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Testimony Regarding Online Privacy

Testimony of the New York Civil Liberties Union before The New York State Senate Committee on Consumer Protection and the New York State Senate Committee on Internet and Technology regarding A Joint Public Hearing to Conduct Discussion on Online Privacy and What Role the State Legislature Should Play in Overseeing It

The New York Civil Liberties Union (NYCLU) is grateful for the opportunity to submit the following testimony regarding online privacy and the role the state legislature should play in overseeing it. The NYCLU, the New York State affiliate of the American Civil Liberties Union, is a not-for-profit, nonpartisan organization with eight offices across the state and over 190,000 members and supporters.

The NYCLU defends and promotes the fundamental principles and values embodied in the Bill of Rights, the U.S. Constitution, and the New York Constitution through an integrated program of litigation, legislative advocacy, public education, and community organizing. As part of a nationwide network of ACLU affiliates, we offer not only our own experience working at the intersection of privacy and technology, but also the lessons learned by our sister affiliates in states that have been on the cutting edge of legislating to protect privacy in the digital age.

It is no longer possible to participate in society without providing personal information to private companies and other third parties that may, in and of itself reveal intimate details of one’s life, or that, when combined with other data and analyzed, may expose such information. The consequences can be profound. For example, personal information has been leveraged to ensure that only younger men see certain job postings and to exclude African-Americans from viewing certain housing advertisements.[1]

Cambridge Analytica put consumer privacy on the map in March of last year when the public learned that it had obtained more than 50 million Facebook users’ personal information from an unsavory app developer and purported to use that information to engage in “psychographics” to convince voters to cast their ballots for Mr. Trump.[2] During the 2016 election, personal information was also used to target advertisements to African-Americans urging them not to vote.[3]

Reporting on these and other phenomena, the New York Times observed in September that exploitation of personal information enables “unequal consumer treatment, financial fraud, identity theft, manipulative marketing, and discrimination.”[4] Against this backdrop, the Committees’ consideration of online privacy and the state legislature’s role in overseeing it could not be timelier.

This testimony will proceed by explaining the scope of the problem as we see it, as well as a brief overview of the legal landscape that any privacy legislation will fall into. It will then outline two of the major lessons learned and pitfalls to avoid from our sister states. Finally, it will offer specific feedback on Senator Thomas’ New York Privacy Act.

  1. Scope of the Problem

When we at the NYCLU began to work on consumer privacy, we made a list of the harms that stem from the pervasive collection, retention, sharing, monetization, use, and misuse of personal information. Here are some of the harms we are cognizant of:

Entities – whether businesses, employers, schools, landlords, health insurers, or credit-issuing agencies – can use amassed personal information to limit individuals’ awareness of and access to opportunities. This can be deliberate or inadvertent, and, depending on the opportunity in question, amassed personal information and sophisticated algorithms can be used to circumvent our civil and human rights protections. As described above, some employers have consciously targeted advertisements to keep older workers from learning of certain job opportunities,[5] and landlords have prevented racial minorities from seeing certain housing advertisements.[6]

Even when advertisers are not acting deliberately to discriminate, individuals’ opportunities may be inadvertently limited as a result of the online advertising industry functioning as intended. For example, Leigh Freund of the Network Advertising Initiative testified at November’s Federal Trade Commission hearings on Big Data, Privacy, and Competition that “women are less likely to see employment ads for careers in the science/technology/engineering/math field . . . simply because they have higher value to other advertisers because women do more shopping.”[7]

In addition, as entities increasingly turn to sophisticated algorithms and automated decision-making to place ads, screen resumes, or even, in government hands, to make bail decisions, decide where to deploy police, or to make child custody decisions, the training data used to develop the algorithms can have outsized impacts on individuals’ opportunities and outcomes.[8] Algorithms work by identifying correlation, not causation, and the training data used to “teach” algorithms what patterns to look for often reflect and then magnify entrenched historical biases.[9]

For example, researchers at Carnegie Mellon and the International Computer Science Institute found that user “profiles . . . pegged as male were much more likely to be shown ads for higher-paying executive jobs than those . . . identified as female – even though the simulated users were otherwise equivalent.”[10] Amazon, famously, pulled the plug on its resume-screening algorithm, because the algorithm, trained on Amazon’s predominantly-male existing workforce, systematically downgraded female resumes and elevated male applicants.[11]

