...education.
Sec. 218. Competition for technology that detects and watermarks the use of
generative artificial intelligence.
Subtitle C—Plans, Reports, and Other Matters
Sec. 221. Department of Defense prize competitions for business systems mod-
ernization.
Sec. 222. Update to plans and strategies for artificial intel...
...ze competitions for business systems mod-
ernization.
Sec. 222. Update to plans and strategies for artificial intelligence. Sec. 223. Western regional range complex demonstration. Sec. 224. Report on feasibility and advisability of establishing a quantum com-
puting innovation center.
Sec. 225. Briefing on the impedimen...
...f technology transition program for strategic nuclear
deterrence. 4
†S 2226 ESSec. 230. Review of artificial intelligence investment.
TITLE III—OPERATION AND MAINTENANCE
Subtitle A—Authorization of Appropriations
Sec. 301. Authorization of appropriations.
Subtitle B—Energy and Environment
Sec. 311. Requirement for ...
...pro-
gram.
Subtitle I—Additional Matters Relating to Artificial Intelligence
Sec. 6096. Report on artificial intelligence regulation in financial services in-
dustry.
Sec. 6097. Artificial intelligence bug bounty programs. Sec. 6098. Vulnerability analysis study for artificial intelligence-enabled mili-
tary applicatio...
...Sec. 6097. Artificial intelligence bug bounty programs. Sec. 6098. Vulnerability analysis study for artificial intelligence-enabled mili-
tary applications.
Sec. 6099. Report on data sharing and coordination.
TITLE LXII—MATTERS RELATING TO FOREIGN NATIONS
Subtitle C—Matters Relating to Europe and the Russian Federation...
..., including applications, tools, 13
and models, for the detection and watermarking of 14
generative artificial intelligence (AI)— 15
(A) to facilitate the research, development, 16
testing, evaluation, and competition of secure 17
generative artificial intelligence detection and 18
watermark technologies that can support ...
...cilitate the research, development, 16
testing, evaluation, and competition of secure 17
generative artificial intelligence detection and 18
watermark technologies that can support each 19
Secretary of a military department and the 20
commanders of combatant commands to sup- 21
port warfighting requirements; and 22
(B) to...
...term ‘‘detection’’ means a technology 5
that can positively identify the presence of genera- 6
tive artificial intelligence in digital content. 7
(2) The term ‘‘watermarking’’ means embed- 8
ding a piece of data onto detected artificial intel- 9
ligence generated digital content, conveying attribu- 10
tion to the source g...
...Secretaries of the military departments shall each 12
consider the following: 13
(A) Integration of artificial intelligence or 14
machine learning capabilities. 15
(B) Data analytics or business intelligence, 16
or related visualization capability. 17
(C) Automated updating of business archi- 18
tectures, business systems...
...fines outcomes of near-term and long-term 5
strategies and plans relating to— 6
(A) the adoption of artificial intelligence; 7
(B) adoption and enforcement of policies 8
on the ethical use of artificial intelligence sys- 9
tems; and 10
(C) the identification and mitigation of 11
bias in artificial intelligence algorithms;...
...tion of artificial intelligence; 7
(B) adoption and enforcement of policies 8
on the ethical use of artificial intelligence sys- 9
tems; and 10
(C) the identification and mitigation of 11
bias in artificial intelligence algorithms; 12
(3) issue Department-wide guidance regard- 13
ing— 14
(A) methods to monitor accountabil...
... of artificial intelligence sys- 9
tems; and 10
(C) the identification and mitigation of 11
bias in artificial intelligence algorithms; 12
(3) issue Department-wide guidance regard- 13
ing— 14
(A) methods to monitor accountability for 15
artificial intelligence-related activity, including 16
artificial intelligence perfor...
...
(3) issue Department-wide guidance regard- 13
ing— 14
(A) methods to monitor accountability for 15
artificial intelligence-related activity, including 16
artificial intelligence performance indicators 17
and metrics; 18
(B) means to enforce and update ethics 19
policy and guidelines across all adopted artifi- 20
cial int...
...(A) methods to monitor accountability for 15
artificial intelligence-related activity, including 16
artificial intelligence performance indicators 17
and metrics; 18
(B) means to enforce and update ethics 19
policy and guidelines across all adopted artifi- 20
cial intelligence systems; and 21
(C) means to identify, monito...
...ifi- 20
cial intelligence systems; and 21
(C) means to identify, monitor, and miti- 22
gate bias in artificial intelligence algorithms; 23
(4) develop a strategic plan for the develop- 24
ment, use, and cybersecurity of generative artificial 2585
†S 2226 ESintelligence, including a policy for use of, and de- 1
fense agai...
...al workforce needs across the 4
future years defense plan to support the continued 5
development of artificial intelligence capabilities, in- 6
cluding recruitment and retention policies and pro- 7
grams; 8
(6) assess the availability and adequacy of the 9
basic artificial intelligence training and education 10
curricula ...
... and retention policies and pro- 7
grams; 8
(6) assess the availability and adequacy of the 9
basic artificial intelligence training and education 10
curricula available to the broader Department civil- 11
ian workforce and military personnel to promote ar- 12
tificial intelligence literacy to the nontechnical work- 13
fo...
...acy to the nontechnical work- 13
force and senior leadership with responsibilities adja- 14
cent to artificial intelligence technical development; 15
(7) develop and issue a timeline and guidance 16
for the Chief Digital and Artificial Intelligence Offi- 17
cer of the Department and the Secretaries of the 18
military depa...
...tment and the Secretaries of the 18
military departments to establish a common termi- 19
nology for artificial intelligence-related activities; 20
(8) develop and implement a plan to protect 21
and secure the integrity, availability, and privacy of 22
artificial intelligence systems and models, including 23
large language...
...evelop and implement a plan to protect 21
and secure the integrity, availability, and privacy of 22
artificial intelligence systems and models, including 23
large language models, data libraries, data reposi- 2486
†S 2226 EStories, and algorithms, in training, development, and 1
production environments; 2
(9) develop and...
