Court filing
Exhibit A-17 to Declaration of Susan Fahringer — Brooks v. Thomson Reuters Corporation (Dkt. 186-5, N.D. Cal. No. 3:21-cv-01418)
Filed March 28, 2023 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 | 2023-03-28 |
U.S. District Court for the Northern District of California · No. 3:21-cv-01418-EMC · Doc. 186-5 · 2023-03-28 · Docket on CourtListener
Full text
EXHIBIT A-17
REDACTED - PUBLICLY FILED VERSION OF DOC. 151-17
PURSUANT TO COURT ORDER,
DATED MARCH 21, 2023 (DOC. 178)
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UNITED STATES DISTRICT COURT
NORTHERN DISTRICT OF CALIFORNIA
SAN FRANCISCO DIVISION
CAT BROOKS and RASHEED SHABAZZ,
individually and on behalf of all others
similarly situated
v.
THOMSON REUTERS CORPORATION,
Defendant.
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Case No. 3:21-cv-1418-EMC
HIGHLY CONFIDENTIAL –
ATTORNEYS’ EYES ONLY
EXPERT REPORT OF DOUGLAS KIDDER
September 7, 2022
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Table of Contents
1
Scope of Work ........................................................................................................................ 3
2
Qualifications ......................................................................................................................... 3
3
Summary of Conclusions ...................................................................................................... 4
3.1
The Turow Report ............................................................................................................ 4
3.2
The Lloyd Report ............................................................................................................. 4
4
Background ............................................................................................................................ 6
4.1
CLEAR ............................................................................................................................. 7
4.2
Class Definition .............................................................................................................. 10
4.3
Economics of Information .............................................................................................. 10
4.4
Unjust Enrichment Relief ............................................................................................... 12
5
Discussion of the Turow Report ......................................................................................... 13
5.1
Summary of the Turow Report....................................................................................... 13
5.2
Discussion of the Turow Report as it Relates to Damages ............................................ 15
5.3
The Lloyd Report Is Unrelated to the Turow Report ..................................................... 16
6
Discussion of the Lloyd Report........................................................................................... 17
6.1
Overview of the Lloyd Report ....................................................................................... 17
6.2
Mr. Lloyd Has Not Measured Unjust Enrichment ......................................................... 19
6.3
Calculation Errors .......................................................................................................... 21
6.3.1
Unreliable Profit Margin ......................................................................................... 22
6.3.1.1 Mr. Lloyd Has Not Calculated Net Profits as Described in the Restatement ..... 22
6.3.1.2 Mr. Lloyd Has Not Calculated Gross or Incremental Profits .............................. 25
6.3.1.3 Mr. Lloyd’s
Cost Estimate Does Not Include All Attributable Costs .......... 28
6.3.1.4 Mr. Lloyd Does Not Deduct Costs for California Data ...................................... 29
6.3.1.5 Summary of Unreliable Profit Margin ................................................................ 31
6.3.2
Estimates for California are Unreliable .................................................................. 31
6.3.3
Estimates for Business Data Are Unreliable ........................................................... 34
6.4
Mr. Lloyd Has No Methodology to Allocate Damages to Class Members ................... 35
7
Signature Page ..................................................................................................................... 38
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1
SCOPE OF WORK
1.
I have been retained by counsel for Thomson Reuters Corporation (“Thomson
Reuters”) to review and reply to two expert reports filed on behalf of Cat Brooks, Rasheed
Shabazz and the proposed class (“Plaintiffs”) in this matter. The first report was submitted by
Professor Joseph Turow on June 1, 20221 (the “Turow Report.”) I have not been asked to
comment on all aspects of the Turow Report – only those aspects that relate to damages. The
second report was submitted by Terry Lloyd on behalf of the Finance Scholars Group, Inc. on
June 1, 20222 (the “Lloyd Report”) and I have been asked to comment on it in its entirety.
2.
The opinions contained in my report are based on the opinions, information and
data available to me as of the date of service of this report. If additional data, opinions, or
information become available, I reserve the right to modify or change the opinions expressed in
this report based on any such data, opinions, or information.
2
QUALIFICATIONS
3.
My name is Douglas Kidder. I am a Managing Partner with OSKR, LLC, a firm
that provides expert services primarily in the area of damages calculations. I was also an
Adjunct Professor at Golden Gate University teaching a graduate course on damages in the
school of accounting. I am also a member of the Licensing Executives Society, a former
Director of i-cap Partners – a venture capital fund investing in technology companies – and a
former member of the Trade New Zealand advisory board – a group formed to review New
Zealand-based startups for support entering the U.S. market.
4.
I have been performing business analyses and valuations for over thirty years, as a
consultant, business owner, board member and manager. My focus is on the economics of
knowledge and information generally typically in connection with damages associated with
patents, copyrights, trade secrets and trademarks. I have published and spoken on business and
valuation issues and have co-authored seven published articles relating to intellectual property
damages. I have been retained to render expert opinions in the context of litigation, to assist in
licensing and evaluation of intellectual property that is not subject to litigation and to develop
and refine business strategies.
1
On July 25, 2022, I received an updated version of this report that was also dated June 1, 2022.
2
On July 25, 2022, I received an updated version of this report that was also dated June 1, 2022.
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5.
I hold a B.A. in Mathematics and English with Honors from Amherst College
(1983) and a Master of Science from the University of California at Berkeley (1986). While at
Berkeley, I was a lecturer in the Computer Science department.
6.
A copy of my resume is attached as Exhibit 1. A list of documents reviewed in
connection with this Report is attached as Exhibit 2. I am being compensated at an hourly rate
of $650 per hour, plus reimbursement of expenses. I have been assisted in this matter by OSKR
staff, working under my supervision and control. I have no financial interest in the outcome of
this matter.
3
SUMMARY OF CONCLUSIONS
3.1
THE TUROW REPORT
7.
Professor Turow states that CLEAR causes class members to “lose the value of the
information.”3 He presents no methodology in support of this theory. His conclusion that the
mere existence of CLEAR causes a loss in value of the information accessible through CLEAR
is contrary to the economics of information. One of the defining characteristics of information is
that, by giving or selling someone my personal information, I do not lose the use of that
information for myself. Based on generally accepted principles in the fields of economics, there
is no sense in which Californians have “lost” the value of that information simply because that
information is accessible via CLEAR.
8.
Professor Turow does not offer any methodology that might assist him or the Court
to determine the “lost” value of any information as a result of CLEAR.
9.
There is no nexus between Professor Turow’s report and Mr. Lloyd’s opinion. As a
result, Professor Turow’s opinion is irrelevant to the Lloyd Report.
3.2
THE LLOYD REPORT
10. The Lloyd Report purports to calculate the profit (which he calls, inaccurately, “net
profit”) attributable to “using and selling” Californians’ data through CLEAR. Mr. Lloyd’s
approach is unscientific and without basis. The Lloyd Report does not offer any methodology to
determine what portion of Thomson Reuters’ revenues from CLEAR are attributable to the
3
Turow Report, p. 19.
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wrongful or “unjust” conduct alleged in this case. Instead, the Lloyd Report assumes that all
income received in connection with CLEAR is attributable to “using and selling” personal
information accessible in CLEAR. At least some profits from CLEAR are driven by
functionalities of CLEAR other than the data it makes accessible. Mr. Lloyd’s approach does not
ascribe any revenues or profits to these other functionalities. For example, as discussed in
Section 6.3.1.4, below, CLEAR revenues depend at least in part on product functionality in
contrast to data. CLEAR has an understandable user interface, is designed to not display wholly
irrelevant information and provides access to data other than data on individuals. These
functionalities have value and are responsible for at least some portion of Thomson Reuters’
revenues from CLEAR. Yet Mr. Lloyd does not take them into account. The Lloyd Report treats
all revenues from CLEAR as entirely resulting from the availability of data and it does not
separate Thomson Reuters’ revenues derived from collecting or providing access to data from
revenues derived from other CLEAR functionality. Mr. Lloyd, therefore, offers no reliable
methodology to determine profits that result from the allegedly unjust conduct in this case.
11.
Further, I understand that the two claims remaining in this case are for unjust
enrichment and unfair competition, and that both of these claims require balancing the benefit or
utility of the conduct targeted in this case against the harm it allegedly causes. But the Lloyd
Report does not purport to measure, evaluate, calculate, or even consider any benefits or utility
of CLEAR.
12. The Lloyd Report also includes several critical methodological errors. For example,
I understand that unjust enrichment must be calculated as net profits, yet Mr. Lloyd calculates an
amount he characterizes as total incremental profits or gross profits. Nor does Mr. Lloyd deduct
many costs, including royalties, that are clearly related to collecting and providing access to data
on Californians and would be properly deducted when calculating either incremental or gross
profits.
13. As another example of a critical methodological error, Mr. Lloyd’s calculation of
the proportion of revenue attributable to Californian’s data is unreliable. He attributes
of
Thomson Reuters’ “net profits” to California based on (a) California’s share of United States
economic activity (GDP) in 2021, and (b) the 2018 California arrest rate. Mr. Lloyd does not
offer any basis for his assumption that there is a direct relationship between California’s share of
United States economic activity, or the California arrest rate to CLEAR’s revenues. Determining
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the portion of CLEAR revenue that results from the availability of data about Californians,
requires analyzing the how many searches are actually tied to data about Californians. Mr.
Lloyd has only vaguely asserted that GDP and arrest rates are related to some of the possible
searches performed on CLEAR.
14. Finally, Mr. Lloyd presents no opinion on how his proposed unjust enrichment
figure should or could be apportioned among class members. There is simply no connection
between his proposed unjust enrichment figure and the profits made by Thomson Reuters from
data associated with any individual class member. Because not all class members will have had
information about them displayed as a result of a search, the degree to which Thomson Reuters
has been purportedly unjustly enriched by a particular class member will vary depending on at
least: the information available about the individual, whether a search displayed any information
about the individual, and the pricing plan of the customer doing the search. All of these
variables may affect whether income received by Thomson Reuters from a particular customer is
in fact attributable to data relating to any Californian, much less a particular Class member. Yet
the Lloyd Report ignores all of these differences. To be clear, my criticism is not just that Mr.
Lloyd’s proposed methodology would require individualized inquiry; it is that Mr. Lloyd has not
proposed any methodology for apportioning disgorged profits to class members, nor do I believe
that any feasible methodology exists.
4
BACKGROUND
15. On December 3, 2020, Cat Brooks and Rasheed Shabazz filed a class action
complaint against Thomson Reuters Corporation alleging that Thomson Reuters’ CLEAR:
• Violated the common law right to publicity/misappropriation of likeness
• Violated the California Unfair competition law, §17200 (Monetary and
public injunctive relief)
• Unjustly enriched Thomson Reuters4
16. On August 16, 2021, the Court dismissed Plaintiffs’ right to publicity claim and
also limited their relief under California’s unfair competition law to injunctive relief.5 I
4
Complaint at, e.g., pp. 16–20.
5
Order Granting In Part and Denying in Part Defendant’s Motion to Dismiss, August 16, 2021.
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understand that the sole remaining claim for monetary relief in the case is based on a theory of
unjust enrichment.
4.1
CLEAR
17. Thomson Reuters describes CLEAR as follows:
Thomson Reuters CLEAR® is powered by billions of data points and leverages
cutting-edge public records technology to bring all key content together in a
customizable dashboard. Locate hard-to-find information and quickly identify
potential concerns associated with people and businesses to determine if further
analysis is needed. The user-friendly platform was designed with intuitive
navigation and simple filtering parameters, so you can quickly search across
thousands of data sets and get accurate results in less time.6
18. Thomson Reuters specifically notes that CLEAR is not providing consumer reports:
Thomson Reuters is not a consumer reporting agency and none of its services or
the data contained therein constitute a ‘consumer report’ as such term is defined in
the Federal Fair Credit Reporting Act (FCRA), 15 U.S.C. sec. 1681 et seq. The data
provided to you may not be used as a factor in consumer debt collection
decisioning, establishing a consumer’s eligibility for credit, insurance,
employment, government benefits, or housing, or for any other purpose authorized
under the FCRA. By accessing one of our services, you agree not to use the service
or data for any purpose authorized under the FCRA or in relation to taking an
adverse action relating to a consumer application. 7
19. All of the data available through CLEAR is from third party sources and databases.8
Data that is restricted (e.g. DMV records) are only available to entities that are authorized to
view such data under applicable law (e.g. the Driver’s Privacy Protection Act). Every customer
must certify to Thomson Reuters that CLEAR is being used for a permissible purpose.9
20. Use cases for CLEAR vary widely but generally are focused on the detection,
investigation, and prevention of fraud. They include, for example, criminal investigations, anti-
6
https://legal.thomsonreuters.com/en/products/clear-investigation-software.
7
https://legal.thomsonreuters.com/en/products/clear-investigation-software.
8
Thomson Reuters Responses to Plaintiffs First Set of Interrogatories, Attachment A, April 4, 2022.
9
Thomson Reuters Responses to Plaintiffs First Set of Interrogatories, Attachment A, April 4, 2022.
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money laundering activities, insurance fraud investigations, and unemployment insurance
investigations. Thomson Reuters describes some of these uses in case studies, including:
• Helping courts, banks, and other public and private entities perform
Know Your Customer (“KYC”) diligence and combat fraud;
• Helping law enforcement find missing persons and kidnapped children;
• Supporting law enforcement officers with solving crimes, including, for
example, investigating cold murder cases, combating drug trafficking,
combating human trafficking, dismantling child exploitation groups, and
identifying criminal perpetrators;
• Supporting public defenders, including in exoneration attempts for
wrongful convictions;
• Investigating, identifying, and combating fraud, including financial
fraud, identity theft, and fraud in various government benefits programs;
• Supporting regulatory compliance programs, including compliance with
the Bank Secrecy Act and its Anti-Money Laundering regulations;
• Combating tax evasion, including Social Security and property tax
fraud;
• Providing support for people in need, including finding relatives to keep
children out of the welfare system, and finding absentee parents who
owe child support;
• Responding to active shooter situations, such as the December 2015 San
Bernadino terrorist attack;
• Helping the US Veterans Affairs Department locate veterans to continue
providing them with benefits after moving;
• Identifying updated address information to provide adequate notice of a
class action to class members;
• Supporting corporate security needs to keep public and private locations
safe; and
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• Helping law enforcement recover stolen goods. 10
21.
.11 The top ten customers of CLEAR are shown
in the table below along with their revenue from December 2020 to February 2021:
12
22. The majority of CLEAR revenues come from recurring revenue – also described as
subscription plans. Under a typical CLEAR subscription plan, a customer signs a contract and
pays a monthly amount that allows for a certain number of searches. If the customer exceeds the
number of searches for their subscription plan, they will be charged an additional amount.
Between 2017 and 2021, the percent of revenue from subscription plans was between
and
with the remaining revenue described as “transactional.”13
10 Thomson Reuters Responses to Plaintiffs First Set of Interrogatories, Attachment A, April 4, 2022.
11 TR-BROOKS047405. See also TR-BROOKS127541.
12 TR-BROOKS127541, tab “Trans by Cust by Sub”.
13 Thomson Reuters First Supplemental Answers to Plaintiffs First Set of Interrogatories, May 24, 2022.
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23. CLEAR is not a separate business unit within Thomson Reuters. It is treated as a
product that is sold alongside other Thomson Reuters products by customer-focused business
segments including Legal Professionals, Corporates, and Tax & Accounting.14 Thus, while
CLEAR’s revenues are tracked by Thomson Reuters’ accounting system, all of the expenses
incurred to support CLEAR are not separately identified in the accounting system.15
4.2
CLASS DEFINITION
24. The complaint defines the proposed class as follows:
All persons residing in the state of California whose name, photographs, personal
identifying information, or other personal data is or was included in the CLEAR
database during the limitations period.
The proposed class definition excludes any officers and directors of Thomson
Reuters; Class Counsel; and the judicial officer(s) presiding over this action and the
members of his/her immediate family and judicial staff.16
25. Note that the class is defined by residency in California while the data accessed via
CLEAR about that person is not limited to California as it can include information from when
the individual resided in other states or other countries. On a personal level, my information
would include data from periods when I resided in Massachusetts, Maryland and Illinois – and
might include information from the six months I spent on an extended assignment in Hong Kong.
4.3
ECONOMICS OF INFORMATION
26. The economics of information – of which personal data is one type – differ from the
economics of physical goods. As a starting point, information has the characteristic of being
non-rivalrous for consumption whereby we can both use the same information at the same time
without affecting the value of the information.17 For example, if I tell you my name, address and
phone number I am not deprived of the use of my name, address or phone number. In contrast,
14 TR-BROOKS014840–038 at 847–849 (Thomson Reuters Annual Report 2020, pp. 6 – 8).
15 Conversations with Irene Caratto and Kelly Shelton, July 20, 2022.
16 Complaint, ¶¶70 - 71.
17 See, e.g., Jones, Charles I., and Christopher Tonetti. 2020. "Nonrivalry and the Economics of Data." American
Economic Review, 110 (9): 2819-58.
