...isclosure
and
retention
of
27
genetic information.
28
The
legislature
further
finds
that
the
use of automated decision
29
systems to make core government and business decisions
raises
concerns
30
around
due process, fairness, accountability, and transparency, as well
31
as other civil rights and liberties.
R...
...ness, accountability, and transparency, as well
31
as other civil rights and liberties.
Reliance
on
automated
decision
32
systems
without
adequate
transparency,
oversight,
or safeguards can
33
undermine market predictability, harm consumers, and
deny
historically
34
disadvantaged
or
vulnerable
groups
the
ful...
...sed singular-
5
ly or in combination with other characteristics, or with other
informa-
6
tion,
for
automated
recognition
of
a
known
or unknown individual.
7
Examples of such term shall include, but not be
limited
to:
finger-
8
prints,
retina
and
iris
patterns,
voiceprints, DNA sequence, facial
9
characteris...
... welfare.
24
(ii)
"Automated decision system impact assessment" shall mean a study
25
evaluating an automated
decision
system
and
the
automated
decision
26
system's
development
processes, including the design and training data
27
of the automated decision system, for
statistical
impacts
on
classes
28
protect...
...ion system impact assessment" shall mean a study
25
evaluating an automated
decision
system
and
the
automated
decision
26
system's
development
processes, including the design and training data
27
of the automated decision system, for
statistical
impacts
on
classes
28
protected
under section two hundred ninet...
...omated
decision
26
system's
development
processes, including the design and training data
27
of the automated decision system, for
statistical
impacts
on
classes
28
protected
under section two hundred ninety-six of the executive law, as
29
well as for impacts on privacy, and security that includes at a minim...
...r impacts on privacy, and security that includes at a minimum:
30
(A) A detailed description
of
the
automated
decision
system,
its
31
design, its training, its data, and its purpose;
32
(B)
An assessment of the relative benefits and costs of the automated
33
decision system in light of its purpose, taking
in...
...training, its data, and its purpose;
32
(B)
An assessment of the relative benefits and costs of the automated
33
decision system in light of its purpose, taking
into
account
relevant
34
factors,
including
data minimization practices, the duration for which
35
personal information and the results of the
autom...
...
data minimization practices, the duration for which
35
personal information and the results of the
automated
decision
system
36
are
stored,
what
information
about the automated decision system are
37
available to the public, and the recipients of the results of the
auto-
38
mated decision system;
39
(C)
An ...
...ormation and the results of the
automated
decision
system
36
are
stored,
what
information
about the automated decision system are
37
available to the public, and the recipients of the results of the
auto-
38
mated decision system;
39
(C)
An assessment of the risk of harm posed by the automated decision
40
sy...
...esults of the
auto-
38
mated decision system;
39
(C)
An assessment of the risk of harm posed by the automated decision
40
system and the risk that such automated decision system may result in or
41
contribute to inaccurate, unfair, biased,
or
discriminatory
decisions
42
impacting individuals; and
43
(D)
The
...
...
An assessment of the risk of harm posed by the automated decision
40
system and the risk that such automated decision system may result in or
41
contribute to inaccurate, unfair, biased,
or
discriminatory
decisions
42
impacting individuals; and
43
(D)
The
measures
the state agency will employ to minimize th...
...ll not purchase, obtain,
38
procure, acquire, employ, use, deploy, or
access
information
from
an
39
automated
decision system unless it first engages a neutral third party
40
to conduct an automated decision system impact assessment and
publishes
41
on its public website that automated decision system impact...
...from
an
39
automated
decision system unless it first engages a neutral third party
40
to conduct an automated decision system impact assessment and
publishes
41
on its public website that automated decision system impact assessment:
42
(i)
Of
existing
automated
decision
system
within one year of the
43
effec...
... conduct an automated decision system impact assessment and
publishes
41
on its public website that automated decision system impact assessment:
42
(i)
Of
existing
automated
decision
system
within one year of the
43
effective date of this subdivision and every two years thereafter.
44
(ii) Of new automated d...
...ishes
41
on its public website that automated decision system impact assessment:
42
(i)
Of
existing
automated
decision
system
within one year of the
43
effective date of this subdivision and every two years thereafter.
44
(ii) Of new automated decision systems prior to acquisition and
every
45
two years ther...
...ne year of the
43
effective date of this subdivision and every two years thereafter.
44
(ii) Of new automated decision systems prior to acquisition and
every
45
two years thereafter.
46
c. Upon publication of an automated decision system impact assessment,
47
the public shall have forty-five days to submit c...
...cision systems prior to acquisition and
every
45
two years thereafter.
46
c. Upon publication of an automated decision system impact assessment,
47
the public shall have forty-five days to submit comments on such assess-
48
ment
to the state and any governmental agency, political subdivision or
49
public ben...
...hether to purchase, obtain, procure,
52
acquire, employ, use, deploy, or access information
from
an
automated
53
decision
system and shall post responses to such public comments to its
54
website within forty-five days after the close
of
the
public
comment
55
period.
S. 2277
20
1
d.
The
state
procurement
cou...
...n
rights
3
and
experts
and
representatives
from
the
communities
that will be
4
directly affected by automated decision systems,
promulgate
rules
and
5
regulations
to set the minimum standard entities shall meet to serve as
6
neutral
third
parties
conducting
automated
decision
system
impact
7
assessments.
8
e...
...ions
to set the minimum standard entities shall meet to serve as
6
neutral
third
parties
conducting
automated
decision
system
impact
7
assessments.
8
e.
The
state procurement council shall maintain a publicly available
9
list of neutral third parties that meet the qualifications
outlined
in
10
paragraph d of...
... rights and experts and representatives from the commu-
14
nities
that
will
be
directly affected by automated decision systems,
15
shall complete and publish on its website a comprehensive study
of
the
16
statistical
impacts
of automated decision systems on classes protected
17
under section two hundred nine...
...15
shall complete and publish on its website a comprehensive study
of
the
16
statistical
impacts
of automated decision systems on classes protected
17
under section two hundred ninety-six of the executive law, including but
18
not limited to, evaluating the use of proxies and the types of data used
19
in tra...
...ta.
21
(i)
As
part
of
such
study,
the
office of information technology
22
services shall review the automated decision system
impact
assessments
23
that
have
been
published prior to completion of the study, as well as
24
the public comments submitted in response
to
such
automated
decision
25
impact assessmen...
...d prior to completion of the study, as well as
24
the public comments submitted in response
to
such
automated
decision
25
impact assessments.
26
(ii) The office may request data and information from: state agencies;
27
consumer
protection,
civil
rights, and privacy advocates; researchers
28
and academics; pr...
...ights, and privacy advocates; researchers
28
and academics; private entities that develop or deploy
automated
deci-
29
sion
systems;
and
other
relevant sources to meet the purpose of such
30
study. The office shall receive, upon request,
data
from
other
state
31
agencies.
32
10.
Automated
decision
system use...
