Fighting the Fog: Evaluating the Clarity of Privacy Disclosures in the Age of CCPA

1]Rex Chen
Institute of Software Research,
School of Computer Science,
Carnegie Mellon University

2]Fei Fang
Institute of Software Research,
School of Computer Science,
Carnegie Mellon University

3]Thomas Norton
Center on Law and Information Policy (CLIP), School of Law,
Fordham University

4]Aleecia M. McDonald
Institute of Software Research,
School of Computer Science,
Carnegie Mellon University

5]Norman Sadeh
Institute of Software Research,
School of Computer Science,
Carnegie Mellon University

Vagueness and ambiguity in privacy policies threaten the ability of consumers to make informed choices about how businesses collect, use, and share their personal information. The California Consumer Privacy Act (CCPA) of 2018 was intended to provide Californian consumers with more control by mandating that businesses (1) clearly disclose their data practices and (2) provide choices for consumers to opt out of specific data practices. In this work, we explore to what extent CCPA's disclosure requirements, as implemented in actual privacy policies, can help consumers to answer questions about the data practices of businesses. First, we analyzed 95 privacy policies from popular websites; our findings showed that there is considerable variance in how businesses interpret CCPA's definitions. Then, our user survey of 364 Californian consumers showed that this variance affects the ability of users to understand the data practices of businesses. Our results suggest that CCPA's mandates for privacy disclosures, as currently implemented, have not yet yielded the level of clarity they were designed to deliver, due to both vagueness and ambiguity in CCPA itself as well as potential non-compliance by businesses in their privacy policies.

<concept_desc>Social and professional topics Privacy policies</concept_desc>
<concept_desc>Applied computing Law</concept_desc>
<concept_desc>Security and privacy Usability in security and privacy</concept_desc>
<concept_desc>Security and privacy Privacy protections</concept_desc>

[500]Social and professional topics Privacy policies
[500]Security and privacy Privacy protections
[500]Applied computing Law
[300]Security and privacy Usability in security and privacy

§ INTRODUCTION

Privacy policies are generally difficult to understand. Most privacy policies contain vague or ambiguously-worded statements, for which even legal experts often cannot agree on the correct interpretations <cit.>. For consumers, vague and ambiguous privacy policies pose a risk: a fundamental tenet of consumer privacy regulation in the United States is that consumers must be able to make informed decisions about the collection and use of their data, and clear privacy policies are the primary mechanism that provides consumers with the information necessary to make these decisions <cit.>.

One of the main goals of the California Consumer Privacy Act (CCPA) of 2018 has been to introduce more stringent requirements that provide consumers with “more control over the personal information that businesses collect about them” <cit.>. CCPA provides consumers with the rights (1) to request that a business provide specific disclosures regarding the use and sharing of personal information collected from them; (2) to request that a business not sell their personal information by opting out of sales; (3) to request that a business delete personal information that it has collected about them; and (4) to not be discriminated against based on exercising their CCPA privacy rights <cit.>. One year after CCPA went into force, we explore how businesses have responded to its requirements by providing the first systematic assessment focusing on the clarity of their CCPA-mandated privacy disclosures.

To this end, we analyzed the privacy policies of 95 of the most popular websites in the United States. We found that the legal terms introduced by CCPA have been used inconsistently by different businesses. For example, while many businesses state that they do not “sell” personal information, others with ostensibly similar practices acknowledge that their sharing of information with third parties may fall under CCPA's definition of a “sale”. Different CCPA disclosures include also inconsistent levels of detail about what categories of personal information are shared with what categories of recipients; what categories of personal information may be sold; and what outcomes consumers may expect for requests to delete their personal information. If businesses do not consistently interpret CCPA's requirements, consumers also cannot be reasonably expected to consistently interpret these businesses' privacy policies.

We also conducted a user survey ($n = 364$) to evaluate how the wording of disclosures affects consumers' understanding of three potential ambiguities that we identified in our privacy policy analysis: (1) the recipients of specific categories of shared personal information are often specified vaguely; (2) the extent to which opt-out requests can limit the sharing of personal information with third parties is often unclear; and (3) the purposes of retaining personal information after a successful deletion request, as well as potential disclosures of this information, are often undefined. We showed respondents excerpts from privacy policies that reflect a substantial range of existing patterns in disclosure content. Then, we asked them to evaluate the likelihood of data usage scenarios given the excerpts, and we compared their responses with our ground truth answers. Our results show that, separately from policy-level usability (cf. <cit.>), respondents' understandings of disclosures suffered from inconsistent usage of terminology along with a lack of knowledge about how terms such as “sale”, “business purpose”, and “service provider” are to be interpreted under CCPA.

Our results suggest that CCPA requirements for privacy disclosures, as currently implemented, have not sufficiently eliminated vagueness and ambiguity in privacy policies. This is in part due to a lack of specificity in some requirements, differences in interpretations of the requirements, as well as limitations on the enforcement actions taken so far. Our results suggest a need for further clarification and refinement of disclosure requirements to eliminate sources of vagueness and misinterpretation, through revisions such as the recently-passed California Privacy Rights Act (CPRA), in combination with more systematic enforcement activities.

§ BACKGROUND

§.§ The “notice-and-choice” paradigm

In the United States, the regulation of consumer privacy has historically been based on the notice-and-choice paradigm: businesses are responsible for providing consumers with notices about how their data is collected, shared, and used, as well as choices for these practices <cit.>. This paradigm was founded on the Fair Information Practice Principles (FIPPs) described in a 1973 report by the Department of Health, Education and Welfare and adopted by the Federal Trade Commission in 1998 <cit.>, as well as the privacy guidelines established by the Organization for Economic Co-operation and Development (OECD) <cit.>. The United States has taken a market-driven approach to privacy regulation: businesses voluntarily provide notice using privacy policies, but there are few regulations about the format, length, and readability of privacy policies <cit.>.

Notice-and-choice has been considered ineffective <cit.>. A primary concern has been the lack of transparency in privacy policies <cit.>. Businesses have no incentive to make specific disclosures, lest they restrict potential future usage of their data <cit.>. Legally speaking, the non-disclosure of a practice does not mean that a business is prohibited from performing it <cit.>, which incentivizes businesses to use ambiguous language. Another major issue has been the length of privacy policies. <cit.> estimated that a typical Internet user who carefully reads the privacy policies on the websites that they frequent would need to spend, on average, 244 hours doing so annually. Furthermore, consumers usually have few choices for the entities that they can do business with; combined with the “take it or leave it” approach to privacy controls <cit.> that has been adopted by many businesses, this implies that the element of choice in notice-and-choice is ultimately illusory <cit.>.

§.§ The California Consumer Privacy Act

Owing to a 1972 ballot measure, California is now among the ten US states where privacy is enshrined as a constitutional right <cit.>. In 2004, the California Online Privacy Protection Act (CalOPPA), then the most expansive privacy law in the US, came into effect. Yet, it was still focused on the “notice” aspect of the notice-and-choice paradigm <cit.>. On June 28, 2018, Californian legislators passed the California Consumer Privacy Act (CCPA), which provided consumers with rights for both notice and choice (see Section <ref>). Other states have since passed laws that are similar to CCPA <cit.>.

