked Exhibit 9. It is a
25
spreadsheet with the Bates number ending 082062.
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entire document so you can view it properly.
2
THE WITNESS: I will do that, because I'm
3
trying to enlarge it as well, and then the document
4
doesn't load. So give me a minute. I will
5
download it.
6
MS. MENALDO: If you just click on the
7
three dots, there's an option to download. And it
8
should do that fairly quickly.
9
BY MR. FOX CAHN:
10
Q. Mr. Fox, have you been able to download
11
the document?
12
A. Yes, it is downloaded. I can see it now.
13
Q. Do you recognize it?
14
A. I don't specifically recognize this
15
document, no.
16
Q. All right. Do you recognize the
17
categories of data that are listed in the document?
18
A. Yes, I do.
19
Q. And are these categories of data that are
20
accessible using CLEAR?
21
A. Yes, these are data categories that
22
appear in the CLEAR product.
23
Q. And does this data include individuals in
24
California?
25
A. Yes, I see some that are specific to
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California.
2
Q. And is this data the same throughout the
3
United States?
4
A. No, it is not.
5
Q. So some of these databases are only
6
applicable to individuals in California?
7
A. The geographic coverage of each one of
8
these data categories will be different and vary
9
from state to state.
10
Q. Which of these data categories only apply
11
to entities within California?
12
13
14
15
16
17
18
19
Q. Are there any others?
20
A. Yes, there are others.
21
Q. What does it mean when it says
22
searchable?
23
A. The searchable reference indicates that
24
within the CLEAR product, that an end user would
25
have the ability to search by that particular
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THE WITNESS: I have no idea. I wouldn't
2
be able to estimate that with any degree of
3
accuracy.
4
BY MR. FOX CAHN:
5
Q. Are there any documents that you could go
6
to to figure out how many data points are
7
accessible in CLEAR?
8
A. I can't think of any.
9
Q. Are there any Thomson Reuters' employees
10
who you might consult who could help answer that
11
question?
12
A. I can't think of any. It doesn't seem to
13
be the type of figure that would be relevant.
14
Q. So you haven't discussed the number of
15
data points accessible through CLEAR?
16
A. I can't think of a time that I have, no.
17
Q. I'm going to mark Exhibit 10. It should
18
be accessible to you now on the platform. It is a
19
document with the Bates number ending in 79617. Do
20
you see that?
21
A. I do see that.
22
Q. Have you had time to review this
23
document?
24
A. Give me a couple of minutes. Okay.
25
Q. In the upper right corner of the document
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Golkow Litigation Services
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it says, "CLEAR's proprietary pinning process and
2
real-time live gateways provide customers with more
3
current and accurate data than insert competitor
4
name"; is that correct?
5
A. You read that correctly, yes.
6
Q. And then in the third box on the
7
right -- sorry. Strike that.
8
In the third row on the right-hand
9
side it says, "CLEAR is powered by billions of data
10
points and leverages cutting-edge public records
11
technology to bring all key content together in a
12
customizable dashboard"; is that correct?
13
A. You read that correctly, yes.
14
Q. How is the number of data points
15
calculated?
16
MS. MENALDO: Objection.
17
THE WITNESS: I don't know. And I'm not
18
even sure what the phrase "data point" means.
19
BY MR. FOX CAHN:
20
Q. Just to go back. Have you seen this
21
document before?
22
A. I have not.
23
Q. And you don't know what the data point
24
could be referencing here?
25
A. I don't.
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Q. I'm now marking Exhibit 11. It is an
2
e-mail thread with the Bates number ending in 72634
3
appearing on the bottom of the first page. Can you
4
see that document?
5
A. I can.
6
Q. And I'm just going to ask you about the
7
e-mail on the third page.
8
MS. MENALDO: Mr. Fox, you have the right
9
to review the entire document.
10
THE WITNESS: Yeah. I will do that. All
11
right, I've read it.
12
BY MR. FOX CAHN:
13
Q. Looking at the top of page 3, under the
14
sentence starting, "This is what's available,"
15
there are several different categories listed;
16
correct?
17
A. Yes.
18
Q. What are the numbers listed next to each
19
category?
20
MS. MENALDO: Objection, foundation.
21
BY MR. FOX CAHN:
22
Q. Strike that.
23
So Mr. Fox, you've -- you've seen this
24
e-mail before; correct?