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physical goods have rivalrous consumption. If I am using a hammer, you cannot also be using
that hammer.
27. There is also a time-based component to information that is neatly encapsulated by
the phrase “yesterday’s news.” Today’s news can be valuable and interesting, but yesterday’s
news – which was valuable and interesting yesterday – is no longer as valuable and interesting.18
This is unlike the hammer example; to this day I use my grandfather’s hammer, but I don’t have
much interest in what was news to him.
28. Information is also only valuable to the extent that it is used and acted upon. There
is no value to my listening to a weather forecast indicating rain if I do not alter my behavior
based on that forecast. Information can reduce uncertainty about the future, and thereby affect
future actions.19
29. Another important characteristic of information is that the reproduction cost for
digital information is close to zero. The economists Carl Shapiro and Hal Varian wrote a
seminal book – Information Rules – in 1999 discussing the economics of information. Below I
have excerpted parts of the first chapter that I believe are germane to this case:
Information is costly to produce but cheap to reproduce. Books that cost hundreds
of thousands of dollars to produce can be printed and bound for a dollar or two and
100-million dollar movies can be copied on videotape for a few cents.
Economists say that the production of an information good involves high fixed
costs but low marginal costs. The cost of producing the first copy of an information
good may be substantial, but the cost of producing (or reproducing) additional
copies is negligible. This sort of cost structure has many implications. For
example, cost-based pricing makes no sense when unit cost is zero. You must price
your information goods according to consumer value, not according to your
production cost.
Since people have widely different values for a particular piece of information,
value-based pricing leads naturally to differential pricing. …
…
Economists say that a good is an experience good if consumers must experience it
to value it. Virtually any new product is an experience good, and marketers have
18 See, e.g. Avinash Dixit and Robert Pindyck, Investment Under Uncertainty, 1994, Princeton University Press.
19 See, e.g. Avinash Dixit and Robert Pindyck, Investment Under Uncertainty, 1994, Princeton University Press.
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developed strategies such as free samples, promotional pricing, and testimonials to
help consumers learn about new goods.
But information is an experience good every time it’s consumed. How do you know
whether today’s Wall Street Journal is worth 75 cents until you’ve read it? Answer:
you don’t.
…
The brand name of the Wall Street Journal is one of its chief assets and the Journal
invests heavily in building a reputation for accuracy, timeliness and relevance.
…
Now that information is available so quickly, so ubiquitously, and so inexpensively,
it is not surprising that everyone is complaining of information overload. Nobel
prize-winning economist Herbert Simon spoke for us all when he said that “a wealth
of information creates a poverty of attention.”
Nowadays, the problem is not information access but information overload. The
real value produced by an information provider comes in locating, filtering and
communicating what is useful to the consumer.20
30. All of the information accessed via CLEAR is obtained from other sources.21 Thus,
CLEAR offers its customers a tool to be used to reduce search costs for information. As Shapiro
and Varian point out, the real value that CLEAR offers is derived from CLEAR’s effectiveness
in locating, filtering and communicating the information that is most useful to CLEAR
customers.
4.4
UNJUST ENRICHMENT RELIEF
31. As described in the Restatement (Third) of Restitution and Unjust Enrichment § 51
(2011) (“Restatement”), also cited by Mr. Lloyd, it is my understanding that, when calculating
unjust enrichment, care must be taken to separate profits generated by the underlying wrong
from profits generated by lawful actions:
20 Shapiro, C., Varian, H., Information Rules: A Strategic Guide to the Network Economy, 1999, Harvard Business
School Press, pp. 3-6. Emphasis in the original.
21 TR-BROOKS144207 – 10 at 07.
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The profit for which the wrongdoer is liable by the rule of § 51(4) is the net increase
in the assets of the wrongdoer, to the extent that this increase is attributable to the
underlying wrong.
…
Calculation of profits is simplest when the whole of the wrongdoer's unjust
enrichment is captured in the ownership, possession, or disposition of specific
property. … Elsewhere the application of the disgorgement remedy turns on
problems of attribution, as the court attempts to decide what portion of the
defendant's assets or income is properly attributable to the underlying wrong to the
claimant.22
32. This understanding informs my opinion as to the proper measure of unjust
enrichment, but I am not offering a legal opinion.
5
DISCUSSION OF THE TUROW REPORT
33. In the following section, I first provide an overview of the Turow Report as it
relates to recovery under a theory of unjust enrichment (I will refer to this monetary relief as
“damages”). Then I provide a discussion of the implications of his opinions for calculation of
unjust enrichment in this matter.
5.1
SUMMARY OF THE TUROW REPORT
34. Professor Turow states that the purpose of his report is to:
… assist the Court in evaluating, at this stage of the case, whether Thomson
Reuters’ operation of the CLEAR product affects a privacy interest of Californians
in such a way that all Californians whose information is accessible through CLEAR
could claim to be harmed in the same way. [And] … to offer a method for
understanding how the accumulation, connection, and sale of individual
information through online databases without robust opportunities for individuals
to control, correct, opt-out, or contextualize the information in those databases,
violates long-held conceptions of individual privacy and causes cognizable
economic harm.23
22 Restatement (Third) of Restitution and Unjust Enrichment § 51 (2011). Emphasis added.
23 Turow Report, p. 4.
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35. Professor Turow’s report defines the class in this case as “individuals – California
residents – whose information is available in CLEAR.”24 Throughout his report, he appears to
abbreviate this definition as “all Californians.”25
36. Professor Turow concludes that:
Thomson Reuters’ operation of the CLEAR product affects privacy interests of
Californians – the right to control personal information and to be let alone – in such
a way that all Californians whose information is accessible through CLEAR are
harmed. … Thomson Reuters’ practice of aggregating disparate sources of
information, interconnecting that information into dossiers, and selling it for profit
without the consent, input, or, in most cases, even the knowledge of those profiled
also causes those individuals whose information is aggregated and made available
by Thomson Reuters to lose the value of the information itself, which they would
retain and have the option to capture in the absence of such practices.26
37. Professor Turow opines that the privacy harm is the lack of control and the
violation of the right to be let alone:
While the specific content of individual reports may vary, every Californian whose
information is accessible through CLEAR has suffered the same fundamental
privacy harm of a lack of control and violation of their right to be let alone.27
38. Professor Turow opines that the resulting economic harm to Californians from the
alleged privacy harms is the diminished value of their information:
By taking disaggregated sources of information, compiling dossiers, and selling
those dossiers for profit (without giving Californians the opportunity to control or
profit from that practice), Californians lose the value the information would have
retained, value they could have chosen to capture themselves.28
24 Turow Report, pp. 9 – 10. Following the complaint which defines the class as “All persons residing in the state
of California whose name, photographs, personal identifying information, or other personal data is or was
included in the CLEAR database during the limitations period.” Complaint, ¶70.
25 See, e.g., Turow Report, pp. 4, 5, 13, 16.
26 Turow Report, pp. 5-6.
27 Turow Report, p. 13.
28 Turow Report, p. 19.
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39. Thus, as it relates to damages, Professor Turow’s opinion is that the underlying
harm arises from Californians’ alleged inability to control the information about them, thereby
diminishing the value of that information to the individual.
5.2
DISCUSSION OF THE TUROW REPORT AS IT RELATES TO DAMAGES
40. Professor Turow’s opinion that “individuals …lose the value of the information
itself which they would retain”29 is without basis and unscientific. First, Professor Turow does
not support this opinion with empirical evidence. Professor Turow has not identified any way in
which this value might be realized by the individual or quantified by how much that value was
reduced.30 Second, this opinion is contrary to the economics of information described in Section
4.3 above. Because information is a non-rivalrous good, sharing information with another person
does not prevent the first person from also using the information. There is no sense in which the
Plaintiffs or proposed class members have lost the value of the information about them that is
available through CLEAR.
41. Further, as discussed above at paragraph 14, the attribution of income received from
Thomson Reuters in connection with CLEAR, whether that income is attributable to data about
any Californian, will depend on many variables. Professor Turow does not propose any
methodology that could be used to apportion damages among proposed class members. As he
stated in his deposition:
THE WITNESS: It -- earlier, I said that I'm not quantifying the -- the amount of
harm that Californians have. We didn't talk about valuation of privacy. 31
…
Beyond the idea that many, many people suffer the harm, virtually all Californians,
I haven't quantified the amount of harm per person. No, that was not part of my
mandate.32
29 Turow Report, p. 5.
30 Deposition of Joseph Turow, August 26, 2022 at 106:21 – 107:4, 128:10 – 13.
“Relatedly, do you have any background or specialized training in quantifying the amount of damage or harm
experienced by any person or persons?
A. That's not -- that's not what I was asked to do in this case.”
“THE WITNESS: It -- earlier, I said that I'm not quantifying the -- the amount of harm that Californians have.
We didn't talk about valuation of privacy.”
31 Deposition of Joseph Turow, August 26, 2022 at 128:10 - 13.
32 Deposition of Joseph Turow, August 26, 2022 at 187:16 – 19.
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5.3
THE LLOYD REPORT IS UNRELATED TO THE TUROW REPORT
42. Mr. Lloyd’s calculations do not follow from Professor Turow’s opinion on harm to
the proposed class. The only input from the Turow Report to the Lloyd Report is an
understanding of the CLEAR product.33 As stated by Mr. Lloyd in his deposition:
Q How does your report relate to this report from Professor Turow?
A This report provides some context that addresses the issues that you and I
discussed a few minutes ago. It's contextual for me. We were assigned to do
different things. But I found it informative at least as it relates to the case and data
and privacy and those issues.
…
Q Mr. Lloyd, my question is, did you attempt to calculate the loss of value of
information that Californians did not retain as a result of CLEAR?
A That was not my assignment.
…
Q In your own work in this case, did you ever attempt to calculate any diminished
value theory of damages?
A No. We were engaged to calculate unjust enrichment, or the benefit allegedly
derived by the defendant and not the loss suffered by the plaintiff.34
43. Additionally, Professor Turow and Mr. Lloyd never spoke to each other, and
Professor Turow was unaware that Mr. Lloyd had issued a report.35
44. Thus, there is no causal link between the harm alleged by Plaintiffs according to the
Turow Report and the calculation performed by Mr. Lloyd.
33 Lloyd Report, p. 5, footnote 14.
34 Deposition of Terry Lloyd, August 22, 2022 at 262:4 – 11, 264:17 – 20, 265:15 - 20.
35 Deposition of Terry Lloyd, August 22, 2022 at 269:18 - 20.
“Q Have you had any conversations with Professor Turow?
A No, sir, I have not.”
Deposition of Joseph Turow, August 26, 2022 at 357:7 – 21.
“Q. Okay. The -- and, again, for clarity, have you read the report of another expert that's been engaged by the
Plaintiffs in this case, FSG, Finance Scholars Group is the name of that company, and the person, I believe, who
created that report is a fellow named Lloyd. Did you review the other report that's been offered in this case by
Plaintiffs?
A. No. No, I did not.
Q. Okay. Do you have any understanding of what that report says?
A. I didn't even know about that report's existence --
Q. Okay.
A. -- you know, so...”
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6
DISCUSSION OF THE LLOYD REPORT
45. Mr. Lloyd’s opinion on what he calls “net profits” attributable to CLEAR’s
inclusion of data about “Californians” is flawed and unreliable for at least three reasons. First,
Mr. Lloyd has not measured unjust enrichment to Thomson Reuters – at best he has measured all
of Thomson Reuters profits from CLEAR (attributed to California) whether or not those profits
result from the allegedly unjust conduct in this case. Second, Mr. Lloyd’s estimate of profits
from CLEAR attributable to Californians is inflated, methodologically flawed and unreliable.
Finally, Mr. Lloyd does not address a critical question of how the court might go about allocating
any unjust enrichment to each proposed class member.
46. In the following section, I first provide an overview of the Lloyd Report and then
discuss flaws in Mr. Lloyd’s opinions.
6.1
OVERVIEW OF THE LLOYD REPORT
47. Mr. Lloyd understands the class to be composed of “California residents.”36
48. Mr. Lloyd states that the purpose of his report was to calculate Thomson Reuters’
profits from CLEAR attributable to the presence of data on California residents:
On behalf of FSG, I have been asked to evaluate the feasibility of calculating the
total net profits that Thomson Reuters has derived since December 3, 2017, in
connection with making information about California residents available through
CLEAR.37
49. He concludes that it is feasible to calculate Thomson Reuters’ net profits
attributable to “using and selling Californians’ data through CLEAR”:
I have concluded that it is possible to calculate Thomson Reuters’s net profits
attributable to using and selling Californians’ data through CLEAR. Based on
publicly available information and discovery produced to date, I have structured a
calculation, consistent with standard methodology, for determining these net profits
dating back to December 2017, which shows total net profits of approximately
as of the end of 2021.38
36 Lloyd Report, p. 1.
37 Lloyd Report, p. 1.
38 Lloyd Report, p. 1.
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50. Mr. Lloyd explicitly does not calculate net profits. He claims to calculate
Thomson Reuters’ gross or incremental profits:
Throughout this report, I use the term “net profit” to describe what Plaintiffs seek
to calculate for purposes of their unjust enrichment claim. I use that language
because it is the term used in the cases and Restatement section that I cite in footnote
number four above. However, the measure of profitability called “net profit” by the
Restatement and other authorities is what an accountant or financial analyst would
more likely call “gross margin,” “gross profit,” or “incremental profit.”39
51. As a starting point, “gross profit” and “incremental profit” are two different
concepts as Mr. Lloyd acknowledges.40 Further, Mr. Lloyd calculates neither gross profit nor
incremental profit as I discuss in Section 6.3.1. Throughout my report I will refer to his
calculation as providing an estimate of “incremental profits” because he only deducts what he
views to be incremental costs.41 Mr. Lloyd calculates this “incremental profit” through the
following methodology:
Table 2: Lloyd Calculation42
Total Worldwide CLEAR Revenue, December 2017 – 2021
Percent of CLEAR Revenue from the U.S.
Percent of Revenue Attributable to California
Percent of Database Attributable to Individuals (not businesses)
Profit Margin
TR CA Profits on CLEAR
39 Lloyd Report, pp. 7 – 8.
40 Lloyd Report, p. 8, footnote 28. I disagree with Mr. Lloyd’s assertion that gross profit and incremental profit
are equivalent in this case.
41 Lloyd Report, p. 9.
42 Lloyd Report, Exhibit 1.
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52. Mr. Lloyd’s critical estimate that
of CLEAR’s U.S. revenue is attributable to
California is calculated as the average of two other figures:43
• California’s share of U.S. economic activity at
• California’s arrest rate at
.
53. Mr. Lloyd cites, but does not incorporate into his calculation, California’s share of
the U.S. population at 11.8%.44
6.2
MR. LLOYD HAS NOT MEASURED UNJUST ENRICHMENT
54. The Lloyd Report claims to estimate “Thomson Reuters’ net profits attributable to
using and selling Californians’ data through CLEAR.”45 As Mr. Lloyd describes it, the correct
measure of unjust enrichment is a calculation of “profits … attributable to the alleged
misconduct” or, as he states in his report:
Plaintiffs allege that Thomson Reuters’s conduct in operating CLEAR violates a
California statute known as the Unfair Competition Law and also that it has led to
Thomson Reuters’s unjust enrichment from monetizing the Plaintiffs’ personal
data. I am informed that California law generally allows plaintiffs to recover the
net profits of the defendant that are attributable to the alleged misconduct.46
55. Mr. Lloyd’s calculation is not a measure of unjust enrichment, it is simply his
estimate of all of Thomson Reuters’ profits from CLEAR that he has attributed to California
based on the California arrest rate and California’s share of U.S. GDP. Mr. Lloyd’s approach
does not distinguish between profits that are attributable to the alleged misconduct and profits
that are attributable to other actions or investments.
56. Mr. Lloyd defines the underlying wrong in this matter as “[t]he aggregation and
compilation and distribution of personal data of Californians for profit by Thomson Reuters.”47
Yet he makes no attempt to attribute the profits he calculates to that wrong. Mr. Lloyd does not
explain whether or why he believes all of CLEAR’s profits that he attributes to Californians’
data to be attributable to the “aggregation and compilation and distribution of personal data of
43 Lloyd Report, p. 13.
44 Lloyd Report, p. 12.
45 Lloyd Report, p. 1.
46 Lloyd Report, p. 2. Emphasis added.
47 Deposition of Terry Lloyd, August 22, 2022 at 269:2 – 4.
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Californians for profit,” as opposed to, for example, the functionality of CLEAR or data
regarding people who are not California residents.
