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This document provides a template for school leaders to create their own AI policy, addressing the integration of AI in education, its benefits, and the risks associated with its use.
Year:
2025
Region / City:
UK
Subject:
Artificial Intelligence in Education
Document Type:
Policy Template
Author:
South West Grid for Learning Trust (SWGfL)
Target Audience:
School Leaders, Teachers, Education Administrators
Implementation Period:
Ongoing
Approval Date:
January 2025
Amendment Date:
N/A
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Year:
Not provided
Region / City:
Not specified
Topic:
Research ethics, manuscript submission
Document type:
Template
Author:
Not specified
Target audience:
Authors submitting research articles
Period of validity:
Not provided
Approval date:
Not specified
Date of changes:
Not specified
Year:
2024
Region / city:
Stanford University
Subject:
Artificial Intelligence, Machine Learning
Document Type:
Problem Set
Author:
Christoph F. Eick, Raunak Sarbajna, Md/Mahin
Target Audience:
Students of COSC 4368
Period of Action:
Spring 2024
Submission Deadline:
November 21, 11:59p
Responsible TA:
Farzana Yasmin
Last Updated:
September 2, 8a
Task Weight:
20% of the Problem Set Points
Dataset:
Stanford Cars
Note:
Learning Objectives
Note:
Date
Author:
Kurt Krause
Context:
A letter addressing the proposed amendments by the Ontario Energy Board regarding the use of AI systems in regulatory filings.
Year:
2023
Region / City:
Federation University, Australia
Topic:
Artificial Intelligence, Academic Integrity, Education
Document Type:
Guideline
Institution:
Federation University
Author:
Not specified
Target Audience:
University staff, students
Period of validity:
Not specified
Approval Date:
Not specified
Modification Date:
Not specified
Year:
2023-2024
Region / City:
Patna
Theme:
Artificial Intelligence, Education, Admissions
Document Type:
Admission Notification
Institution:
Indian Institute of Technology Patna
Author:
Centre of Excellence in Artificial Intelligence, Vishleshan I-Hub Foundation
Target Audience:
Prospective students applying for M.Tech. in Artificial Intelligence
Period of Validity:
June 14, 2023 (Application Deadline)
Approval Date:
Not specified
Amendment Date:
Not specified
Year:
2026
Organization:
NAIC Innovation, Cybersecurity and Technology (H) Committee
Type of document:
Regulatory guidance / Supplementary tool
Audience:
State insurance regulators
Topics:
Artificial intelligence, machine learning, insurance risk assessment, consumer protection
Sections:
Exhibit A – Quantify Regulated Entity’s Use of AI Systems; Exhibit B – AI Systems Governance Risk Assessment Framework; Exhibit C – AI Systems High-Risk Model Details; Exhibit D – AI Systems Model Data Details
Scope:
Financial and consumer risk evaluation of AI systems usage in insurance companies
Year:
2025
Region / City:
Bangor
Subject:
Academic Integrity, Artificial Intelligence, Assessment
Document Type:
Guidance Document
Organization / Institution:
Bangor University
Author:
Bangor University
Target Audience:
University Faculty, Students
Period of Validity:
Effective from 1st September 2025
Approval Date:
2025
Review Date:
January 2026
Review Frequency:
Annual
Year:
2024
Region / City:
Global
Topic:
Artificial Intelligence, Biotechnology, Bibliometric Analysis
Document Type:
Research Paper
Author:
Multiple authors (da Silva, Khan et al., Peng & Rajjou, etc.)
Target Audience:
Researchers, Funding Agencies, Policymakers
Period of Application:
2000–2025
Date of Approval:
Not specified
Date of Modifications:
Not specified
Keywords:
Artificial Intelligence, Biotechnology, Bibliometric Analysis, Machine Learning, Bioinformatics, Research Trends
Year:
2025
Region / City:
Malaysia
Topic:
Export control regulations for advanced AI chips
Document type:
Guideline
Organization:
Strategic Trade Secretariat, Ministry of Investment, Trade and Industry (MITI)
Author:
Strategic Trade Secretariat
Target Audience:
Exporters, manufacturers, regulatory bodies
Effective Period:
Ongoing from 2025
Approval Date:
2025
Amendment Date:
N/A
Year:
2023
Region / City:
United States
Subject:
Artificial Intelligence, Insurance, Risk Management
Document Type:
Regulatory Tool
Institution:
National Association of Insurance Commissioners (NAIC)
Author:
Big Data and AI Working Group (BDAIWG)
Target Audience:
State Regulators, Insurance Companies
Period of Validity:
Ongoing
Approval Date:
N/A
Date of Amendments:
N/A
Year:
2025
Date of Recording:
March 21, 2025
Speakers:
Maureen McGuire-Kuletz, Rob Froehlich, Dr. Nichole Tichy
Institution:
George Washington University
Type of Document:
Presentation Transcript
Topic:
Ethics, Artificial Intelligence, Vocational Rehabilitation
Audience:
Counselors, Rehabilitation Professionals
Related Codes:
CRC Code of Ethics 2023, American Counseling Association Guidelines
Learning Objectives:
Ethical principles in AI, client privacy, informed consent, bias mitigation, professional responsibility
Endorsing Body:
CRCC Ethics Committee (speakers’ affiliation)
Contextual Description:
Transcript of a professional presentation discussing ethical considerations in the use of artificial intelligence within vocational rehabilitation and counseling, including confidentiality, professional responsibility, and compliance with relevant codes.