25
A. I have. I don't specifically recall it,
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but I'm in the e-mail chain, so I have.
2
Q. And it is an e-mail about the data
3
available on CLEAR; is that correct?
4
A. That is correct.
5
Q. And in the paragraph at the head of
6
page 3, there are several categories of data
7
listed; correct?
8
A. At the top of page 3, you mean?
9
Q. Yes.
10
A. Yes.
11
Q. And then there are numbers for each line;
12
correct?
13
A. Yes.
14
15
16
A. Without verifying the accuracy of the
17
information, but based on who provided that
18
information, I believe that would be the number of
19
arrest records that were available at that point in
20
time.
21
Q. So is it fair to say that these numbers
22
reflect the number of records available at the time
23
this e-mail was sent for each of the categories
24
listed?
25
MS. MENALDO: Objection.
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THE WITNESS: I don't -- sorry. Again, I
2
don't know for sure, but based on the author and
3
the subject matter of the e-mail, that's what I
4
believe.
5
BY MR. FOX CAHN:
6
Q. So this is an e-mail sent on Thursday,
7
January 21st, at -- 2021 at 9:55 a.m. by Paul J.
8
Wohletz; correct?
9
A. That's correct.
10
Q. And he is asking, "Can you provide this
11
detail, please,
12
correct?
13
A. That's what it says, yes.
14
Q. And by "all of the loaded content listed
15
below," he means categories of data available in
16
CLEAR; correct?
17
18
CLEAR. CLEAR is the acronym for CLEAR. So I'm not
19
sure what he's referring to.
20
21
A. Again, I didn't write that, so I don't
22
know.
23
Q. And do you think it would be strange that
24
he would reference CLEAR in the subject of the
25
e-mail list and then ask a question unrelated to
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Golkow Litigation Services
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CLEAR?
2
A. Not really. At the base of -- the data
3
that's made available in the CLEAR product, the
4
data available in CLEAR would represent the base of
5
data. But there are features and functionality
6
within CLEAR that may contain a subset or data
7
that's only relevant to a specific use case.
8
Q. So could this represent a subset of the
9
data available in CLEAR?
10
A. It could.
11
Q. Do you have any reason to doubt that the
12
amount -- strike that.
13
Do you have any reason to think that
14
the amount of data available in CLEAR is lower than
15
the numbers provided in this e-mail?
16
A. I wouldn't be able to answer that one way
17
or another.
18
Q. All right. I'm now introducing
19
Exhibit 12. It is an e-mail thread with a Bates
20
number on the first page ending in 20290. Do you
21
see that?
22
A. I do see that.
23
Q. I'm just going to ask you about the
24
e-mail visible on the top of the second page. So
25
could you please review that?
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A. I will.
2
MS. MENALDO: And I'll remind you that
3
you have the right to review the entire document.
4
Thank you.
5
BY MR. FOX CAHN:
6
Q. And apologies, I'll actually be asking
7
about a portion at the bottom of page 3.
8
A. Okay.
9
Q. And you've had a chance to review this
10
document?
11
A. I have.
12
Q. What is this document?
13
A. It is an e-mail between myself and a few
14
others.
15
Q. And at the -- near the bottom of page 3,
16
do you see where it says,
17
18
19
A. I do see that.
20
Q. Is that referencing the addition of
21
to the CLEAR -- strike that.
22
Is that referencing the addition of
23
to CLEAR?
24
MS. MENALDO: Objection, foundation.
25
THE WITNESS: Yeah, I'm not sure what
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Justin is referring to with that sentence.
2
BY MR. FOX CAHN:
3
Q. All right. At the top of this e-mail, it
4
says, "The excitement and madness of March is
5
spreading off the basketball courts this month and
6
into the CLEAR product through new enhancements";
7
correct?
8
A. Correct.
9
Q. So this is an e-mail describing
10
enhancements to CLEAR; correct?
11
A. That appears to be the case, yes.
12
Q. So given that this is an e-mail about
13
enhancements to CLEAR, what do you take the phrase
14
"general lift in person entities from 550 million
15
records" to mean?
16
A. The wording of that particular sentence
17
does not make a whole lot of sense to me, so I'm
18
not sure what Justin is referring to.
19
Q. And two bullet points below it says,
20
"Huge lift of 190 million DL records"; correct?