CCPA has been considered to be inspired by the European Union General Data Protection Regulation (GDPR) (e.g., <cit.>). In particular, the opt-out and deletion choices in CCPA and its broad applicability across industry sectors are more reminiscent of GDPR than prior sectoral US legislation. However, fundamental differences show that CCPA and GDPR are still grounded in divergent approaches toward privacy <cit.>. Specifically, CCPA places an emphasis on opting out, i.e. companies may collect personal information about adult consumers until they withdraw their consent. Meanwhile, GDPR places an emphasis on opting in, i.e. companies may not collect or process personal information without either obtaining consent from the consumer or specifying a valid legal basis <cit.>. (For children younger than 16, CCPA also requires opt-in consent.)

§.§.§ Provisions

CCPA includes the following provisions for the privacy rights of consumers who are adult California residents, which provide notice and control about the collection and use of their personal information by businesses operating in California:

* The right to know: Consumers have the right to request that businesses disclose the “categories of personal information” they have collected; “the categories of sources” from which the information was collected; “the business or commercial purpose for collecting or selling” information; “the categories of third parties” with whom information has been shared; and “the specific pieces of information” that have been collected (California Civil Code 1798.110(a)). In response to a verifiable request from a consumer, a business must provide this information free of charge based on its activity in the past 12 months (1798.130(a)(2)). Businesses must also disclose, “at or before the point of collection”, the categories of personal information that they collect and the purposes for which it will be used (1798.100(a)).

* The right to delete: Consumers have the right to request that businesses delete any personal information that has been collected from them (1798.105(a)). Businesses will be required to comply with deletion requests except when the information is used for one of several business purposes, including legal, security, and research activities, but also other commercial and internal activities that are “reasonably anticipated within the context of a business's ongoing business relationship with the consumer” (1798.105(d)).

* The right to opt out of sale: Consumers have the right to direct businesses that sell their personal information to not sell their personal information (1798.120(a)). Businesses must provide notice that they sell personal information and that consumers have the right to opt out (1798.120(b)), and they must respect opt-out requests for at least 12 months before asking the consumer again (1798.135(a)(5)). CCPA defines the term “sell” as “selling, renting, releasing, disclosing, disseminating, making available, transferring, or otherwise communicating [...] a consumer's personal information by the business to another business or a third party for monetary or other valuable consideration” (1798.140 (t)(1)). For consumers under 16 years of age, businesses must obtain opt-in consent (1798.120(c)) before selling information.

* The right to non-discrimination: Businesses are not permitted to discriminate against consumers who exercise the previously-defined rights, including by denying goods or services; charging different prices; providing different levels of quality; or suggesting that the price or level of quality provided will be different (1798.125(a)), except if the differences are “reasonably related to the value provided to the consumer by the consumer's data” (1798.125(b)).

We now expand on several terms and definitions in CCPA that are relevant to the scope of our study.

* Personal information is defined as information that identifies or can be reasonably linked with individual consumers or households, including one of twelve categories: identifiers (e.g., name, postal address, email address, etc.); protected classifications under state or federal law (e.g., gender, race, religion, etc.); commercial information (e.g., purchase records, histories, or tendencies); biometric information; internet or other electronic network activity information (e.g., browsing or search history, or activity on a website); geolocation; sensory information (e.g., audio, electronic, visual, thermal, olfactory, etc.); professional or employment-related information; non-publicly available education information; and inferences drawn from the preceding categories of personal information (1798.140(o)). Responses to right-to-know requests must follow this categorization (1798.130(a)).

* A service provider is a for-profit legal entity “that processes information on behalf of a business and to which the business discloses a consumer's personal information for a business purpose pursuant to a written contract”, provided that the contract binds the service provider from using the information for purposes outside of the contract (1798.140(v)). Businesses must direct their service providers to delete the personal information of consumers in response to deletion requests that they have received (1798.105(c)).

* Verifiable consumer requests refer to requests for which the business can reasonably verify that the requester is the consumer “about whom the business has collected personal information” (or an authorized representative, or a parent if the consumer is a minor). Businesses are not obliged to respond to requests if they are unable to verify the identity of the consumer or their representative (1798.140(y)).

§.§.§ Expansions of CCPA

After CCPA came into effect on January 1, 2020, it was augmented with a set of regulations approved on August 14, 2020, which provide further guidance to businesses on how to implement CCPA's mandates <cit.>. Several modifications to the regulations have been proposed, with the fourth set of proposed modifications having been most recently released on December 14, 2020. These modifications went into effect on March 15, 2021 <cit.>. We now highlight some of the currently implemented regulations that are relevant to the scope of our study.

* With respect to notices made by businesses at the point of collection of personal information, the descriptions of the categories of information collected must provide consumers with “a meaningful understanding of the information being collected” (California Code of Regulations 999.305(b)). “For each category of personal information identified”, the privacy policy text must list “the categories of third parties to whom the information was disclosed or sold” for business purposes. (CCPA and CCPA regulations currently use “share” and “disclose” interchangeably; we adopt the former terminology to avoid confusion.) Privacy policies must also give notice of the right to know. (999.308(c)(1))

* The privacy policy text must explain whether the business sells personal information, and that the user has the right to opt-out of the sale of their personal information regardless of whether the business sells or does not sell personal information (999.308(c)(3)). However, if the business does not sell personal information, a notice of this right separate from the privacy policy is not needed (999.306(d)).

* The privacy policy text must also explain consumers' right to deletion, along with instructions to submit verifiable deletion requests and a description of the process by which the business verifies deletion requests (999.308(c)(2)).

Concurrently, the California Privacy Rights Act (CPRA) <cit.> introduced an expansion of CCPA. CPRA was proposed as a new ballot initiative and approved as California Proposition 24 on November 3, 2020. However, it will not go into effect until January 1, 2023. CPRA will delegate enforcement of consumer privacy to a new, independent agency, the California Privacy Protection Agency, instead of the California Attorney General <cit.>. In Section <ref>, we will consider the changes introduced by CPRA in light of our results concerning vagueness and ambiguity in privacy policies.

§.§.§ Criticism of CCPA

In an effort to replace a stricter ballot initiative that would have been more difficult to modify, the passage of CCPA was rushed through both houses of the California State Legislature <cit.>. This resulted in “aggressive language and ambiguous terms” in the version of the Act that was initially passed <cit.>. The concerns that have been raised over CCPA are twofold: businesses have raised concerns about CCPA's practical implementability, while consumer advocates have raised concerns about the clarity and strength of CCPA's provisions. Both groups have drawn attention to errors in CCPA that require updates. <cit.>

Corporate representatives have highlighted the implementation costs of CCPA compliance, especially to smaller businesses (although some exemptions apply) <cit.>. This issue is exacerbated by ambiguities in CCPA's definition of the terms “sale” (especially the term “valuable consideration” in the definition), “consumer”, “personal information”, “inferences”, “publicly available information”, and “business purpose” <cit.>, which has led to confusion on the scope of necessary compliance actions. Such ambiguities do not just impact businesses: consumers are placed at risk when businesses adopt more restrictive interpretations of these terms than they do <cit.>. A comparison of corporate and consumer public comments on CCPA showed that this was the case <cit.>.

The exemptions provisioned by CCPA have also been viewed as problematic. For instance, the right to delete may be undermined by the exemption for “reasonably anticipated” internal activities, and the non-discrimination clause may allow businesses to determine the “value” of personal information in a way that effectively permits discrimination against consumers <cit.>.

