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II
117TH CONGRESS
1ST SESSION
S. 2134
To establish the Data Protection Agency.
IN THE SENATE OF THE UNITED STATES
JUNE 17, 2021
Mrs. GILLIBRAND (for herself and Mr. BROWN) introduced the following bill;
which was read twice and referred to the Committee on Commerce,
Science, and Transportation
A BILL
To establish the Data Protection Agency.
Be it enacted by the Senate and House of Representa-
1
tives of the United States of America in Congress assembled,
2
SECTION 1. SHORT TITLE.
3
This Act may be cited as the ‘‘Data Protection Act
4
of 2021’’.
5
SEC. 2. DEFINITIONS.
6
In this Act:
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(1) AGENCY.—The term ‘‘Agency’’ means the
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Data Protection Agency established under section 3.
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(2)
ANONYMIZED
DATA.—The
term
10
‘‘anonymized data’’ means information—
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(A) that does not identify an individual;
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and
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(B) with respect to which there is no rea-
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sonable basis to believe that the information
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can be used on its own or in combination with
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other reasonably available information to iden-
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tify an individual.
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(3) AUTOMATED DECISION SYSTEM.—The term
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‘‘automated decision system’’ means a computational
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process, including one derived from machine learn-
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ing, statistics, or other data processing or artificial
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intelligence techniques, that makes a decision, or fa-
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cilitates human decision making.
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(4) BIOMETRIC INFORMATION.—The term ‘‘bio-
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metric information’’—
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(A) means information regarding the phys-
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iological or biological characteristics of an indi-
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vidual that may be used, singly or in combina-
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tion with each other or with other identifying
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data, to establish the identity of an individual;
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(B) includes—
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(i) genetic data;
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(ii) imagery of the iris, retina, finger-
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print, face, hand, palm, vein patterns, and
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voice recordings, from which an identifier
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•S 2134 IS
template, such as a faceprint, a minutiae
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template, or a voiceprint, can be extracted;
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(iii) keystroke patterns or rhythms,
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gait patterns or rhythms, and sleep,
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health, or exercise data that contain identi-
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fying information; and
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(iv) any mathematical code, profile, or
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algorithmic model derived from informa-
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tion regarding the physiological or biologi-
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cal characteristics of an individual;
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(C) does not include information captured
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from a patient in a health care setting for a
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medical purpose or information collected, used,
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or stored for health care treatment, payment, or
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operations under the Health Insurance Port-
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ability and Accountability Act of 1996 (Public
16
Law 104–191); and
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(D) does not include an X-ray, roentgen
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process, computed tomography, MRI, PET
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scan, mammography, or other image or film of
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the human anatomy used to diagnose, prognose,
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or treat an illness or other medical condition or
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to further validate scientific testing or screen-
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ing.
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(5) COLLECT.—The term ‘‘collect’’—
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(A) means buying, renting, gathering, ob-
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taining, receiving, or accessing any personal
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data by any means; and
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(B) includes—
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(i) receiving personal data from an in-
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dividual or device; and
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(ii) creating, deriving, or inferring
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personal data by analyzing data about an
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individual or about groups of individuals
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similar to the individual.
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(6) DATA
AGGREGATOR.—The term ‘‘data
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aggregator’’—
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(A) means any person that collects, uses,
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or shares, in or affecting interstate commerce,
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an amount of personal data that is not de mini-
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mis, as well as entities related to that person by
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common ownership or corporate control; and
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(B) does not include an individual who col-
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lects, uses, or shares personal data solely for
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non-commercial reasons.
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(7) DEVICE.—The term ‘‘device’’ means any
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physical object that—
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(A) is capable of connecting to the internet
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or other communication network; or
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(B) has computer processing capabilities
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that can collect, send, receive, or store data.
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(8) DIRECTOR.—The term ‘‘Director’’ means
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the Director of the Data Protection Agency.
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(9) ELECTRONIC DATA.—The term ‘‘electronic
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data’’ means any information that is in an electronic
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or digital format or any electronic or digital ref-
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erence that contains information about an individual
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or device.
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(10) FEDERAL PRIVACY LAW.—The term ‘‘Fed-
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eral privacy law’’ means the provisions of this Act,
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any other rule or order prescribed by the Agency
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under this Act, and the following laws (including any
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amendments made to such laws):
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(A) Title V of the Gramm-Leach-Bliley Act
15
(Public Law 106–102; 113 Stat. 1338).