...a plan to defend the people, orga- 8
nizations, and systems of the Department against 9
adversarial artificial intelligence, including identifica- 10
tion of organizations within the Department that 11
could provide red teams capabilities for operational 12
and developmental needs; 13
(11) develop and implement a policy f...
...idance on the instances for and 10
role of human intervention and oversight in the exer- 11
cise of artificial intelligence algorithms for use in the 12
generation of offensive or lethal courses of action for 13
tactical operations. 14
(b) D UE DATE FOR PROCEDURES , G UIDANCE , 15
PLANS , ASSESSMENT , AND TIMELINES .— 16
...
..., the Secretary of Defense 22
shall— 23
(1) review the current investment into applica- 24
tions of artificial intelligence to the platforms, proc- 25101
†S 2226 ESesses, and operations of the Department of Defense; 1
and 2
(2) categorize the types of artificial intelligence 3
investments by categories including but not ...
...
†S 2226 ESesses, and operations of the Department of Defense; 1
and 2
(2) categorize the types of artificial intelligence 3
investments by categories including but not limited 4
to the following: 5
(A) Automation. 6
(B) Machine learning. 7
(C) Autonomy. 8
(D) Robotics. 9
(E) Deep learning and neural network. 10
(F) Natu...
...s of the 20
Secretary align with stated strategies of the Depart- 21
ment of Defense with regard to artificial intelligence 22
and performance objectives established in the De- 23
partment of Defense Data, Analytics, and Artificial 24
Intelligence Adoption Strategy. 25102
†S 2226 ESTITLE III—OPERATION AND 1
MAINTENANCE 2...
...ces used in shipyards to make oper-2
ations more efficient and demonstrate a digital mainte-3
nance artificial intelligence platform that analyzes data on 4
the maintenance and health of shipboard assets of the 5
Navy at shipyards, which shall improve readiness of the 6
Armed Forces, predict and diagnose issues before the...
...nce delays on shipboard assets 10
of the Navy and assess the potential cost savings of adopt-11
ing artificial intelligence predictive maintenance tech-12
nology techniques that help determine the condition of in- 13
service equipment to estimate when maintenance should 14
be performed rather than waiting until failure or...
...luation of opportunities to dem- 20
onstrate commercial best practices at shipyards, in- 21
cluding artificial intelligence technologies to ensure 22
timely predictions for maintainers and planners at 23
shipyards by connecting datasets, executing models, 24
and providing outputs in near real-time; 25130
†S 2226 ES(3) an...
...ipyard assets of the 1
Navy with sufficient data available to enable near- 2
term demonstrations of artificial intelligence pre- 3
dictive maintenance and an estimate of resources 4
needed within the Navy to accelerate the demonstra- 5
tion of predictive artificial intelligence capabilities 6
with respect to those assets;...
...an estimate of resources 4
needed within the Navy to accelerate the demonstra- 5
tion of predictive artificial intelligence capabilities 6
with respect to those assets; and 7
(4) an identification of any policy or technical 8
challenges to implementing artificial intelligence or 9
machine learning for purposes of carrying...
...o those assets; and 7
(4) an identification of any policy or technical 8
challenges to implementing artificial intelligence or 9
machine learning for purposes of carrying out the 10
Shipyard Infrastructure Optimization Program. 11
(c) B RIEFING TO COMMITTEE .—Not later than 180 12
days after the date of the enactment of t...
...d government and commercial 5
standards. 6
(7) Ensuring that requirements processes for 7
software, artificial intelligence, data, and related ca- 8
pability areas enable a rapid, dynamic, and iterative 9
approach than traditional hardware systems. 10
(c) E LEMENTS .—The implementation of streamlined 11
requirements shall...
...rkforce of the Depart-15
ment of Defense, including technical and nontechnical 16
skills related to artificial intelligence and software coding. 17
(b) S TRATEGY REQUIRED .— 18
(1) I N GENERAL .—The Secretary of Defense, in 19
consultation with the Secretaries of each military de- 20
partment and the Chairman of the Joint...
...c talent management mechanisms aligned 10
with the work roles related to computer pro- 11
gramming, artificial intelligence and machine 12
learning competency, and software engineering 13
under the Department of Defense Cyber Work- 14
force Framework to allow for the military de- 15
partments to identify, assess, track, m...
...dentify, assess, track, manage, 16
and assign personnel with computer program- 17
ming, coding, and artificial intelligence skills 18
through established mechanisms, under the 19
policies of the military departments with respect 20
to career field management, including— 21
(i) development, modification, or re- 22
validati...
...hnical occu- 23
pational position that supports computer program- 24579
†S 2226 ESming, coding, or artificial intelligence operations and 1
development, including the following positions: 2
(A) Data scientists. 3
(B) Data engineers. 4
(C) Data analysts. 5
(D) Software developers. 6
(E) Machine learning engineers. 7
(F) P...
...ase opportunities for 24
engagement on NATO’s priority technology areas, 25819
†S 2226 ESincluding artificial intelligence, data, autonomy, 1
quantum-enabled technologies, biotechnology, 2
hypersonic technologies, space, novel materials and 3
manufacturing, and energy and propulsion; and 4
(4) through DIANA, NATO allies ...
...n projects with the Department of Defense, 1
with priority given to projects in the areas of— 2
(A) artificial intelligence; 3
(B) undersea domain awareness; 4
(C) air combat and support; 5
(D) munitions; and 6
(E) mobility. 7
(2) Eligibility to enter into reciprocal agree- 8
ments with the Department of Defense for the c...
...ls 10
intelligence capabilities; and 11
‘‘(ii) the need for automated and ma- 12
chine learning- or artificial intelligence-as- 13
sisted electronic warfare capabilities. 14
‘‘(C) Order of battle. 15
‘‘(D) Individual and unit training. 16
‘‘(E) Tactics, techniques, and procedures, 17
including— 18
‘‘(i) maneuver, distribu...
...r 7
the purposes described in subsection (a); and 8
(3) ensure that advanced analytics, including 9
artificial intelligence technology, are developed and 10
applied to the analysis of data assets in support of 11
the purposes described in subsection (a). 12
(d) S EMIANNUAL BRIEFINGS .—Not later than 120 13
days after the ...