§ PRIVACY POLICY ANALYSIS

To understand how businesses have interpreted and implemented CCPA's requirements in light of the legal ambiguities mentioned in Section <ref>, we analyzed the language and formatting used in the privacy policies of a sample of popular websites. We believe that such policies will be representative of those typically encountered by consumers because the popularity of websites follows a long-tailed power law distribution <cit.>. Specifically, we analyzed the privacy policies of 95 out of the 100 most popular websites in the United States (excluding 5 adult websites, as adult websites have access patterns and demographics distinct from other websites <cit.>), as ranked by Alexa <cit.> on February 15, 2021. Appendix <ref> includes links to Internet Archive snapshots of the policies as they appeared on the date of the analysis. For policies that contained sections addressing the disclosure requirements of CCPA regulations (999.308(c)), we focused our analysis on these sections, along with any other sections that were referenced by this text. If the policy did not contain such sections, we analyzed the entire policy.

We performed de-duplication on our sample of 95 privacy policies by identifying all sets of websites that linked to the same privacy policies in their footers. This left 86 unique privacy policies, 67 of which include one or more sections dedicated to CCPA disclosures. The 19 unique privacy policies without CCPA-specific disclosures include those for government organizations (the USPS, the California government, the IRS, and the NIH); foreign businesses (Tmall, TikTok, QQ, Sohu, and Alibaba, based in China; the BBC, based in the UK); and entities that collect minimal personal information (Wikipedia, DuckDuckGo). Other privacy policies without CCPA-specific disclosures do not fall under these exemptions, but have mostly incorporated the required disclosures into the text (Shopify, Dropbox, Twitter, Heavy, TradingView, WordPress, and CNBC).

Overall, we observed substantial variation in the content and structure of CCPA-mandated disclosures. Except for passages of text that are based on or reference the language of CCPA, these disclosures are largely tailored to the specific activities and data practices of each business. This is a positive signal that these businesses have not relied on boilerplate text. Yet, the variability we observed also extends to businesses' interpretations of CCPA's terms and regulations. Descriptions of consumers' privacy rights or businesses' data practices in these privacy policies are often vague and ambiguous, which may reflect CCPA's underlying lack of clarity.

After an initial exploratory analysis, we selected three types of privacy disclosures that permit comparative analysis in the context of past work on GDPR: (1) the right to know, along with the categories and recipients of personal information that the business has shared (California Code of Regulations 999.308(c)(1)); (2) the right to opt out of sale and whether the business sells personal information (999.308 (c)(3)); and (3) the right to deletion and the deletion request process (999.308 (c)(2)). Based on our exploratory analysis, we also developed a list of patterns of interest for each disclosure type, which we applied to the privacy policy excerpts in two subsequent rounds of coding. Privacy policy excerpts that exemplify the patterns we observed are listed in Appendix <ref>.

§.§ Sharing of personal information

2*Purpose association     5c|Personal information/recipient category association     2*Total

Mapping     Examples by PI     Examples by recipient     Separate lists     Shared PI missing

Mapping by PI     10 (12.35%)     0 (0%)     0 (0%)     1 (1.23%)     2 (2.47%)     13 (16.05%)

Examples by PI     1 (1.23%)     1 (1.23%)     3 (3.7%)     0 (0%)     0 (0%)     5 (6.17%)

Mapping by recipient     3 (3.7%)     0 (0%)     9 (11.11%)     9 (11.11%)     6 (7.41%)     27 (33.33%)

Examples by recipient     2 (2.47%)     3 (3.7%)     4 (4.94%)     6 (7.41%)     6 (7.41%)     21 (25.93%)

Separate lists     4 (4.94%)     0 (0%)     1 (1.23%)     8 (9.88%)     3 (3.7%)     16 (19.75%)

Total     20 (24.69%)     4 (4.94%)     17 (20.99%)     24 (29.63%)     17 (20.99%)     82

Summary of patterns in sharing disclosures across all 82 unique privacy policies with such disclosures. See text of Section <ref> for pattern definitions. Percentages show the proportion of all policies with sharing disclosures that exhibit a given pattern or combination of patterns. Shaded cells denote possible non-compliance. PI stands for “personal information”.

All but four businesses (which lack CCPA-specific disclosures or do not collect personal information) describe their sharing practices in their privacy policies. Among the descriptions of sharing practices in 82 unique privacy policies, we found inconsistent levels of specificity regarding the categories of personal information that businesses share and the categories of recipients that they share this information with. CCPA regulations stipulate that the recipients for each category of shared personal information must be specified individually (999.308(c)(1)). We observed the following patterns with respect to this association, which are summarized in Table <ref>.

* One-to-one mapping (Excerpt <ref>): Following CCPA regulations, the text exhaustively lists (i.e., does not indicate that any list consists of examples) every category of personal information that is shared with each category of recipients.

* Examples by PI category (Excerpt <ref>): The text exhaustively lists categories of personal information, but indicates that the lists of recipients associated with these categories are incomplete (by “for example”, “such as”, or similar).

* Examples by recipient category (Excerpt <ref>): The text exhaustively lists categories of recipients or sharing purposes, but indicates that the associated lists of personal information are incomplete (by “for example”, “such as”, or similar).

* Separate lists (Excerpt <ref>): The text does not associate categories of personal information and categories of recipients, or it uninformatively specifies that each category of personal information is shared with all recipients (or vice versa).

* No list of shared personal information categories (Excerpt <ref>): The text does not include a list of personal information that is shared, but instead generically refers to “personal information” in its description of sharing practices.

Based on CCPA regulations, we would expect all of the sharing disclosures to fall into the first category; yet, 75.61% of disclosures do not. Particularly troublesome are those that make no category-based association whatsoever, including those that only vaguely refer to “personal information”. The latter disclosures invariably list the categories of personal information that are collected by these businesses — a reasonable inference is that all categories of the personal information they collect may be shared, but this cannot be confirmed from the text of these disclosures.

This lack of clarity is illustrative of the vagueness often found in privacy policies. If privacy policies do not clearly associate categories of shared personal information with their recipients, consumers cannot determine the extents to which these different categories of information are shared with different recipients. Such vagueness can be equated to a form of “dark pattern” <cit.>, as it can lead consumers to misconstrue the text of disclosures such that they fail to recognize the possibility of undesirable sharing practices. Our user survey results in Section <ref> echo this theme.

We also examined disclosures regarding the business purposes for which information is shared, which are not mandatory under CCPA. The following patterns are also summarized in Table <ref>:

* Mapping by PI category (Excerpt <ref>): The text exhaustively defines purposes of sharing personal information, associating them with categories of personal information.

* Examples by PI category (Excerpt <ref>): The same, but the text indicates that the list of purposes is incomplete.

* Mapping by recipient category (Excerpt <ref>): The text exhaustively defines purposes of sharing personal information, associating them with categories of recipients.

* Examples by recipient category (Excerpt <ref>): The same, but the text indicates that the list of purposes is incomplete.

* Generic list (Excerpt <ref>): The text does not associate purposes of sharing with personal information or recipients.

Interestingly, across the different types of associations between personal information and recipient categories, we found that the specificity of disclosures about the purposes of sharing personal information did not differ appreciably. Even 65.85% of policies that provide no such association still organize their purposes of sharing by categories of recipients. We speculate that these disclosures are more complete because GDPR has stringent mandates regarding the “legal bases” of processing personal information <cit.>.