57. CLEAR’s customers are not just paying for access to the data via CLEAR. They
are also paying for sophisticated search engine functionality, potentially access to other
databases (such as news databases whose value is only incidentally related to individual
information) and potentially access to customizable risk scoring. Therefore, only some of the
revenue and profits from CLEAR are attributable to what Mr. Lloyd describes as CLEAR’s
“aggregation and compilation and distribution of personal data of Californians for profit.”
58. As an example of additional functionality, the plans offered to Law Enforcement
entities include functionalities such as web searching and articles from the Thomson Reuters
newsroom that are unrelated to data on Californians. 48 Law Enforcement entities are provided
with the options of CLEAR for Law Enforcement (basic plan) and CLEAR for Law Enforcement
Plus (premium plan). 49 The descriptions of both plans note that “Price varies by plan features”
so there are likely a wide variety of plans in use. The basic plan includes the ability to “View a
full list of your subject’s web results” while the premium plan includes the ability to “View
public and proprietary articles from Reuters newsroom.” 50 Thus, at least some portion of the
payments by Law Enforcement professionals are attributable to CLEAR functionality and
Thomson Reuters’ own property, yet Mr. Lloyd’s methodology does not take this into account in
any way.
59. The CLEAR subscription plans targeted to corporations and government agencies
offer a similar range of functionalities, which increase as the price paid by the customer
increases. In other words, the price paid by these customers is driven not by the data accessible
through CLEAR, but by the platform’s functionality. For example, CLEAR contains
functionality that determines an individual’s “associates” and any businesses to which they are
connected.51 This functionality, while it includes some personal information, is also the result of
analyzing and synthesizing that information and is of separate value from the underlying data.52
48 https://legal.thomsonreuters.com/en/products/clear-investigation-software/plans-pricing#publicsafety.
49 https://legal.thomsonreuters.com/en/products/clear-investigation-software/plans-pricing#publicsafety.
50 https://legal.thomsonreuters.com/en/products/clear-investigation-software/plans-pricing#publicsafety.
51 https://legal.thomsonreuters.com/en/products/clear-investigation-software/plans-pricing#corporate.
52 Shapiro, C., Varian, H., Information Rules: A Strategic Guide to the Network Economy, 1999, Harvard Business
School Press, p. 6.
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Lloyd’s estimate that
of revenues are attributable to individuals as opposed to businesses
appears to rely on a subjective classification by one of Plaintiffs’ attorneys.
6.3.1 UNRELIABLE PROFIT MARGIN
66. Mr. Lloyd's estimated incremental profit margin of
is flawed for at least three
reasons. First, Mr. Lloyd did not calculate net profits, which his own sources declare to be the
proper measure for disgorgement in unjust enrichment cases. Instead, Mr. Lloyd calculated what
he describes as incremental or gross profit. Second, Mr. Lloyd did not calculate incremental
profits correctly. He starts with allocated CLEAR revenues but deducts incremental CLEAR
costs to produce a profit margin that is neither incremental nor gross profits. Third, Mr. Lloyd
omitted multiple costs that should have been deducted even from a gross or incremental profit
calculation.
6.3.1.1 Mr. Lloyd Has Not Calculated Net Profits as Described in the Restatement
67. Mr. Lloyd states his belief that the correct measure of unjust enrichment is “gross
profit” even though the term “net profits” is used in the Restatement. As Mr. Lloyd states in his
report:
Throughout this report, I use the term “net profit” to describe what Plaintiffs seek
to calculate for purposes of their unjust enrichment claim. I use that language
because it is the term used in the cases and Restatement section that I cite in footnote
number four above. However, the measure of profitability called “net profit” by the
Restatement and other authorities is what an accountant or financial analyst would
more likely call “gross margin,” “gross profit,” or “incremental profit.” 54
68. I note that Mr. Lloyd does not support his opinion by citing any particular part of
the Restatement; he simply asserts that the Restatement did not use the right language.
69. I do not agree that the Restatement did not use the right language. The term “net
profits” is initially described in the Restatement as:
(5) In determining net profit the court may apply such tests of causation and
remoteness, may make such apportionments, may recognize such credits or
deductions, and may assign such evidentiary burdens, as reason and fairness dictate,
consistent with the object of restitution as specified in subsection (4). The following
rules apply unless modified to meet the circumstances of a particular case:
54 Lloyd Report, pp. 7 – 8.
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(a) Profit includes any form of use value, proceeds, or consequential gains (§ 53)
that is identifiable and measurable and not unduly remote.
…
(c) A conscious wrongdoer or a defaulting fiduciary may be allowed a credit for
money expended in acquiring or preserving the property or in carrying on the
business that is the source of the profit subject to disgorgement. By contrast, such
a defendant will ordinarily be denied any credit for contributions in the form of
services, or for expenditures incurred directly in the commission of a wrong to the
claimant.55
70. The Restatement further clarifies appropriate deductions:
g. Apportionment. The general question of attribution may include issues of
apportionment at one or more levels. If the defendant's business is complex, and
the underlying wrong to the claimant affects only one of its various components,
threshold apportionment issues may involve (i) the proportion of the firm's overall
results properly attributable to the particular business in which the wrong has been
committed, and (ii) the proportion of overhead or other common expenses properly
charged against these results in determining the net profits of the business in
question. Because similar questions need to be addressed for a variety of purposes,
unrelated to liability in restitution, it may be possible to find appropriate answers
in existing accounting practice.
…
h. Deductions and credits. A recurring issue of the accounting described in § 51(5)
is the extent to which the defendant should be allowed a deduction (that is, a credit
against liability) for contributions made by the defendant to the gain for which the
defendant is liable. As a general rule, the defendant is entitled to a deduction for all
marginal costs incurred in producing the revenues that are subject to disgorgement.
Denial of an otherwise appropriate deduction, by making the defendant liable in
excess of net gains, results in a punitive sanction that the law of restitution normally
attempts to avoid. See § 42, Comment i.
By contrast, the defendant will not be allowed to deduct expenses (such as ordinary
overhead) that would have been incurred in any event, if the result would be that
defendant's wrongful activities—by defraying a portion of overall expenses—yield
an increased profit from defendant's operations as a whole.
[Illustration] 19. Edwards discovers and develops a cave located partially under
Lee's property, as described in § 40, Illustration 4, and in Illustrations 13 and 15,
supra. Edwards is liable to disgorge 30 percent of the net profits realized from the
exhibition of the cave, but the court must decide what deductions to allow from
gross revenues in calculating these net profits. In the ensuing accounting, Edwards
will typically be allowed a credit for cash outlays necessary to the operation of the
business from which the profit has been realized. Under the circumstances, such
outlays include the cost of building walkways and installing electric lights, as well
55 Restatement (Third) of Restitution and Unjust Enrichment § 51 (2011).
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as operating expenses such as wages and utilities. No credit is allowed for
Edwards's personal services in the discovery, development, and subsequent
management of the cave, despite the fact that no profit would have been realized
without these contributions.56
71. I am not offering a legal opinion on the proper measure of profits for unjust
enrichment. My opinion, as a damages expert reading the Restatement, is that I do not agree
with Mr. Lloyd’s assertion that gross profits are the proper measure of unjust enrichment. In
particular, I note that the Restatement identifies “operating expenses” as being properly deducted
in the discussion of Illustration 19. As I describe below, operating expenses are deducted from
revenues when calculating either operating profits or net profits – but they are not deducted from
revenues when calculating incremental or gross profits.
72. The difference between gross profits and net profits is significant – particularly in
this case. Every business has multiple measures of profit including gross, operating and net
profits. Profits result from deducting expenses from revenues; the measure of profit varies
depending on which expenses are deducted from revenues. In essence, there are different layers
of profits that are calculated by deducting different expenses. Gross profits are calculated by
deducting only the cost of goods sold (also described as direct costs) from revenues. Operating
profits are calculated by deducting direct costs and operating costs such as R&D or sales from
revenues. Finally, net profits are calculated by deducting direct costs, operating costs and all
other business costs such as overhead and financing costs from revenues. In table form showing
the layering of profit levels:
56 Restatement (Third) of Restitution and Unjust Enrichment § 51 (2011).
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Table 3: Levels of Profit57
Revenues
- Cost of Goods Sold
= Gross Profit
- Operating Costs
= Operating Profit
- Overhead, Financing and Other Costs
= Net Profit
73. Mr. Lloyd’s decision to measure Thomson Reuters’ gross or incremental profits
rather than operating profit or net profit significantly overstates the net profits attributable to
CLEAR by not giving Thomson Reuters any credit for (i) most of its direct costs to provide
access to data, (ii) any operating costs such as I/T infrastructure, R&D or sales, or (iii) any
overhead, financing or other costs.
6.3.1.2 Mr. Lloyd Has Not Calculated Gross or Incremental Profits
74. In fact, Mr. Lloyd does not actually calculate gross profits or even incremental
profits. While in some cases gross profits and incremental profits can be the same, they are not
in this case. Mr. Lloyd equates gross profits and incremental profits:
However, the measure of profitability called “net profit” by the Restatement and
other authorities is what an accountant or financial analyst would more likely call
“gross margin,” “gross profit,” or “incremental profit.” In other words, speaking
generically rather than about CLEAR specifically, the concept refers to the
difference between the sales price of additional units and the cost required to
produce those additional units, that is the “marginal” or “incremental” profit from
selling an additional unit.58
…
57 See, generally, FASB ASC Master Glossary https://asc fasb.org/glossary; New York Society of CPAs
Accounting Terminology Guide https://www.nysscpa.org/professional-resources/accounting-terminology-
guide#sthash.tWSUqFQr.dpbs; Deposition of Terry Lloyd, August 22, 2022, 57:7 – 8: “Generally speaking, the
difference between gross and net are operating costs, many of which are fixed.” I note that the classification of
any particular expense as being, e.g., a cost of goods sold as opposed to an operating cost can vary by business
and by accountant.
58 Lloyd Report, pp. 7 – 8.
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Using the example of a grocery store, the marginal cost of a gallon of milk is
typically the same for the first gallon sold as for the last one. For some items, like
assets held in digital form (music, movies, images, data), there may be little if any
additional cost to create another unit sold to the latest customer. In some cases, such
as tickets to a less-than-full stadium or movie theater, there may be no additional
cost incurred to produce the additional revenue from the last ticket sold. In those
cases, the incremental profit from the sale is the entire revenue.59
75. While I agree with Mr. Lloyd that the gross profits and the incremental profits from
the sale of a gallon of milk are the same, they are not the same for his example of the less-than-
full stadium. In the case of a less-than-full stadium, while the incremental profits from one more
attendee may be equal to the price of the ticket (after commissions), the gross profits from the
show would deduct at least the amount paid to the band playing the show and the cost of renting
the venue from the total ticket sales. The difference is that the incremental profits in his case
arise from the sale of one additional ticket. However, the incremental profit from the show (a
large group of tickets) deducts the costs to put on the show. In short, when calculating
incremental profits, the definition of the increment matters. The incremental profits from a ticket
are different from the incremental profits from a show.
76. Mr. Lloyd claims to be starting from incremental revenue, but his starting point is
an allocation of revenue.60 Mr. Lloyd states that he is trying to determine revenue from
“additional units.”61 In his deposition, Mr. Lloyd described the additional unit as being an
additional sale of a CLEAR license to a customer or an additional one-time use due to the
inclusion of data on Californians.62 Yet nowhere does Mr. Lloyd attempt to determine what
59 Lloyd Report, p. 9.
60 Deposition of Terry Lloyd, August 22, 2022 at 203:8 – 14, 207:8 – 10.
“Q So did -- do you know what's included in technology infrastructure or whether that's properly included as a
marginal cost?
A As a marginal cost, it appears to have some marginal features to the overall business, but not to the
incremental user or the incremental revenue derived by usage of the data.”
…
“But for our purposes here, but for my purposes, is to look at the incremental cost or the incremental revenue of
using that data.”
61 Lloyd Report, pp. 7 – 8.
62 Deposition of Terry Lloyd, August 22, 2022 at 191:18 – 192:8.
“…like any digital business, the incremental profits are phenomenal.
Q The increment that you're discussing here is the additional sale of a CLEAR license to a CLEAR customer;
right?
A Or a one-time usage. Either way, it's that additional or incremental sale.”
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CLEAR revenues are incremental – in the sense that they are sales that are either solely or
largely attributable to ability to access data on Californians via CLEAR. Mr. Lloyd simply
allocates all of CLEAR’s revenues according to his estimate of the relative size of California.
77. In connection with allocating CLEAR’s revenue to Californians, Mr. Lloyd deducts
incremental expenses (as he’s defined them) from allocated revenue to arrive at a profit figure.
As stated by Mr. Lloyd in his deposition:
I didn't calculate marginal revenues. I calculated total revenues derived by CLEAR
using data on California persons, and then calculated the marginal or incremental
cost related to producing that revenue. 63
…
We're looking at the revenues in the aggregate and under the methodology of
calculating unjust enrichment. We start with those revenues and then subcontract
[sic] from those the incremental costs.64
78. Mr. Lloyd’s calculation is, therefore, neither incremental profits for providing
access to data on Californians nor gross profits – it is a hybrid based on allocated revenues and
incremental expenses. To calculate incremental profits, Mr. Lloyd should have started with
incremental revenues – revenues from performing an additional search – and subtracted the
incremental expenses attributable to that search. For Thomson Reuters, the incremental revenue
associated with one more search is zero for most customers because they are on subscription
plans.65 To calculate gross profits, Mr. Lloyd should have started with CLEAR’s revenues and
subtracted its direct expenses including – at the very least – the royalty costs to allow access to
the data. To be consistent in his analysis, if Mr. Lloyd believes that it is appropriate to allocate
all of CLEAR’s revenue on the basis of the relative size of California, he should also allocate all
of CLEAR’s expenses on the basis of the relative size of California. Graphically, what Mr.
Lloyd has done is:
63 Deposition of Terry Lloyd, August 22, 2022 at 226:8 - 17.
64 Deposition of Terry Lloyd, August 22, 2022 at 233:20 – 234:11.
65 Lloyd Report, p. 7.
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Table 4: Lloyd’s Profit Methodology
Allocated
Incremental
Revenues
✔
Expenses
✔
Profits
?
?
79. Instead of allocating costs to follow his allocated revenue methodology, Mr. Lloyd
argues that:
…costs, such as sales, editorial, and other operational expenses … do not actually
appear to vary based on customer usage or the availability of particular data within
CLEAR (namely, the availability of data about Californians in CLEAR).66
…
Based on my review of Thomson Reuters’s reported costs during the relevant time
period, the only marginal costs for CLEAR are royalties that Thomson Reuters pays
to other vendors for data made available through CLEAR.67
80. In particular, and quoting the language he uses for his analysis of costs, Mr. Lloyd
does not consider whether revenues varied “…based on customer usage or the availability of
particular data within CLEAR (namely, the availability of data about Californians in
CLEAR).”68 Mr. Lloyd only performed that analysis on the cost side.
81. Mr. Lloyd’s methodology – subtracting his estimate of marginal costs from his
estimate of allocated revenues – is not an estimate of incremental costs and significantly
overstates Thomson Reuters’ gross profits.
6.3.1.3 Mr. Lloyd’s
Cost Estimate Does Not Include All Attributable Costs
82. Mr. Lloyd justifies using a
profit margin for CLEAR on the basis that the only
incremental costs that should be considered are transactional royalty costs:
66 Lloyd Report, p. 16.
67 Lloyd Report, p. 16.
68 Lloyd Report, p. 16.
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Various documents produced in discovery reflect that Thomson Reuters’s
transactional royalty costs are consistently at or below
of the corresponding
revenues. For that reason, my calculations use the
figure as a reasonable
estimate of the relevant marginal costs incurred by Thomson Reuters on CLEAR.69
83. As a starting point, it is worth noting that Mr. Lloyd’s
figure is based on two
documents – an email exchange and an Excel document – neither of which explain what the
actually represents or how it should be used, and there is no indication in the Lloyd Report that
Mr. Lloyd understands the veracity of, or the basis for the
figures in these two documents.70
84. Mr. Lloyd’s cost estimate is also flawed because he opines that Thomson Reuters’
only marginal costs are for royalties:
Based on my review of Thomson Reuters’s reported costs during the relevant time
period, the only marginal costs for CLEAR are royalties that Thomson Reuters pays
to other vendors for data made available through CLEAR.71
85. However, Mr. Lloyd did not consider other marginal costs for Thomson Reuters
such as servers, storage and bandwidth (hosting costs) or sales costs. Mr. Lloyd assumes that
of Thomson Reuters’ revenue is tied to data on Californians. Removing that revenue would
also remove costs for web hosting as less data is stored and fewer searches were run. Thomson
Reuters might also be able to reduce its sales force in California. Each of those costs would be
marginal costs for Thomson Reuters that are directly tied to allowing customers to access data on
Californians via CLEAR.