... follows: 7
‘‘(i) To streamline the organizational 8
structure of the Department as it relates 9
to artificial intelligence development, im- 10
plementation, and oversight. 11
‘‘(ii) To improve coordination on arti- 12
ficial intelligence governance with the de- 13
fense industry sector. 14
‘‘(iii) To establish and overse...
...telligence tool, system, or algorithm ad- 5
heres to all Department established policy 6
related to artificial intelligence. 7
‘‘(vi) To provide periodic status up- 8
dates on the efforts of the Department to 9
develop and implement artificial intel- 10
ligence into existing Department programs 11
and processes. 12
‘‘(vii...
...s, or testing or valida- 15
tion infrastructure. 16
‘‘(viii) to implement and oversee a 17
data and artificial intelligence educational 18
program for the purpose of familiarizing 19
the Department at all levels on the applica- 20
tions of artificial intelligence in their oper- 21
ations. 22
‘‘(ix) To implement and overse...
...rogram for the purpose of familiarizing 19
the Department at all levels on the applica- 20
tions of artificial intelligence in their oper- 21
ations. 22
‘‘(ix) To implement and oversee a 23
data decree scorecard. 241170
†S 2226 ES‘‘(x) Such other duties as the Council 1
determines appropriate. 2
‘‘(F) P ERIODIC REPORTS ....
...03040A ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING AD-
VANCED TECHNOLOGIES.13,187 18,187
Tactical artificial intelligence and machine learning ............................. [5,000]
31 0603041A ALL DOMAIN CONVERGENCE ADVANCED TECHNOLOGY ..... 33,332 33,332
32 0603042A C3I ADVANCED TECHNOLOGY ..............................
...ices of the House of Representatives a report on its 251615
†S 2226 ESgap in knowledge relating to artificial intelligence, includ-1
ing an analysis on— 2
(1) which tasks are most frequently being as- 3
sisted or completed with artificial intelligence in the 4
institutions the agency regulates; 5
(2) current governance s...
...ud-1
ing an analysis on— 2
(1) which tasks are most frequently being as- 3
sisted or completed with artificial intelligence in the 4
institutions the agency regulates; 5
(2) current governance standards in place for 6
artificial intelligence use at the agency and current 7
standards in place for artificial intelligence ov...
...gence in the 4
institutions the agency regulates; 5
(2) current governance standards in place for 6
artificial intelligence use at the agency and current 7
standards in place for artificial intelligence oversight 8
by the agency; 9
(3) potentially additional regulatory authorities 10
required by the agency to continue to ...
...dards in place for 6
artificial intelligence use at the agency and current 7
standards in place for artificial intelligence oversight 8
by the agency; 9
(3) potentially additional regulatory authorities 10
required by the agency to continue to successfully 11
execute its mission; 12
(4) where artificial intelligence may l...
...horities 10
required by the agency to continue to successfully 11
execute its mission; 12
(4) where artificial intelligence may lead to 13
overlapping regulatory issues between agencies that 14
require clarification; 15
(5) how the agency is currently using artificial 16
intelligence, how the agency plans to use such arti...
... monetary or other re- 21
sources, if any, the agency requires to both adapt to 22
the changes that artificial intelligence will bring to 23
the regulatory landscape and to adequately adopt 241616
†S 2226 ESand oversee the use of artificial intelligence across 1
its operations described in paragraph (5). 2
(b) R ULE OF C...
...ing to 23
the regulatory landscape and to adequately adopt 241616
†S 2226 ESand oversee the use of artificial intelligence across 1
its operations described in paragraph (5). 2
(b) R ULE OF CONSTRUCTION .—Nothing in this sec- 3
tion may be construed to require an agency to include con-4
fidential supervisory information ...
...ence Officer of the 16
Department of Defense shall develop a bug bounty 17
program for foundational artificial intelligence mod- 18
els being integrated into Department of Defense 19
missions and operations. 20
(2) C OLLABORATION .—In developing the pro- 21
gram required by paragraph (1), the Chief may col- 22
laborate wi...
...4
veloped pursuant to paragraph (1) in order for 15
the Department to incorporate a foundational 16
artificial intelligence model. 17
(b) B RIEFING .—Not later than one year after the 18
date of the enactment of this Act, the Chief shall provide 19
the congressional defense committees a briefing on— 20
(1) the development...
...TION OF FOUNDATIONAL ARTIFICIAL IN- 1
TELLIGENCE MODEL .—In this section, the term 2
‘‘foundational artificial intelligence model’’ means an 3
adaptive generative model that is trained on a broad set 4
of unlabeled data sets that can be used for different tasks, 5
with minimal fine-tuning. 6
SEC. 6098. VULNERABILITY ANALY...
...lyzing the 13
vulnerabilities to the privacy, security, and accuracy of, 14
and capacity to assess, artificial intelligence-enabled mili-15
tary applications, as well as research and development 16
needs for such applications. 17
(b) E LEMENTS .—The study required by subsection 18
(a) shall cover the following: 19
(1) Res...
...ch and development needs and transi- 20
tion pathways to advance explainable and interpret- 21
able artificial intelligence-enabled military applica- 22
tions, including the capability to assess the under- 23
lying algorithms and data models of such applica- 24
tions. 251619
†S 2226 ES(2) Assessing the potential risks to...
...tial risks to the privacy, 1
security, and accuracy of underlying architectures 2
and algorithms of artificial intelligence-enabled mili- 3
tary applications, including the following: 4
(A) Individual foundational artificial intel- 5
ligence models, including the adequacy of exist- 6
ing testing, training, and auditing fo...
...ON OF FOUNDATIONAL ARTIFICIAL IN- 21
TELLIGENCE MODEL .—In this section, the term 22
‘‘foundational artificial intelligence model’’ means an 23
adaptive generative model that is trained on a broad set 241623
†S 2226 ESof unlabeled data sets that can be used for different tasks, 1
with minimal fine-tuning. 2
SEC. 6099. RE...