21
A. Correct.
22
Q. DL records means driver's license
23
records?
24
A. That's correct.
25
Q. And so given that the sentence says,
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"Nationwide coverage for driver's licenses, huge
2
3
new driver's
4
license records for the CLEAR platform?
5
A. No, it is not.
6
Q. What does that mean then?
7
A. Well, the -- that portion of the e-mail
8
is
9
And we don't -- and
10
11
12
13
MS. MENALDO: Objection, foundation.
14
THE WITNESS: Yeah, again, I mean,
15
it's -- it's Justin's e-mail, but given my
16
familiarity with that, contents, that is what I
17
believe he's referring to.
18
BY MR. FOX CAHN:
19
Q. And would Justin be able to provide a
20
more complete answer?
21
A. I don't know, but it is his e-mail, so I
22
would hope so.
23
Q. I'm now marking Exhibit 13. It is a
24
two-page document with a Bates number at the bottom
25
of the first page ending in 60012. Do you see that
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Golkow Litigation Services
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A. Yes. It appears to be in the format of a
2
CLEAR person report without data.
3
Q. And is this what a report would look like
4
for an individual?
5
A. There are many ways that customers can
6
print or customize reports, but it does look like
7
the form of a report that a customer could -- could
8
format a report, yes.
9
Q. Does this report show every category of
10
content that might be available for an individual
11
before a customization?
12
A. Looking at the report section summary, it
13
looks to be comprehensive. And without doing a
14
data set by data set analysis, it looks
15
comprehensive to me.
16
Q. Are there categories that are
17
not -- strike that.
18
Are there categories of data that are
19
not available for all individuals?
20
A. Can you ask that question again? I'm not
21
sure that I understand.
22
Q. For the categories of data shown on this
23
report, are some of them only available for a
24
portion of the user -- strike that.
25
For the categories of data shown in
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this report, is there a portion of them that are
2
only available for a portion of the individuals
3
within CLEAR's various databases?
4
A. Assuming that a subject has a record that
5
fits into one of these categories, it should apply
6
to all users.
7
Q. Are any of these categories of data
8
unique to California?
9
A. I don't see any of these categories that
10
would be unique to California, but consistent with
11
my previous testimony, there are many that would
12
not contain any California data because we don't
13
get the corresponding data from California.
14
Q. How does the information in these reports
15
get into the CLEAR database?
16
A. When a vendor supplies us with a file,
17
again, based on previous testimony,
18
it enters into our systems,
19
gets processed, and goes into the CLEAR data
20
warehouse and will eventually make it into a CLEAR
21
report.
22
Q. And CLEAR pays for the information that
23
is entered into -- strike that.
24
And Thomson Reuters pays for the
25
information entered into a CLEAR report?
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that question.
2
Q. Well, has any vendor or prospective
3
vendor ever declined to enter into an agreement to
4
provide data for CLEAR based on privacy concerns?
5
A. Based on the fact that most of the
6
vendors or data partners that we work with or that
7
I identify have files that they intend to license
8
for regulated uses, I'm not sure that I have ever
9
encountered a vendor that has invoked privacy as a
10
reason for not licensing a file to us.
11
Q. Have you ever seen concerns from a vendor
12
or a prospective vendor that Thomson Reuters shares
13
information with law enforcement without a warrant?
14
MS. MENALDO: Objection, form.
15
16
17
18
19
20
21
22
23
24
25
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2
3
4
5
BY MR. FOX CAHN:
6
Q. I'm now marking Exhibit 16, which should
7
be available to you on the online platform. And it
8
is an e-mail with a Bates number ending in 80527 at
9
the bottom of the seventh page.
10
MS. MENALDO: Mr. Cahn, I've just
11
realized that we've been on the record for a little
12
over an hour. So maybe after this line of
13
questioning, we could take another short break.
14
MR. FOX CAHN: Sure thing.
15
THE WITNESS: Okay, I do see that
16
document.
17
BY MR. FOX CAHN:
18
Q. And do you recognize this document?
19
A. I do.
20
Q. What is it?
21
22
23
24
25
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Golkow Litigation Services
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A. Let me review it first.
2
Q. And Mr. Fox, I'll just be asking you one
3
question about the e-mail on page 7.