86. Indeed, Mr. Lloyd admitted that “servers or support or security” could be
considered marginal costs and that he had not accounted for them in his report or calculations.72
6.3.1.4 Mr. Lloyd Does Not Deduct Costs for California Data
87. Mr. Lloyd’s estimated profit margin of
does not give credit to Thomson
Reuters for any costs other than his estimate of what he describes as transactional royalty costs.73
69 Lloyd Report, p. 17.
70 Lloyd Report, p. 17, footnote 61: TR-BROOKS110695; TR-BROOKS129381.
71 Lloyd Report, p. 16.
72 Deposition of Terry Lloyd, August 22, 2022 at 276:15 – 22.
“A I'd have to think about that one, but I think if they removed all of that data, there might be some -- you and I
discussed at length fixed and variable costs, there might be some cost savings, say, in servers or support or
security, but also the primary driver of that would be the royalties they saved that they didn't have to pay for not
using the data.”
73 Lloyd Report, pp. 16 – 17.
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Mr. Lloyd cites no evidence that these transactional royalty costs are attributable to California or
are a complete set of royalties paid by Thomson Reuters’ for accessing data on individual
Californians.
88. He dismisses what he describes as “flat fee royalties” by stating:
I see no indication that material flat fee royalty costs would have been avoided had
Thomson Reuters not made information about Californians available through
CLEAR. Instead, the agreements impose flat fee royalty costs in connection with
data that is mostly multistate and nationwide in scope.74
89. Note that the majority of CLEAR’s subscriptions would also be characterized as
“flat fee” yet are included in his estimate of revenues. 75 Thus, Mr. Lloyd, when confronted with
flat fee revenue amounts paid by CLEAR customers, allocated those revenues, but when
confronted with flat fee royalty amounts paid for that data, Mr. Lloyd concludes that none of
those flat fee royalty amounts would have been avoided.
90. Furthermore, Mr. Lloyd does not account for the fact that some of the data costs are
incurred solely to acquire data related to Californians. For example, in his deposition, Mr. Lloyd
was shown two agreements under which Thomson Reuters agreed to purchase data from the
.76 Mr. Lloyd was
not familiar with either of these documents and did not consider whether the payments in the
agreements might be properly tied to allowing access to data on Californians via CLEAR.77
These data costs are unequivocally “a credit for money expended in acquiring or preserving the
property or in carrying on the business that is the source of the profit subject to disgorgement.”78
74 Lloyd Report, p. 16.
75 Lloyd Report, p. 7.
76 Deposition of Terry Lloyd, August 22, 2022, Exhibits F16 & F17.
77 Deposition of Terry Lloyd, August 22, 2022 at 257:22 – 259:10.
“My question is: Does your
figure account for the cost savings of terminating a recurring data
licensing agreement.
[Objection]
A I cannot answer your -- I cannot answer your question because the entire premise is unfounded.
…
A We did not parse down to individual components within contracts or individual contracts.
That Thomson Reuters knows its transactional royalty costs better than any of us, and I accept their
representations at face value as representative of transactional royalty costs across the entire spectrum of
licensing agreements.”
78 Restatement (Third) of Restitution and Unjust Enrichment § 51 (2011).
Case 3:21-cv-01418-EMC Document 186-5 Filed 03/28/23 Page 31 of 58
HIGHLY CONFIDENTIAL – ATTORNEYS’ EYES ONLY
31
Even under Mr. Lloyd’s purported incremental cost methodology, these must be considered
marginal costs. However, Mr. Lloyd’s calculation gives no such credit.
6.3.1.5 Summary of Unreliable Profit Margin
91. In summary, Mr. Lloyd’s calculation of a
profit margin on sales is the
unreliable result of an ad hoc and unsound methodology. In my reading of it, the Restatement
does not support his claim that the proper measure of unjust enrichment is gross profits as
opposed to net profits. While claiming to calculate gross or incremental profits, he does neither –
he deducts only some of the incremental costs from his allocated revenue. Most notably, he does
not give Thomson Reuters credit for the amounts it spent to allow access to data on Californians.
92. In the following sections I describe errors in Mr. Lloyd’s attribution of revenues to
individual Californians.
6.3.2 ESTIMATES FOR CALIFORNIA ARE UNRELIABLE
93. Mr. Lloyd’s estimate of the share of “CLEAR’s revenue attributable to
Californians” is unreliable and flawed.79 Mr. Lloyd dismisses the most obvious way to allocate
the revenue – the percentage of U.S. citizens living in California by stating:
… while California’s share of the total U.S. population is 11.8%, I understand the
Class to encompass natural persons who resided in California at any time during
the relevant time period, including those who lived in California at one point and
then moved out of state, along with those who initially lived out of state but then
moved into California. For that reason, statistics that identify the fixed population
within California at any given time would likely undercount the total number of
“Californians” included in the Class relevant to this Case.80
94. Thus, Mr. Lloyd objects that any estimate of the number of Californians at a single
point in time would be unreliable. But Mr. Lloyd’s interpretation of the proposed class is not, in
fact, what is alleged in the Complaint, which defines the class as “All persons residing in the
state of California whose name, photographs, personal identifying information, or other personal
data is or was included in the CLEAR database during the limitations period.” The proposed
79 Lloyd Report, p. 12.
80 Lloyd Report, pp. 12 – 13.
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32
class is composed of current California residents, and the Lloyd Report does not measure net
profits associated with that population.81
95. In addition, Mr. Lloyd bases his calculation on an average of arrest data from 2018
and GDP data from 2021. Mr. Lloyd claims that this approach avoids the issue of proposed class
members who moved in or out of state. I disagree. Both of his favored metrics – GDP for 2021
and arrest rates for 2018 – are tied to the number of residents of California at the time the metric
was calculated and do not account for movement in or out of the state.82
96. Mr. Lloyd has justified his use of GDP data on the basis that:
First, CLEAR is used in large part as a tool related to economic activity. For that
reason, to the extent the proportion of U.S. economic activity conducted within
California is not the same as the proportion of the U.S. population within California,
then California’s share of economic activity is likely to be more useful in
conducting this apportionment analysis.83
97. Yet Mr. Lloyd has provided no evidence that “CLEAR’s revenue attributable to
Californians” bears any relationship to economic activity in the state of California. There is no
evidence that economic activity affects the portion of CLEAR’s revenue that might be
attributable to proposed class members.
98. Mr. Lloyd’s only justification for the use of the arrest rate is:
To the extent CLEAR is used by law enforcement for non-economic purposes, I
note that California also has a higher arrest rate
than its share of the U.S.
population
.84
99. Mr. Lloyd has not provided any analysis that indicates what percent of CLEAR’s
revenues are from police departments – particularly not police departments located in the state of
California which might have a particular interest in arresting Californians.
100. Mr. Lloyd notes that CLEAR is used for a broad set of use cases:
81 Second, even if it did reflect the proposed class in this case (it does not), Mr. Lloyd’s estimate does not take into
account data available on people moving into and out of California. See, e.g.,
https://www.capolicylab.org/pandemic-patterns-california-is-seeing-fewer-entrances-and-more-exits-april-
2022-update/.
82 See, e.g., https://www.capolicylab.org/pandemic-patterns-california-is-seeing-fewer-entrances-and-more-exits-
april-2022-update/.
83 Lloyd Report, p. 12.
84 Lloyd Report, p. 13.
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33
I understand CLEAR to … target industries and customers in the financial services
(banks, brokerages, etc.), insurance, and retail sectors, among others. The data is
used for a broad set of “use cases.”85
101. This highlights a fundamental problem with Mr. Lloyd’s approaches – he has not
done any analysis indicating what information accessible via CLEAR is of interest to CLEAR’s
customers, nor has he determined whether, how, or to what extent that information is related to
the California arrest rate or economic activity. Mr. Lloyd simply assumes, without any basis, that
the percentage of CLEAR revenues from the “aggregation and compilation and distribution of
personal data of Californians for profit” via CLEAR is directly related to the arrest rate and
economic activity in the state of California.
102. In addition, although Mr. Lloyd has gone out of his way to avoid apportioning
CLEAR’s revenues on the basis of the number of current California residents, his preferred
metrics are highly related to the number of Californians at any given point in time.
103. Furthermore, Mr. Lloyd appears to have made a math error when calculating his
figure. Mr. Lloyd’s representation that the FBI arrest data indicates that California
accounted for
of arrests in 2018 is not supported by the data.86 The data purportedly used
by Mr. Lloyd reports
arrests in California out of a total of
arrests in the U.S.
for a percentage of arrests in California of
.87 Yet even this
overstates the true
percentage because the FBI arrest data states that it is incomplete. There are notes in the source
data file indicating that the arrest data for Illinois is incomplete and that no arrest data was
received from the New York City Police Department. The file also does not present any data for
Iowa.88 Thus, the actual percentage is somewhat lower than
and Mr. Lloyd’s
is
unsupported and inflated. Furthermore, if
arrests are made each year in the U.S., then
that means that
or
of Americans were arrested in 2018.89 Extrapolating the
percent of revenues for CLEAR attributable to Californians based on the
of the U.S.
population that was arrested is not representative and is not reliable.
85 Lloyd Report, p. 5.
86 Nor does Mr. Lloyd provide any exhibit which supports his estimate.
87 Exhibit 3. FBI Crime Stats Table 69
88 https://ucr fbi.gov/crime-in-the-u.s/2018/crime-in-the-u.s.-2018/topic-pages/tables/table-69?
89 https://www.macrotrends.net/countries/USA/united-states/population.
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34
104. Mr. Lloyd’s selection of California’s share of GDP at
is based on 2021. In
2020, his own data shows that the share was
.90 GDP figures from 2020 and 2021 should
also be viewed with some caution as they were affected by the pandemic.
105. Mr. Lloyd’s averaging arrest rates from 2018 and GDP from 2021 results in an ad
hoc number that has no real interpretation. This average is a meaningless number that is based
on figures that are only arguably related to two of the many possible use cases for CLEAR.
106. In summary, Mr. Lloyd’s allocation of
of CLEAR revenues to the state of
California is ad hoc, unreliable and based on an apparent math error.
6.3.3 ESTIMATES FOR BUSINESS DATA ARE UNRELIABLE
107. Mr. Lloyd's attribution of CLEAR revenues to data on businesses is unreliable. Mr.
Lloyd recognizes that “CLEAR…aggregates and makes available to its customers information
relating to individuals and businesses.”91 He categorizes
of revenue as being derived
from searches related to individuals on the basis of an analysis of search types apparently
performed by one of Plaintiffs’ attorneys.92 Mr. Lloyd describes the methodology as:
Totaling the search types reasonably tied to natural persons (i.e., excluding
company search, court search, search all business, risk inform business standalone,
and intellectual property searches), the data indicates that approximately
of
all CLEAR searches relate to individuals.93
108. The underlying data does not support Mr. Lloyd’s division between business
searches and searches tied to natural persons. E.g. a search term for a business name and a last
name is not categorizable as being related to an individual or a business – it is both. The
calculation relied upon by Mr. Lloyd categorizes all searches described as “Phone Search” as
being a search for a person.94 As a matter of logic, some of those phone searches must be for
phone numbers related to businesses, and, in fact one of the searches categorized as a “Phone
90 https://www.bea.gov/sites/default/files/2022-03/qgdpstate0322.pdf.
91 Lloyd Report, p. 5.
92 Lloyd Report, p. 14; Deposition of Terry Lloyd, August 22, 2022, Exhibit F21, tab “Search Summary” cell A1
“Zeke Person Search Totals:”.
93 Lloyd Report, p. 14.
94 Deposition of Terry Lloyd, August 22, 2022, Exhibit F21, tab “Search Summary” cell A1 “Zeke Person Search
Totals:” includes cell C5 for “Phone Search.”
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HIGHLY CONFIDENTIAL – ATTORNEYS’ EYES ONLY
35
Search” is just “businessName.” 95 Thus, the attorney’s calculation is nothing more than a
subjective assessment that is not supported by the underlying data and does not give any insight
into the relative value of information on businesses and individuals in CLEAR.96
109. In summary, Mr. Lloyd’s allocation of revenues to individuals is subjective and
unreliable.
6.4
MR. LLOYD HAS NO METHODOLOGY TO ALLOCATE DAMAGES TO CLASS MEMBERS
110. The Lloyd Report is flawed in that it does not propose a methodology to determine
damages due to each class member.97
111. Mr. Lloyd explicitly rejects estimating damages according to the number of
residents of California and, thereby, implicitly rejects allocating his estimated damages equally
to each member of the proposed class.98 I also believe that an equal allocation would not be a
reasonable way to allocate damages to individual class members because it would ignore
significant variability among the class. Variations that would likely be relevant to individual
damage apportionment would include, at a minimum, differences between class members in the
quantity of data, the accuracy of data, the time of residency in California, and the benefits or
harms enjoyed or suffered by each member as a result of access to their information via CLEAR.
112. As an example of the difficulty in apportioning damages to individual class
members, I do not know of any logical method that accounts for differences in the availability of
data among class members. The information accessible via CLEAR for each individual will vary
in both amount and type. The revenues attributable to that information will also vary depending
95 Deposition of Terry Lloyd, August 22, 2022, Exhibit F21, tab “Fields By Search”, row 6460.
96 Deposition of Terry Lloyd, August 22, 2022 at 284:15 – 285:6.
“Q Similar question to what I asked you earlier. Here it says: "Zeke person search totals. Zeke nonperson search
totals." Do you see that at the top of Exhibit F21?
A I do.
Q And Zeke to you is the lawyer representing plaintiffs here?
A He's not the only Zeke I know, but he's the only one that would appear in this document.
Q Okay. And is it possible that you took your
figure from these Zeke calculations?
A Yes. It's possible that I directed him using the data to perform some calculations, but yes, this appears to be
the source of the
.”
97 I note that Professor Turow did not “…[quantify] the amount of harm per person. No, that was not part of my
mandate.” Deposition of Joseph Turow, August 26, 2022 at 187:18 – 19.
98 Lloyd Report, pp. 12 – 13. “…statistics that identify the fixed population within California at any given time
would likely undercount the total number of ‘Californians’ included in the Class relevant to this Case.”
Case 3:21-cv-01418-EMC Document 186-5 Filed 03/28/23 Page 36 of 58
HIGHLY CONFIDENTIAL – ATTORNEYS’ EYES ONLY
36
on whether that information is presented as the result of a search. Each CLEAR customer may
perform searches that only present data on Californians, searches that present no data on
Californians, and searches that present a mix of data. I know of no way to determine which
searches presented information on Californians that the searcher found relevant.
113. Apportioning damages based on search results would not be possible. As an initial
matter, I understand that Thomson Reuters does not possess search results from which such
analyses could be conducted.
114. Moreover, since CLEAR’s revenues are largely the result of subscription plans, it is
not obvious how to determine revenue attributable to any individual search.99 The incremental
revenue attributable to any particular search performed under a subscription plan is generally
zero – i.e. if a customer did not perform a particular search for a particular person, Thomson
Reuters’ revenues would not change. Allocating revenues by dividing by the number of searches
performed by that customer into the subscription fees for that customer would provide an
allocated figure for revenue per search, but it leaves unanswered the questions of which searches
disclose information on proposed class members and the value of that information. For example,
we would have no way of knowing whether, even if information was disclosed about a particular
proposed class member, whether that information was of any value to the searcher, i.e. whether
that information was the point of the search.
115. There are at least five issues that must be addressed to determine unjust enrichment
related to any individual in the proposed class:100
• What information was displayed as the result of a search.
99 Lloyd Report, p. 7.
100 Note that assessing individual harm compounds these problems as it requires considering each individuals’
privacy preferences. See, e.g., Deposition of Cat Brooks, August 10, 2022 at 173:17 – 174:9.
“A. So my overall position is that the utilization of people's information without their knowledge or consent is
more harmful than any benefit that could come from it.
Q. Any benefit whatsoever?
A. That's my position.
Q. Do you think everyone would agree with you?
A. Again, I cannot speak for everyone.
Q. Because --
A. I think many, many, many, many people might agree with me, yes.
Q. Do you think some people might disagree with that?
A. There's always a possibility for someone to disagree with me.”
Case 3:21-cv-01418-EMC Document 186-5 Filed 03/28/23 Page 37 of 58
HIGHLY CONFIDENTIAL – ATTORNEYS’ EYES ONLY
37
• Whether any proposed class member’s information was part of the
information displayed.
• Whether the proposed class member whose information was displayed
was the target of the search or just incidental information that was of no
value to the searcher.