...are applica- 17
tions. 18
‘‘(5) A RTIFICIAL INTELLIGENCE DEFINED .—In 19
this subsection, the term ‘artificial intelligence’ has 20
the meaning given the term in section 238(g) of the 21
National Defense Authorization Act for Fiscal Year 22
2019 (Public Law 115–232; 10 U.S.C. 4001 note).’’. 231828
†S 2226 ESSEC. 6304. ST...
...ersonic and 3
counter hypersonic capabilities, quantum 4
technologies, undersea technologies, and 5
artificial intelligence. 6
(3) I NTERNATIONAL TRAFFIC IN ARMS REGULA - 7
TIONS .—The term ‘‘International Traffic in Arms 8
Regulations’’ means subchapter M of chapter I of 9
title 22, Code of Federal Regulations (or succes...
...up— 242297
†S 2226 ES‘‘(i) of the investments made by the 1
People’s Republic of China in— 2
‘‘(I) artificial intelligence; 3
‘‘(II) next-generation energy 4
technologies, especially small modular 5
reactors and advanced batteries; and 6
‘‘(III) biotechnology; and 7
‘‘(ii) that identifies— 8
‘‘(I) competitive practices o...
... policies for the acquisi- 15
tion, adoption, development, use, coordination, and 16
maintenance of artificial intelligence capabilities 17
that— 18
‘‘(A) establish a lexicon relating to the use 19
of machine learning and artificial intelligence 20
developed or acquired by elements of the intel- 21
ligence community; 22
‘...
...e capabilities 17
that— 18
‘‘(A) establish a lexicon relating to the use 19
of machine learning and artificial intelligence 20
developed or acquired by elements of the intel- 21
ligence community; 22
‘‘(B) establish guidelines for evaluating the 23
performance of models developed or acquired by 242301
†S 2226 ESelements ...
...ligence community, such as 1
by— 2
‘‘(i) specifying conditions for the con- 3
tinuous monitoring of artificial intelligence 4
capabilities for performance, including the 5
conditions for retraining or retiring models 6
based on performance; 7
‘‘(ii) documenting performance objec- 8
tives, including specifying how performa...
...partments shall each 12
consider the following: 13
(A) Integration of artificial intelligence or 14
machine learning capabilities. 15
(B) Data analytics or business intelligence, 16
or related visualization capability. 17
(C) Automated updating of business archi- 18
tectures, business systems integration, or docu- ...
...identification of any policy or technical 8
challenges to implementing artificial intelligence or 9
machine learning for purposes of carrying out the 10
Shipyard Infrastructure Optimization Program. 11
(c) B RIEFING TO COMMITTEE .—Not later than 180 12
days after the date of the enactment of this Act, the Sec-13
re...
...th a focus on emerging tech- 23
nologies such as quantum computing, artificial 24
intelligence, and machine learning, including 25817
†S 2226 ESthrough the work of the Defence Innovation Ac- 1
celerator for the North Atlantic initiative (com- 2
monly known as ‘‘DIANA’’); 3
(10) the European Deterrence Initiative r...
...re the ability to emulate 7
advanced nation-state threats, automation, artificial 8
intelligence or machine learning capabilities, and 9
data collection and correlation; 10
(2) to establish joint service standards and 11
metrics to ensure cyber red teams are adequately 12
trained, staffed, and equipped to emulate a...
...to which critical and emerging 9
technologies and concepts such as artificial intel- 10
ligence and machine learning enabled analysis and 11
process automation can reduce the amount of person 12
hours operators spend on maintenance and reporting 13
to maximize research and training time. 14
(3) Identification of tr...
...content forgery’’ means 4
the use of emerging technologies, including artificial 5
intelligence and machine learning techniques to fab- 6
ricate or manipulate audio, visual, or text content 7
with the intent to mislead. 8
(3) The term ‘‘digital content provenance’’ 9
means the verifiable chronology of the origin an...
...CE AND MACHINE LEARNING AD-
VANCED TECHNOLOGIES.13,187 18,187
Tactical artificial intelligence and machine learning ............................. [5,000]
31 0603041A ALL DOMAIN CONVERGENCE ADVANCED TECHNOLOGY ..... 33,332 33,332
32 0603042A C3I ADVANCED TECHNOLOGY ...................................................
...her gaps in analysis. 10
(4) While innovative technologies such as artifi- 11
cial intelligence and machine learning have the po- 12
tential to empower the Department to analyze and 13
act upon data at scale, systematized, sustainable 14
data management and information synthesis remain 15
a core competency necessar...
..., if appro- 16
priate, facilitate the responsible adoption of ar- 17
tificial intelligence (AI) and machine learning 18
applications to help inform decisions by policy- 19
makers and to support programs and manage- 20
ment operations of the Department of State; 21
and 22
‘‘(B) to act as the principal advisor to the...
...2
onstrated skill and competency in— 3
‘‘(A) the use and application of data ana- 4
lytics, AI, and machine learning; and 5
‘‘(B) transformational leadership and orga- 6
nizational change management, particularly 7
within large, complex organizations. 8
‘‘(4) P ARTNER WITH THE CHIEF INFORMATION 9
OFFICER ON SCALIN...
...rtificial intelligence capabilities 17
that— 18
‘‘(A) establish a lexicon relating to the use 19
of machine learning and artificial intelligence 20
developed or acquired by elements of the intel- 21
ligence community; 22
‘‘(B) establish guidelines for evaluating the 23
performance of models developed or acquired by...
...11
chives and Records Administration— 12
(1) research a technology-based solution— 13
(A) utilizing machine learning and artifi- 14
cial intelligence to support efficient and effec- 15
tive systems for classification and declassifica- 16
tion; and 17
(B) to be implemented on an interoperable 18
and federated basis ...
...: 5
(A) Automation. 6
(B) Machine learning. 7
(C) Autonomy. 8
(D) Robotics. 9
(E) Deep learning and neural network. 10
(F) Natural language processing. 11
(b) R EPORT TO CONGRESS .—Not later than 120 days 12
after the completion of the review and categorization re-13
quired by subsection (a), the Secretary of Def...