... "Automated decision system use policy" shall mean:
42
(A)
A
description
of
the
capabilities
of
the automated decision
43
system, any decisions that such system is used
to
make
or
assist
in
44
making
and
any
specific
types
or
groups of persons protected under
45
section two hundred ninety-six of the executiv...
...ules, processes, and guidelines issued by the state agency
regu-
48
lating
access
to
or use of such automated decision system, as well as
49
any prohibitions or restrictions on use;
50
(C) Safeguards or security measures designed
to
protect
information
51
collected
by or inputted into such automated decision...
...feguards or security measures designed
to
protect
information
51
collected
by or inputted into such automated decision system, including
52
but not limited to, the existence of encryption and access control mech-
53
anisms;
54
(D) Policies and practices relating to the retention, access, and
use
55
of data c...
... practices relating to the retention, access, and
use
55
of data collected by or inputted into such automated decision system, as
56
well as the decisions rendered by such automated decision system;
S. 2277
21
1
(E) Whether other entities outside the state agency have access to the
2
information
and
data
use...
...ed by or inputted into such automated decision system, as
56
well as the decisions rendered by such automated decision system;
S. 2277
21
1
(E) Whether other entities outside the state agency have access to the
2
information
and
data
used
by or inputted into the automated decision
3
system or the decisions
r...
...ies outside the state agency have access to the
2
information
and
data
used
by or inputted into the automated decision
3
system or the decisions
rendered
by
the
automated
decision
system,
4
including
whether
the
outside
entity
is
local,
state, federal, or
5
private, the type of information and data that may ...
...
and
data
used
by or inputted into the automated decision
3
system or the decisions
rendered
by
the
automated
decision
system,
4
including
whether
the
outside
entity
is
local,
state, federal, or
5
private, the type of information and data that may be disclosed, and any
6
safeguards
or
restrictions imposed by...
...sion;
9
(F)
Whether any training is required by the state agency for an indi-
10
vidual to use such
automated
decision
system
or
access
information
11
collected
by
or
inputted
into
such automated decision system or the
12
decisions rendered by the automated decision system;
13
(G) A description of the intern...
...l to use such
automated
decision
system
or
access
information
11
collected
by
or
inputted
into
such automated decision system or the
12
decisions rendered by the automated decision system;
13
(G) A description of the internal and
external
audit
and
oversight
14
mechanisms,
including
the
mechanism
for
human r...
...11
collected
by
or
inputted
into
such automated decision system or the
12
decisions rendered by the automated decision system;
13
(G) A description of the internal and
external
audit
and
oversight
14
mechanisms,
including
the
mechanism
for
human review required under
15
paragraph g of this subdivision, to en...
...m
for
human review required under
15
paragraph g of this subdivision, to ensure compliance with the automated
16
decision use policy and that the
automated
decision
system
does
not
17
result in harm to an individual;
18
(H)
Relevant
technical
information
about
the
automated
decision
19
system, including the ...
... g of this subdivision, to ensure compliance with the automated
16
decision use policy and that the
automated
decision
system
does
not
17
result in harm to an individual;
18
(H)
Relevant
technical
information
about
the
automated
decision
19
system, including the system's name, vendor, and version, as well
as...
...system
does
not
17
result in harm to an individual;
18
(H)
Relevant
technical
information
about
the
automated
decision
19
system, including the system's name, vendor, and version, as well
as
a
20
description
of
the
automated
decision system's general capabilities,
21
including reasonably foreseeable capabili...
...ion
19
system, including the system's name, vendor, and version, as well
as
a
20
description
of
the
automated
decision system's general capabilities,
21
including reasonably foreseeable capabilities outside the scope
of
the
22
agency's proposed use;
23
(I)
The
type
or
types
of
data inputs that the automated ...
...outside the scope
of
the
22
agency's proposed use;
23
(I)
The
type
or
types
of
data inputs that the automated decision
24
system uses, how that data is generated, collected, and
processed,
and
25
the types of data the system is reasonably likely to generate;
26
(J)
How
and
when
the automated decision system ...
...ssed,
and
25
the types of data the system is reasonably likely to generate;
26
(J)
How
and
when
the automated decision system will be deployed or
27
used and by whom, including but not limited to, the factors that will be
28
used to determine where, when, and how the technology is deployed;
29
(K) A descript...
...ction with the auto-
31
mated decision system; and
32
(L)
A
description
of
the
fiscal
impact of the automated decision
33
system, including initial acquisition costs,
ongoing
operating
costs,
34
such
as maintenance, licensing, personnel, legal compliance, use audit-
35
ing, data retention, and security costs...
...rchases,
obtains,
38
procures, acquires, employs, uses, deploys, or accesses information from
39
an automated decision system shall publish on its website at least nine-
40
ty
days
prior to the purchase, obtaining, use, acquisition, or deploy-
41
ment of new automated decision systems and, for existing autom...
...east nine-
40
ty
days
prior to the purchase, obtaining, use, acquisition, or deploy-
41
ment of new automated decision systems and, for existing automated deci-
42
sion systems, within one hundred eighty days of the
effective
date
of
43
this subdivision, an automated decision system use policy.
44
(i)
When t...
...obtaining, use, acquisition, or deploy-
41
ment of new automated decision systems and, for existing automated deci-
42
sion systems, within one hundred eighty days of the
effective
date
of
43
this subdivision, an automated decision system use policy.
44
(i)
When the state and any governmental agency, politic...
...i-
42
sion systems, within one hundred eighty days of the
effective
date
of
43
this subdivision, an automated decision system use policy.
44
(i)
When the state and any governmental agency, political subdivision
45
or public benefit corporation of the state seeks to change or changes an
46
automated decision ...
...olitical subdivision
45
or public benefit corporation of the state seeks to change or changes an
46
automated decision system in a way that affects the results or
outcomes
47
of
the automated decision system or uses such automated decision system
48
for a purpose or manner not previously disclosed
through
an...
... or changes an
46
automated decision system in a way that affects the results or
outcomes
47
of
the automated decision system or uses such automated decision system
48
for a purpose or manner not previously disclosed
through
an
automated
49
decision system use policy, it shall provide an addendum to the exis...
...stem in a way that affects the results or
outcomes
47
of
the automated decision system or uses such automated decision system
48
for a purpose or manner not previously disclosed
through
an
automated
49
decision system use policy, it shall provide an addendum to the existing
50
automated
decision
system
use
p...
... uses such automated decision system
48
for a purpose or manner not previously disclosed
through
an
automated
49
decision system use policy, it shall provide an addendum to the existing
50
automated
decision
system
use
policy describing such change or addi-
51
tional use and retain an archived copy of the pr...
...through
an
automated
49
decision system use policy, it shall provide an addendum to the existing
50
automated
decision
system
use
policy describing such change or addi-
51
tional use and retain an archived copy of the previous
automated
deci-
52
sion
system
so that decisions made under the old system use pol...
...se
policy describing such change or addi-
51
tional use and retain an archived copy of the previous
automated
deci-
52
sion
system
so that decisions made under the old system use policy may
53
be challenged under paragraph g of this subdivision.