Year:
2024
Region / city:
Sophia Antipolis, France
Subject:
AI/ML Management for 5G Networks
Document Type:
Technical Specification
Organization / Institution:
3GPP
Author:
3GPP Organizational Partners
Target Audience:
5G Network Professionals, Developers, and Researchers
Effective Period:
Not specified
Approval Date:
Not specified
Revision Date:
Not specified
Note:
Contextual Description
Year:
2024
Note:
Region / City
Topic:
Research involving AI tools
Document Type:
Worksheet
Target Audience:
IRB members, researchers
Year:
2022
Region / City:
N/A
Subject:
Psychology, Face Perception
Document Type:
Peer Review
Organization / Institution:
Collabra: Psychology
Author:
Alexa Tullett
Target Audience:
Researchers in psychology, particularly those interested in face perception and trustworthiness studies
Period of validity:
N/A
Approval Date:
N/A
Date of Changes:
N/A
Context:
Peer review feedback on a manuscript concerning the trustworthiness and attractiveness of faces labelled as artificial, highlighting methodological concerns and proposing further experiments.
Date created:
1 July 2024
Last updated:
3 July 2024
Authorised by:
Chief Judge Peter Kidd
Language:
English
Document type:
Guidelines
Region / City:
Victoria
Topic:
Artificial Intelligence, Litigation, Law
Target audience:
Legal practitioners, self-represented litigants
Period of validity:
Ongoing
Approval date:
1 July 2024
Date of last update:
3 July 2024
Year:
Not provided
Region / City:
Not specified
Topic:
Research ethics, manuscript submission
Document type:
Template
Author:
Not specified
Target audience:
Authors submitting research articles
Period of validity:
Not provided
Approval date:
Not specified
Date of changes:
Not specified
Program:
Next Generation Technologies Fund
Priority level:
Tier 2
Theme:
Integrated Intelligence, Surveillance and Reconnaissance (ISR)
Related strategy:
More, Together: Defence Science and Technology Strategy 2030
Related STaR Shots:
Agile Command and Control; Operations in a Chemical, Biological, Radiological and Nuclear Environment; Information Warfare
Responsible organisation:
Defence Science and Technology Group (DST)
Geographic scope:
Australia
Target participants:
Australian small to medium enterprises
Activity type:
Research and development proposals
Focus areas:
Automated information processing and reasoning; Human and Artificial Intelligence interaction; Distributed multi-domain networks
Application domains:
Defence and civilian sensing and surveillance systems
Source type:
Government research funding priority description
Year:
2024
Region / city:
Stanford University
Subject:
Artificial Intelligence, Machine Learning
Document Type:
Problem Set
Author:
Christoph F. Eick, Raunak Sarbajna, Md/Mahin
Target Audience:
Students of COSC 4368
Period of Action:
Spring 2024
Submission Deadline:
November 21, 11:59p
Responsible TA:
Farzana Yasmin
Last Updated:
September 2, 8a
Task Weight:
20% of the Problem Set Points
Dataset:
Stanford Cars
Note:
Learning Objectives
Year:
2019
Region / city:
England & Wales
Topic:
Family Justice System, Data Research
Document Type:
Summary document
Author:
Nuffield Family Justice Observatory
Target Audience:
Practitioners, policy makers, data analysts
Period of validity:
Not specified
Approval Date:
May 2019
Date of changes:
Not specified
Note:
Date
Author:
Kurt Krause
Context:
A letter addressing the proposed amendments by the Ontario Energy Board regarding the use of AI systems in regulatory filings.