....—The authority under this section does not 21
include major defense acquisition programs, major 22
automated information system programs, or acquisi- 23
tions of foundational infrastructure or software ar- 24319
†S 2226 ESchitectures the duration of which is expected to last 1
more than five years. 2
SEC. ...
...productivity 16
software suite of the congressional defense commit- 17
tees; or 18
(2) enabling the automated transmission of 19
scheduling data through another software solution. 20
SEC. 925. OPERATIONALIZING AUDIT READINESS. 21
(a) M ETRICS REQUIRED .— 22
(1) I N GENERAL .—The Secretary of Defense, in 23
c...
...ons to exist- 3
ing data sets; 4
‘‘(B) current means and methods for the 5
collection of data in an automated manner, in- 6
cluding the identification of areas in which gaps 7
exist that may require new means for data col- 8
lection or visualization of such data; and 9
‘‘(C) the development of an analysis an...
...ork-centric electronic warfare and signals 10
intelligence capabilities; and 11
‘‘(ii) the need for automated and ma- 12
chine learning- or artificial intelligence-as- 13
sisted electronic warfare capabilities. 14
‘‘(C) Order of battle. 15
‘‘(D) Individual and unit training. 16
‘‘(E) Tactics, techniques, and...
...funding to ensure that 3
any Department investment in an artificial 4
intelligence tool, system, or algorithm ad- 5
heres to all Department established policy 6
related to artificial intelligence. 7
‘‘(vi) To provide periodic status up- 8
dates on the efforts of the Department to 9
develop and implement arti...
4161 results:
Description: An original bill to authorize appropriations for fiscal year 2024 for military activities of the Department of Defense, for military construction, and for defense activities of the Department of Energy, to prescribe military personnel strengths for such fiscal year, and for other purposes.
Collection: Legislation
Status date: July 11, 2023
Status: Introduced
Primary sponsor: Jack Reed
(sole sponsor)
Last action: Senate ordered measure printed as passed. (July 27, 2023)
Category:
Societal Impact
Data Governance
System Integrity
Data Robustness (see reasoning)
Sector:
Government Agencies and Public Services
Private Enterprises, Labor, and Employment
Academic and Research Institutions (see reasoning)
Keywords (occurrence): artificial intelligence (108) machine learning (17) neural network (1) deep learning (1) automated (20) algorithm (1) show keywords in context
Societal Impact
Data Governance
System Integrity
Data Robustness (see reasoning)
The National Defense Authorization Act for Fiscal Year 2024 includes several mentions of artificial intelligence technologies and their applications within the military context. The text highlights AI-related activities such as the development of AI strategies, automation in shipyard operations, and competitive technology developments that include aspects of generative artificial intelligence. Due to the emphasis on the implications of AI strategies in defense operations and technological advancements, it is particularly relevant to the categories of Social Impact, Data Governance, System Integrity, and Robustness, even though the extent and implication in some areas may vary. Overall, the connections to AI in this legislation reflect significant considerations about the impact, governance, integrity, and robustness of AI technologies in military settings.
Sector:
Government Agencies and Public Services
Private Enterprises, Labor, and Employment
Academic and Research Institutions (see reasoning)
This legislation clearly relates to multiple sectors as outlined. The most relevant sectors include Government Agencies and Public Services, as it directly addresses the military and defense capabilities of government agencies. Additionally, aspects pertaining to Private Enterprises, Labor, and Employment are relevant due to the focus on technology and workforce implications around military service and contracting. The references to the integration of AI in public service operations suggest wider implications for governmental applications. Therefore, the scores reflect a robust association with sectors impacted by AI, especially within government operations and military contexts.
Keywords (occurrence): artificial intelligence (108) machine learning (17) neural network (1) deep learning (1) automated (20) algorithm (1) show keywords in context
Collection: Congressional Record
Status date: Aug. 23, 2024
Status: Issued
Source: Congress
Category:
Societal Impact (see reasoning)
Sector:
Academic and Research Institutions (see reasoning)
Keywords (occurrence): artificial intelligence (1) show keywords in context
Societal Impact (see reasoning)
The text specifically mentions 'artificial intelligence' in the context of supporting education and professional development related to it. This reference ties directly to key legislative considerations regarding how AI impacts society, particularly in terms of education and workforce development. Therefore, the relevance to the Social Impact category is clear. While the text briefly touches on the topic, it primarily emphasizes the educational facet rather than addressing deeper societal impacts or systemic integrations. This narrow focus supports a moderately relevant score. In terms of Data Governance, System Integrity, and Robustness, there are no explicit concerns or mentions related to data management, system security, or performance benchmarks specified in the text, resulting in a score of 1 for these categories.
Sector:
Academic and Research Institutions (see reasoning)
The text indicates a focus on supporting education within the National Science Foundation related to artificial intelligence. This primarily relates to the Academic and Research Institutions sector, highlighting development in education associated with AI. While there are implications for workforce training, the tie to direct employment impacts or regulations of AI within specific sectors like healthcare or government is absent. Thus, the score for the Academic and Research Institutions category is 4 due to this connection. Other sectors do not see direct relevance from the text, particularly as there are no discussions surrounding AI in politics, healthcare, or other specified environments, leading to scores of 1 for those.
Keywords (occurrence): artificial intelligence (1) show keywords in context
Description: A bill to require the imposition of sanctions with respect to the People's Republic of China if the People's Liberation Army initiates a military invasion of Taiwan.
Collection: Legislation
Status date: July 25, 2024
Status: Introduced
Primary sponsor: Dan Sullivan
(2 total sponsors)
Last action: Read twice and referred to the Committee on Banking, Housing, and Urban Affairs. (July 25, 2024)
Category:
None
(see reasoning)
Sector: None (see reasoning)
Keywords (occurrence): artificial intelligence (1) machine learning (1) show keywords in context
The text of the STAND with Taiwan Act of 2024 primarily deals with sanctions in relation to military actions rather than directly addressing concerns related to AI technologies. There are no explicit references to AI, algorithms, or automated decision-making processes. Consequently, all categories are assessed as not relevant to the contents of this bill.