54
(ii) Upon publication of, or addendum to, any proposed autom...
...ed under paragraph g of this subdivision.
54
(ii) Upon publication of, or addendum to, any proposed automated deci-
55
sion system policy, the public shall
have
forty-five
days
to
submit
S. 2277
23
1
comments
on
such
policy
to
the state and any governmental agency or
2
political subdivision or public benefit...
... subdivision or
4
public benefit corporation shall consider public
comments
and
provide
5
the final automated decision system use policy to the office of informa-
6
tion
technology
services,
the
committee
on open government, and the
7
state procurement council, and shall post such decision to
its
website
8
n...
...pportunity
to
provide
online,
16
written, and oral testimony, prior to:
17
(i)
Seeking
funds
for
an automated decision system that assigns or
18
contributes to the determination of rights, benefits, opportunities,
or
19
services for an individual, including but not limited to, applying for a
20
grant,
or
sol...
...ccepting state or federal funds or in-kind or
21
other donations;
22
(ii) Acquiring or borrowing an automated decision system that
assigns
23
or
contributes to the determination of rights, benefits, opportunities,
24
or services for an individual, whether or not such acquisition
is
made
25
through the exchan...
...
is
made
25
through the exchange of monies or other consideration;
26
(iii)
Using
a new or existing automated decision system that assigns
27
or contributes to the determination of rights, benefits,
opportunities,
28
or
services for an individual, or data derived therefrom, for a purpose
29
or in a manner no...
...ntering into an agreement with any
32
other person or entity to acquire, share, or otherwise use an
automated
33
decision
system
that
assigns
or
contributes to the determination of
34
rights, benefits, opportunities, or services for an individual or
auto-
35
mated decision system data.
36
d.
The
committee
on...
...ated decision system data.
36
d.
The
committee
on
open government shall conduct annual audits of
37
automated decision system use policies that shall:
38
(i)
Assess
whether
each
state
agency
that
purchases,
obtains,
39
procures, acquires, employs, uses, deploys, or accesses information from
40
an
automated
d...
...rchases,
obtains,
39
procures, acquires, employs, uses, deploys, or accesses information from
40
an
automated
decision
system complies with the terms of the automated
41
decision system use policy;
42
(ii) Describes any known or reasonably
suspected
violations
of
any
43
automated decision system use policies...
...eploys, or accesses information from
40
an
automated
decision
system complies with the terms of the automated
41
decision system use policy;
42
(ii) Describes any known or reasonably
suspected
violations
of
any
43
automated decision system use policies; and
44
(iii)
Publish
recommendations,
if
any, relating ...
...ecision system use policy;
42
(ii) Describes any known or reasonably
suspected
violations
of
any
43
automated decision system use policies; and
44
(iii)
Publish
recommendations,
if
any, relating to revision of the
45
relevant automated decision system use policies.
46
e. The state and any governmental
agency...
...use policies; and
44
(iii)
Publish
recommendations,
if
any, relating to revision of the
45
relevant automated decision system use policies.
46
e. The state and any governmental
agency,
political
subdivision
or
47
public
benefit
corporation
of
the
state shall not purchase, obtain,
48
procure, acquire, employ,...
...ll not purchase, obtain,
48
procure, acquire, employ, use, deploy, or
access
information
from
an
49
automated
decision
system
that assigns or contributes to the determi-
50
nation of rights, benefits, opportunities, or services for an individual
51
unless it first implements a process to provide a plain-lang...
...lain-language notifi-
52
cation to any individual whose personal information is processed by
the
53
automated decision system and whom the automated decision system's deci-
54
sion
affects of the fact that such system is in use, the system's name,
55
vendor, and version, what decision or decisions will be us...
...individual whose personal information is processed by
the
53
automated decision system and whom the automated decision system's deci-
54
sion
affects of the fact that such system is in use, the system's name,
55
vendor, and version, what decision or decisions will be used to make
or
56
support; and what poli...
...hall
not
purchase,
obtain,
3
procure,
acquire,
employ,
use,
deploy, or access information from an
4
automated decision system that assigns or contributes
to
the
determi-
5
nation of rights, benefits, opportunities, or services for an individual
6
unless it first implements a process to provide a plain-langua...
...plain-language notifi-
7
cation to any individual whose personal information is processed by such
8
automated
decision
system
and
whom
such automated decision system's
9
decision affects, of the involvement of an automated decision system
in
10
making the decision, the degree of human intervention in the sys...
...ndividual whose personal information is processed by such
8
automated
decision
system
and
whom
such automated decision system's
9
decision affects, of the involvement of an automated decision system
in
10
making the decision, the degree of human intervention in the system, how
11
the
automated
decision syste...
...ision
system
and
whom
such automated decision system's
9
decision affects, of the involvement of an automated decision system
in
10
making the decision, the degree of human intervention in the system, how
11
the
automated
decision system made the decision, the justification for
12
the decision, the variables...
...cision system
in
10
making the decision, the degree of human intervention in the system, how
11
the
automated
decision system made the decision, the justification for
12
the decision, the variables considered in rendering the decision, wheth-
13
er and how the decision deviated from the automated decision's
...
...variables considered in rendering the decision, wheth-
13
er and how the decision deviated from the automated decision's
system's
14
recommendation,
how the individual may contest the decision pursuant to
15
paragraph g of this subdivision, and the process
for
requesting
human
16
review of the decision pursu...
...vices, and
24
experts and representatives from the communities that will
be
directly
25
affected
by
automated decision systems, may promulgate rules and regu-
26
lations specifying the requirements for such notice.
27
g. The state and any governmental
agency,
political
subdivision
or
28
public
benefit
corpor...
...ll not purchase, obtain,
29
procure, acquire, employ, use, deploy, or
access
information
from
an
30
automated
decision
system
that assigns or contributes to the determi-
31
nation of rights, benefits, opportunities, or services for an individual
32
unless it first develops a process for human review.
33
(i) ...
...rnment and
35
experts and representatives from the communities that will
be
directly
36
affected
by
automated decision systems, may promulgate rules and regu-
37
lations specifying
the
requirements
for
human
review
of
decisions
38
rendered by automated decision systems.
39
(ii) An individual who was denied o...
...rules and regu-
37
lations specifying
the
requirements
for
human
review
of
decisions
38
rendered by automated decision systems.
39
(ii) An individual who was denied or assigned a right, benefit, oppor-
40
tunity
or service, may request human review of the decision rendered by
41
the automated decision system...
..., benefit, oppor-
40
tunity
or service, may request human review of the decision rendered by
41
the automated decision system.
42
(iii) Where the human review overturns a decision rendered by an auto-
43
mated decision system, the affected individual
experiences
harm
as
a
44
result
of
the
overturned
decision...
...will not provide a remedy, or where the human review does
not
47
overturn
a
decision
rendered
by
an
automated
decision system, the
48
affected individual, or their heirs, assigns, estate, or
successors
in
49
interest,
may
bring
in
any court of competent jurisdiction an action
50
alleging a violation of this ...