Based on prior analyses of privacy policies within the framework of GDPR, the patterns of vagueness we observed are not novel: the automated analysis of <cit.> identified a large proportion of privacy policies that are insufficiently specific about the categories of shared personal information, and <cit.> specifically pointed to several privacy policies with unclear disclosures about sharing practices. Yet, our result is still surprising given that CCPA has more stringent requirements: GDPR does not require categories of personal information to be mapped to recipients <cit.>. The broad pattern of apparent non-compliance in 75.61% of disclosures suggests that inadequate enforcement may contribute to the status quo.

§.§ Sale of personal information

5c|Interpretation of “sale”     2*Total

No sale     Advertising     Sharing (other)     No reframing     Silence

3*Justification     Operational     13 (15.12%)     12 (13.95%)     9 (10.47%)     2 (2.33%)     N/A     36 (41.86%)

Legal     13 (15.12%)     2 (2.33%)     3 (3.49%)     0 (0%)     N/A     18 (20.93%)

None     21 (24.42%)     N/A     N/A     1 (1.16%)     10 (11.63%)     32 (37.21%)

2*Disclosure of advertising     Direct     26 (30.23%)     14 (16.28%)     10 (11.63%)     2 (2.33%)     6 (6.98%)     58 (67.44%)

Indirect     8 (9.3%)     0 (0%)     2 (2.33%)     1 (1.16%)     2 (2.33%)     13 (15.12%)

4*Opt out of sales     Provided     3 (3.49%)     14 (16.28%)     12 (13.95%)     3 (3.49%)     1 (1.16%)     33 (38.37%)

Hypothetical     2 (2.33%)     N/A     N/A     N/A     2 (2.33%)     4 (4.65%)

Denied     6 (6.98%)     N/A     N/A     N/A     0 (0%)     6 (6.98%)

[rgb]1,1,1     Silence     36 (41.86%)     0 (0%)     0 (0%)     0 (0%)     7 (8.14%)     43 (50%)

3*Categorization of PI     Full     N/A     8 (9.3%)     9 (10.47%)     1 (1.16%)     N/A     18 (20.93%)

Partial     N/A     4 (4.65%)     2 (2.33%)     0 (0%)     N/A     6 (6.98%)

None     47 (54.65%)     2 (2.33%)     1 (1.16%)     2 (2.33%)     10 (11.63%)     62 (72.09%)

2c|Total     47 (54.65%)     14 (16.28%)     12 (13.95%)     3 (3.49%)     10 (11.63%)     86

Summary of patterns in sale disclosures across all 86 unique privacy policies. See text of Section <ref> for pattern definitions. Percentages show the proportion of all policies that exhibit a given pattern or combination of patterns. Shaded cells denote possible non-compliance. PI stands for “personal information”.

We found that disclosures in privacy policies about the right to opt out of sale are fundamentally inconsistent in their varying interpretations of CCPA's definition of a “sale”. We identified five types of interpretations, which are summarized in Table <ref>:

* No sale (Excerpt <ref>, <ref>): The text states directly that the business does not sell personal information.

* Reframed as sharing (Excerpt <ref>): The text states that some of the business' sharing practices may fall under the definition of a “sale”, but not in the traditional sense.

* Reframed as advertising (Excerpt <ref>): The text primarily (i.e., as the longest example or the first example) refers to the business' advertising or marketing activities as being possibly interpretable as “sales”.

* No reframing (Excerpt <ref>, <ref>): The text states that the business sells personal information without qualifying such statements by appealing to an alternate definition.

* Silence: The text does not state whether the business sells any kind of personal information.

While these patterns could reflect genuine variation in practice, our analysis suggested that this may not be the case: the justifications provided by businesses for their interpretations of CCPA's definition are also inconsistent. This suggests that the latitude provided by CCPA's vague definition may also be a contributing factor. We found the following types of justifications, as shown in Table <ref>:

* Operational justification (Excerpt <ref>, <ref>): The text highlights specific commercial activities or purposes that fall under the definition of a “sale”, regardless of whether the business engages in those activities or purposes.

* Legal justification (Excerpt <ref>, <ref>): The text only refers to CCPA's definition of a “sale” and does not enumerate the types of commercial activities that may fall under it.

* No justification (Excerpt <ref>): The text does not elaborate upon the stated stance in either of the preceding ways. This applies only to policies which state that the business does or does not sell personal information without qualification.

A majority (54.65%) of sale disclosures state that the associated businesses do not sell personal information, and nearly half of them do not provide further elaboration. But do consumers have any reason to trust such statements, especially when similar businesses state that they do “sell” personal information? As also shown in Table <ref>, each interpretation of the term “sale” is associated with explicit and implicit disclosures of advertising practices:

* Direct disclosure of advertisers (Excerpt <ref>, <ref>): The text lists advertising or marketing companies among the recipients of personal information shared by the business.

* Indirect disclosure of advertising (Excerpt <ref>): The text references targeted or personalized advertising or marketing as a purpose for which personal information is shared.

Such practices are described by all of the disclosures that assert it is sold in some way, but also by 72.34% of disclosures that assert information is not sold. Thus, despite the variance in interpretations of the word “sale”, at least some of these businesses are conceivably performing the same practices in reality. These patterns align with those found by <cit.> in their usability study of CCPA sale opt-outs.

Especially considering the revelations of the Cambridge Analytica scandal and their wide-reaching impacts on consumer attitudes towards data privacy <cit.>, modern consumers negatively view the “selling” of data between businesses in scenarios where they lack the agency to control such practices <cit.>. As potential responses to either consumers or regulators, 84.88% of disclosures thus state that no personal information is sold or attempt to qualify their “sale” of personal information. Yet, the common presence of advertising practices suggests that these statements may not translate into practice. We should thus question whether consumers can use the text of privacy policies to meaningfully differentiate between sharing practices that may or may not involve “valuable consideration”.

Our results support prior criticism of the term “sale” in CCPA, but they also document a new phenomenon of vagueness. This is because the distinction between “sharing” and “selling” is a novelty of CCPA; GDPR generically refers to the “processing” of personal information <cit.>. Still, the practical issues caused by the vagueness of “selling” in CCPA mirror those caused by the term “profiling” in GDPR, which is defined as “any form of automated processing of personal data consisting of the use of personal data to evaluate certain personal aspects relating to a natural person” (4.4). While GDPR provides the right for individuals to not be subject to “solely automated decision-making” (22.1), it is similarly unclear what types of activities would fall under this definition. <cit.>

For privacy policies which state that no personal information is sold, there are four types of statements regarding whether consumers can still opt out of sales. As shown in Table <ref>, these are:

* Provision of opt-out (Excerpt <ref>): The text specifies a mechanism by which consumers can opt out of sales.

* Hypothetical assurance of opt-out (Excerpt <ref>): The text states that, if the business sells personal information in the future, the consumer will have an option to opt out.

* Denial of opt-out (Excerpt <ref>): The text states that the business does not offer an opt-out for the sale of personal information because it does not sell personal information.

* Silence: The text does not inform consumers about the right to opt out of the sale of personal information under CCPA.

CCPA regulations require the right to opt out of sale to be disclosed in privacy policies regardless of whether personal information is sold. Yet, a majority (76.6%) of disclosures which state that personal information is not sold fall into the last type, which is potentially non-compliant. This contrasts with the setting of GDPR, where <cit.> found that 90% of privacy policies notified consumers of opt-outs to the processing of personal information for marketing. The difference may involve the unpalatability of the word “sale”.