• The amount of revenue CLEAR would have lost had the search not been
performed.
• When the search was performed relative to the residency in California of
the individual.
116. In summary, Mr. Lloyd proposes no methodology for allocating any unjust
enrichment to each proposed class member. Nor do I believe that such an analysis is feasible as
it goes beyond just individualized inquiry; it requires an inquiry into each search based on data
that is not available.
Case 3:21-cv-01418-EMC Document 186-5 Filed 03/28/23 Page 38 of 58
Case 3:21-cv-01418-EMC Document 186-5 Filed 03/28/23 Page 39 of 58
Exhibit 1: Kidder Resume
1
Douglas G. Kidder
510.899.7183 (office)
(510) 610-0325 (cell)
dkidder@oskr.com
CURRENT EMPLOYMENT
2008 - Present
Managing Partner
OSKR, LLC
Emeryville, CA
Patent valuation and business strategy expert with over 25 years of experience analyzing
patents, business opportunities and risks. Consult for clients on complex damages and
licensing issues with a particular focus on technology companies. www.oskr.com
PRIOR EXPERIENCE
2014 – 2020
Adjunct Professor Golden Gate University
San Francisco, CA
Taught a graduate-level course in the School of Accounting on damages.
2001 – 2007
Principal
LECG, LLC
Emeryville, CA
1997 – 1999
Primarily consulted for companies on damages issues arising from allegations of
antitrust and intellectual property infringement.
2005
Office Director
Responsible for the operations of a 90-person office including reviews, hiring, firing,
promotions, morale and general administration.
2001 - 2005
Special Assistant to the Chairman, Strategy
Advised the Chairman on corporate acquisitions and general strategic direction.
2000 - 2001
Managing Director
SCIENT
San Francisco, CA
Joined corporate strategy group to help design and implement a turn-around for this
Internet consulting firm. Responsible for company organizational transition.
1999 - 2000
VP Operations
KENAMEA
San Francisco, CA
Helped develop strategy and business plan for an Internet software startup. Managed the
operations of the company as we grew from 4 to 25 people.
1996 - 1997
Principal
MANAGEMENT RESOURCES
Berkeley, CA
Independent consultant performing due diligence and analyses of startup high-tech
business opportunities.
1995 – 1996
Vice President
Business Development
WALT DISNEY
IMAGINEERING
Glendale, CA
Evaluated new business ideas for WDI including creative concepts and technology
initiatives.
1993 - 1995
Director
VALSPAR
Chicago, IL
Managed the production planning, distribution and I/T functions for the $200 million
Consumer Paint Division.
1992-1993
1990-1991
1987-1989
Senior Associate
Associate
Analyst
BOOZ, ALLEN
San Francisco, CA
Performed general business strategy and organization assignments across a wide range
of industries. Exceptional (second in the history of the firm) promotion granted from
Analyst to Associate waiving the usual requirement for an MBA.
Case 3:21-cv-01418-EMC Document 186-5 Filed 03/28/23 Page 40 of 58
Exhibit 1: Kidder Resume
2
1984 - 1986
Lecturer
UC BERKELEY
Berkeley, CA
Taught an introductory computer science class.
1986
Chief Engineer
WINDWARD YACHTS
Oakland, CA
Responsible for the detailed design of custom yachts.
OTHER BUSINESS EXPERIENCE
2013 – Present
Naval Architect
Berkeley, CA
Design custom rowing shells for open water.
2001 - 2013
President
MAAS BOAT COMPANY
Richmond, CA
Purchased, managed and sold a company that manufactures and sells open water rowing
shells in the U.S. and around the world. Primary responsibilities were design,
management, marketing, finance, and license negotiation.
2008 – 2012
President
NAOWRC, Inc.
Richmond, CA
Created a national championship for open water rowing that brought together rowers
from around the U.S. and the world.
2004 – 2011
President
KIDDER RACING
Richmond, CA
Developed design brief for an innovative one-person sailing skiff. Founded company
and was responsible for final design, strategy, marketing and finance.
Board Positions
Skyflow Inc. (former), NextWindow (former), Hero Arts (Advisory Board,
former),Trade New Zealand (Advisory Board, former), Berkeley Rowing Club (former)
Other
Member of the Licensing Executives Society
Member of the National Associate of Business Economists
Member of The Sedona Conference
Participant in the Stanford IP Roundtable
Booz, Allen & Hamilton Professional Excellence Award
Outstanding Graduate Student Instructor Award
Significant experience evaluating new businesses.
EDUCATION
1986
M.Sc., University of California at Berkeley
1983
B.A. with Honors, Amherst College
Elected to Sigma Xi, National Scientific Honor Society
PUBLICATIONS & PRESENTATIONS
“Are Patents Really Options?”, les Nouvelles Journal of the Licensing Executives
Society, V. 38(4), December 2003.
“Most Favored Licensee Clauses: Draining the Swamp” presentation at Advanced
Topics in IP Valuation to the Intellectual Property Society, July 2004.
“Reasonable Royalties by the New Rules”, Dunn on Damages, Summer 2011.
Case 3:21-cv-01418-EMC Document 186-5 Filed 03/28/23 Page 41 of 58
Exhibit 1: Kidder Resume
3
“Infringer’s Profits Should Not Be the Focus of Patent Damages Cases”, Dunn on
Damages, Fall 2011.
“Simply Wrong: The 25% Rule Examined”, les Nouvelles Journal of the Licensing
Executives Society, December, 2011.
“For Want of Damages the Case was Tossed: Judge Posner’s Ruling in Apple v.
Motorola”, Dunn on Damages, Fall 2012.
“Nash Bargaining and Patent Damages”, les Nouvelles Journal of the Licensing
Executives Society, March 2014.
“Lump Sums, Running Royalties and Real Options”, les Nouvelles Journal of the
Licensing Executives Society, December 2015.
Case 3:21-cv-01418-EMC Document 186-5 Filed 03/28/23 Page 42 of 58
Exhibit 1: Kidder Resume
4
Litigation Experience
Ossur Holdings Inc. and Generation II USA, Inc., v. Bellacure, Inc., Shane Sterling and
Maurice Cannon. Before United States District Court, Western District of Washington at
Seattle. Civil Action No: 05-CV-01552-CMP. Retained by counsel for plaintiffs, re: lost
profits and unjust enrichment due to alleged theft of trade secrets in the medical device
industry (osteoarthritis knee braces).
Google, Inc. v. American Blind & Wallpaper Factory, Inc. Before United States District
Court, Northern District of California. Case No. C 03-5340 JF EAI. Retained by counsel
for plaintiffs re: damages arising from Google’s alleged infringement of American Blind
& Wallpaper’s trademarks.
Comcast Cable Communications Corporation, LLC v. Finisar Corporation. Before
United States District Court for the Northern District of California. Case No. C 06-04206
WHA. Retained by counsel for plaintiffs re: damages arising from Comcast’s alleged
infringement of Finisar patent number 5,404,505.
Carter Bryant, an individual v. Mattel Inc. and Consolidated Actions. Before United
States District Court for the Central District of California, Eastern Division. Case No.
CV 04-9049 SGL (RNBx) Consolidated with Case No. CV 04-09059 Case No. CV
OS02727. Retained by counsel for plaintiff re: damages arising from Mr. Bryant’s
alleged theft of copyrighted materials, breach of fiduciary duty and theft of trade secrets.
American Airlines, Inc. v. Google, Inc. Before United States District Court for the
Northern District of Texas, Fort Worth Division. Case No. 4-07CV-487-A. Retained by
counsel for defendant re: damages arising from Google’s alleged infringement of
American Airline’s trademarks.
H. Richard Dallas, Shareholder Representative for dMarc v. Google Inc. Before JAMS,
reference #1100054656. Retained by counsel for defendant re: damages arising from a
breach of contract claim arising from Google’s acquisition of dMarc.
Flashseats, LLC. v. Paciolan Inc. Before United States District Court, District of
Delaware. Case No. CA 07-575 (JJF). Retained by counsel for defendant re: damages
arising from Paciolan’s alleged infringement of Flashseats’ patent number 6,496,809.
Charlotte Russe Holding, Inc. v. Versatile Entertainment, Inc. and People’s Liberation,
Inc. Before Superior Court of the State of California, County of Los Angeles, Central
District. Case No. BC424734. Retained by counsel for plaintiff re: damages arising from
alleged breach of contract.
Case 3:21-cv-01418-EMC Document 186-5 Filed 03/28/23 Page 43 of 58
Exhibit 1: Kidder Resume
5
M&H Realty Partners V L.P. v. Aerojet-General Corporation, Boeing Realty
Corporation, The Boeing Company, McDonnell Douglas Corporation. Before Superior
Court for the State of California, County of Orange. Case No. 30-2008-00080378-
CUTT-CXC. Retained by counsel for plaintiff re: damages arising from environmental
contamination at a property redevelopment.
Firefly Digital, Inc. v. Google Inc. Before United States District Court, Western District
of Louisiana, Lafayette Division. Case number 6:10cv00133-TLM-PJH. Retained by
counsel for defendant re: damages arising from alleged trademark infringement.
American Technology, Inc., v. FrozenCPU.com, Inc. Before the United States District
Court, Middle District of Florida, Orlando Division. Case Number 6:11-CV-110-
ORLACC-GJK. Retained by counsel for defendant re: damages arising from alleged
patent infringement.
C&C Jewelry Mfg., Inc. v. Trent West. Before United States District Court, Northern
District of California, San Jose Division, Case No. 5:09-cv-01303-JF-HRL. Retained by
counsel for plaintiff re: reasonable royalty damages arising from alleged patent
infringement.
Pixart Imaging, Inc. v. Avago Technologies General IP (Singapore) PTE. LTD. Before
United States District Court Northern District of California, San Jose Division. Case No.
C 10-00544 JW. Retained by counsel for plaintiff re: additional royalties due from
alleged breach of a patent license agreement.
EasyWeb Innovations, LLC. v. Twitter, Inc. Before United States District Court, Eastern
District of New York. Case No. 2:11-cv-04550-JFB-WDW. Retained by counsel for
defendant re: reasonable royalty damages arising from alleged patent infringement.
Oncology Tech, LLC v. Elekta AB and Elekta, Inc. Before United States District Court,
Western District of Texas, San Antonio Division. Case No: 5:12-CV-00314-HLH.
Retained by counsel for defendants re: damages arising from alleged breach of contract.
American Medical Response, Inc. v. Paramedics Plus, LLC. Before Superior Court of the
State of California, County of Alameda. Case No: RG10541623. Retained by counsel
for defendant re: damages arising from alleged low-cost bid for emergency medical
services.
AMC Technology, L.L.C., v. Cisco Systems, Inc. Before United States District Court,
Northern District of California, San Jose Division. Case No: C-11-03403 (PSG).
Retained by counsel for plaintiff re: damages arising from alleged breach of contract.
Silicon Storage Technology, Inc. v. National Union Fire Insurance Company of
Pittsburgh, PA and XL Specialty Insurance Company. Before United States District
Court, Northern District of California. Case No: 5:13-CV-05658. Retained by counsel
for defendants re: damages arising from a claim for theft of trade secrets.
Case 3:21-cv-01418-EMC Document 186-5 Filed 03/28/23 Page 44 of 58
Exhibit 1: Kidder Resume
6
Neustar, Inc. v. F5 Networks, Inc. Before United States District Court, Northern District
of California, San Jose Division. Case No: CV12-02574. Retained by counsel for
plaintiff re: damages arising from alleged breach of contract.
Qiang Wang v. Palo Alto Networks, Inc. Before United States District Court, Northern
District of California, San Francisco Division. Case No: C 12-05579 WHA. Retained by
counsel for defendant re: damages arising from alleged misappropriation of trade secrets
and alleged patent infringement.
Affymetrix, Inc. v. Enzo Biochem Inc. Before United States District Court, Southern
District of New York, Case No. 1:04-cv-01555-RJS. Retained by counsel for Plaintiffs
re: damages arising from an alleged breach of contract.
Enzo BioChem, Inc. v. Affymetrix, Inc. Before United States District Court, Southern
District of New York, Case No. 1:03-cv-08907-RJS. Retained by counsel for Defendants
re: damages arising from an alleged breach of contract.
Wyde Voice, LLC and Free Conferencing Corporation v. Global IP Solutions, Inc. and
Google Inc. Before Superior Court of the State of California, County of San Francisco,
Case No. CGC-12-522868. Retained by counsel for defendants re: damages arising from
an alleged breach of contract.
Alexander Stross v. ZipRealty, Inc. Before United States District Court, Western District
of Texas, Austin Division. Civil Action No. A-13-CV-419-SS. Retained by counsel for
defendants re: damages arising from alleged copyright infringement.
Collarity, Inc. v. Google, Inc. Before United States District Court, District of Delaware.
Case No. 11-1103 MPT. Retained by counsel for defendants re: damages arising from
alleged patent infringement.
TomTom International, B.V. v. Broadcom Corporation. Before United States District
Court, Central District of California. Case No. 8:14-cv-00475 PA (DFMx). Retained by
counsel for defendants re: damages arising from alleged breach of warranty.
In Re Google Inc. Privacy Policy Litigation. Before United States District Court,
Northern District of California, San Jose Division. Case No. 12-CV-01382 PSG.
Retained by counsel for Google re: damages arising from alleged breach of privacy
policy.
Sarvint Technologies, Inc. v. Athos Works, Inc., and Mad Apparel, Inc. (and related cases
filed by Sarvint against OMSignal, Ralph Lauren, Victoria’s Secret, Textronics and
adidas, and Sensoria). Before United States District Court, Northern District of Georgia,
Atlanta Division. Civil Action No. 1:15-CV-00068-TCB. Retained by counsel for
defendants re: irreparable harm arising from alleged patent infringement.
Case 3:21-cv-01418-EMC Document 186-5 Filed 03/28/23 Page 45 of 58
Exhibit 1: Kidder Resume
7
California Expanded Metal Products Co., v. ClarkWesternDietrich Building Systems
LLC, James Klein and BlazeFrame Industries, Ltd. Before United States District Court,
Central District of California, Case No. 2:12-cv-10791-DDP-MRWx. Retained by
counsel for defendants re: damages arising from alleged breach of contract and patent
infringement.
In Re: Multiple Listing Service Real Estate Photo Litigation. Before United States
District Court, Southern District of California, Case No.: 14CV1158 BAS (JLB).
Retained by counsel for defendant (CoreLogic) re: damages arising from an alleged
breach of copyright.
TeleSign Corporation v. Twilio, Inc. Before United States District Court, Central District
of California, Case No. 15-3240-PSG-SS. Retained by counsel for defendant re:
irreparable harm in the context of a motion for preliminary injunction.
Quantum Corporation v. Crossroads Systems, Inc. Before United States District Court,
Northern District of California, San Francisco Division, Case No. 3:14-cv-04293-WHA.
Retained by counsel for plaintiff re: lost profits and reasonable royalty arising from
alleged patent infringement.
United States of America ex rel. Floyd Landis v. Tailwind Sports Corp., Lance
Armstrong and Johan Bruyneel. Before United States District Court, District of
Columbia, Case No. 1:10-cv-00976 (CRC). Retained by counsel for Lance Armstrong re:
benefits received by the U.S. Postal Service from its sponsorship of the USPS Cycling
Team.
Integra LifeSciences Corp., Integra LifeSciences Sales LLC, Confluent Surgical, Inc., and
Incept LLC, v. HyperBranch Medical Technology, Inc. Before United States District
Court, District of Delaware, Case No. C.A. No. 15-1819 (LPS)(CJB). Retained by
counsel for defendant re: irreparable harm in the context of a motion for preliminary
injunction.
Alice Svenson, individually and on behalf of all others similarly situated, v. Google, Inc.
and Google Payment Corporation. Before United States District Court, Northern District
of California, Case No. CV-13-04080-BLF. Retained by counsel for defendant re:
damages from alleged breach of privacy policy.
Telecom Asset Management, LLC v. Cellco Partnership d/b/a Verizon Wireless, Verizon
Sourcing LLC, Verizon Corporate Resources Group LLC. Before United States District
Court, Southern District of New York, Case No.: 15 Civ 2786 (SHS) (RLE). Retained on
behalf of defendants re: damages from alleged breach of contract.
Celestica (USA) Inc. v. The Crossbow Group, LLC, Before JAMS, San Jose, CA. JAMS
Ref. No. 1110018525. Retained by counsel for plaintiffs re: damages from alleged
breach of contract.
Case 3:21-cv-01418-EMC Document 186-5 Filed 03/28/23 Page 46 of 58
Exhibit 1: Kidder Resume
8
Varentec, Inc. v. Gridco, Inc. et al. Before United States District Court for the District of
Delaware, C.A. No. 16-217-RGA. Retained by counsel for defendants re: irreparable
harm in the context of a motion for preliminary injunction.