...purchases,
obtains,
8
procures, acquires, employs, uses, deploys, or accesses information from
9
an automated decision system that assigns or contributes to the determi-
10
nation of rights, benefits, opportunities, or services for an individual
11
shall
annually publish publicly on its website metrics on th...
... on its website metrics on the number of
12
requests for human review of a decision rendered by the automated
deci-
13
sion
system
it
received
and
the
outcome
of such human review. The
14
metrics may include de-identified information in the aggregate but shall
15
not include any personal information.
16
§ 8....
...llows:
18
21.
Notwithstanding
any
inconsistent
provision
of law, no payment
19
shall be made for an automated decision system, as
defined
in
section
20
one
hundred
sixty-five of this chapter, that assigns or contributes to
21
the determination of rights, benefits, opportunities, or services for an
22
individ...
...1
the determination of rights, benefits, opportunities, or services for an
22
individual unless the automated decision system uses
only
open
source
23
software
and the acquiring agency has complied with the automated deci-
24
sion system impact assessment and automated decision system
use
policy
25
requireme...
...ed decision system uses
only
open
source
23
software
and the acquiring agency has complied with the automated deci-
24
sion system impact assessment and automated decision system
use
policy
25
requirements
in section one hundred sixty-five of this chapter. For the
26
purposes of this subdivision, "open sourc...
...and the acquiring agency has complied with the automated deci-
24
sion system impact assessment and automated decision system
use
policy
25
requirements
in section one hundred sixty-five of this chapter. For the
26
purposes of this subdivision, "open source software" shall mean software
27
for which the huma...
...llows:
31
22. Notwithstanding any inconsistent
provision
of
law,
no
payment
32
shall
be
made
for an automated decision system, as defined in section
33
one hundred sixty-five of this chapter, that assigns or
contributes
to
34
the determination of rights, benefits, opportunities, or services for an
35
individ...
...apter.
38
23. Notwithstanding any inconsistent
provision
of
law,
no
payment
39
shall
be
made
for an automated decision system, as defined in section
40
one hundred
sixty-five
of
this
chapter,
if
the
vendor's
contract
41
contains
nondisclosure
or other provisions that prohibit or impair the
42
state and any g...
...apter.
45
24. Notwithstanding any inconsistent
provision
of
law,
no
payment
46
shall
be
made
for an automated decision system, as defined in section
47
one hundred sixty-five of this chapter, if the automated decision system
48
discriminates against an individual, or treats an individual less favor-
49
ably ...
... automated decision system, as defined in section
47
one hundred sixty-five of this chapter, if the automated decision system
48
discriminates against an individual, or treats an individual less favor-
49
ably than another, in whole or in part, on the
basis
of
one
or
more
50
factors
enumerated
in
section two...
...1
law.
52
25. Notwithstanding any inconsistent
provision
of
law,
no
payment
53
shall
be
made
for an automated decision system that makes final deci-
54
sions, judgments, or conclusions without human intervention that
impact
55
the
constitutional
or legal rights, duties, or privileges of any indi-
S. 2277
26
...
...r legal rights, duties, or privileges of any indi-
S. 2277
26
1
vidual in New York state or
for
any
automated
decision
system
that
2
deploys or triggers any weapon.
3
§ 10. Section 814 of the education law, as added by chapter 526 of the
4
laws
of
2006
and subdivision 3 as added by chapter 545 of the laws of...
...ing data" shall mean the datasets used to train
an
auto-
34
mated
decision
system,
machine
learning
algorithm, or classifier to
35
create and derive patterns from a prediction model.
36
b. The state and any governmental
agency,
political
subdivision
or
37
public
benefit
corporation
of
the
state shall not pur...
4840 results:
Description: Enacts the "digital fairness act"; requires any entity that conducts business in New York and maintains the personal information of 500 or more individuals to provide meaningful notice about their use of personal information; establishes unlawful discriminatory practices relating to targeted advertising.
Summary: The "Digital Fairness Act" mandates entities in New York with personal data on 500+ individuals to provide clear notice on data usage, address consent, and prohibit discriminatory ad practices.
Collection: Legislation
Status date: Jan. 19, 2023
Status: Introduced
Primary sponsor: Brian Kavanagh
(sole sponsor)
Last action: REFERRED TO INTERNET AND TECHNOLOGY (Jan. 3, 2024)
Category:
Societal Impact
Data Governance
System Integrity (see reasoning)
Sector:
Government Agencies and Public Services
Private Enterprises, Labor, and Employment (see reasoning)
Keywords (occurrence): automated (97) algorithm (1) show keywords in context
Societal Impact
Data Governance
System Integrity (see reasoning)
The text of the Digital Fairness Act addresses various issues related to the impact of AI and data algorithms on society, such as discrimination resultant from targeted advertising and automated decision systems. It acknowledges the potential harms caused by the misuse of personal information—issues that directly correlate with societal concerns about AI's influence, discrimination, and privacy. Additionally, the text mentions the need for oversight and transparency in automated decision-making, indicating the role AI plays in potential civil rights infringements, further intensifying its relevance in the social impact framework. Given this pointed focus on discrimination and fairness in technology use, the category of Social Impact is scored very high. Regarding Data Governance, the legislation explicitly targets the management of personal data and the algorithms affecting that data, such as obtaining informed consent for processing personal information, suggesting robust oversight on data practices. Hence, this category is rated very relevant. System Integrity discusses regulations ensuring security and accountability in AI deployment; since the text's purpose is partly to ensure transparency and fair use of algorithms, it aligns well here but is somewhat less central than the previous categories, resulting in a moderate score. Robustness, concerning AI performance benchmarks, is less applicable as the document emphasizes data privacy and protection rather than benchmarks for AI systems, thus earning it a low relevance score.
Sector:
Government Agencies and Public Services
Private Enterprises, Labor, and Employment (see reasoning)
The Digital Fairness Act focuses primarily on protection for individuals in digital contexts by regulating how their personal information is handled, particularly concerning targeted advertising and potential biases that could affect individuals unfairly in a number of ways including employment and financial services. It relates to Government Agencies and Public Services, as it pertains to how public entities might utilize personal information and automated decision systems that could impact civil rights, earning a moderate score. The legislative intent does not directly address the Judicial System, Healthcare, or Academic and Research Institutions, thus those sectors receive low scores. The implications for Private Enterprises, Labor, and Employment are significant given the focus on accountability of businesses regarding consumer data practices, earning this sector a moderate score as well. International Cooperation and Standards receive a slight score considering the broad implications of data regulation but are not a central theme in this text. Nonprofits and NGOs are similarly affected as organizations that might collect personal data, hence a slightly relevant score, while the hybrid category could apply but is also low due to lack of specificity. Overall, the primary relevance centers around individual data protection in business practices with tolerable ties to government regulations.