Sector: None (see reasoning)
The text does not mention the use of AI in the context of politics, public services, healthcare, or any other sectors described. It focuses on geopolitical relations and military actions concerning Taiwan and China, thus no indication of AI involvement is noted.
Keywords (occurrence): artificial intelligence (1) machine learning (1) show keywords in context
Description: An act to add Section 111612 to the Health and Safety Code, relating to public health.
Collection: Legislation
Status date: May 13, 2024
Status: Engrossed
Primary sponsor: Akilah Weber
(sole sponsor)
Last action: Ordered to third reading. (Aug. 8, 2024)
Category:
Societal Impact
Data Governance
System Integrity (see reasoning)
Sector:
Healthcare (see reasoning)
Keywords (occurrence): automated (1)
Societal Impact
Data Governance
System Integrity (see reasoning)
The text clearly addresses disclosures related to medical devices, particularly those that involve the collection and analysis of medical information. The references to automated decision systems align it with AI's role in healthcare decision-making. The requirement for manufacturers to disclose known limitations based on patient characteristics connects it to issues of fairness and bias, which are significant concerns of social impact. It doesn't explicitly delve into data governance or system integrity beyond the scope of medical device regulation. While robustness isn't a focus here, concerns about device performance can be loosely tied to it in the context of healthcare. Overall, its principal relevance lies in how AI, through automated decision systems, can affect public health and individual patient outcomes.
Sector:
Healthcare (see reasoning)
The text specifically relates to healthcare by addressing the regulation of medical devices and their disclosures, particularly in context to their effectiveness and the population they serve. The concerns raised about automated decision systems directly tie to how these technologies are used within healthcare. Since the bill is primarily focused on improving health outcomes and understanding device limitations, it firmly belongs in the healthcare sector. Other sectors like politics and elections, public services, and labor do not pertain to the content of the text, making them less relevant.
Keywords (occurrence): automated (1)
Description: To require digital social companies to adopt terms of service that meet certain minimum requirements.
Collection: Legislation
Status date: July 24, 2024
Status: Introduced
Primary sponsor: Katie Porter
(sole sponsor)
Last action: Referred to the House Committee on Energy and Commerce. (July 24, 2024)
Category:
Societal Impact
Data Governance
System Integrity (see reasoning)
Sector:
Politics and Elections
Government Agencies and Public Services (see reasoning)
Keywords (occurrence): artificial intelligence (2) automated (1) show keywords in context
Societal Impact
Data Governance
System Integrity (see reasoning)
The Digital Social Platform Transparency Act addresses AI primarily through content moderation mechanisms that involve automated systems. This includes the usage of 'artificial intelligence software' for flagging content and determining actions on flagged items. The consideration of these automated systems points to a significant engagement with issues of accountability, transparency, and bias, impacting societal implications. As such, while primarily focused on transparency and accountability, the act’s provisions around AI usage in content moderation make it relevant to multiple categories, particularly Social Impact and System Integrity, as they both pertain to the usage of AI in public spheres and the implications this has for society. Data Governance is relevant due to the need for accurate reporting on flagged content, which indirectly involves data management governed by AI systems. Robustness is less relevant here since the focus isn’t primarily on performance benchmarks or compliance standards, but rather on operational transparency and accountability of digital social platforms.
Sector:
Politics and Elections
Government Agencies and Public Services (see reasoning)
The act directly pertains to sectors such as Politics and Elections due to its implications for content moderation and misinformation, particularly related to political discourse. It also engages the Government Agencies and Public Services sector by requiring reporting to the Attorney General regarding practices and misconduct, ensuring accountability for digital social platforms. Although it does not primarily address the Judicial System or Healthcare, its potential effects on public trust and interaction with digital media in influence and transparency connect it to broader implications in these sectors. Thus, while primarily focused on digital social platforms, its effects on political discourse and public services establish its relevance.
Keywords (occurrence): artificial intelligence (2) automated (1) show keywords in context
Description: Revised for 1st Substitute: Making 2023-2025 fiscal biennium operating appropriations and 2021-2023 fiscal biennium second supplemental operating appropriations.Original: Making 2023-2025 fiscal biennium operating appropriations.
Collection: Legislation
Status date: May 16, 2023
Status: Passed
Primary sponsor: Christine Rolfes
(3 total sponsors)
Last action: Effective date 5/16/2023. (May 16, 2023)
Category:
None
(see reasoning)
Sector: None (see reasoning)
Keywords (occurrence): artificial intelligence (2) automated (13) algorithm (1) show keywords in context
The text primarily pertains to fiscal appropriations and budgetary measures without any mention or explicit relation to AI-related terms or legislation affecting AI technologies. Given that the text focuses on budget allocations and legislative procedures, its content does not address social impacts, data governance issues, system integrity, or robustness aspects that would be relevant for AI-related discussions. Hence, it is deemed not relevant for all the categories.
Sector: None (see reasoning)
The text does not contain any references or relevance to AI applications within the identified sectors. There are no indications of AI's regulation in politics and elections, public services, judicial matters, healthcare, private enterprises, academic settings, international cooperation, or nonprofit activities. It discusses budgetary provisions but nothing related to AI use or regulation in these sectors.
Keywords (occurrence): artificial intelligence (2) automated (13) algorithm (1) show keywords in context
Description: Revised for 1st Substitute: Making 2023-2025 fiscal biennium operating appropriations and 2021-2023 fiscal biennium second supplemental operating appropriations.Original: Making 2023-2025 fiscal biennium operating appropriations.
Collection: Legislation
Status date: May 16, 2023
Status: Passed
Primary sponsor: Christine Rolfes
(3 total sponsors)
Last action: Effective date 5/16/2023. (May 16, 2023)
Category:
None
(see reasoning)
Sector: None (see reasoning)
Keywords (occurrence): artificial intelligence (2) automated (13) algorithm (1) show keywords in context
The text primarily pertains to fiscal appropriations and budgetary measures without any mention or explicit relation to AI-related terms or legislation affecting AI technologies. Given that the text focuses on budget allocations and legislative procedures, its content does not address social impacts, data governance issues, system integrity, or robustness aspects that would be relevant for AI-related discussions. Hence, it is deemed not relevant for all the categories.