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(B) The Fair Credit Reporting Act (15
17
U.S.C. 1681 et seq.).
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(C) The Telemarketing and Consumer
19
Fraud and Abuse Prevention Act (15 U.S.C.
20
6101 et seq.).
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(D) The Fair and Accurate Credit Trans-
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actions Act of 2003 (Public Law 108–159; 117
23
Stat. 1952).
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(E) The CAN-SPAM Act of 2003 (15
1
U.S.C. 7701 et seq.).
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(F) Sections 222, 227, 338(l), 631, and
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705 of the Communications Act of 1934 (47
4
U.S.C. 222, 227, 338(l), 551, 705).
5
(G) The Children’s Online Privacy Protec-
6
tion Act of 1998 (15 U.S.C. 6501 et seq.).
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(H) The Right to Financial Privacy Act of
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1978 (12 U.S.C. 3401 et seq.).
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(I) The Identity Theft Assumption and
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Deterrence Act of 1998 (Public Law 105–318;
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117 Stat. 3007).
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(J) The General Education Provisions Act
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(20 U.S.C. 1221 et seq.) (commonly known as
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the ‘‘Family Educational Rights and Privacy
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Act of 1974’’).
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(K) Section 552a of title 5, United States
17
Code.
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(L) The E-Government Act of 2002 (Pub-
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lic Law 107–347; 116 Stat. 2899).
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(M) The Computer Security Act of 1987
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(40 U.S.C. 1441 note).
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(N) The Employee Polygraph Protection
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Act of 1988 (29 U.S.C. 2001 et seq.).
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(O) The Communications Assistance for
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Law Enforcement Act (Public Law 103–414;
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108 Stat. 4279).
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(P) Sections 1028A, 1030, 1801, 2710,
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and 2721 and chapter 119, of title 18, United
5
States Code.
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(Q)
The
Genetic
Information
Non-
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discrimination Act of 2008 (Public Law 110–
8
233; 122 Stat. 881).
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(R) The Taxpayer Browsing Protection
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Act (Public Law 105–35; 111 Stat. 1104).
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(S) The Privacy Protection Act of 1980
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(42 U.S.C. 2000aa et seq.).
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(T) The Cable Communications Policy Act
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of 1984 (Public Law 98–549; 98 Stat. 2779).
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(U) The Do-Not-Call Implementation Act
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(Public Law 108–10; 117 Stat. 557).
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(V) The Wireless Communications and
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Public Safety Act of 1999 (Public Law 106–81;
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113 Stat. 1286).
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(W) Title XXX of the Public Health Serv-
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ice Act (42 U.S.C. 300jj et seq.).
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(11) HIGH-RISK
DATA
PRACTICE.—The term
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‘‘high-risk data practice’’ means an action by a data
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aggregator that involves—
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(A) the use of an automated decision sys-
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tem;
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(B) the processing of data in a manner
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that involves an individual’s protected class, fa-
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milial status, lawful source of income, financial
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status such as the individual’s income or as-
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sets), veteran status, criminal convictions or ar-
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rests, citizenship, past, present, or future phys-
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ical or mental health or condition, psychological
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states, or any other factor used as a proxy for
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identifying any of these characteristics;
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(C) a systematic processing of publicly ac-
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cessible data on a large scale;
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(D) processing involving the use of new
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technologies, or combinations of technologies,
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that causes or materially contributes to privacy
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harm;
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(E) decisions about an individual’s access
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to a product, service, opportunity, or benefit
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which is based to any extent on automated deci-
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sion system processing;
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(F) any profiling of individuals on a large
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scale;
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(G) any processing of biometric informa-
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tion for the purpose of uniquely identifying an
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•S 2134 IS
individual, with the exception of one-to-one bio-
1
metric authentication;
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(H) combining, comparing, or matching
3
personal data obtained from multiple sources;
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(I) processing which involves an individ-
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ual’s precise geolocation;
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(J) the processing of personal data of chil-
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dren and teens under 17 or other vulnerable in-
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dividuals such as the elderly, people with dis-
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abilities, and other groups known to be suscep-
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tible for exploitation for marketing purposes,
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profiling, or automated processing; or
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(K) consumer scoring or other business
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practices that pertain to the eligibility of an in-
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dividual, and related terms, rights, benefits, and
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privileges, for employment (including hiring, fir-
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ing, promotion, demotion, and compensation),
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credit, insurance, housing, education, profes-
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sional certification, or the provision of health
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care and related services.