Connectus, LLC d/b/a eDegree Advisor v. Ampush Media, Inc. and DGS Edu LLC.
Before United States District Court, Middle District of Florida, Tampa Division, Case
No.: 8:15-cv-02778-VMC-JSS. Retained by counsel for plaintiffs re: damages from
breach of contract, unjust enrichment and unfair competition.
Doug Baird, Doug Hesse and Bob Schmitt Derivatively on Behalf of BlinkMind, Inc. v.
Joe Baird, Nathan Stratton, Michael Tessler, Exario Networks, Inc., and BroadSoft, Inc.
Before District Court of Harris County, Texas, 270th Judicial District, Cause No. 2015-
16576. Retained by counsel for defendants Joe Baird, Nathan Stratton and BroadSoft re:
damages from theft of trade secrets.
Integra LifeSciences Corp., Integra LifeSciences Sales LLC, Confluent Surgical, Inc., and
Incept LLC, v. HyperBranch Medical Technology, Inc. Before United States District
Court, District of Delaware, Case No. C.A. No. 15-1819 (LPS)(CJB). Retained by
counsel for defendant re: damages from patent infringement.
Klaustech, LLC. v. AdMob, Inc. Before United States District Court, Northern District of
California, Oakland Division. Case No. 10-CV-05899-JSW. Retained by counsel for
defendant re: damages from patent infringement.
Google LLC, v. Anthony Scott Levandowski and Lior Ron. Before JAMS, San
Francisco, Case No. 1100086069 & 1100086032. Retained by counsel for plaintiff re:
damages from breach of contract, fraud, and disloyalty.
Express Mobile, Inc., v. Svanaco, Inc., BigCommerce, Inc. Before United States District
Court For the Eastern District of Texas, Marshall Division. Retained by counsel for
defendant re: damages from patent infringement.
Safeway, Inc. v. Sheppard Mullin Richter & Hampton, LLP. Before JAMS, San
Francisco, Case No. 1220052996. Retained by counsel for defendant re: damages from
legal malpractice.
Juliana Griffo v. Oculus VR, Inc. and Palmer Luckey. Before United States District
Court, Central District of California, Southern Division (Santa Ana), Case No. 8:15-cv-
01228-DOC (JCGx). Retained by counsel for defendants re: damages from copyright
infringement.
Beijing Choice Electronic Technology Co., Ltd. v. Contec Medical Systems USA INC.
and Contec Medical Systems Co., Ltd. Before United States District Court, Northern
District of Illinois, Case No: 18-cv-00825. Retained by counsel for defendants re:
irreparable harm in the context of a motion for a preliminary injunction.
Case 3:21-cv-01418-EMC Document 186-5 Filed 03/28/23 Page 47 of 58
Exhibit 1: Kidder Resume
9
Alarm.com, Inc. and ICN Acquisition, LLC v. SecureNet Technologies, LLC. Before
United States District Court, District of Delaware. Case No.: 1:15-cv-00807-GMS.
Retained by counsel for defendants re: damages from patent infringement.
Ameranth, Inc. v. Mobo Systems (d/b/a Olo). Before United States District Court,
Southern District of California, San Diego Division. Case No.: 3:12-cv-01642-JLS-NLS.
Retained by counsel for defendant re: damages from patent infringement.
International Longshore and Warehouse Union and Pacific Maritime Association vs.
ICTSI Oregon, Inc. Before the United States District Court for the District of Oregon.
Case No. 3:12-cv-01058-SI. Retained by counsel for plaintiff and counterclaim
defendant re: damages from labor slowdown.
International Code Council, Inc. v. UpCodes, Inc., Garrett Reynolds and Scott Reynolds.
Before the United States District Court for the Southern District of New York. Case No.
1:17-cv-6261. Retained by counsel for defendants re: damages from copyright
infringement.
United States of America v. Sushovan Tareque Hussain. Before the United States District
Court, Northern District of California. Case No. CR 16-00462 CRB. Retained by
counsel for defendant re: gains from fraud.
Nevro Corp., v. Stimwave Technologies, Inc. Before the United States District Court for
the District of Delaware. Case No. 19-325 (CFC). Retained by counsel for defendant re:
irreparable harm in the context of a motion for a preliminary injunction.
CellInfo, LLC v. American Tower Corporation and American Tower Do Brasil. Before
American Arbitration Association, Boston Regional Office. Case No. 01-18-0004-5894.
Retained by counsel for plaintiff re: damages from misappropriation of trade secrets and
confidential information.
Booker T. Huffman v. Activision Publishing, Activision Blizzard and Major League
Gaming Corp. Before the United States District Court for the Eastern District of Texas,
Marshall Division. Case No. 2:19-cv-00050-RWS-RSP. Retained by counsel for
defendant re: damages from copyright infringement.
PTP OneClick, LLC v. Avalara, Inc. Before the United States District Court, Western
District of Washington at Seattle. Case No. 2:19-cv-00640-JLR. Retained by counsel for
defendant re: damages from misappropriation of trade secrets and breach of contract.
Arendi S.A.R.L. v. Motorola Mobility LLC. Before the United States District Court,
District of Delaware. Case No. 12-1601-LPS. Retained by counsel for defendant re:
damages from patent infringement.
Case 3:21-cv-01418-EMC Document 186-5 Filed 03/28/23 Page 48 of 58
Exhibit 1: Kidder Resume
10
Arendi S.A.R.L. v. Google LLC. Before the United States District Court, District of
Delaware. Case No. 13-919-LPS. Retained by counsel for defendant re: damages from
patent infringement.
FurnitureDealer.net, Inc. v. Amazon.com, Inc., and COA, Inc. d/b/a Coaster Company of
America. Before the United States District Court, District of Minnesota. Case No. 18-
232 (JRT/HB). Retained by counsel for defendant re: copyright infringement.
Crown Building Maintenance, Inc. v. Metro Services Group, Jeff Dachenhaus, Mark
Nolan and Derek Schulze. Before the Superior Court of the State of California, County
of San Francisco. Case No. CGC-18-566118. Retained by counsel for plaintiffs re:
damages from breach of contract and misappropriation of trade secrets.
Hong Kong Ucloudlink Network Technology Limited v. SIMO Holdings Inc. and
Skyroam, Inc. Before the United States District Court, Northern District of California.
Case No. 8-cv-05031. Retained by counsel for plaintiffs re: damages from patent
infringement.
Fisher & Paykel Healthcare, Ltd v. Flexicare Incorporated. Before the United States
District Court, Central District of California. Case No. 8:19-cv-00835-JVS-DFM.
Retained by counsel for defendants re: damages from patent infringement.
Hughes & Company Construction, Inc. v. Weber Hung Family Trust. Before American
Arbitration Association. Case No. 01-20-0004-8744. Retained by counsel for defendants
/ counterclaimants re: damages from breach of contract.
Equicare Health Inc. v. Varian Medical Systems, Inc. Before the American Arbitration
Association. Case No.: 01-19-0002-4132. Retained by counsel for defendant re:
damages from breach of contract.
Personalized Media Communications, LLC v. Netflix, Inc. Before the United States
District Court, Eastern District of Texas, Marshall Division, Case No. 2:19-cv-00091-
JRG. Retained by counsel for defendant re: damages from patent infringement.
Red Hydrogen, LLC v. CloudMinds (HK) Ltd. Before JAMS Arbitration, JAMS Ref.
No. 1220062943. Retained by counsel for defendant re: factors relating to alter ego and
damages from breach of contract.
USC IP Partnership, L.P., v. Facebook, Inc. Before the United States District Court for
the Western District of Texas, Waco Division, Case No. 6:20-cv-00555-ADA. Retained
by counsel for defendant re: damages from patent infringement.
Brad Peters, David Gray and Paul Staelin v. Infor (US), Inc. Before the United States
District Court, Northern District of California, San Francisco Division, Civil Action No.
19-cv-8102 Retained by counsel for defendants / counter-claimant re: damages from
breach of contract.
Case 3:21-cv-01418-EMC Document 186-5 Filed 03/28/23 Page 49 of 58
Exhibit 1: Kidder Resume
11
Netlist v. Samsung Electronics, Co., Ltd. Before United States District Court, Central
District of California, Southern Division, Case No. 8:20-cv-993-MCS (ADSx). Retained
by counsel for defendants re: damages from breach of contract.
Alexander Walker v. Kitty Hawk Corporation. Before JAMS, JAMS Ref. No.
1100110678. Retained by counsel for defendants re: damages from alleged fraud and
breach of contract.
Contour Data Solutions, LLC. v. Gridforce Energy Management LLC, NAES
Corporation, CDW Corporation, CDW Direct. Before United States District Court,
Eastern District of Pennsylvania, Case No. 2:20-CV-03241. Retained by counsel for
Gridforce and NAES re: breach of contract.
Rex Medical, L.P. v. Intuitive Surgical, Inc., Intuitive Surgical Operations, Inc. and
Intuitive Surgical Holdings, LLC. Before United States District Court, District of
Delaware, Civil Action No. 19-cv-5-MN. Retained by counsel for Rex Medical re:
damages from patent infringement.
Estech Systems, Inc. v. Howard Midstream Energy Partners d/b/a Howard Energy
Partners. Before United States District Court, Western District of Texas, Waco Division,
Civil Action No.: 6-20-cv-00777. Retained by counsel for Howard Energy Partners re:
damages from patent infringement.
Bay Materials, LLC v. 3M Company. Before United States District Court, District of
Delaware, Civil Action No. 21-cv-1610-RGA-JLH. Retained by counsel for 3M
Company re: irreparable harm in the context of a motion for a preliminary injunction.
RSB Spine, LLC v. DePuy Synthes Sales, Inc. and DePuy Synthes Products, Inc. Before
United States District Court, District of Delaware, C.A. No. 19-1515-RGA. Retained by
counsel for RSB Spine re: damages from patent infringement.
RSB Spine, LLC v. Medacta USA, Inc. Before United States District Court, District of
Delaware, C.A. No. 18-1973-RGA. Retained by counsel for RSB Spine re: damages
from patent infringement.
RSB Spine, LLC v. Precision Spine, Inc. Before United States District Court, District of
Delaware, C.A. No. 18-1974-RGA. Retained by counsel for RSB Spine re: damages
from patent infringement.
Quest Media & Supplies v. Aerojet Rocketdyne, Inc. Before Superior Court of the State
of California, County of Sacramento, Case No. 34-2017-00207975. Retained by counsel
for Quest Media re: damages from breach of contract.
Case 3:21-cv-01418-EMC Document 186-5 Filed 03/28/23 Page 50 of 58
Exhibit 1: Kidder Resume
12
Dennis P. Flynn v. Sara L. Flynn and Christopher J. Dressel. Before JAMS, Reference
No. 1100111518. Retained by counsel for Dennis Flynn re: dissolution of partnerships
and valuation of real estate interests.
AlphaSense v. Sentieo. Before United States District Court, District of Delaware, C.A.
No. 21-1011-CFC. Retained by counsel for Sentieo re: irreparable harm in the context of
a motion for preliminary injunction.
Case 3:21-cv-01418-EMC Document 186-5 Filed 03/28/23 Page 51 of 58
Cat Brook, Rasheed Shabazz,
et. al. v. Thomson
Exhibit 2: Documents Considered
Highly Confidential.
Attorneys' Eyes Only
Documents Reviewed
Exhibit 2
Legal Filings
Class Action Complaint, December 3, 2020
Defendant Thomson Reuters Corporation's Answer and Affirmative Defenses to Plaintiffs' Class
Action Complaint, September 10, 2021
Defendant Thomson Reuters Corporation's First Supplemental Answers and Objections to
Plaintiffs' First Set of Interrogatories to Defendant, May 24, 2022
Defendant Thomson Reuters Corporation's Responses and Objections to Plaintiffs' First Set of
Interrogatories to Defendant, April 4, 2022
Ivie v. Kraft Foods Global, Inc. , NDCAL, C-12-02554-RMW, Jan. 14, 2015.
Notice of Defendant's Motion to Dismiss Pursuant to FRCP 12(b)(6), and Motion to Strike
Pursuant to California Code of Civil Procedure § 425.16, and Memorandum In Support,
April 5, 2021
Order Granting In Part and Denying in Part Defendant's Motion to Dismiss, August 16, 2021
Plaintiffs' First Set of Interrogatories to Defendant, March 4, 2022
Plaintiffs' First Set of Requests for Production of Documents to Defendant, October 1, 2021
Plaintiffs' Second Set of Interrogatories to Defendant, March 11, 2022
Stipulation to Set Case Schedule and Order, August 26, 2021
Thomson Reuters First Supplemental Answers to Plaintiffs First Set of Interrogatories, May 24, 2022
Thomson Reuters Responses to Plaintiffs First Set of Interrogatories, Attachment A, April 4, 2022
Expert Reports
Professor Joseph Turow, June 1, 2022, revised July 25, 2022
Terry Lloyd, June 1, 2022, revised July 25, 2022
Depositions
Deposition and Exhibits of Dorian Buckethal, May 18, 2022
Deposition and Exhibits of Paul Godlewski, May 6, 2022
Deposition and Exhibits of Steven Fox, May 16, 2022
Deposition and Exhibits of Terry Lloyd, August 22, 2022.
Deposition and Exhibits of Joseph Turow, August 26, 2022.
Deposition and Exhibits of Rasheed Shabazz, August 18, 2022
Deposition and Exhibits of Cat Brooks, August 10, 2022
Correspondences
Conversations with Irene Caratto and Kelly Shelton, July 20, 2022
Financial Filings
Thomson Reuters Annual Report, 2021, pp. 6 - 8.
Literature & Articles
Page 1 of 5
Case 3:21-cv-01418-EMC Document 186-5 Filed 03/28/23 Page 52 of 58
Cat Brook, Rasheed Shabazz,
et. al. v. Thomson
Exhibit 2: Documents Considered
Highly Confidential.
Attorneys' Eyes Only
"Gross Domestic Product by State, 4th Quarter 2021 and Year 2021 (Preliminary)." Bureau of
Economic Analysis, U.S. Department of Commerce, March 31, 2022,
https://www.bea.gov/news/2022/gross-domestic-product-state-4th-quarter-2021-and-year-2021-
preliminary. Press Release.
Adam S. Chilton & Omri Ben-Shahar, "Simplification of Privacy Disclosures: An Experimental
Test" (Coase-Sandor Working PaperSeries in Law and Economics No. 737, 2016).
Dixit, Avinash and Robert Pindyck, Investment Under Uncertainty , 1994, Princeton University
Press.
Jones, Charles I., and Christopher Tonetti. 2020. "Nonrivalry and the Economics of Data." American
Economic Review , 110 (9): 2819-58.
Laudon, Kenneth C. "Markets and Privacy." Communications of The ACM , September 1996, 39
(9): 92-104.
Restatement (Third) of Restitution and Unjust Enrichment § 51 (2011).
Shapiro, C., Varian, H., Information Rules: A Strategic Guide to the Network Economy , 1999,
Harvard Business School Press, pp. 3-6.
Thomson Reuters CLEAR Information Security Summary, December 2021.
Zakrzewski, Cat and Aaron Schaffer., "The Technology 202: Activists are suing Thomson Reuters
over its sale of personal data." The Washington Post , March 18, 2021.
Websites
https://asc.fasb.org/glossary
https://legal.thomsonreuters.com/en/insights/case-studies/bank-investigation-case-study
https://legal.thomsonreuters.com/en/insights/case-studies/clear-investigation
https://legal.thomsonreuters.com/en/insights/case-studies/kinecta-case-study-clear
https://legal.thomsonreuters.com/en/insights/case-studies/thomson-reuters-clear-helps-find-absent-
parents-for-child-support
https://legal.thomsonreuters.com/en/products/clear-investigation-software
https://legal.thomsonreuters.com/en/products/clear-investigation-software/plans-pricing
https://legal.thomsonreuters.com/en/products/clear-investigation-software/plans-pricing#corporate
https://legal.thomsonreuters.com/en/products/clear-investigation-software/plans-pricing#publicsafety
https://legal.thomsonreuters.com/en/products/clear-investigation-software/plans-pricing?searchid=
TRPPCSOL/Google/LegalUS_IV_CLEAR_Main_Se
https://ucr.fbi.gov/crime-in-the-u.s/2018/crime-in-the-u.s.-2018/tables/table-69/table-69.xls/
@@template-layout-view?override-view=data-declaration.
https://www.bea.gov/sites/default/files/2022-03/qgdpstate0322.pdf.
https://www.capolicylab.org/pandemic-patterns-california-is-seeing-fewer-entrances-and-more-
exits-april-2022-update/.
https://www.macrotrends.net/countries/USA/united-states/population
https://www.nysscpa.org/professional-resources/accounting-terminology-guide#sthash.
tWSUqFQr.dpbs
Bates-Stamped Documents
PLAINTIFFS_011325 - 336
PLAINTIFFS_011337 - 345
PLAINTIFFS_011346 - 357
PLAINTIFFS_011358
Page 2 of 5
Case 3:21-cv-01418-EMC Document 186-5 Filed 03/28/23 Page 53 of 58
Cat Brook, Rasheed Shabazz,
et. al. v. Thomson
Exhibit 2: Documents Considered
Highly Confidential.