Keywords (occurrence): automated (97) algorithm (1) show keywords in context
Summary: The bill sets standards for laboratory testing procedures across various disciplines, ensuring accurate diagnostic results through routine controls and documentation, enhancing quality control in laboratory practices.
Collection: Code of Federal Regulations
Status date: Oct. 1, 2023
Status: Issued
Source: Office of the Federal Register
Category:
None
(see reasoning)
Sector: None (see reasoning)
Keywords (occurrence): automated (1) show keywords in context
The text primarily outlines standards and procedures related to laboratory controls and testing methods in various biological and chemical contexts. While it pertains to rigorous testing and control processes, it lacks explicit references to AI-related concepts. Thus, it's challenging to tie these standards to the categories associated with AI. This results in very low relevance for all categories. Specifically, it does not address societal impacts, data governance, system integrity, or robustness in a way that relates to AI developments or practices, as it focuses on laboratory standards rather than AI systems or applications.
Sector: None (see reasoning)
The text describes standard procedures in laboratory settings without any implications or direct connections to the aforementioned sectors. While it mentions procedures important for health diagnostics, there is no indication that these are related to AI applications within healthcare or any other specified sector. Hence, the scores remain very low across all sectors.
Keywords (occurrence): automated (1) show keywords in context
Summary: The bill outlines the congressional agenda for the week of November 7-10, 2023, detailing Senate and House committee meetings, nominations, and legislative activities planned during that timeframe.
Collection: Congressional Record
Status date: Nov. 6, 2023
Status: Issued
Source: Congress
Category:
Societal Impact
System Integrity (see reasoning)
Sector:
Government Agencies and Public Services
Healthcare
Academic and Research Institutions
Hybrid, Emerging, and Unclassified (see reasoning)
Keywords (occurrence): deepfake (1)
Societal Impact
System Integrity (see reasoning)
The text includes portions that explicitly reference AI in a healthcare context, particularly in relation to a Senate committee hearing examining the policy considerations for AI in health care. Additionally, it discusses the philosophy of AI in a hearing setting, indicating a broader exploration of AI implications. There are also mentions of the advances in deepfake technology relevant to system integrity concerns, but the text does not delve into AI governance, fairness, or bias issues. Therefore, the relevance to each category will vary, reflecting how directly the content discusses AI and its effects on society, governance, and systems.
Sector:
Government Agencies and Public Services
Healthcare
Academic and Research Institutions
Hybrid, Emerging, and Unclassified (see reasoning)
The text makes several references to the use of AI in different contexts. Specifically, it highlights AI's role in healthcare legislation, as well as discussions on deepfake technology within the context of cybersecurity and privacy. However, while these references are relevant, they may not fully encompass the breadth of implications for each sector. The healthcare sector receives a slightly higher score due to the explicit mention of AI policies related to healthcare, while political, legislative, and rights implications are touched upon, resulting in moderate relevance across sectors without strong emphasis on specific applications in others.
Keywords (occurrence): deepfake (1)
Summary: This bill concerns the nominations of Harry Coker, Jr. as National Cyber Director, Jeff Rezmovic as Chief Financial Officer of DHS, and Suzanne E. Summerlin as General Counsel for the FLRA, highlighting their roles in enhancing national security, financial oversight, and labor relations.
Collection: Congressional Hearings
Status date: Nov. 2, 2023
Status: Issued
Source: Senate
Category:
None
(see reasoning)
Sector: None (see reasoning)
Keywords (occurrence): artificial intelligence (7) show keywords in context
The document primarily discusses the nominations of three individuals for high-level positions within the U.S. government without focusing on AI specifically. There are references to cybersecurity, which could intersect with AI-related topics, but no direct mention of AI technologies, ethical frameworks, or societal impacts attributable to AI systems. Therefore, it does not strongly align with the 'Social Impact', 'Data Governance', 'System Integrity', or 'Robustness' categories that focus explicitly on AI applications and implications.
Sector: None (see reasoning)
While this document pertains to government positions and operations that may involve regulations or oversight that could implicate AI, it does not explicitly address the sectors defined. It discusses the nominations in a general context with a focus on individual candidates' qualifications and roles related to national security and finance, rather than their specific interactions with AI. Consequently, the legislative or oversight aspects that could relate to sectors like 'Government Agencies and Public Services' or 'International Cooperation and Standards' are not represented in a manner that meets the relevance criteria.
Keywords (occurrence): artificial intelligence (7) show keywords in context
Summary: Senate Amendment 1092 appropriates funds for military construction and related services for fiscal year 2024, ensuring resources for the Department of Defense and Veterans Affairs.
Collection: Congressional Record
Status date: Sept. 7, 2023
Status: Issued
Source: Congress
Category:
None
(see reasoning)
Sector: None (see reasoning)
Keywords (occurrence): automated (3)
The text primarily discusses appropriations for military construction and various defense-related activities. It does not explicitly mention AI technologies or their implications. Consequently, none of the four categories—Social Impact, Data Governance, System Integrity, or Robustness—directly apply, as there is no discussion regarding the societal or ethical implications of AI, data management specific to AI systems, integrity measures for AI, or performance benchmarks for AI technologies. Therefore, the categories are considered not relevant at all.
Sector: None (see reasoning)
The text does not pertain to the application of AI in sectors such as politics, government services, healthcare, or business. It strictly relates to the appropriations for military purposes, with no mention of AI's role or any regulatory framework surrounding AI applications. Therefore, all sectors—Politics and Elections, Government Agencies and Public Services, Judicial System, Healthcare, Private Enterprises, Labor and Employment, Academic Institutions, International Cooperation, Nonprofits, and the Hybrid Sector—are deemed not relevant to this text.
Keywords (occurrence): automated (3)
Summary: The "Orbital Sustainability Act of 2023" aims to establish programs for active remediation of orbital debris and develop uniform standards to enhance safety and sustainability in space operations.
Collection: Congressional Record
Status date: Oct. 31, 2023
Status: Issued
Source: Congress
Category:
None
(see reasoning)
Sector:
Government Agencies and Public Services
International Cooperation and Standards (see reasoning)
Keywords (occurrence): automated (1) show keywords in context
The text is primarily concerned with orbital debris management and does not directly address AI concepts or technologies. However, there are references to 'automated identification capability' and mentions of requiring collaboration with various entities in research, which implies a potential connection to technology development. This relationship is tenuous, and the overall focus remains on sustainable practices in space rather than on AI itself. Therefore, relevance to the categories is limited.
Sector:
Government Agencies and Public Services
International Cooperation and Standards (see reasoning)
While the text discusses aerospace and space operations, it does not explicitly touch upon the sectors defined. The mention of 'commercial space industry' and 'public services' in relation to debris remediation indicates a minimal connection. Overall, the text is more focused on regulatory aspects of space activity rather than a direct impact on the specified sectors.
Keywords (occurrence): automated (1) show keywords in context
Description: Amends the Freedom of Information Act. Provides that, for purposes of the Act, "public body" includes the judicial branch and components of the judicial branch of the State. Exempts records that pertain to the preparation of judicial opinions and orders. Excludes denials of requests of records from the judicial branch or components of the judicial branch from the jurisdiction of the Public Access Counselor.