Lastly, among the privacy policies which state that personal information is “sold” in some way, there are also varying levels of specificity about the categories of personal information involved:

* Full categorization (Excerpt <ref>): The text exhaustively lists all categories of personal information that may be sold.

* Partial categorization (Excerpt <ref>): The text indicates that its listing of categories of sold personal information is incomplete (by “for example”, “such as”, or similar).

* No categorization (Excerpt <ref>): The text generally refers to personal information in the context of selling information.

Helpfully, many (62.07%) of the disclosures in this category do provide a comprehensive categorization, usually based on the categorization that CCPA mandates for right-to-know requests.

§.§ Right to deletion

5c|Implementation of verification     3*Total

2*Info. request     2c|Login wall

Soft     Hard     -2*Generic description     -2*Silence

Present     N/A     5 (6.02%)     2 (2.41%)     N/A     N/A     7 (8.43%)

[rgb]0.9,0.9,0.9 [rgb]1,1,1-2*Login wall explanation     Absent     N/A     31 (37.35%)     7 (8.43%)     N/A     N/A     38 (45.78%)

2*Retention — basis     Specific     6 (7.23%)     12 (14.46%)     2 (2.41%)     5 (6.02%)     6 (7.23%)     19 (22.89%)

Generic     8 (9.64%)     4 (4.82%)     2 (2.41%)     3 (3.61%)     4 (4.82%)     16 (19.28%)

3*Retention — scope     Full     0 (0%)     2 (2.41%)     1 (1.2%)     2 (2.41%)     2 (2.41%)     4 (4.82%)

Partial     0 (0%)     5 (6.02%)     1 (1.2%)     2 (2.41%)     3 (3.61%)     8 (9.64%)

Generic     14 (16.87%)     9 (10.84%)     2 (2.41%)     4 (4.82%)     5 (6.02%)     23 (27.71%)

2c|No retention disclosed     21 (25.3%)     20 (24.1%)     5 (6.02%)     6 (7.23%)     15 (18.07%)     48 (57.83%)

2*Propagation to third parties     Present     4 (4.82%)     3 (3.61%)     0 (0%)     0 (0%)     3 (3.61%)     7 (8.43%)

Absent     31 (37.35%)     33 (39.76%)     9 (10.84%)     14 (16.87%)     22 (26.51%)     76 (91.57%)

3*Disruption of experience     Account-level     5 (6.02%)     10 (12.05%)     3 (3.61%)     3 (3.61%)     5 (6.02%)     16 (19.28%)

Function-level     4 (4.82%)     5 (6.02%)     1 (1.2%)     1 (1.2%)     3 (3.61%)     8 (9.64%)

None     26 (31.33%)     21 (25.3%)     5 (6.02%)     10 (12.05%)     17 (20.48%)     59 (71.08%)

2c|Total     35 (42.17%)     36 (43.37%)     9 (10.84%)     14 (16.87%)     25 (30.12%)     83

Summary of patterns in deletion disclosures across all 83 unique privacy policies with instructions for deletion requests. See text of Section <ref> for pattern definitions. Percentages show the proportion of all policies with instructions for deletion requests that exhibit a given pattern or combination of patterns. Shaded cells denote possible non-compliance.

All but three privacy policies (which lack CCPA-specific disclosures) specify at least one method by which consumers can submit deletion requests. Beyond this, however, substantial variation exists. As shown in Table <ref>, we observed the following patterns concerning the description of the process for verifying deletion requests:

* Information request (Excerpt <ref>): The text states that the business may request additional information to verify the consumer's deletion request before processing it.

* Login wall (Excerpt <ref>): The text provides different steps for submitting deletion requests to users who do and users who do not hold accounts with the business.

* Hard login wall (Excerpt <ref>): The text only provides instructions for submitting deletion requests to users who hold accounts, and not to non-account holders.

* Generic description (Excerpt <ref>): The text states that the business will verify the consumer's identity before processing the deletion request, but does not specify what actions the consumer needs to take after submitting their request.

* Silence: The text does not discuss verification.

Given the latitude in what “general descriptions” of verification processes may consist of, all but the last of these patterns would likely be compliant with CCPA regulations (999.308 (c)(2)). Yet, a substantial minority (30.12%) of disclosures are indeed silent about their verification processes. Silence may imply that no verification takes place, which could be “reasonable” if unauthorized access or deletion would not affect consumers (cf. 999.323 (b)(3)b).

As for “login walls”, such distinctions can be reasonably expected for types of personal information that will only be collected from account holders. They in fact conform to CCPA regulations, which require businesses to verify the identity of non-account holders “to a reasonable degree of certainty” (999.325 (b)), and to deny deletion requests to users for which this is impossible (999.325 (f)). However, the latter must be clearly explained in privacy policies (999.325 (g)), which we only observed in 15.56% of these policies:

* Login wall explanation (Excerpt <ref>): The text states that deletion requests from users who lack accounts may be rejected because they cannot be verified to CCPA's standards.

Businesses also provide varying levels of detail about the possible retention of personal information after a successful deletion request, as also summarized in Table <ref>. The purposes for retaining personal information may be described in one of the following ways:

* Specific operational basis (Excerpt <ref>): The text makes reference to specific business purposes that are exempt under CCPA to explain why information may be retained.

* Generic operational basis (Excerpt <ref>): The text does not specify which types of commercial activities personal information would need to be retained for, including when the text lists all exempt business purposes under CCPA.

Meanwhile, the categories of personal information that are retained may be described in one of the following ways:

* Full categorization: The text exhaustively lists all categories of personal information that may be retained.

* Partial categorization: The text indicates that its listing of categories of personal information that may be retained is incomplete (by “for example”, “such as”, or similar).

* Generic categorization: The text generally refers to personal information that may be retained.

Notably, the 42.17% of privacy policies which state that personal information may be retained all specify at least one operational basis for which this information may be retained, and 54.29% of such disclosures are reasonably specific. Meanwhile, only 34.29% of them describe the categories of information that may be retained. CCPA regulations do not require the latter disclosures for privacy policies; their presence may stem from GDPR disclosure requirements regarding retention, particularly 13.2(a) and 14.2(a) <cit.>. These inconsistencies in the clarity of retention purposes and scopes echo the findings of <cit.> within the context of GDPR.

These vague statements of retention purposes also point to a pitfall in CCPA's definition of “business purposes”: we believe that businesses could share or sell the retained personal information depending on their interpretation of “reasonably anticipated” commercial activities. Only four privacy policies state otherwise:

* Propagation to third parties (Excerpt <ref>): The text states that the business will relay deletion requests to other parties with access to the consumer's personal information (such as service providers or clients).

While this procedure is mandated by CCPA (1798.105(c)), few consumers will probably be aware of this provision (indeed, few consumers are aware of CCPA's provisions; see Section <ref>). Without seeing such disclosures, consumers would likely underestimate the extent of their privacy's protection under CCPA (see Section <ref>).

Lastly, a sizeable minority (28.92%) of deletion disclosures state that a user's experience with the business may change after their personal information is deleted. We observed two such types of patterns, as also summarized in Table <ref>:

* Account-level disruption (Excerpt <ref>): The text states that a successful deletion request could result in the deletion or deactivation of the user's entire account.