Attorneys' Eyes Only
PLAINTIFFS_011359
PLAINTIFFS_011360
PLAINTIFFS_011361
PLAINTIFFS_011362
PLAINTIFFS_011363 - 364
PLAINTIFFS_011365
PLAINTIFFS_011473 - 476
TR-BROOKS002367
TR-BROOKS002588
TR-BROOKS014840 - 5038
TR-BROOKS016716 - 758
TR-BROOKS016867 - 933
TR-BROOKS016934 - 959
TR-BROOKS016961 - 7028
TR-BROOKS017029 - 068
TR-BROOKS017074
TR-BROOKS018218 - 219
TR-BROOKS018228
TR-BROOKS018254
TR-BROOKS018497
TR-BROOKS018675
TR-BROOKS018682 - 687
TR-BROOKS018837 - 840
TR-BROOKS018912 - 913
TR-BROOKS018977 - 978
TR-BROOKS019093 - 115
TR-BROOKS019229 - 231
TR-BROOKS019293
TR-BROOKS019397 - 399
TR-BROOKS019433
TR-BROOKS019802
TR-BROOKS019827 - 830
TR-BROOKS019904 - 909
TR-BROOKS019990
TR-BROOKS020153 - 154
TR-BROOKS020168 - 171
TR-BROOKS020178
TR-BROOKS020279 - 282
TR-BROOKS020376 - 379
TR-BROOKS020399
TR-BROOKS020412 - 418
TR-BROOKS020430 - 443
TR-BROOKS020519 - 520
TR-BROOKS020536 - 539
TR-BROOKS020766 - 767
TR-BROOKS020771 - 775
TR-BROOKS020790 - 796
Page 3 of 5
Case 3:21-cv-01418-EMC Document 186-5 Filed 03/28/23 Page 54 of 58
Cat Brook, Rasheed Shabazz,
et. al. v. Thomson
Exhibit 2: Documents Considered
Highly Confidential.
Attorneys' Eyes Only
TR-BROOKS024042 - 066
TR-BROOKS024549 - 550
TR-BROOKS025679 - 681
TR-BROOKS026283 - 284
TR-BROOKS029281
TR-BROOKS029282
TR-BROOKS031286 - 287
TR-BROOKS035635 - 9381
TR-BROOKS047029 - 039
TR-BROOKS047405
TR-BROOKS050846 - 850
TR-BROOKS051170
TR-BROOKS052564
TR-BROOKS053386
TR-BROOKS053483
TR-BROOKS053499
TR-BROOKS054545
TR-BROOKS060007 - 008
TR-BROOKS061093
TR-BROOKS061094
TR-BROOKS061893 - 897
TR-BROOKS061969
TR-BROOKS061971
TR-BROOKS064661
TR-BROOKS064718
TR-BROOKS064995
TR-BROOKS065056 - 058
TR-BROOKS065060
TR-BROOKS065185
TR-BROOKS066326 - 350
TR-BROOKS066418
TR-BROOKS067628
TR-BROOKS067976 - 8007
TR-BROOKS068983
TR-BROOKS073513
TR-BROOKS074445 - 447
TR-BROOKS074471
TR-BROOKS074600
TR-BROOKS076076 - 083
TR-BROOKS077436 - 438
TR-BROOKS078674 - 698
TR-BROOKS082062
TR-BROOKS083972 - 4017
TR-BROOKS086877
TR-BROOKS090324
TR-BROOKS106480
TR-BROOKS107599 - 617
Page 4 of 5
Case 3:21-cv-01418-EMC Document 186-5 Filed 03/28/23 Page 55 of 58
Cat Brook, Rasheed Shabazz,
et. al. v. Thomson
Exhibit 2: Documents Considered
Highly Confidential.
Attorneys' Eyes Only
TR-BROOKS107761
TR-BROOKS107762
TR-BROOKS110695 - 699
TR-BROOKS144207 - 210
TR-BROOKS114745
TR-BROOKS122783
TR-BROOKS123263 - 277
TR-BROOKS124419
TR-BROOKS125018 - 078
TR-BROOKS127538 - 540
TR-BROOKS127541
TR-BROOKS129381
TR-BROOKS135972 - 988
TR-BROOKS137048 - 053
TR-BROOKS144611 - 615
TR-BROOKS157508 - 614
TR-BROOKS174416 - 418
TR-BROOKS176757 - 764
Page 5 of 5
Case 3:21-cv-01418-EMC Document 186-5 Filed 03/28/23 Page 56 of 58
Exhibit 3 - FBI Crime Stats Table 69
Highly Confidential -
Attorneys Eyes Only
Cat Brook, Rasheed Shabazz, et. al. v. Thomson
United States FBI Crime Statistics, Table 69
Source https //ucr.fbi.gov/crime-in-the-u.s/2018/crime-in-the-u.s.-2018/tables/table-69/table-69.xls/@@template-layout-view?override-view=data-declaration.
Table 69
Arrests
by State, 2018
State
Total
all
classes1
Violent
crime2
Property
crime2
Murder and
nonnegligent
manslaughte
r
Rape3
Robbery
Aggravated
assault
Burglary
Larceny-
theft
Motor
vehicle
theft
Arson
Other
assaults
Forgery and
counterfeitin
g
Fraud
Embezzlemen
t
property;
buying,
receiving,
possessin
g
Vandalism
Weapons;
carrying,
possessing
,
etc
Prostitution
and
commercialize
d
vice
Sex
offenses
(except
rape and
prostitution)
Drug
abuse
violations Gambling
against
the
family
and
children
Driving
under the
influence
Liquor
laws
Drunkenness
4
Disorderl
y
conduct
Vagranc
y
All other
offenses
(except
traffic)
Suspicio
n
Curfew
and
loitering
law
violations
Number
of
agencies
2018
estimated
population
Percent
of Total
Arrests
Percent of
Population
Under 18
3,578
296
959
13
22
111
150
212
627
112
8
608
2
19
0
92
82
88
0
9
130
0
11
26
131
24
250
0
851
0
0
171
3,070,799
1.5%
1.1%
Total all ages
126,404
4,761
15,609
214
245
919
3,383
2,352
12,332
840
85
13,027
768
2,103
112
1,756
1,004
1,585
0
446
8,217
0
420
6,391
1,434
5,300
1,815
34
61,622
0
0
Under 18
1,687
206
439
4
35
21
146
96
218
103
22
374
5
6
6
4
109
18
0
34
183
0
3
35
65
1
10
0
184
0
5
32
733,747
0.4%
0.3%
Total all ages
30,620
2,686
3,763
38
149
367
2,132
602
2,392
726
43
4,943
154
201
54
120
1,103
387
2
263
1,046
0
174
3,148
592
47
843
17
11,072
0
5
Under 18
20,478
1,127
3,298
16
65
388
658
535
2,414
325
24
3,866
21
77
12
87
1,631
247
2
221
3,239
1
248
141
1,060
74
1,424
27
3,022
0
653
91
6,586,181
3.0%
2.4%
Total all ages
256,785
11,628
32,622
281
328
1,940
9,079
3,883
26,621
1,711
407
25,198
1,121
2,055
854
1,087
10,177
3,093
349
1,386
32,272
2
2,448
19,200
7,082
11,514
14,723
567
78,700
54
653
Under 18
7,697
427
1,423
6
48
82
291
291
1,030
93
9
1,668
18
33
4
187
311
114
1
17
925
0
3
50
158
74
579
0
1,446
0
259
241
2,640,116
1.4%
1.0%
Total all ages
120,240
4,650
12,516
141
238
474
3,797
1,748
10,118
594
56
11,688
820
852
49
1,736
1,544
1,112
136
83
17,954
6
434
5,761
1,265
5,035
2,301
303
51,736
0
259
Under 18
42,958
7,210
7,484
84
245
2,937
3,944
2,864
3,048
1,402
170
8,026
37
118
17
915
2,030
2,748
12
876
2,967
8
1
474
930
522
1,007
88
6,836
0
652
700
39,431,921
12.8%
14.7%
Total all ages
1,093,080
110,236
97,247
1,409
2,539
16,670
89,618
35,230
42,468
18,020
1,529
81,812
4,118
6,105
921
16,227
16,652
28,290
6,418
8,901
219,251
403
268
127,250
5,948
58,286
3,451
7,290
293,353
1
652
Under 18
17,906
758
3,161
18
90
211
439
338
2,455
314
54
1,895
4
78
13
22
700
279
2
145
2,257
0
37
217
1,056
0
1,762
0
4,747
0
773
180
4,952,541
2.3%
1.8%
Total all ages
193,216
7,832
24,136
195
549
1,166
5,922
2,301
19,199
2,437
199
16,477
688
2,243
112
526
4,843
2,313
376
521
16,172
7
2,466
20,353
7,007
144
6,887
549
78,790
1
773
Under 18
7,106
325
1,359
6
27
153
139
206
862
273
18
1,763
10
41
1
135
284
153
0
64
489
1
34
18
18
0
1,460
0
950
0
1
104
3,457,743
1.1%
1.3%
Total all ages
95,709
3,399
12,312
79
212
870
2,238
1,624
9,834
778
76
17,370
582
921
140
692
1,640
1,088
184
360
8,087
10
1,363
7,484
96
11
10,505
41
29,423
0
1
Under 18
2,851
302
547
2
15
86
199
134
370
41
2
788
4
48
2
62
114
82
1
28
279
1
0
0
49
1
228
0
283
0
32
52
964,106
0.3%
0.4%
Total all ages
28,742
1,965
5,337
33
77
391
1,464
688
4,511
116
22
6,121
210
1,348
163
324
755
322
121
107
3,707
9
185
427
669
323
1,164
164
5,289
0
32
Under 18
505
92
34
0
0
64
28
0
32
2
0
111
0
1
0
5
12
13
0
2
10
0
0
0
1
0
53
0
171
0
0
2
0
0.2%
0.0%
Total all ages
13,682
185
86
0
2
113
70
0
76
9
1
411
3
3
0
14
35
42
0
20
290
0
2
9
817
49
300
13
11,403
0
0
Under 18
48,213
3,218
12,686
46
253
1,090
1,829
3,040
7,380
2,209
57
8,152
48
401
32
119
890
799
0
290
5,399
4
0
69
405
0
0
0
15,701
0
0
596
21,278,278
8.4%
7.9%
Total all ages
715,424
34,907
89,456
712
1,936
5,761
26,498
14,757
66,157
8,295
247
80,570
1,989
11,207
1,086
1,632
6,129
6,604
1,920
2,862
134,142
123
0
32,127
10,590
0
0
0
300,080
0
0
Under 18
15,400
836
3,161
50
24
233
529
590
2,311
228
32
2,451
32
74
1
241
467
391
4
264
2,053
2
122
139
207
14
1,387
77
3,328
6
143
258
6,742,246
2.4%
2.5%
Total all ages
200,643
7,920
22,314
307
168
990
6,455
2,689
18,597
913
115
16,260
1,573
2,298
127
2,147
2,919
2,619
322
1,629
37,291
152
2,607
23,449
1,467
1,273
9,230
366
64,518
19
143
Under 18
1,762
104
309
1
9
46
48
32
233
40
4
307
1
3
0
51
7
12
0
31
337
0
0
11
49
0
18
0
413
0
109
2
1,148,121
0.3%
0.4%
Total all ages
24,487
828
2,413
40
75
204
509
290
1,844
252
27
2,968
51
109
0
449
92
185
104
125
1,873
149
17
4,288
319
0
463
0
9,945
0
109
Under 18
5,993
192
978
2
57
19
114
136
766
48
28
759
5
30
7
14
257
94
1
71
928
0
7
78
196
25
188
0
2,046
3
114
74
1,554,954
0.6%
0.6%
Total all ages
52,292
1,542
4,896
16
162
90
1,274
777
3,911
157
51
4,559
132
355
47
175
788
283
12
243
8,777
1
716
5,689
874
333
1,455
8
21,290
3
114
Under 18
7,366
786
1,876
18
29
564
175
143
897
826
10
1,297
2
14
0
45
264
620
0
17
834
47
6
1
27
0
564
0
916
0
50
2
2,865,349
1.0%
1.1%
Total all ages
86,947
5,581
14,859
416
437
2,422
2,306
1,015
9,514
4,267
63
16,749
127
247
0
84
2,696
6,798
115
350
17,060
706
355
2,825
181
0
3,987
28
14,149
0
50
Under 18
8,831
615
1,784
9
29
163
414
199
1,339
220
26
1,652
20
63
8
24
342
203
0
64
1,155
0
203
36
457
16
518
9
1,556
2
104
202
4,025,425
1.5%
1.5%
Total all ages
125,536
7,236
14,135
184
212
1,118
5,722
1,617
11,037
1,408
73
10,492
968
1,434
210
289
1,054
2,024
204
540
25,058
7
912
11,890
2,824
3,261
3,177
39
39,648
30
104
Under 18
0.0%
0.0%
Total all ages
Under 18
1,639
43
105
0
12
4
27
17
77
10
1
165
0
2
7
8
42
3
0
12
202
0
14
31
335
0
108
0
562
0
0
213
1,308,859
0.4%
0.5%
Total all ages
32,837
387
1,005
5
43
15
324
116
802
78
9
1,590
58
271
25
120
285
83
1
44
2,242
0
152
4,554
1,971
119
946
0
18,984
0
0
Under 18
2,985
161
691
9
24
59
69
125
428
107
31
767
6
12
16
86
77
24
0
28
257
0
2
39
11
27
137
0
643
0
1
332
3,500,586
2.4%
1.3%
Total all ages
205,075
1,982
12,269
126
252
517
1,087
2,060
9,363
723
123
9,649
812
989
378
1,459
806
508
95
237
19,355
1
4,729
14,812
168
14,231
3,664
23
118,907
0
1
Under 18
16,533
1,175
3,683
31
97
202
845
1,099
2,223
328
33
3,231
52
33
0
408
390
439
4
117
1,496
6
88
15
78
12
2,076
29
2,963
2
236
165
3,954,330
2.1%
1.5%
Total all ages
176,520
10,465
30,218
334
443
1,376
8,312
5,163
23,652
1,304
99
21,314
703
1,283
138
2,761
3,019
3,648
405
1,102
30,437
33
1,727
5,650
1,287
2,880
7,178
250
51,773
13
236
Under 18
2,845
51
673
3
9
16
23
96
532
39
6
531
6
16
3
11
205
6
0
33
304
0
1
22
395
0
95
0
483
0
10
134
1,338,404
0.5%
0.5%
Total all ages
40,851
756
5,456
16
73
135
532
561
4,615
235
45
4,877
209
480
46
116
1,032
144
54
167
3,692
2
137
5,811
2,049
15
1,360
1
14,432
5
10
Under 18
17,825
1,907
3,705
22
83
1,048
754
608
2,462
525
110
4,697
19
29
5
47
784
615
5
153
2,046
19
13
41
311
1
967
16
2,369
8
68
153
5,879,299
2.1%
2.2%
Total all ages
181,434
10,327
21,592
266
477
3,283
6,301
3,851
15,404
2,030
307
21,826
440
866
103
337
2,527
3,694
809
690
31,914
76
1,821
18,150
4,439
56
4,843
204
56,390
262
68
Under 18
4,508
464
615
0
17
88
359
132
428
39
16
1,343
6
25
1
67
299
72
1
56
132
1
21
18
103
17
227
0
1,040
0
0
327
5,884,293
1.2%
2.2%
Total all ages
101,681
6,608
10,308
21
315
709
5,563
1,478
8,263
512
55
17,237
391
1,087
112
794
2,207
913
360
304
7,125
9
1,185
8,280
1,280
5,168
3,554
3
34,756
0
0
Under 18
13,267
1,044
3,054
12
174
229
629
497
2,266
253
38
2,711
23
151
42
221
416
284
5
110
1,668
0
4
166
282
0
498
0
2,338
0
250
611
9,857,904
2.8%
3.7%
Total all ages
235,757
12,793
23,212
299
970
1,190
10,334
3,034
18,770
1,201
207
29,164
702
3,767
1,149
2,019
2,873
4,798
216
663
30,320
26
2,642
26,130
4,739
284
5,724
107
84,179
0
250
Under 18
19,391
864
4,165
2
100
351
411
378
3,318
441
28
2,419
27
188
3
297
697
316
0
105
1,698
2
15
154
1,609
0
2,110
108
4,154
0
460
378
5,570,925
1.7%
2.1%
Total all ages
147,370
5,482
23,768
101
588
1,005
3,788
2,014
20,063
1,595
96
14,842
1,075
3,428
15
1,964
2,662
1,859
153
878
20,404
30
585
20,186
7,099
23
8,994
225
33,238
0
460
Under 18
2,453
80
562
2
9
28
41
120
402
35
5
348
8
12
2
31
42
69
0
8
190
0
197
41
27
15
301
4
432
0
84
53
1,161,807
0.7%
0.4%
Total all ages
60,902
1,201
7,352
58
67
322
754
1,003
5,998
314
37
4,884
303
704
275
642
571
945
16
119