4
A. Hold on one second, still. Okay.
5
6
7
8
9
10
11
12
13
Q. Well, all resellers, or just those that
14
make it available to law enforcement without a
15
warrant?
16
A. My understanding with discussions with
17
Equifax is all resellers in the industry no longer
18
were able to receive the file.
19
Q. Has Equifax raised concerns about any
20
other data that is made available by CLEAR?
21
A. Not to me, no.
22
Q. Are you aware if they've raised those
23
concerns to anyone else at Thomson Reuters?
24
A. I am not.
25
MR. FOX CAHN: All right. Well, why
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Golkow Litigation Services
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1
given the data that's available in the underlying
2
records, he had an unrealistic expectation of how
3
the technology would be able to -- how the
4
technology would be able to make the proper match.
5
Q. Why was the expectation un -- strike
6
that.
7
Why was the expectation unreasonable?
8
A. Specifically with criminal records, there
9
is not always a lot of underlying data in the
10
record, which is why we instruct customers that
11
this is unverified and as is. And with certain
12
data, we expect them to carefully look at the data
13
themselves and verify it if necessary.
14
Q. So what would be a reasonable accuracy
15
expectation for this sort of data?
16
A. I think in this instance, the data was
17
the information that was provided by CLEAR was as
18
good as the underlying data and technology could
19
make it, and it's up to the customer to come to
20
their own conclusions in terms of matching or
21
associating data with underlying subjects.
22
Q. And can customers do that sort of
23
matching and analysis based only on CLEAR data?
24
A. Not necessarily, no. It sometimes
25
requires them to independently verify information
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Golkow Litigation Services
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from this document.
2
Does CLEAR contain information on the
3
elderly?
4
A. CLEAR contains information on consumers
5
of all ages, yes.
6
Q. And does it contain information on
7
disabled consumers?
8
A. CLEAR contains information on pretty much
9
all consumers, regardless of status.
10
Q. And since Thomson Reuters has data on
11
nearly all consumers as part of CLEAR, we
12
understand that there are some consumers who seek
13
to access their data; is that correct?
14
A. Per our privacy policy, consumers can
15
make a request of Thomson Reuters to see what data
16
Thomson Reuters has about them.
17
Q. And consumers can request that Thomson
18
Reuters correct information about them; correct?
19
A. Per the privacy laws in specific states,
20
that is correct.
21
Q. Is one of those states California?
22
A. To my belief, yes.
23
Q. I'm now introducing what is being marked
24
as Exhibit 24. It is a document with a Bates
25
number ending in 17559 at the bottom of the first
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Q. And what about the person warehouse?
2
A. Based on my knowledge, I don't make -- I
3
would not be able to make a distinction between the
4
two.
5
Q. And when you think of the people
6
available through Thomson Reuters' search
7
products -- strike that.
8
When you think of the people whose
9
information is available on CLEAR, that includes
10
people who have been arrested; correct?
11
A. The CLEAR product contains arrest
12
records, yes.
13
14
15
16
17
18
19
20
21
22
23
24
25
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2
3
4
5
Q. And as part of your evaluation of the
6
quality of a potential vendor as you described it
7
before, does that include its relationship with the
8
court to identify when an arrest has been expunged
9
or sealed?
10
A. The relationship between a vendor and the
11
source of the records is a factor in evaluating the
12
quality of the vendor.
13
Q. And do you know if you've ever
14
specifically evaluated a vendor's capacity to
15
update arrest records to reflect when they are
16
expunged or sealed as part of your evaluation of
17
that vendor?
18
A. The vendor that provides us with our
19
criminal and arrest content pre-dates my
20
involvement with evaluating vendors, so I don't
21
know, but that was a factor.
22
Q. And it's not something that you've
23
evaluated when thinking about future product
24
changes or enhancements?
25
A. It has -- the topic has come up from time
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A. Based on the search criteria --
2
Q. Correct.
3
A. -- state and zip code? I think that's
4
why I'm struggling with coming up with a name of a
5
person that would do that. But we do occasionally
6
get requests from data sources where they -- where
7
the source does want to know, for example, how many
8
motor vehicle registration records from the state
9
of Florida have been produced.
10
Q. And would you have copies of the
11
responses to those sorts of queries?
12
A. No.
13
Q. I'm going to now introduce Exhibit 26.
14
It is an e-mail thread with a Bates stamp ending in
15
40077 on the first page. Apologies, this -- strike
16
that. One moment.