In government hands, algorithms trained on historical policing and criminal justice system data are likely to lock up more black and brown people simply because the training data reflect the systematic racism that has been endemic in the criminal justice system since before the nation’s founding.[12]

In addition to race, sex, and age discrimination and other forms of discrimination based on protected classes, amassed personal information can be used to engage in unfair price discrimination. For example, Wall Street Journal investigators discovered that shows individuals who live near rival stores lower prices.[13] Because stores are more likely to be situated in wealthier areas, this practice often means that Staples charges poorer people higher prices.[14]

Pervasive collection and use of personal information can exacerbate information disparities and contribute to the erosion of trust and free expression as individuals find themselves facing personalized, curated newsfeeds that reflect their own points of view or customized recommended videos that show increasingly radicalized versions of their own perspectives.[15] And, as described above, at its most extreme, manipulation of these curated newsfeeds and targeted advertising, coupled with stores of personal information, may be used influence individuals’ selections in the voting booth.[16]

Collection and pooling of personal information also creates treasure troves for government access. This is because the antiquated third-party doctrine dictates that personal information, once shared with a third party, forfeits all Fourth Amendment protections, and the government need not go before a court, show that there is good reason to believe that the information will turn up evidence of a crime, and get a warrant in order to obtain it.[17] The government can simply get the information from the third party without ever telling the individual to whom the information pertains. This means that e-mails receive less protections than physical mail stored in an individual’s filing cabinet and photos stored on Facebook or Flickr are more vulnerable than those kept in an album at home.[18]

The personal information third parties collect online may be useful to federal government actors going on fishing expeditions for undocumented immigrants or to the federal Drug Enforcement Agency, should New York legalize marijuana, seeking marijuana users, growers, and industry participants. Moreover, the pooling of personal information in third party hands threatens to undermine the critical criminal justice safeguards the framers thought wise to include in the Fourth Amendment.

The collection and retention of personal information does not merely create a target for law enforcement. It creates a bullseye for data thieves – whether those seeking profit or those seeking to interfere in U.S. elections.[19] Data breaches – as well as misuse of personal information – can lead to financial harm, reputational harm, emotional harm, or physical harm. The revelation of personal information can undermine an individual’s job prospects or family and friend relationships and can increase the risk of future harms. As individuals grapple with these harms, they may be reluctant to participate fully in digital life and to utilize online services.[20]

Compounding these problems, individuals in New York State, like individuals across the nation, do not know or consent to the manner in which entities collect, use, retain, share, and monetize their personal information. This misunderstanding is, at least in part, due to obfuscation on the part of the entities leveraging individuals’ personal information. Researchers at Carnegie Mellon found that it would take 76 work days for individuals to read all of the privacy policies they encounter in a year.[21]

Although the advertising industry developed a common logo and slogan to notify individuals of the opportunity to opt-out of targeted advertising, following market research, the industry selected the slogan and logo that few individuals understood, seemingly to discourage opt-out.[22] Moreover, entities that collect, use, retain, share, and monetize personal information have specialized knowledge about the algorithms and data security measures they use, as well as about how they collect, use, retain, share, and monetize personal information, that the average individual is unlikely to know or understand.

Although individuals may not fully understand how entities collect, use, retain, share, and monetize their personal information, they demonstrate time and again that they care about privacy. Ninety-two percent of Facebook users alter the social network’s default privacy settings, indicating that they wish to choose with whom they share personal information.[23]

Similarly, ninety-two percent of Americans believe companies should obtain individuals’ permission before sharing or selling their personal information.[24] The same percentage believe that entities should be compelled to provide individuals with a list of all the data they have collected about them,[25] and more individuals in the United States use Microsoft’s dashboard to access the personal information Microsoft has about them than individuals in Europe do.[26]

  1. The Legal Landscape

Drafters seeking to author privacy legislation for New York State are not painting on a clean canvas. Federally, numerous sectoral laws cover aspects of privacy in the digital age.[27] At the state level, New York State already has a data breach notification law,[28] along with other sectoral privacy laws.[29] This is not to say that the field is covered – many of these laws are out-of-date, and comprehensive privacy legislation bringing New York into the digital age is much needed. However, any legislation must be carefully crafted to interact well with existing New York and federal privacy laws.