Summary: The bill amends the Freedom of Information Act in Illinois to include the judicial branch as a public body, allows for certain judicial records to be exempt, and limits jurisdiction over record request denials.
Collection: Legislation
Status date: Dec. 20, 2023
Status: Introduced
Primary sponsor: Curtis Tarver
(sole sponsor)
Last action: Rule 19(a) / Re-referred to Rules Committee (April 5, 2024)
Category:
None
(see reasoning)
Sector: None (see reasoning)
Keywords (occurrence): automated (1) show keywords in context
This text primarily amends existing legislation, the Freedom of Information Act, with a focus on the inclusion of the judicial branch and its components as 'public bodies.' It does not contain specific references to AI or its applications. Although the legislation affects the transparency and access to information in government processes, it does not address AI's social impact, data governance, system integrity, or robustness specifically, as there are no mentions of these topics or relevant AI terms. Thus, the relevance of each category is determined to be low.
Sector: None (see reasoning)
The legislation does not directly address the use or regulation of AI across any sectors mentioned. It focuses solely on amendments related to transparency and records within the judicial branch and does not touch on sectors such as healthcare, politics, or business, where AI applications might be relevant. There are no explicit mentions of AI technologies or their implications in the listed sectors.
Keywords (occurrence): automated (1) show keywords in context
Summary: The bill addresses concerns regarding TikTok's role in promoting anti-Israel propaganda and censorship, suggesting it is a tool for the Chinese Communist Party to manipulate public opinion and threatening U.S. national security. It advocates for banning TikTok in the United States.
Collection: Congressional Record
Status date: Nov. 27, 2023
Status: Issued
Source: Congress
Category:
Societal Impact (see reasoning)
Sector:
Politics and Elections
Government Agencies and Public Services (see reasoning)
Keywords (occurrence): algorithm (1) show keywords in context
Societal Impact (see reasoning)
The text discusses the impact of TikTok and its algorithms on political propaganda and societal division, as well as issues such as censorship and surveillance which relate to the social impact of AI. It highlights how TikTok, through its algorithm, shapes public discourse, thus directly connecting it to societal repercussions. While there are elements that touch upon data tracking, the main focus is on the ramifications of AI systems on society. Therefore, Social Impact is the most relevant, as the legislation reflects on how such technologies can manipulate sentiment and information in society. Data Governance is slightly relevant due to the mention of tracking mechanisms; however, the emphasis is more on the sociopolitical effects rather than direct management of data per se. System Integrity and Robustness do not receive significant attention in regards to security protocols or system performance evaluations in the text, making them less relevant.
Sector:
Politics and Elections
Government Agencies and Public Services (see reasoning)
The text primarily revolves around the political implications of AI technology used by TikTok and its effects on sentiment regarding Israel and Hamas in the context of international relations and domestic discourse. It highlights potential governmental actions to address these AI-driven issues, thus correlating most closely with Politics and Elections. The reference to the government's investigation of TikTok's practices also aligns with Government Agencies and Public Services due to the exploration of federal oversight and actions. There’s a minor mention of the impact on public sentiments and social behavior attributed to these algorithms. However, sectors such as the Judicial System, Healthcare, Private Enterprises, Academic Institutions, International Cooperation, Nonprofits, and Hybrid do not find enough direct relevance in this context.
Keywords (occurrence): algorithm (1) show keywords in context
Description: A bill to improve forecasting and understanding of tornadoes and other hazardous weather, and for other purposes.
Summary: The TORNADO Act aims to enhance tornado and hazardous weather forecasting and communication through improved data management, research, and risk communication strategies, promoting public safety and preparedness.
Collection: Legislation
Status date: April 25, 2023
Status: Introduced
Primary sponsor: Roger Wicker
(11 total sponsors)
Last action: By Senator Cantwell from Committee on Commerce, Science, and Transportation filed written report. Report No. 118-138. (Dec. 13, 2023)
Category:
Societal Impact
Data Governance
System Integrity
Data Robustness (see reasoning)
Sector:
Government Agencies and Public Services
Academic and Research Institutions (see reasoning)
Keywords (occurrence): machine learning (2) show keywords in context
Societal Impact
Data Governance
System Integrity
Data Robustness (see reasoning)
The text discusses the role of artificial intelligence (AI) and machine learning in improving the communication of hazardous weather risks. It mentions using AI and machine learning technologies to validate research and data analysis methods. This indicates a significant intersection with AI, particularly with respect to enhancing forecasting and response capacities in understanding and communicating dangers related to tornadoes and hazardous weather events. Other categories such as System Integrity and Robustness may also be indirectly relevant, but the primary focus here is on the application of AI in risk communication and management, which falls within the scope of Social Impact as it addresses implications for public safety and information dissemination.
Sector:
Government Agencies and Public Services
Academic and Research Institutions (see reasoning)
The legislation primarily focuses on improving methods for hazard communication, which is directly applicable to Government Agencies and Public Services, particularly those involved in weather forecasting and public safety. Additionally, the mention of conducting research in collaboration with institutions of higher education highlights relevance to Academic and Research Institutions, as training and research in AI and its applications are essential for the effective execution of this act. There is a limited mention of private enterprise aspects; however, they could indirectly intersect with the implementation of AI technologies in public services.
Keywords (occurrence): machine learning (2) show keywords in context
Summary: The bill addresses the funding challenges of the Highway Trust Fund (HTF) and examines potential long-term solutions for sustainable financing of transportation infrastructure in the U.S.
Collection: Congressional Hearings
Status date: Oct. 18, 2023
Status: Issued
Source: House of Representatives
Category:
None
(see reasoning)
Sector: None (see reasoning)
Keywords (occurrence): artificial intelligence (1) show keywords in context
The text primarily discusses the Highway Trust Fund and its implications for transportation infrastructure funding. AI does not appear to be discussed within the context of this document, making it less relevant for the defined categories. Social Impact might be touched upon as it relates to public infrastructure use and societal implications of transit funding, but without direct references to AI or its societal influences, its relevance is limited. The other categories (Data Governance, System Integrity, and Robustness) do not align with the content of the text, as they focus on specific concerns directly related to AI integration, security, and performance benchmarks rather than transportation funding.
Sector: None (see reasoning)
The text is highly focused on transportation infrastructure and the funding mechanisms surrounding it. There are no references to the use of AI in politics, government agency functions, healthcare, or any other specified sectors. Although the topic of transportation could relate to government operations in a broad sense, the lack of specific discussions regarding AI's role in government or services results in minimal relevance to the given sectors.
Keywords (occurrence): artificial intelligence (1) show keywords in context
Summary: The bill establishes regulations for maritime communication priorities, prohibiting unauthorized transmissions, ensuring proper distress messaging, and maintaining operational standards for stations, including hours of service.