8,003
74
2,160
5,370
747
3,039
3,102
72
21,239
0
84
Under 18
15,560
893
2,886
32
102
265
494
408
2,156
280
42
2,821
19
50
14
367
697
236
5
308
2,018
1
76
108
484
7
1,210
9
2,819
0
532
331
5,406,785
2.3%
2.0%
Total all ages
197,865
9,005
27,019
369
507
1,426
6,703
3,325
21,098
2,383
213
19,443
1,387
2,088
249
2,814
3,484
3,565
269
1,089
32,982
38
2,128
11,874
2,985
197
6,333
773
69,611
0
532
Under 18
3,722
81
666
1
11
10
59
58
546
57
5
501
1
10
2
0
189
15
0
15
358
0
35
38
499
0
254
0
760
0
298
97
995,183
0.3%
0.4%
Total all ages
27,357
1,174
4,114
10
64
97
1,003
296
3,487
305
26
3,962
100
196
40
110
762
75
12
81
2,732
0
321
3,794
1,406
0
2,003
10
6,167
0
298
ILLINOIS6
INDIANA
KANSAS
MISSISSIPPI
MINNESOTA
MISSOURI
IOWA8
MONTANA
MASSACHUSETTS
MAINE
LOUISIANA
KENTUCKY
MICHIGAN
MARYLAND
IDAHO
ALABAMA
ALASKA
ARIZONA
ARKANSAS
CALIFORNIA
COLORADO
CONNECTICUT
DELAWARE
DISTRICT OF COLUMBIA5
HAWAII
FLORIDA6, 7
GEORGIA
Page 1 of 2
Case 3:21-cv-01418-EMC Document 186-5 Filed 03/28/23 Page 57 of 58
Exhibit 3 - FBI Crime Stats Table 69
Highly Confidential -
Attorneys Eyes Only
Table 69
Arrests
by State, 2018
State
Total
all
classes1
Violent
crime2
Property
crime2
Murder and
nonnegligent
manslaughte
r
Rape3
Robbery
Aggravated
assault
Burglary
Larceny-
theft
Motor
vehicle
theft
Arson
Other
assaults
Forgery and
counterfeitin
g
Fraud
Embezzlemen
t
property;
buying,
receiving,
possessin
g
Vandalism
Weapons;
carrying,
possessing
,
etc
Prostitution
and
commercialize
d
vice
Sex
offenses
(except
rape and
prostitution)
Drug
abuse
violations Gambling
against
the
family
and
children
Driving
under the
influence
Liquor
laws
Drunkenness
4
Disorderl
y
conduct
Vagranc
y
All other
offenses
(except
traffic)
Suspicio
n
Curfew
and
loitering
law
violations
Number
of
agencies
2018
estimated
population
Percent
of Total
Arrests
Percent of
Population
Under 18
6,985
207
1,426
6
46
90
65
65
1,222
121
18
1,255
5
61
4
105
394
78
0
66
1,006
0
199
63
504
1
341
0
1,142
0
128
118
1,516,162
0.6%
0.6%
Total all ages
53,007
1,671
6,581
36
213
247
1,175
398
5,735
391
57
7,474
236
1,066
63
736
1,693
775
92
314
8,993
0
945
4,630
2,355
1
1,851
13
13,390
0
128
Under 18
10,026
1,340
1,262
24
70
304
942
266
855
121
20
1,944
5
45
12
169
261
231
55
74
1,244
2
23
70
430
125
615
2
1,757
0
360
47
3,013,371
1.7%
1.1%
Total all ages
140,967
8,012
10,245
191
408
1,411
6,002
3,103
6,314
749
79
17,883
428
1,813
282
1,850
1,635
2,240
2,859
903
11,238
23
961
10,984
3,720
362
2,213
3,182
59,772
2
360
Under 18
3,283
59
349
0
8
16
35
39
278
23
9
600
2
12
6
37
205
4
0
31
344
0
5
29
267
209
68
0
1,026
0
30
184
1,317,257
0.5%
0.5%
Total all ages
46,413
872
3,681
10
76
144
642
309
3,186
165
21
5,668
237
758
91
553
1,254
146
24
130
6,522
5
187
5,053
1,989
3,844
884
99
14,386
0
30
Under 18
11,513
870
1,819
11
44
369
446
305
1,382
97
35
1,003
24
65
12
325
398
470
4
94
2,769
0
13
42
395
0
992
23
1,892
0
303
478
7,844,556
2.7%
2.9%
Total all ages
226,427
7,146
20,307
115
274
1,699
5,058
2,982
16,659
540
126
16,839
852
3,558
214
1,826
2,474
2,766
522
895
48,008
41
7,297
17,230
1,356
24
9,922
197
84,648
2
303
Under 18
3,203
231
478
7
10
22
192
69
360
40
9
664
1
7
4
45
86
66
1
10
472
0
18
53
132
7
161
0
765
1
1
59
1,406,211
0.9%
0.5%
Total all ages
74,786
4,232
7,309
67
103
425
3,637
916
5,993
359
41
8,588
171
324
123
1,015
1,015
535
87
70
5,375
3
1,388
6,464
1,333
568
1,497
30
34,655
3
1
Under 18
14,434
1,207
3,468
22
166
466
553
499
2,536
370
63
2,249
56
96
1
328
1,449
288
3
279
2,643
1
9
59
126
0
393
9
1,770
0
0
505
9,571,301
2.9%
3.6%
Total all ages
244,041
11,433
40,466
244
933
2,630
7,626
4,291
34,122
1,786
267
26,623
2,019
3,749
27
2,752
12,509
3,156
561
1,705
69,571
45
470
25,094
943
0
4,273
580
38,065
0
0
Under 18
11,088
757
2,673
30
13
412
302
708
1,655
290
20
2,013
20
118
22
351
478
386
0
72
1,414
0
18
141
173
0
686
2
1,759
0
5
204
5,380,474
2.4%
2.0%
Total all ages
200,411
9,180
26,731
351
165
2,177
6,487
5,451
20,037
1,115
128
22,676
863
4,412
799
2,682
3,006
4,052
148
608
26,936
39
3,181
27,915
1,490
0
4,183
15
61,490
0
5
Under 18
4,009
91
435
0
19
9
63
44
338
51
2
498
4
20
2
21
122
23
0
30
429
0
243
41
385
1
644
0
914
0
106
103
757,131
0.4%
0.3%
Total all ages
33,210
724
3,100
10
47
63
604
254
2,622
215
9
2,846
140
369
34
278
438
340
11
81
5,448
1
356
5,136
2,623
263
1,583
4
9,329
0
106
Under 18
20,003
873
2,995
17
79
275
502
396
2,351
199
49
4,360
14
119
0
337
760
327
5
92
1,675
5
138
61
409
41
1,722
1
5,685
2
382
417
9,011,984
2.6%
3.3%
Total all ages
218,433
8,085
29,413
237
470
1,548
5,830
3,354
25,004
777
278
30,939
770
2,089
14
2,701
3,142
3,948
792
451
39,708
23
1,275
13,723
4,793
5,855
9,835
20
60,471
4
382
Under 18
7,701
392
1,641
11
20
93
268
306
1,218
81
36
824
8
32
18
307
194
147
0
35
1,146
11
7
70
83
217
567
0
1,350
0
652
400
3,847,775
1.2%
1.4%
Total all ages
101,053
4,859
14,717
138
216
642
3,863
2,388
11,304
856
169
7,785
539
1,332
362
2,932
1,224
2,418
7
376
17,766
28
630
8,660
1,198
10,698
2,195
13
22,658
4
652
Under 18
8,618
351
1,720
4
32
110
205
196
1,310
157
57
1,117
9
55
3
32
553
97
0
49
1,653
0
2
104
632
0
546
0
1,388
0
307
194
3,710,013
1.5%
1.4%
Total all ages
125,230
4,232
18,015
55
217
824
3,136
1,725
14,123
1,911
256
10,735
616
1,871
54
611
3,677
2,113
281
348
13,605
1
342
13,707
2,891
29
6,210
3
45,582
0
307
Under 18
36,034
2,558
4,540
19
225
772
1,542
617
3,338
520
65
4,986
50
948
34
302
1,353
710
5
477
3,231
0
26
280
1,696
128
6,882
34
2,980
0
4,814
1,375
12,629,530
4.1%
4.7%
Total all ages
345,822
19,536
44,478
444
1,132
3,915
14,045
5,185
36,453
2,508
332
40,984
2,222
8,126
446
2,119
6,267
4,921
1,182
2,286
61,934
34
1,806
43,798
6,716
19,808
31,264
234
42,847
0
4,814
Under 18
2,373
121
406
0
13
44
64
70
302
30
4
441
1
16
3
33
138
85
0
11
104
0
25
2
21
0
552
0
396
0
18
48
1,057,315
0.3%
0.4%
Total all ages
25,996
954
2,660
4
77
194
679
498
1,992
158
12
4,169
125
551
75
352
915
347
63
82
2,049
4
74
2,423
337
11
2,269
0
8,518
0
18
Under 18
10,803
616
2,328
28
106
179
303
455
1,692
148
33
1,969
8
50
21
151
299
415
1
48
1,957
0
11
69
283
64
1,103
0
1,377
0
33
373
4,408,967
1.8%
1.6%
Total all ages
152,664
6,970
22,900
287
532
1,209
4,942
3,116
18,578
1,070
136
15,413
1,115
3,333
348
2,366
2,473
2,594
285
284
34,105
70
1,167
15,188
4,092
5,722
8,101
588
25,517
0
33
Under 18
4,886
92
657
1
8
17
66
89
506
55
7
689
2
63
4
26
196
95
0
10
819
0
242
51
447
0
408
0
1,010
0
75
114
816,012
0.5%
0.3%
Total all ages
44,268
1,046
2,866
11
43
72
920
294
2,348
201
23
4,451
124
816
31
152
536
250
15
51
8,108
1
490
5,891
2,164
99
2,409
616
14,077
0
75
Under 18
19,692
1,421
3,843
46
103
410
862
506
2,690
624
23
3,922
59
111
26
147
777
423
0
105
2,380
9
30
104
394
165
1,422
0
3,517
0
837
437
6,363,426
3.9%
2.4%
Total all ages
330,989
14,353
38,557
380
435
1,797
11,741
4,458
30,141
3,822
136
30,862
1,690
5,043
716
1,611
4,177
2,869
527
545
47,876
71
4,361
19,108
3,245
13,627
5,968
10
134,936
0
837
Under 18
55,458
3,946
10,127
67
363
1,242
2,274
1,560
7,577
926
64
11,680
121
320
36
157
1,525
895
34
380
9,893
15
153
349
1,072
567
1,144
21
11,378
0
1,645
876
26,829,159
8.6%
10.0%
Total all ages
729,902
34,166
74,627
747
2,068
5,708
25,643
9,009
60,263
4,952
403
92,541
4,332
6,320
447
862
7,246
12,968
3,987
2,442
139,188
304
3,931
69,643
8,237
54,286
7,549
497
204,684
0
1,645
Under 18
12,307
374
2,523
6
76
93
199
148
2,187
163
25
1,238
11
43
4
113
732
140
14
262
2,258
1
24
92
670
57
354
0
3,075
1
321
109
2,670,944
1.2%
1.0%
Total all ages
104,886
2,327
14,038
36
306
398
1,587
890
12,545
541
62
7,972
704
1,007
35
940
2,868
839
374
686
19,562
1
1,428
7,119
3,826
2,677
2,280
63
35,815
4
321
Under 18
702
40
100
0
16
4
20
13
74
9
4
163
0
8
2
3
75
12
0
9
38
0
5
15
45
0
79
0
108
0
0
72
615,720
0.2%
0.2%
Total all ages
14,334
684
1,637
11
86
38
549
220
1,343
54
20
1,519
52
306
56
98
321
36
1
38
902
0
201
2,576
82
0
853
0
4,972
0
0
Under 18
15,864
719
2,994
18
90
330
281
314
2,420
217
43
2,694
19
126
25
176
515
294
4
109
2,132
0
36
49
503
68
588
0
4,293
0
520
389
8,240,312
3.1%
3.1%
Total all ages
268,094
7,090
26,694
356
558
1,431
4,745
2,309
23,014
1,180
191
30,541
1,572
4,868
1,272
1,085
3,490
4,062
373
597
45,409
12
1,536
20,885
4,131
19,398
2,844
46
91,669
0
520
Under 18
10,996
866
2,274
19
81
323
443
411
1,617
216
30
2,764
8
17
1
165
798
215
4
140
1,053
0
4
152
554
10
263
0
1,699
0
9
198
6,423,244
2.0%
2.4%
Total all ages
171,466
8,384
25,722
150
536
1,767
5,931
4,292
19,762
1,504
164
24,701
677
1,130
55
3,245
4,798
1,824
211
550
11,283
7
257
27,632
1,721
78
2,460
120
56,599
3
9
Under 18
496
38
55
1
2
3
32
9
44
2
0
121
0
1
1
2
22
9
0
6
67
0
0
6
13
7
15
0
124
0
9
131
1,052,107
0.3%
0.4%
Total all ages
29,202
1,173
3,757
28
55
56
1,034
440
3,112
181
24
2,825
214
265
41
263
468
281
60
63
6,044
2
86
3,141
555
727
689
8
8,531
0
9
Under 18
35,109
1,023
4,622
14
220
258
531
472
3,531
578
41
2,419
37
96
36
335
1,443
444
5
521
3,150
1
96
213
1,786
0
6,994
27
10,437
0
1,424
422
5,730,204
2.9%
2.1%
Total all ages
245,015
7,907
25,731
171
925
1,172
5,639
2,080
22,087
1,431
133
16,251
899
2,220
368
1,125
5,531
3,683
451
1,587
31,066
19
2,116
24,368
10,654
0
31,008
530
78,077
0
1,424
Under 18
3,191
52
391
0
1
1
50
62
299
23
7
404
0
5
0
6
108
16
21
21
580
0
9
50
364
15
104
41
906
12
86
54
507,616
0.3%
0.2%
Total all ages
28,437
600
2,197
12
26
21
541
239
1,811
128
19
1,902
36
127
6
80
421
52
53
109
4,895
0
433
3,432
1,725
3,062
840
166
8,198
17
86
Under 18
597,409
269,030,693
Total all ages
8,526,509
1 Does not include traffic arrests.
2 Violent crimes are offenses of murder and nonnegligent manslaughter, rape, robbery, and aggravated assault. Property crimes are offenses of burglary, larceny-theft, motor vehicle theft, and arson.
3 The rape figures in this table are aggregate totals of the data submitted based on both the legacy and revised Uniform Crime Reporting definitions.
4 Drunkenness is not considered a crime in some states; therefore, the figures vary widely from state to state.
5 Includes arrests reported by the District of Columbia Fire and Emergency Medical Services Arson Investigation Unit and the Metro Transit Police. These agencies have no population associated with them.
6 See 2018 arrest data information in the data declaration for further explanation.
8 Limited data for 2018 were available for Iowa.
NOTE Because the number of agencies submitting arrest data varies from year to year, users are cautioned about making direct comparisons between 2018 arrest totals and those published in previous years' editions of Crime in the United States .
Further, arrest figures may vary widely from state to state because some Part II crimes are not considered crimes in some states.
WYOMING
SOUTH CAROLINA
UTAH
TEXAS
TENNESSEE
SOUTH DAKOTA
VERMONT
VIRGINIA
7 The Florida arrest counts for offenses against the family and children, drunkenness, disorderly conduct, vagrancy, suspicion, and curfew and loitering law violations are included under the category All other offenses.
WISCONSIN
WEST VIRGINIA
WASHINGTON
RHODE ISLAND
NEW MEXICO
NEW JERSEY
OKLAHOMA
PENNSYLVANIA
NORTH DAKOTA
NORTH CAROLINA
NEW YORK6
OREGON
OHIO
NEW HAMPSHIRE
NEVADA
NEBRASKA
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