Moreover, comprehensive privacy legislation must be carefully tailored to comport with Supreme Court precedent. In Sorrell v. IMS Health Inc., the Supreme Court overturned a Vermont statute that prohibited regulated entities from “selling or disseminating prescriber-identifying information for marketing,” subjecting content- and speaker-based restrictions “on the sale, disclosure, and use of” personal information to heightened scrutiny.[30]

Any comprehensive privacy law that proscribes the collection, use, retention, sharing, or monetization of personal information based on the purpose for the leveraging or the identity of the entity doing the leveraging is likely suspect under Sorrell.

In addition, the Supreme Court has cast doubt on the constitutionality of mandatory disclosures and notifications.[31] Although commercial speech is often held to a more lenient standard of review than other types of speech, “the Supreme Court does not necessarily apply rational basis review every time the government compels” commercial speech.

“The Court has evaluated some restrictions and prohibitions . . . under intermediate scrutiny, and others under strict scrutiny. Moreover, the commercial speech doctrine is less likely to apply when the speech regulation at issue is content based,”[32] as required privacy notifications may be.

It is incumbent on drafters and advocates to take the time to understand the relevant case law to ensure that the consumer privacy law New York ultimately adopts can withstand constitutional scrutiny, because that law will inevitably be challenged by the entities whose practices it regulates.

  1. Lessons from Other States

New York also has the opportunity to learn from the other states, like California,[33] that have already enacted consumer privacy legislation, as well as to learn from Europe’s experience implementing the General Data Protection Regulation. Here are two lessons we hope New York legislators take to heart:

  1. Any Comprehensive Privacy Legislation Must Reach More Than Just Sale

Legislation that focuses solely or primarily on the sale of personal information, as California’s law does, misses the mark. Many entities that profit off of personal information do not sell that information.[34] Rather, they leverage it to sell advertisements: an advertiser approaches the entity with an audience it would like to reach (say, suburban women with children who drive minivans and like the color blue), and the entity uses the personal information it maintains to match the advertisement to the desired audience.[35]

The fact that the personal information does not change hands is immaterial for individuals’ experiences. They are aware that companies monetize their personal information even if that information is not literally sold. Moreover, this sort of targeting enables many of the harms described earlier in this testimony – from preventing women and older workers from seeing job postings and people of color from seeing housing ads to targeting ads to encourage African-Americans to stay home on election day.

  1. Any Comprehensive Privacy Legislation Must Cover All Personal Information

Federally, too many of the proposed privacy bills maintain the so-called sensitive/non-sensitive distinction. This distinction, which provides heightened protections for so-called sensitive information, like first and last name, social security numbers, and bank account numbers, and lesser protections to other personal information, is increasingly illogical in the digital age. So-called non-sensitive information can be aggregated to reveal sensitive information, and, in fact, some non-sensitive information, in isolation, may reveal sensitive information.

For example, while health status is frequently considered sensitive, shopping history is not. But, if an individual is shopping at TLC Direct[36] and Headcovers Unlimited,[37] two websites that specialize in hats for chemotherapy patients, her shopping history may reveal her health status. In addition, so-called non-sensitive information can be used for purposes that are quite sensitive. For example, if Cambridge Analytica (and, for that matter, the Obama campaign)[38] is to be believed, so-called non-sensitive information, like social media likes, can be leveraged for highly sensitive activities such as influencing how individuals vote.

In addition, sensitivity is highly subjective; different individuals are likely to perceive the sensitivity of different pieces of personal information differently. For these reasons, any line drawing around sensitivity is inherently arbitrary. Comprehensive privacy legislation must instead provide meaningful protections for all personal information – that is, any information that is reasonably linkable, directly or indirectly, to a specific individual, household, or device – and not merely for so-called sensitive information.

  1. The New York Privacy Act and Recommendations

The preceding pages of this testimony sought to paint a robust picture of the landscape the legislature is wading into. This is not to suggest either that the legislature could or should solve for every single one of the harms identified in the first part of this statement in comprehensive privacy legislation nor is it to suggest that legislators should throw your hands up and walk away.

It is, however, to illustrate that this issue is complex, and if we do not have an idea of the problems we seek to solve, we are unlikely to address them. The NYCLU strongly urges the legislature to give comprehensive privacy legislation the attention it deserves and not to rush to pass a bill this session.