Sector: None (see reasoning)
The text does not contain any references or relevance to AI applications within the identified sectors. There are no indications of AI's regulation in politics and elections, public services, judicial matters, healthcare, private enterprises, academic settings, international cooperation, or nonprofit activities. It discusses budgetary provisions but nothing related to AI use or regulation in these sectors.
Keywords (occurrence): artificial intelligence (2) automated (13) algorithm (1) show keywords in context
Collection: Congressional Record
Status date: Aug. 23, 2024
Status: Issued
Source: Congress
Category:
Societal Impact (see reasoning)
Sector:
Academic and Research Institutions (see reasoning)
Keywords (occurrence): artificial intelligence (1) show keywords in context
Societal Impact (see reasoning)
The text contains specific mentions of legislation related to artificial intelligence (AI), particularly concerning education and professional development relating to AI and fostering a diverse research community for AI and AI-powered innovation. This is directly relevant to the Social Impact category, as it addresses the societal impact and educational equity related to AI technology. Data Governance is not relevant here since there is no discussion about data management or integrity associated with these AI programs. System Integrity is not directly addressed either as there are no stipulations concerning the security or oversight of AI systems mentioned. Robustness also does not apply as there are no benchmarks or performance assessments discussed. Overall, the focus on education and professional development most directly aligns with Social Impact and suggests a commitment to ensure that AI contributes positively to society.
Sector:
Academic and Research Institutions (see reasoning)
The text includes bills that propose initiatives relating to AI in educational settings and their implications for underrepresented communities in STEM fields. Thus, it speaks to the role of AI in Academic and Research Institutions. However, there is no mention of AI in contexts such as politics, law, healthcare, or other sectors, removing the relevance of those categories. The entry on AI capacity building may touch lightly on the potential for AI to relate to employment and labor indirectly but is not directly related to this category. Therefore, it strongly pertains to Academic and Research Institutions while being neutral or not relevant for other sectors.
Keywords (occurrence): artificial intelligence (1) show keywords in context
Description:
Collection:
Status date:
Status:
Primary sponsor:
( total sponsors)
Source:
Last action: ()
Category:
None
(see reasoning)
Sector: None (see reasoning)
Keywords (occurrence): artificial intelligence () machine learning () neural network () deep learning () automated () deepfake () synthetic media () large language model () foundation model () chatbot () recommendation system () algorithm () autonomous vehicle ()
Sector: None (see reasoning)
Keywords (occurrence): artificial intelligence () machine learning () neural network () deep learning () automated () deepfake () synthetic media () large language model () foundation model () chatbot () recommendation system () algorithm () autonomous vehicle ()
Description: A bill to prohibit the distribution of false AI-generated election media and to amend the National Voter Registration Act of 1993 to prohibit the removal of names from voting rolls using unverified voter challenge databases.
Collection: Legislation
Status date: July 11, 2024
Status: Introduced
Primary sponsor: Jeff Merkley
(5 total sponsors)
Last action: Read twice and referred to the Committee on Rules and Administration. (July 11, 2024)
Category:
Societal Impact
Data Governance (see reasoning)
Sector:
Politics and Elections
Government Agencies and Public Services (see reasoning)
Keywords (occurrence): artificial intelligence (1) machine learning (1) show keywords in context
Societal Impact
Data Governance (see reasoning)
The text explicitly pertains to the regulation of AI in the context of elections, particularly focusing on the prohibition of the distribution of false AI-generated media. This is critical to the social fabric and integrity of electoral processes, as misinformation can have serious implications for democratic functions. Thus, it relates strongly to Social Impact. The governance and management of data related to voter eligibility and registration also connect to Data Governance since the bill outlines procedures for ensuring the integrity of voter information. Although System Integrity and Robustness concepts like security measures and performance benchmarks are relevant in a broader AI context, they are not explicitly covered in this document. Therefore, Social Impact and Data Governance are the most relevant categories, meriting higher scores while System Integrity and Robustness are less relevant.
Sector:
Politics and Elections
Government Agencies and Public Services (see reasoning)
This legislation directly addresses the misuse of AI in the political realm, specifically how it can affect election integrity through the spread of false media. Thus, Politics and Elections is highly relevant, scoring a 5. Additionally, as it may impact how government agencies manage voter databases and processes, Government Agencies and Public Services would also be moderately relevant with a score of 3. The other sectors, such as Judicial System, Healthcare, Private Enterprises, Academic and Research Institutions, International Cooperation and Standards, Nonprofits and NGOs, and Hybrid, Emerging, and Unclassified, do not have direct relevance in this context, leading to low scores for those areas.
Keywords (occurrence): artificial intelligence (1) machine learning (1) show keywords in context
Collection: Code of Federal Regulations
Status date: Jan. 1, 2023
Status: Issued
Source: Office of the Federal Register
Category:
Societal Impact
System Integrity
Data Robustness (see reasoning)
Sector:
Government Agencies and Public Services
Private Enterprises, Labor, and Employment
International Cooperation and Standards (see reasoning)
Keywords (occurrence): artificial intelligence (1)
Societal Impact
System Integrity
Data Robustness (see reasoning)
The text explicitly addresses ICTS (Information and Communication Technology Supply Chain) transactions that involve AI and machine learning technologies. This section 7.3 of the document mentions that ICTS integral to Artificial Intelligence and Machine Learning is a scope covered under the legislative framework. The considerations around critical infrastructures and sensitive data are also promoted, indicating potential social impacts and issues of robustness for AI implementations. While other categories such as data governance and system integrity may also be relevant, they are not explicitly referenced, which could affect their scoring. This leads to a notable relevance for the Social Impact and Robustness categories.