Collection: Code of Federal Regulations
Status date: Oct. 1, 2023
Status: Issued
Source: Office of the Federal Register
Category:
None
(see reasoning)
Sector: None (see reasoning)
Keywords (occurrence): automated (1) show keywords in context
This text primarily focuses on the regulations of communication systems, particularly in maritime contexts, and does not explicitly address any topics related to AI. The discussion surrounding automation in communication systems, while relevant to AI, does not establish a clear link to the broader implications of AI on society, data governance, system integrity, or robustness. Terms such as 'fully automated system' appear, but they do not delve into concerns typically associated with AI like bias, transparency, or data management. Thus, the text’s relevance to the defined categories is minimal.
Sector: None (see reasoning)
The text pertains largely to telecommunications and maritime safety protocols. While it mentions automated systems, which could implicitly relate to AI, it does not delve into applications or regulations specific to any sector like healthcare, public services, employment, or others defined in the categories. The focus remains strictly on communication protocols and regulations rather than the application of AI in any specific sector. Therefore, the relevance is low across the sectors.
Keywords (occurrence): automated (1) show keywords in context
Summary: The bill appropriates funding for military construction, veterans affairs, and related agencies for FY 2024, aiming to ensure military preparedness and support for veterans while navigating bipartisan legislative challenges.
Collection: Congressional Record
Status date: Nov. 1, 2023
Status: Issued
Source: Congress
Category:
Societal Impact
Data Governance
System Integrity
Data Robustness (see reasoning)
Sector:
Government Agencies and Public Services
Judicial system
Healthcare
Private Enterprises, Labor, and Employment
Academic and Research Institutions
Hybrid, Emerging, and Unclassified (see reasoning)
Keywords (occurrence): artificial intelligence (2) show keywords in context
Societal Impact
Data Governance
System Integrity
Data Robustness (see reasoning)
During the legislative session, there are passages specifically mentioning artificial intelligence (AI) and its implications for the workforce, financial and healthcare sectors, and potential biases, which address societal impacts, data governance, system integrity, and robustness of AI systems and their legislation. The text discusses bipartisan AI Insight Forums focused on the effects of AI on jobs and civil rights. This demonstrates the broader societal considerations AI presents, as well as calls for regulatory measures which are vital for safeguarding the integrity and performance of AI systems. Therefore, the following categories are assigned scores based on the text focus on the societal implications of AI, data governance issues presented by AI technologies, and the call for system integrity to ensure transparency and protection against biases in AI. Such topics fit naturally into the defined categories due to their overarching relevance in discussions about AI.
Sector:
Government Agencies and Public Services
Judicial system
Healthcare
Private Enterprises, Labor, and Employment
Academic and Research Institutions
Hybrid, Emerging, and Unclassified (see reasoning)
The text includes a discussion on AI forums where potential biases in various high-impact sectors such as finance, healthcare, and law enforcement are addressed, indicating a concern regarding the application of AI in these areas. The implications for employment also signal a significant intersection with labor markets among private enterprises. Given that AI systems influence multiple sectors including the judicial system and overall government functions, I have assigned scores reflecting their relevance in terms of both the ongoing deliberations at the Senate regarding regulation and the potential impacts of AI on these sectors. However, direct discussions regarding specific policy impacts on governmental applications of AI and nonprofit usage were not substantial in this text, leading to more moderate scores for those sectors.
Keywords (occurrence): artificial intelligence (2) show keywords in context
Summary: The bill pertains to various amendments being discussed in the House, specifically detailing the process of voting on these amendments, including recorded votes.
Collection: Congressional Record
Status date: July 13, 2023
Status: Issued
Source: Congress
Category:
None
(see reasoning)
Sector: None (see reasoning)
Keywords (occurrence): artificial intelligence (2) show keywords in context
The text provided does not pertain to AI-related content. It primarily consists of procedural announcements about the voting on various amendments in the Congressional Record. There are no mentions of terms specifically related to Artificial Intelligence, such as AI, algorithms, machine learning, or any of the other specified keywords. Consequently, there is no relevance to Social Impact, Data Governance, System Integrity, or Robustness regarding AI legislation.
Sector: None (see reasoning)
Similarly, the text lacks any mention or discussion related to politics, government operations, healthcare, or any other specific sectors that involve the application of AI. It strictly includes procedural elements of legislative votes, without any reference to how AI might be applied or regulated within these contexts. As such, all sectors are rated as non-relevant.
Keywords (occurrence): artificial intelligence (2) show keywords in context
Summary: The bill provides guidance on ADA regulations ensuring public accommodations and commercial facilities do not discriminate against individuals with disabilities, mandating compliance with accessibility standards.
Collection: Code of Federal Regulations
Status date: July 1, 2021
Status: Issued
Source: Office of the Federal Register
Keywords (occurrence):
automated (4)
show keywords in context
Summary: The bill outlines requirements for a state's proposal to receive delegation of oil and gas royalty management functions from ONRR, ensuring states can effectively manage federal leases while adhering to regulatory standards.
Collection: Code of Federal Regulations
Status date: July 1, 2023
Status: Issued
Source: Office of the Federal Register
Category:
None
(see reasoning)
Sector: None (see reasoning)
Keywords (occurrence): automated (3) show keywords in context
The text involves the delegation of royalty management functions related to oil and gas leases, specifying the responsibilities that a State must assume. While there are mentions of automated verification and automated systems, these pertain primarily to administrative efficiency rather than the broader impacts of AI systems on society, data governance, integrity, or robustness. Therefore, the relevance of the categories is limited. The text does not delve into how AI impacts individuals or society (Social Impact), does not discuss the governance of data used by AI systems (Data Governance), lacks content on system security and transparency (System Integrity), and does not present legislative benchmarks for AI performance or compliance (Robustness). This leads to low relevance scores across all categories.
Sector: None (see reasoning)
The text predominantly relates to oil and gas lease management by States rather than focusing on sector-specific uses of AI. While there is mention of automated verification, it does not relate to any sector, such as politics, healthcare, or judicial processes, specifically enough to warrant significant relevance. Overall, it fails to address any legislative issues in the outlined sectors of interest sufficiently, leading to low scores in all sectors as the focus remains purely on administrative processes and delegation proposals unrelated to AI impacts.
Keywords (occurrence): automated (3) show keywords in context
Summary: The bill S.J. Res. 32 seeks to disapprove a rule by the Bureau of Consumer Financial Protection regarding small business lending, aiming to exert congressional oversight in financial regulations.