The Committees are taking an important step by holding this hearing. In addition, the legislature is not starting from a blank slate. More than 105 privacy bills have been introduced this session, some of which contain good ideas. The remainder of this testimony will focus on S.5642, the New York Privacy Act, one of the bills specifically under consideration today.

Senator Thomas’ S.5642 introduces a number of important ideas to the privacy debate in New York. Notably, the bill advances the concept of a data fiduciary,[39] recognizing that entities that collect, use, retain, share, and monetize personal information have specialized knowledge about the algorithms and security measures they use, as well as about how they collect, use, retain, share, and monetize personal information, that the average individual is unlikely to understand.

Just as banks, lawyers, and medical providers, given their specialized knowledge, have special duties to individuals, entities collecting intimate personal information in the digital age and benefiting from similarly specialized knowledge should have similar obligations.

The bill also codifies a requirement that entities conducting business in New York State adhere to an individual’s do not track selection,[40] something that is not required under current law. At present, although an individual can choose to add a do not track extension to her internet browser, websites can decide whether or not to honor the selection. Senator Thomas’ bill would fix this problem and comport the law to individuals’ expectations and desires.

The bill also contains important safeguards for individuals, including the ability to restrict the collection, processing, and transmission of their personal information, as well as access, correction, deletion, transparency, and data portability rights.[41] Finally, the bill contains some algorithmic decision-making protections.[42]

There are also areas where S.5642 could improve. For example, although the bill contains a robust and comprehensive list of privacy risks[43] – strongly suggesting that Senator Thomas has carefully considered what problems comprehensive privacy legislation should solve for – the data fiduciary section only obligates a covered entity to refrain from using personal information in ways that “will result in reasonably foreseeable and material physical or financial harm” to an individual.[44]

Although these harms are important, financial harm, in particular, is among the least likely to occur. That is because when financial loss does arise from a data breach or misuse of data – say, where a credit card number is stolen and fraudulent purchases are made – it is often difficult to trace the stolen information to a particular privacy violation.[45]

When it is possible to trace the financial harm back, banks often reimburse customers for fraudulent purchases, obviating any actual financial loss.[46] Physical harm, of course, can be devastating when it does occur. However, these two harms are a vanishingly small subset of the harms that can arise from the pervasive collection, sharing, monetization, use, and misuse of personal information

The bill also fails to articulate whether the consent for personal information processing must be opt-in or opt-out.[47] This is important, because default is often destiny. Many individuals never change a site’s default settings, meaning that significantly more personal information will be processed under an opt-out regime than under an opt-in regime.[48] This in turn matters because personal information is just that – personal – and individuals should be in the position to decide how, when, and why it is processed and with whom it is shared.

In addition, although S.5642 begins to tackle algorithmic decision-making, it does not do so holistically and fails to sufficiently address the civil rights harms that can arise from algorithmic decision-making, in part because the legislative language is not sufficiently airtight and in part because bill carves out public algorithmic decision systems.[49]

Finally, in addition to the important safeguards articulated in this bill and beyond, New Yorkers need digital literacy and digital privacy education that helps us to identify online fraud, as well as reliable sources and information, and that enables us to better understand how online activities are tracked and recorded, where personal information posted online may go, with whom it may be shared, how it may be used, and how to best protect our digital security and digital privacy.

One of the reasons businesses and governments have so successfully convinced New Yorkers – and individuals across the country – to give away the most intimate details of our lives is that many of us do not know what we are giving away. We do not know what data businesses collect, how our activities are tracked and recorded, where that information goes, or how it is used once it is collected.

Part of the solution lies in requiring companies to be more transparent, to give individuals more choices, and to eschew some of their most problematic practices, but the other part of the solution lies in educating New Yorkers to better safeguard their own privacy and to make better choices about the ways in which they share and consume information in the digital age.

  1. Conclusion

The NYCLU appreciates the opportunity to testify today and stands ready to assist the Committee, Chairman Thomas, and other interested legislators as you craft comprehensive privacy legislation for New York State.

[1] See Galen Sherwin & Esha Bhandari, Facebook Settles Civil Rights Cases by Making Sweeping Changes to Its Online Ad Platform, ACLU Speak Freely, Mar. 19, 2019,

[2] Timothy B. Lee, Facebook’s Cambridge Analytica scandal, explained [Updated], Ars Technica, Mar. 20, 2018,

[3] Natasha Singer, Just Don’t Call It Privacy, NYTimes, Sept. 23, 2018,

[4] Id.