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(12) HIGH-RISK DATA PRACTICE IMPACT EVAL-
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UATION.—The term ‘‘high-risk data practice impact
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evaluation’’ means a study conducted after deploy-
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ment of a high-risk data practice that includes, at
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a minimum—
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(A) an evaluation of a high-risk data prac-
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tice’s accuracy, disparate impacts on the basis
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of protected class, and privacy harms;
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(B) an evaluation of the effectiveness of
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measures taken to minimize risks as outlined in
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any prior high-risk data practice risk assess-
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ments; and
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(C) recommended measures to further min-
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imize risks to accuracy, disparate impacts on
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the basis of protected class, and privacy harms.
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(13) HIGH-RISK DATA PRACTICE RISK ASSESS-
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MENT.—The term ‘‘high-risk data practice risk as-
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sessment’’ means a study evaluating a high-risk data
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practice and the high-risk data practice’s develop-
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ment process, including the design and training data
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of the high-risk data practice, if applicable, for likeli-
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hood and severity of risks to accuracy, bias, dis-
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crimination, and privacy harms that includes, at a
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minimum—
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(A) a detailed description of the high-risk
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data practice, including—
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(i) its design and methodologies;
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(ii) training data characteristics;
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(iii) data; and
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(iv) purpose;
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(B) an assessment of the relative benefits
1
and costs of the high-risk data practice in light
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of its purpose, potential unintended con-
3
sequences, and taking into account relevant fac-
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tors, including—
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(i) data minimization practices;
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(ii) the duration and methods for
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which personal data and the results of the
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high-risk data practice are stored;
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(iii) what information about the high-
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risk data practice is available to individ-
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uals;
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(iv) the extent to which individuals
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have access to the results of the high-risk
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data practice and may correct or object to
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its results; and
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(v) the recipients of the results of the
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high-risk data practice;
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(C) an assessment of the risks of privacy
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harm posed by the high-risk data practice and
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the risks that the high-risk data practice may
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result in or contribute to inaccurate, biased, or
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discriminatory decisions impacting individuals
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or groups of individuals; and
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(D) the decision to accept, reject, or miti-
1
gate and minimize risks and the measures a
2
data aggregator will employ including to mini-
3
mize the risks described in subparagraph(C),
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including technological and physical safeguards.
5
(14)
INDIVIDUAL.—The
term
‘‘individual’’
6
means a natural person.
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(15) PERSON.—The term ‘‘person’’ means an
8
individual, a local, State, or Federal governmental
9
entity, a partnership, a company, a corporation, an
10
association (incorporated or unincorporated), a
11
trust, an estate, a cooperative organization, another
12
entity, or any other organization or group of such
13
entities acting in concert.
14
(16) PERSONAL
DATA.—The term ‘‘personal
15
data’’ means electronic data that, alone or in com-
16
bination with other data—
17
(A) identifies, relates to, describes, is capa-
18
ble of being associated with, or could reasonably
19
be linked, directly or indirectly, with a par-
20
ticular individual, household, or device; or
21
(B) could be used to determine that an in-
22
dividual or household is part of a protected
23
class.
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(17) PRECISE GEOLOCATION.—The term ‘‘pre-
1
cise geolocation’’ means any data that is derived
2
from a device and that is used or intended to be
3
used to locate an individual within a geographic area
4
that is equal to or less than the area of a circle with
5
a radius of one thousand, eight hundred and fifty
6
(1,850) feet.
7
(18) PRIVACY
HARM.—The term ‘‘privacy
8
harm’’ means an adverse consequence, or a potential
9
adverse consequence, to an individual, a group of in-
10
dividuals, or society caused, in whole or in part, by
11
the collection, processing, or sharing of personal
12
data, including—
13
(A) direct or indirect financial loss or eco-
14
nomic harm, including financial loss or eco-
15
nomic harm arising from fraudulent activities
16
or data secu
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