* Function-level disruption (Excerpt <ref>, <ref>): The text states that a successful deletion request may hinder the user's experience in other ways, including through the loss of access to functionality requiring personal information.

Both the privacy policies themselves and CCPA are sufficiently vague that these practices may fall under the exemption in the non-discrimination clause for differences that are “reasonably related” to the value of the personal information (1798.125(b)). Still, the deactivation of user accounts in the former case is a striking instance of the “take it or leave it” approach to privacy controls, which has also been criticized in the context of GDPR <cit.>.

In summary, beyond the vague requirements of CCPA regulations, the privacy policies that we analyzed provide inconsistent levels of detail about the request verification process as well as the retention and use of personal information following successful deletion requests. These vague disclosures may disincentivize users from exercising their privacy rights because they reduce the perceived effectiveness of deletion requests.

§ USER SURVEY BACKGROUND

To evaluate the effect of varying interpretations of CCPA's privacy policy requirements, we conducted an IRB-approved user survey of California residents to assess whether their understanding of businesses' data practices depends on the specificity of these businesses' CCPA-mandated privacy disclosures. We focused on three patterns of variance, each selected from one of the three types of disclosures pertaining to data flows that we focused on in our privacy policy analysis: the mapping between recipients and categories of shared personal information (found in sharing disclosures), the types of commercial activities affected by the right to opt out of sale (found in sale disclosures), and the effects of successful deletion requests on data retention and sharing (found in deletion disclosures).

In our user survey, we asked respondents to read three excerpts (each containing one of the three types of disclosures) from the CCPA disclosures of a single privacy policy. Then, for each excerpt, we presented them with two data usage scenarios based on the content of the disclosure, and we asked the respondents to rate the likelihood that the business would be allowed or required to engage in each of the described data practices. We did not require respondents to rely on the policy alone; thus, they were free to draw upon any prior knowledge they had about relevant regulations.

§.§ Policy selection

To maintain the practical feasibility of our study, we randomly and (as much as possible) evenly showed excerpts from one of nine privacy policies to the respondents, as summarized in Table <ref>. These policies were selected so that they contained substantial variance in the specificity of the disclosures that we considered.

Privacy Policy     $\boldsymbol{n}$     Sharing: Recipient / Info Mapping     Sharing: Sharing Purposes     Sale: Interpretation of “Sale”     Sale: Justification of Stance     Deletion: Retention Purposes     Deletion: Propagation to 3rd Parties

Section Ref         <ref>     <ref>     <ref>     <ref>     <ref>     <ref>

(1) Walmart     40     One-to-one mapping     Examples by recipient     Sharing     Legal     Generic     Service providers

(2) eBay     41     Separate lists     Generic list     Sharing     Operational     Generic     Not specified

(3) New York Times     41     Examples by recipient     Generic list     Sharing     Legal     Records / transactions     Not specified

(4) Hulu     41     Examples by recipient     Examples by recipient     Advertising     Operational     Generic     Not specified

(5) ESPN     40     Separate lists     Generic list     Advertising     Legal     Generic     Not specified

(6) Best Buy     40     One-to-one mapping     Generic list     Advertising     Operational     Transactions     Not specified

(7) Google     40     No list of shared PI     Generic list     No sale     Unjustified     Security / records     Not specified

(8) Microsoft     40     Mapping     Mapping by PI     No sale     Unjustified, no opt out     Generic     Not specified

(9) Netflix     41     One-to-one mapping     Examples by recipient     No sale     Unjustified     Records / legal     Not specified

Summary of the nine privacy policies used for our survey (Section <ref>). $n$ is the number of survey respondents.

For sharing disclosures (Section <ref>), 4 of the policies we selected provide a one-to-one mapping between the categories of personal information that are shared by the business and the categories of recipients. Meanwhile, 2 policies provide examples of categories of personal information for each category of recipients, and 3 policies make no association between personal information and recipients.

Next, for sale disclosures (Section <ref>), 3 policies each describe (1) sharing activities in general as potentially being sales; (2) advertising activities as sales; and (3) no activities as sales. Both categories that disclose “sales” consist of policies that base their stances on CCPA's definition or on specific commercial purposes. Among the policies that do not disclose “sales”, only one policy states that the consumer has no right to opt out of the sale of personal information.

Lastly, for deletion disclosures (Section <ref>), 5 policies do not specify why information may be retained, 3 mention record-keeping as a purpose, and 2 mention transactions as a purpose. Only one specifies that deletion requests are relayed to service providers.

Thus, for each type of disclosure, at least a third of the policies that we selected for our user survey are substantially vaguer than the others. Our power analysis uses this property (Appendix <ref>).

§.§ Research questions

Here, we list the basic types of questions in our user survey; Appendix <ref> contains the full user survey, including the privacy policy excerpts. These questions were adjusted based on the excerpts, including different instantiations for the template fields. Separate versions of Q3 and Q4 were needed because (1) sharing information in exchange for advertising revenue falls under the definition of a “sale” in policies from the “Advertising” category and (2) sale opt-outs do not apply to policies from the “No sale” category.

Sharing disclosures

* If you make purchases through a website owned by Company XYZ, is Company XYZ allowed to share your past purchase history with a payment service provider?
* If you make purchases through a website owned by Company XYZ, is Company XYZ allowed to share your inferred ethnicity (inferred based on your purchase history) with a payment service provider?
Sale disclosures

* “Sharing”

* If you opt out of the sale of your personal information, is Company XYZ allowed to provide your full name and mailing address to an advertising company, without receiving revenue in return from this advertising company?

* If you opt out of the sale of your personal information, is Company XYZ allowed to provide your full name and mailing address to an advertising company so that the advertising company can display advertisements to you on other websites, without receiving revenue in return from this advertising company?

“No sale”

* Could Company XYZ be allowed to provide your full name and mailing address to an advertising company, without receiving revenue in return from this advertising company?

* “Sharing”

* If you opt out of the sale of your personal information, is Company XYZ allowed to provide your full name and mailing address to an advertising company, in return for a portion of revenue from this advertising company?

* If you opt out of the sale of your personal information, is Company XYZ allowed to provide your full name and mailing address to a separately-owned [category of Company XYZ] so that the two companies can provide joint product offers to you, without receiving revenue in return from this partner company?

“No sale”

* If Company XYZ provides your full name and mailing address to an advertising company, without receiving revenue in return from this advertising company, would you have an option to opt-out of this sharing?

Deletion disclosures

* If you request the deletion of your personal information, is Company XYZ required to direct any marketing company that has received your information, either by sharing or selling, from Company XYZ to delete information
about your activity on Company XYZ's websites?
* If you request the deletion of your personal information, is Company XYZ required to direct any marketing company that provides advertising consultation services to Company XYZ (that is, acting in the capacity of a service provider) to delete information about your activity on Company XYZ's websites?

For each question, we asked respondents to answer using a 5-point Likert scale of (1) “Definitely not”, (2) “Probably not”, (3) “I'm really not sure”, (4) “Probably”, and (5) “Definitely”. We then developed a set of ground truth consensus answers from three of the authors who are experts in privacy law and practice. These authors first individually answered all six questions corresponding to each of the nine policies (54 total) using the same Likert scale. Then, all disagreements with the majority answer were discussed and resolved based on the text of CCPA and CCPA regulations.