[5] Julia Angwin, Noam Scheiber, & Ariana Tobin, Facebook Job Ads Raise Concerns About Age Discrimination, NYTimes, Dec. 20, 2017,

[6] Julia Angwin, Ariana Tobin, & Madeleine Varner, Facebook (Still) Letting Housing Advertisers Exclude Users By Race, ProPublica, Nov. 21, 2017,

[7] Leigh Freund, President and CEO, Network Advertising Initiative, Competition and Consumer Protection Issues in Online Advertising, Testimony before the FTC Hearings on Big Data, Privacy, and Competition (Nov. 7, 2018).

[8] There are also entities that wish to use amassed personal information and algorithms for admirable purposes – to engage in affirmative action and to target opportunities and messages specifically to more marginalized communities. See Public Interest Privacy Legislation Principles (Nov. 13, 2018),

[9] Karen Hao, What is machine learning? We drew you another flowchart, MIT Tech. Rev., Nov. 17, 2018,

[10] Sarah Wachter-Boettcher, Why You Can’t Trust AI to Make Unbiased Hiring Decisions, Time, Oct. 25, 2017,

[11] Jeffrey Dastin, Amazon scraps secret AI recruiting tool that showed bias against women, Reuters, Oct. 9, 2018,

[12] See The Use of Pretrial “Risk Assessment” Instruments: A Shared Statement of Civil Rights Concerns (July 30, 2018),

[13] Jennifer Valentino-DeVries, Jeremy Singer-Vine, & Ashkan Soltani, Websites Vary Prices, Deals Based on Users’ Information, Wall Street J., Dec. 24, 2012,

[14] Id.

[15] Conor Friedersdor, YouTube Extremism and the Long Tail, The Atlantic, Mar. 12, 2018,

[16] Timothy B. Lee, Facebook’s Cambridge Analytica scandal, explained [Updated], Ars Technica, Mar. 20, 2018,; Natasha Singer, Just Don’t Call It Privacy, NYTimes, Sept. 23, 2018,

[17] See generally Jay Stanely, The Crisis in Fourth Amendment Jurisprudence, Am. Const. Soc’y Issue Brief, May 2010, at 2,

[18] The Supreme Court last year in Carpenter v. United States made clear that the third-party doctrine does not automatically apply to individuals’ location records held by their cell phone providers. Although the lesson of Supreme Court’s holding should apply equally to any digital database of personal information held by a third party, government entities continue to access personal information without a warrant. Cf. Nathan Freed Wessler, The Government Needs to Get a Warrant if It Wants Access to Our Private Health Information, ACLU Speak Freely, May 29, 2019,

[19] See generally Robert S. Mueller, III, Report on the Investigation Into Russian Interference In The 2016 Presidential Election (2019).

[20] E.g. Avi Goldfarb, Rotman Chair in Artificial Intelligence and Healthcare, Rotman School of Management, University of Toronto, The Impact of Privacy Regulations on Competition and Innovation, Testimony before the FTC Hearings on Big Data, Privacy, and Competition (Nov. 7, 2018) (testifying that “it’s much harder to get people to fill out surveys than it used to be.”); Lior Strahilevitz, Sidley Austin Professor of Law, University of Chicago Law School, The Impact of Privacy Regulations on Competition and Innovation, Testimony before the FTC Hearings on Big Data, Privacy, and Competition (Nov. 7, 2018) (testifying that fewer people answer their cell phones today “if it’s an unrecognized number.”); Amalia Miller, Associate Professor of Economics, University of Virginia, The Impact of Privacy Regulations on Competition and Innovation, Testimony before the FTC Hearings on Big Data, Privacy, and Competition (Nov. 7, 2018) (testifying that if individuals “don’t feel that their data are safe, they may not download apps on their phone . . . They may shut off Facebook or never post their child online because they don’t feel that privacy is protected” and observing that the U.S. has been slower to adopt electronic medical records, leading to “greater mortality, greater infant mortality.”).