17
Do you recognize this document that
18
was previously introduced under another exhibit
19
number as well?
20
A. Yes, I do recognize it.
21
22
23
A. Correct.
24
Q. And that's a way of identifying records
25
with specific individuals?
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MS. MENALDO: Objection, form.
2
3
4
5
BY MR. FOX CAHN:
6
Q. And going to the second e-mail on the
7
first page that was sent by you on June 25, 2015 at
8
2:27 p.m., it says, "He has" -- strike that.
9
It says, "He seems to have a very low
10
tolerance for even a close mismatch"; correct?
11
A. Correct.
12
Q. What do you consider a close mismatch?
13
A. In this context, I consider a close
14
mismatch as being a record that matches on a number
15
of data elements so as to receive a fairly, to me,
16
receive a very high confidence that it is a correct
17
match between the record and the individual, but,
18
even so, it is not a correct match between the
19
record and the individual.
20
Q. And you say that he has a low tolerance;
21
correct?
22
A. Correct.
23
Q. What do you mean by a low tolerance?
24
A. In this instance, my opinion is that this
25
particular user has an expectation that when a
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A. I am not aware of that either.
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
BY MR. FOX CAHN:
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Q. Do you know who might have a more
2
up-to-date version of a document like this?
3
A. I don't.
4
Q. Do you know what portion of revenue for
5
CLEAR comes from the United States?
6
A. In what context?
7
Q. What portion of revenue for CLEAR is
8
generated by searches for subjects located in the
9
United States?
10
A. I don't -- I don't have the knowledge to
11
answer that.
12
Q. Do you know what percentage of CLEAR
13
revenue is generated by searches related to
14
subjects located in the state of California?
15
A. I don't.
16
Q. Earlier you mentioned that the vast
17
majority of CLEAR records are on consumers in the
18
United States; correct?
19
A. That's correct.
20
Q. So is it true that the vast majority of
21
searches relate to consumers in the United States?
22
A. Based on my experience, that would be
23
correct, and also logical, yes.
24
Q. And do you have an estimation of how
25
searches break down between states within the
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1
2
3
4
I, ANITA KORNBURGER, Registered Professional
5
Reporter and Notary Public, do hereby certify
6
that the preceding deposition was recorded by
7
me and reduced to writing under my personal
8
direction.
9
I further certify that said deposition was
10
taken remotely, with all parties appearing by
11
videoconference, on May 16, 2022, commencing at
12
10:02 a.m. and concluding at 5:36 p.m.
13
I further certify that I am not a relative
14
or employee or attorney or counsel of any of
15
the parties, or a relative or employee of such
16
attorney or counsel, or financially interested
17
directly or indirectly in this action.
18
In witness whereof, I have hereunto set my
19
hand and affixed my seal of office, this 20th
20
day of May, 2022.
21
22
__________________________________
ANITA KORNBURGER, RPR - Notary
23
Commission #1166910800033
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My commission expires January 31, 2025.
25
Case 3:21-cv-01418-EMC Document 148-1 Filed 12/14/22 Page 47 of 49
June 17, 2022
Re:
Brooks et al. v. Thomson Reuters Corporation, USDC Northern District of
California - San Francisco Division Case No. 3:21-cv-01418-EMC: Defendant’s
Deposition Errata (Steven Fox Deposition Transcript dated May 16, 2022)
To whom it may concern:
I, Steven Fox, have reviewed the transcript of my deposition in Brooks et al. v. Thomson
Reuters Corporation, Case No. 3:21-cv-01418-EMC, taken on May 16, 2022. Attached hereto
is a list of errata identified in the deposition transcript.
/s/ Steven Fox______________
June 17, 2022
___
STEVEN FOX
DATE
Case 3:21-cv-01418-EMC Document 148-1 Filed 12/14/22 Page 48 of 49
Steven Fox Deposition Errata Sheet
Page:Line(s)
Existing Testimony
Corrected
Testimony
Reason
43:22
“...SCRA, DPPA,
GLB, HIPAA, et
cetera.”
“..FCRA, DPPA,
GLB, HIPAA, et
cetera.”
Transcription error
112:21
“Does not.”
“It does not.”
Transcription error
116:17
“…again, based on
previous testimony,
…”
“…again, based on
previous testimony,
…”
Transcription error
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