To allow for uncertainty in the respondents' answers, we marked them as correct as long as they were sufficiently close to our consensus. For a ground truth of 4 or 5, we accepted both 4 and 5; for 3, we accepted 2, 3, or 4; and for 1 or 2, we accepted both 1 and 2. Based on our evaluation of the correctness of the respondents' answers, we formulated the following research question:

* For each question (Q1, Q2, Q3, Q4, Q5, and Q6), is the proportion of respondents who answer correctly independent of the privacy policy excerpt that is shown to them?

§.§ Survey recruitment

RQ leads to a $\chi^2$ test of independence for each question between two categorical factors: (1) the privacy policy that is shown and (2) answer correctness. For Q1, Q2, Q3, Q5, and Q6, the privacy policy factor has 9 levels. We conduct three tests for Q4 and three additional tests for Q3 because the questions for the three types of opt out disclosures are not entirely comparable; the privacy policy factor for each of these tests has 3 levels. Our power analysis (see Appendix <ref>) led us to recruit a sample of 364 respondents.

Our sample of respondents was recruited through Amazon Mechanical Turk. Respondents were required to be California residents who were at least 18 years old. To avoid low-quality responses, we sampled respondents from the pool of Mechanical Turk users with an approval rate of at least 90%. Before participating in the study, respondents were required to complete a screening questionnaire and a consent form; any respondents who failed to certify that they met the criteria were removed from the participant pool.

§.§ Survey methodology

Respondents were directed to complete (1) a pre-survey questionnaire, (2) the main survey, and (3) a post-survey questionnaire.

* We first assessed respondents' familiarity with privacy legislation by asking them to rate their knowledge of CCPA, CPRA, CalOPPA, and GDPR.

* In the main survey, we implemented a between-subjects design where each respondent was shown three excerpts from a single privacy policy in a randomized order. All company names, website URLs, and telephone numbers were anonymized to prevent priming effects. We reproduced the original formatting of the text as closely as possible, except we removed all hyperlinks. These methods are consistent with <cit.> but not <cit.> (who compared alternate representations of the same text using a within-subjects design).

Note that we only displayed excerpts instead of the entire privacy policy. This is because the goal of our user survey was to assess the ability of consumers to understand and interpret the contents of the excerpts. Indeed, the orthogonal issue of whether consumers can locate relevant text in a privacy policy has already been studied by <cit.>. Our goals and thus our methodology are closer to <cit.> (who assessed comprehension of specific terms in the context of sample sentences) and <cit.>. After each excerpt, we showed each respondent the two questions corresponding to the excerpt on the same page (the questions listed in Section <ref> were worded to avoid priming effects). Again, this was because we aimed to assess comprehension instead of memorization. This approach differs from <cit.> but aligns with <cit.>.

For each question, we provided two free-text response fields where we asked respondents (1) to paste one to two sentences from the excerpt that most influenced their answer, and (2) to briefly explain their answer. We evaluated the effort level of respondents using their free-text responses, along with two simple multiple-choice attention checks based on the content of the questions. We withdrew respondents who provided irrelevant answers for both types of questions.

* Afterward, we presented respondents with two sets of post-survey questions, namely a demographic questionnaire and a standard privacy/security questionnaire <cit.>.

In a pilot of 15 respondents, the mean completion time was 16 minutes, 52 seconds. Using an hourly rate of $12.00, we compensated respondents with a nominal base amount of $3.00. To incentivize respondents to consider their answers carefully, we provided a bonus of $0.15 for every correct answer, plus another $1.00 if they correctly answered all six questions; we provided a mean bonus of $0.55. The median response time for all respondents was 20 minutes, 10 seconds, with the first quartile being 14 minutes, 52 seconds, and the third quartile being 27 minutes, 51 seconds.

We compared the self-reported demographics of our respondents to California's overall demographics from the 2019 American Community Survey <cit.>. Our sample slightly under-represents males (49.4% compared to 49.7%); over-represents single people (58.45% compared to 51.6%), and over-represents people with a college degree or higher (74.45% compared to 35%). Respondents' knowledge of privacy regulations was variable; 56.9% had heard of CCPA, versus 39.6% for CPRA, 25.8% for CalOPPA, and 23.6% for GDPR.

§ USER SURVEY RESULTS

In Figure <ref>, we show the distribution of answers for each question and policy. Our overall results in terms of question correctness and our statistical tests are summarized in Table <ref> in Appendix <ref>.

Based on their free-text responses, we found that respondents rarely referenced legal knowledge. Only 5.52% of rationales explicitly mentioned the definitions or provisions of CCPA or other California laws. This was even true for respondents who self-reported that they had heard of CCPA (6.18% of rationales from these respondents mentioned CCPA), which suggests that an individual knowing of CCPA is not a strong signal that they will use that knowledge to evaluate their privacy in practice. At the same time, 28.18% of rationales mentioned that the excerpts alone did not address the scenarios clearly enough for them to give a certain answer.

Q1: Sharing, purchase history

Q2: Sharing, inferred ethnicity

Q3: Sale, without revenue exchange

Q4: Sale, revenue / Joint offer / Opt-out

Q5: Deletion, all third parties

Q6: Deletion, service providers

Boxplots of Likert scale survey responses from 364 respondents. Orange lines show the median respondent answer; blue lines show the ground truth. Numbers on the horizontal axis correspond to the privacy policies listed in Section <ref>.

§.§ Sharing disclosures

For Q1 and Q2, our ground truth states that both purchase history and inferred ethnicity could probably be shared by all of the businesses, since they fall under the categories of personal information that could be disclosed to service providers according to these businesses' privacy policy excerpts. We found that 80.77% of respondents agreed with our consensus answer for Q1, but only 63.74% of respondents agreed with our consensus answer for Q2.

Our statistical tests indicated that there was a statistically significant difference in answer correctness between the nine policies on both Q1 ($p \approx 0.0113$) and Q2 ($p \approx 0.0321$). For all privacy policies except those for New York Times, Hulu, ESPN, and Best Buy, 4 (“Probably allowed”) was the first quartile of answers to Q1, but this was only true of Walmart and eBay on Q2. We infer that respondents were overall more certain that sharing would be permitted for Q1 but were less confident on some policies, while they were more ambivalent overall for Q2.

In 87.28% of rationales for correct answers on both questions (83.38% of all rationales), respondents referenced list entries that contain relevant categories of shared personal information and recipients. This was even true for policies that provide no association between them, on which respondents inferred the sharing of every category of personal information with every category of recipients.

However, many respondents were confused about the correct categorizations that the presented scenarios fell under. We found that 35.53% of rationales for incorrect answers (22.63% overall) did not identify the correct category of personal information in the disclosure. For Q2 in particular, 40.34% and 29.97% of all rationales considered inferred ethnicity as a demographic or as an inference (both of which are plausible), and 9.52% incorrectly classified it as an identifier. Meanwhile, 14.72% (16.9% overall) of rationales showed confusion about recipients (including the conflation of “service providers” and “third parties”, which are distinct under CCPA).