Collection: Congressional Record
Status date: Oct. 18, 2023
Status: Issued
Source: Congress
Category:
Societal Impact
Data Governance
System Integrity (see reasoning)
Sector:
Government Agencies and Public Services
Healthcare
Private Enterprises, Labor, and Employment
Academic and Research Institutions
Hybrid, Emerging, and Unclassified (see reasoning)
Keywords (occurrence): artificial intelligence (1)
Societal Impact
Data Governance
System Integrity (see reasoning)
The text includes a section focused on an AI Insight Forum organized by the Senate, discussing bipartisan efforts for AI innovation and necessary guardrails to mitigate risks. This direct mention of AI innovation, risks, and bipartisan discussions makes it highly relevant to the Social Impact category, as it pertains to AI's transformational potential and its associated risks. The AI discussions also relate to Data Governance, as establishing guardrails involves ensuring responsible data practices and responsible AI development. The text mentions the need for oversight and appropriate measures to address the implications of AI systems, which connects to System Integrity. Finally, while it discusses performance and innovation in AI, it does not specifically cover auditing, transparency, or compliance checks which are typically aligned with the Robustness category, leading to its lower score here. Overall, the relevance of AI discussions to its social impact and governance makes a strong case for its categorization in these areas.
Sector:
Government Agencies and Public Services
Healthcare
Private Enterprises, Labor, and Employment
Academic and Research Institutions
Hybrid, Emerging, and Unclassified (see reasoning)
The text discusses an AI Insight Forum which focuses on the implications and risks associated with AI, potentially impacting various sectors. The bipartisan series of forums indicates a pursuit of regulation and oversight of AI, relevant to Government Agencies and the delivery of public services enhancing operational efficiency and ethical considerations. While the explicit references to political campaigns or electoral processes are absent, the discussions around AI could intersect with sectors like Healthcare or Private Enterprises in terms of application, as they explore innovative solutions and risks. However, without direct mentions of AI's applications in specific sectors, scores reflect a moderate connection to these broader sector concerns.
Keywords (occurrence): artificial intelligence (1)
Summary: The bill introduces various legislative proposals, including measures for rural post office restoration, school meal debt cancellation, and expansion of telehealth services, addressing diverse social and economic issues.
Collection: Congressional Record
Status date: Sept. 21, 2023
Status: Issued
Source: Congress
Category:
None
(see reasoning)
Sector: None (see reasoning)
Keywords (occurrence): automated (1) show keywords in context
The legislative text primarily lists various bills and their titles without delving into specifics regarding Artificial Intelligence (AI) or related themes. As a result, there are no explicit mentions or discussions around AI concepts, which are essential to evaluate the relevance of the categories. Given the absence of relevant content, all categories will receive low scores based on their definitions related to AI impact, governance, integrity, or robustness.
Sector: None (see reasoning)
Similar to the category ratings, the text does not mention any sectors regarding politics, government agencies, healthcare, or any other relevant areas. The absence of AI applications in these sectors means they are not pertinent to the current document. As such, all sectors will equally receive the lowest score indicating minimal to no relevance to the content presented.
Keywords (occurrence): automated (1) show keywords in context
Summary: The bill amends the Small Business Act to increase contract thresholds for socially disadvantaged small businesses and provides legal preparedness measures for servicemembers abroad while authorizing appropriations for military and intelligence activities in fiscal year 2024.
Collection: Congressional Record
Status date: July 26, 2023
Status: Issued
Source: Congress
Category:
None
(see reasoning)
Sector: None (see reasoning)
Keywords (occurrence): artificial intelligence (7) machine learning (1) automated (7) show keywords in context
The text largely focuses on amendments related to military contracting and provisions concerning small business concerns. There are no explicit references to AI or related technologies that would tie this text to the provided categories regarding AI impacts or governance. Because the focus is on legislative amendments without clear AI relevance, the scores reflect a low connection to all categories.
Sector: None (see reasoning)
The text does not mention AI applications in political contexts, public services, legal systems, healthcare, business practices, or research. It primarily deals with military-related legislative amendments with no contextual connection to the sectors provided, resulting in low relevance assignments for all sectors.
Keywords (occurrence): artificial intelligence (7) machine learning (1) automated (7) show keywords in context
Summary: The bill mandates Medicare Advantage (MA) organizations report and return identified overpayments based on erroneous payment data submitted to CMS, including an appeals process for disputes.
Collection: Code of Federal Regulations
Status date: Oct. 1, 2023
Status: Issued
Source: Office of the Federal Register
Category:
None
(see reasoning)
Sector: None (see reasoning)
Keywords (occurrence): algorithm (1) show keywords in context
The text primarily pertains to Medicare Advantage (MA) organizations and their financial reporting obligations regarding overpayments, which do not directly relate to AI. There are no explicit mentions of AI technologies or their implications in healthcare, data governance, systemic integrity, or robustness concerning AI. The references to terms like 'payment data' and 'data correction' do not explicitly invoke AI functionalities, algorithms, or automated decision-making processes. Hence, while it addresses important regulatory matters within the Medicare system, it lacks a direct connection to the specified AI-related categories and concepts.
Sector: None (see reasoning)
The text deals with regulations specific to Medicare Advantage organizations, focusing on payment processes and the return of overpayments. While healthcare is the central theme of this text, it does not engage with AI regulations, applications of AI, or how AI intersects with payment systems in healthcare. Therefore, it does not specifically address the applications of AI in healthcare settings, nor does it provide insights into AI's role within healthcare management or decision-making. Hence, this text receives a low relevance score across all sectors.
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Summary: The bill includes a variety of proposed legislation addressing issues such as drug disposal, education programs, disaster assistance, and health services, aiming to improve public welfare and allocate resources effectively.
Collection: Congressional Record
Status date: Sept. 21, 2023
Status: Issued
Source: Congress
Category:
Societal Impact
Data Governance
System Integrity (see reasoning)
Sector:
Politics and Elections
Government Agencies and Public Services (see reasoning)
Keywords (occurrence): automated (1) show keywords in context
Societal Impact
Data Governance
System Integrity (see reasoning)
The text includes a mention of legislation (H.R. 5628) that directs the Federal Trade Commission to conduct impact assessments of automated decision systems. This shows a clear connection to the Social Impact category as it addresses how AI and automated systems affect individuals and society, potentially impacting fairness, bias, consumer protection, and the accountability of these systems. The nature of the assessments suggests a focus on societal outcomes associated with AI use. Data Governance is also relevant since impact assessments would inherently concern the secure and accurate management of data used within those AI systems. System Integrity is implicated as well, as there would need to be transparency and oversight concerning how these automated systems function and are evaluated. Robustness is less relevant here since the text doesn't discuss performance benchmarks or regulatory compliance per se. Overall, the legislation exhibited critical connections to the Social Impact, Data Governance, and System Integrity categories, supporting higher scores in those areas.
Sector:
Politics and Elections
Government Agencies and Public Services (see reasoning)
The legislation included in the text, particularly H.R. 5628 regarding automated decision systems, could have implications across various sectors. Politics and Elections may be tied in cases where automated systems influence voter engagement or election processes. The relevance to Government Agencies and Public Services is significant since public agencies are increasingly utilizing AI in decision-making processes. The Judicial System might also experience effects, especially considering the use of AI in legal contexts. However, the text does not strongly reference specific proceedings related to these sectors. Other sectors like Healthcare and Private Enterprises were not specifically relevant here. Therefore, Government Agencies and Public Services received a relatively high score due to the direct implications of AI use in public programs and services.
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