Sector:
Government Agencies and Public Services
Private Enterprises, Labor, and Employment
International Cooperation and Standards (see reasoning)
The scope outlined in this regulation covers various sectors, including critical infrastructure and integrates AI technologies that are highly relevant across multiple domains. However, it does not provide specific applications or mention regulations directly tied to the political sphere, healthcare, or judicial considerations. The mention of AI and machine learning hints at impacts on a broad spectrum of sectors, but specific connections to agriculture, education, or non-profits aren't sufficiently present, making it less applicable to sectors outside a generalized governmental framework, especially immediate applications under private enterprises or public services. Thus, the scoring reflects relevant insights primarily in government-related contexts.
Keywords (occurrence): artificial intelligence (1)
Collection: Code of Federal Regulations
Status date: Jan. 1, 2021
Status: Issued
Source: Office of the Federal Register
Keywords (occurrence):
artificial intelligence (1)
Collection: Code of Federal Regulations
Status date: April 1, 2021
Status: Issued
Source: Office of the Federal Register
Keywords (occurrence):
algorithm (1)
Collection: Code of Federal Regulations
Status date: April 1, 2021
Status: Issued
Source: Office of the Federal Register
Keywords (occurrence):
automated (1)
algorithm (1)
Collection: Code of Federal Regulations
Status date: Jan. 1, 2023
Status: Issued
Source: Office of the Federal Register
Category:
None
(see reasoning)
Sector: None (see reasoning)
Keywords (occurrence): automated (1)
The text provided is a detailed description of requirements and regulations related to the food assistance program but does not mention Artificial Intelligence (AI) or related terms such as algorithms, machine learning, or automated decision-making. As such, the text seems to focus primarily on administrative and operational aspects of the food and nutrition service without addressing any AI implications. Therefore, its relevance to the specified categories related to AI is minimal.
Sector: None (see reasoning)
The text outlines various provisions and operational guidelines under the USDA's Food and Nutrition Service related to SNAP (Supplemental Nutrition Assistance Program). While it addresses certain administrative and procedural requirements, there is no content that directly relates to the use of AI in political campaigns, public services, judicial systems, healthcare, or any other sector definitions as categorized. Thus, the overall relevance of the text to the specific sectors listed is very low.
Keywords (occurrence): automated (1)
Collection: Code of Federal Regulations
Status date: Jan. 1, 2021
Status: Issued
Source: Office of the Federal Register
Keywords (occurrence):
neural network (3)
Collection: Code of Federal Regulations
Status date: Jan. 1, 2023
Status: Issued
Source: Office of the Federal Register
Category:
None
(see reasoning)
Sector: None (see reasoning)
Keywords (occurrence): automated (2)
The text primarily details regulations regarding the export and re-export of aircraft, vessels, and spacecraft. It addresses various rules related to the operational control and licensure requirements for these modes of transportation in relation to different countries, specifically concerning national security and compliance with export laws. The content does not include any explicit mentions or relevant discussions pertaining to AI technologies, their societal impacts, data governance, system integrity, or robustness. Thus, it is determined that there is no relevance to the described categories regarding social impact, data governance, system integrity, or robustness.
Sector: None (see reasoning)
The text does not specify any regulations or discussions related to the application of AI within the context of politics and elections, government agencies and public services, judicial systems, healthcare, private enterprises, academic institutions, international cooperation, nonprofits, or any emerging sectors. The focus is entirely on the regulatory aspects of aviation and shipping as they relate to exports without any connection to AI or its specific applications across these sectors. Therefore, the relevance scored across all sectors remains at the lowest level.
Keywords (occurrence): automated (2)
Collection: Code of Federal Regulations
Status date: Jan. 1, 2023
Status: Issued
Source: Office of the Federal Register
Category:
None
(see reasoning)
Sector: None (see reasoning)
Keywords (occurrence): automated (1)
The text provided pertains strictly to regulations surrounding the importation of agricultural products, specifically onions and tomatoes. There is no mention of Artificial Intelligence, algorithms, data governance, transparency in systems, or any AI-related frameworks that might relate to the defined categories. Hence, all categories are deemed not relevant to the content of the text.
Sector: None (see reasoning)
Similarly, the sector categories address the application of AI across various domains such as politics, healthcare, and international cooperation. The text is focused solely on import regulations for agricultural products, which does not engage with any aspect of AI or related sectors. Consequently, all sector categories score as not relevant.
Keywords (occurrence): automated (1)
Collection: Code of Federal Regulations
Status date: Jan. 1, 2023
Status: Issued
Source: Office of the Federal Register
Category:
None
(see reasoning)
Sector: None (see reasoning)
Keywords (occurrence): automated (1)
The text primarily outlines the requirements and procedures related to federal payments and internal controls over federally funded activities. It does not explicitly reference AI or its impact on society, data governance, system integrity, or robustness. The focus on internal controls, financial accountability, and procedures indicates no relevant discussions regarding AI-specific legislation, nor its social implications, governance needs, integrity concerns, or robustness in performance. Therefore, all categories scored low relevance.
Sector: None (see reasoning)
This text relates to federal payment processes and does not engage with AI applications in politics, public services, the judicial system, healthcare, or any other sectors mentioned. AI is not a subject of direct discussion, nor is there any implication regarding regulations or oversight that would connect it to any specific sector. The absence of AI-centric content across sectors results in a score of 1 for all sectors.
Keywords (occurrence): automated (1)
Collection: Code of Federal Regulations
Status date: Jan. 1, 2023
Status: Issued
Source: Office of the Federal Register
Category:
None
(see reasoning)
Sector: None (see reasoning)
Keywords (occurrence): automated (2)
The text primarily addresses the exclusion process for steel articles under Section 232, emphasizing factors for determining exclusion validity periods and the review process by the U.S. Department of Commerce. There are no explicit mentions of AI, algorithms, or related technologies. As such, the relevance of the four AI-related categories is minimal. Social Impact, Data Governance, System Integrity, and Robustness do not have any context or content related to AI systems, their governance, or their impact on society. Thus, all categories are rated as 1: Not relevant.
Sector: None (see reasoning)
The text predominantly deals with regulatory processes surrounding steel imports and has no content related to the sectors provided (politics, healthcare, etc.). There are no mentions or implications of AI application in any of the listed sectors. Therefore, each sector is evaluated as 1: Not relevant.
Keywords (occurrence): automated (2)