[21] Alexis C. Madrigal, Reading the Privacy Policies You Encounter in a Year Would Take 76 Work Days, The Atlantic, Mar. 1, 2012,

[22] See FPF Staff, Online Behavioral Advertising “Icon” Study, Future of Privacy Forum (Feb. 15 2010),; Jonathan Mayer, Tracking the Trackers: The AdChoices Icon, Stanford Law School: The Center for Internet & Society (Aug. 18, 2011),

[23] Emil Protalinksi, 13 million US Facebook users don’t change privacy settings, ZDNet, May 3, 2012,

[24] Christopher Boone, Vice President of Real World Data and Analytics, Pfizer, The Business of Big Data, Testimony before the FTC Hearings on Big Data, Privacy, and Competition (Nov. 6, 2018).

[25] Id.

[26] Julie Brill, Corporate Vice President and Deputy General Counsel for Global Privacy and Regulatory Affairs, Microsoft, Former Enforcers Perspective: Where Do We Go From Here? What is Right, Wrong, or Indeterminate about Data Policy?, Testimony before the FTC Hearings on Big Data, Privacy, and Competition (Nov. 8, 2018).

[27] E.g. 5 U.S.C. 552a (the Privacy Act of 1974); 12 U.S.C. 3401 et seq. (the Right to Financial Privacy Act of 1978); 15 U.S.C. 1681 et seq. (the Fair Credit Reporting Act); 15 U.S.C. 1692 et seq. (the Fair Debt Collection Practices Act); 15 U.S.C. 6501 et seq. (the Children’s Online Privacy Protection Act); 15 U.S.C. 6801 et seq. (Title V of the Gramm-Leach-Bliley Act); 18 U.S.C. 119; 18 U.S.C. 123; 18 U.S.C. 206; 20 U.S.C. 1232g (the Family Educational Rights and Privacy Act of 1974); 20 U.S.C. 1232h; 42 U.S.C. 2000aa et seq. (the Privacy Protection Act of 1980); 42 U.S.C. 1320d-2 note (the Health Insurance Portability and Accountability Act of 1996); 47 U.S.C. 222, 227.

[28] N.Y. Gen. Bus. Law § 899-aa (McKinney).

[29] E.g. N.Y. Educ. Law § 2-d (McKinney) (protecting student privacy); N.Y. Lab. Law § 203-d (McKinney) (protecting employee privacy); N.Y. Gen. Business Law § 899-aa (Information Security Breach and Notification Act”); and N.Y. Technology Law § 208 (same, applicable to state entities);  Personal Privacy Protection Law, N.Y. Public Officers Law, Article 6-A, §§ 91-99 (McKinney) (regulating the manner in which the state collects, maintains and disseminates personal information); N.Y. Civil Rights Law § Section 79-L (McKinney) (providing confidentiality for genetic test records). See also 23 NYCRR § 500 et seq. (establishing “Cybersecurity Requirements for Financial Services Companies”).

[30] 564 U.S. 552, 562 – 65 (2011).

[31] See generally NIFLA v. Becerra, 585 U.S. ___, ___ (2018).

[32] Stuart v. Loomis, 992 F. Supp. 2d 585, 593 (M.D.N.C. 2014) (internal citations omitted).

[33] Cal. Civ. Code § 1798.175 et seq. (West).

[34] E.g. Kurt Wagner, This is how Facebook uses your data for ad targeting, Recode, Apr. 11, 2018,

[35] Id. Some entities are also set up to find look-alike audiences with similar traits to a pre-populated list an advertiser provides. Some also permit an advertiser to target particular individuals. Upturn, Leveling the Platform: Real Transparency for Paid Messages on Facebook (May 2018).

[36] TLC Direct, (last visited Nov. 2, 2018).

[37] Headcovers Unlimited, (last visited Nov. 2, 2018).

[38] Tim Murphy, Inside the Obama Campaign’s Hard Drive, Mother Jones, Sept./Oct. 2012,

[39] S.5642 § 2, 2019-2020 Reg. Sess. (N.Y. 2019).

[40] Id.

[41] Id.

[42] Id.

[43] Id.

[44] Id.

[45] See Nicole Hong, For Consumers, Injury Is Hard to Prove in Data-Breach Cases, Wall Street J., June 26, 2016,

[46] Id.

[47] S.5642 § 2, 2019-2020 Reg. Sess. (N.Y. 2019).

[48] Lena V. Groeger, Set It and Forget It: How Default Settings Rule the World, Pro Publica, July 27, 2016,

[49] S.5642 § 2, 2019-2020 Reg. Sess. (N.Y. 2019).


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