§.§ Sale disclosures

For Q3, our ground truth states that businesses would probably be allowed to share information without receiving revenue in return, provided that they interpret these activities as not falling under CCPA's definition of a “sale” and any benefits they receive as not representing “valuable consideration”. Overall, respondents struggled with these definitions. For policies in the “Sharing” and “Advertising” categories, the majority of respondents disagreed with our answer, with only 38.52% and 30.58% of their answers respectively matching our consensus. Among incorrect answers, 38.85% of rationales considered this revenue-less scenario to fall under the opt-out for sales, while 28.66% interpreted the opt-out as covering all forms of sharing. Meanwhile, the proportion of correct answers for “No sale” was much higher, at 65.29%. For correct answers, 68.35% of these rationales excluded non-monetary forms of sharing from the definition of “sale” — explicit statements from the businesses that they do not sell personal information appear to have reduced respondents' perceived scope of a “sale”. The differences across all policies are statistically significant ($p \approx 1.944 \times 10^{-6}$), although the question is worded differently for the three categories. Within-category statistical tests indicated that only the “Sharing” category had marginally significant inter-policy differences ($p \approx 0.0488$).

On Q4 for the “Sharing” policies, 80.33% of respondents agreed with our ground truth that exchanging personal information for ad revenue would likely constitute a “sale”, and thus would probably not be allowed after they have opted out of the sale of personal information. Indeed, 60.2% of rationales for correct answers recognized that the scenario fell under the opt-out. However, 33.33% of rationales for incorrect answers emphasized the ambiguity in the definition of a “sale”. The statistical tests did not find significant differences in correctness between the policies in this category.

For the “Advertising” policies, our ground truth recognizes that the answer to Q4 would be dependent on how regulators interpret the term “valuable consideration”. Partner businesses in a co-marketing relationship might not exchange any revenue from their sales. Even so, joint offers would likely have super-additive benefits to the customer bases of both businesses, which may be “valuable”. CCPA is much vaguer in this regard than the Gramm-Leach-Bliley Act, which applies to financial institutions and provides exemptions for co-marketing <cit.>. Despite this ambiguity, we found that 54.55% of respondents were confident enough to give a definite answer. Again, we found no statistically significant inter-policy differences.

Lastly, on Q4 for the “No sale” policies, our ground truth considers that third party advertisers who receive information from the businesses would likely provide opt-outs for such sharing practices, regardless of whether the first party provides an opt-out. While 61.16% of respondents answered the question correctly, their reasoning was often incorrect. We found that 52.05% of rationales for correct answers identified the right to deletion as the right to opt out; only 24.66% mentioned an opt-out separately from deletion. Our statistical test found significant differences in correctness between policies ($p \approx 0.0008$); this was likely related to Microsoft's statement that they do not provide an opt-out, which was mentioned in 83.33% of rationales for incorrect answers on this policy.

§.§ Deletion disclosures

For Q5, according to our ground truth, CCPA requires businesses to relay deletion requests to service providers, but probably not to all third party recipients. Overall, 57.69% of respondents agreed with our conclusion. For correct answers, 66.67% of rationales recognized that the right to deletion does not cover all third parties, and 47.34% noted that the text does not discuss third parties. Our statistical test showed significant differences in correctness between policies ($p \approx 0.0010$); the median answers for two policies differ from our ground truth. Walmart's policy states that they would “direct any service providers” to carry out deletion requests; 70% of incorrect rationales interpreted this as applying to third parties. The brevity of Microsoft's description likely led 45.45% of incorrect rationales to suggest that the excerpt did not clearly address the scenario.

Lastly, for Q6, our ground truth states that businesses would probably be required to relay deletion requests to marketing companies acting as service providers, again based on CCPA. Only 35.44% of respondents arrived at the same answer; the median answer was unchanged from Q5 on six out of nine policies. For incorrect answers, 70% of rationales (often correctly) recognized that the policies did not address service providers either. Yet, this was also the case for 42.85% of such rationales on Walmart, despite the policy's clear statement. They were confused by the service provider being a marketing company; such confusion may be alleviated by reiterating examples of service providers in the text. We again found significant inter-policy differences in correctness ($p \approx 0.0010$).

In summary, deletion disclosures led many respondents to form an incorrect but less harmful conclusion: that they would not be protected, whereas in reality they would be. However, as we suggested in Section <ref>, this may also reduce their confidence in deletion requests. Regardless, our findings highlight a lack of awareness regarding CCPA's deletion requirements for service providers.

§ CONCLUSION

In this work, we evaluated the clarity and effectiveness of currently implemented CCPA disclosures at informing consumers of their privacy rights. From our analysis of 95 privacy policies on popular websites, we found that the level of detail in disclosures was often inconsistent, with many of them obfuscating important information that would be relevant to consumers' privacy concerns. We also suggest that not all disclosures describe businesses' data practices at the level of clarity mandated by CCPA regulations. Our user survey then showed that different types of wording led consumers to different conclusions about businesses' data practices and their own privacy rights, even when the legal ground truth was the same.

§.§ Limitations

Due to constraints of practicality, we were unable to perform a more comprehensive evaluation of CCPA disclosures through either our privacy policy analysis or our user survey. Our privacy policy analysis was restricted to 95 of the most popular websites across the entire United States. The level of variance among disclosures may differ for less popular websites; preliminary analysis suggests that boilerplate text is more common. However, the privacy policies we analyzed are likely representative of those on most websites that the average California resident would visit (see Section <ref>). We did not try to expand our analysis using natural language processing due to the error inherent in such approaches (cf. <cit.>), which would hinder an accurate assessment of the status quo of privacy policy clarity under CCPA. Nevertheless, automating the analysis of CCPA disclosures is a valuable direction of future work that could improve their interpretability by consumers and policy-makers.

Our user survey also considered only a subset of the patterns found in CCPA disclosures. Although we included a diverse sample of excerpts, we could not capture the entire space of variation due to the highly customized nature of CCPA disclosures on popular websites. Still, the statistically significant effects that we observed, in spite of our limited sets of policies and respondents, suggest that variation in wording does impact consumers' perceptions. Also, our experimental design attempted to mitigate brand-based priming effects (cf. <cit.>) as much as possible. Based on the respondents' rationales, we do not believe that any of them made associations with real businesses, but we cannot entirely exclude this possibility.

§.§ Implications for policy makers

Our results echo prior literature in highlighting problematic ambiguities in CCPA's terminology. Specifically, our privacy policy analysis showed that businesses do not consistently interpret the terms “sale”, “valuable consideration”, or “business purpose”, nor CCPA regulations' requirements for privacy policies. These effects translated to confusion among survey respondents because the policy excerpts often failed to clarify the businesses' assumptions.

CPRA, which is intended to address CCPA's flaws, will soon come into force. While CPRA addresses some of our findings, it may introduce more ambiguity in other areas. CPRA clarifies that non-personalized advertising is a business purpose; provides an opt-out for targeted advertising; extends the requirement for relaying deletion requests to all third parties, not just service providers; and introduces a GDPR-like data minimization requirement <cit.>. Yet, CPRA also distinguishes “contractors” from service providers as entities to which businesses merely make personal information available, which has already been considered unclear <cit.>.

Many states, such as Virginia, are now following suit in passing CCPA-like laws <cit.>. If these laws are to succeed, policy makers and regulators must exercise due diligence in addressing vagueness and ambiguity through not just legislation but also enforcement, as suggested by the apparent non-compliance we observed. Encouragingly, some of these laws provide more clarity than CCPA <cit.> (e.g., the monetary definition of a “sale” in Nevada's new privacy law). Still, we argue that more standardized and structured disclosures based on a uniform interpretation of terminology would better mitigate the issue of vague and ambiguous privacy policies.