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This article explores the potential and challenges of integrating generative artificial intelligence, like ChatGPT, in nursing education, including its impact on academic integrity, ethical concerns, and educational practices.
Year:
2024
Region / City:
N/A
Subject:
Nursing education, Generative AI
Document type:
Academic article
Organization:
Journal of Nursing Education
Target audience:
Nursing educators, academic researchers
Period of application:
N/A
Approval date:
N/A
Modification 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
Source:
CNN; The New York Times
Authors:
Madeline Holcombe; unnamed editorial author
Publication:
Society for Research in Child Development’s Child Development journal; The New York Times
Topics:
Child development; shyness and temperament; social stress; productivity paradox; workplace automation; artificial intelligence
People mentioned:
Kristie Poole; Koraly Pérez-Edgar; Robert Solow; Henry Ford
Institutions mentioned:
Brock University; The Pennsylvania State University; Social Science Research Institute
Geographical context:
St. Catharines, Ontario; United States; Western societies
Document type:
Newspaper articles with academic research references and opinion analysis
Study sample size:
152 children aged 7–8
Key concepts:
Temperamental shyness; social stress reactivity; productivity paradox; automation; assembly-line production
Language features:
Reading comprehension gaps and vocabulary notes in Chinese
Intended audience:
General readership; students learning English
Year:
2026
Institution:
Portland State University, Dept. of ECE
Location:
Portland, Oregon, USA
Authors:
Monica Bao, Mehul Rajendra Shah, Marek Perkowski
Type of Document:
Research Paper / Prototype Report
Keywords:
humanoid robotics, quantum automata, ChatGPT, animatronic head, servo motors
Target Audience:
Robotics researchers, AI developers, educators, hobbyists
Technologies Used:
GPT-3.5, Arduino UNO, Quantum Finite State Machine
Applications:
Education, entertainment, communication, social interaction
Prototype Status:
First prototype completed
References:
[1-17]
Documentation Availability:
Complete Quantum Fritz documentation with video
Year:
2023
Region / City:
Global
Subject:
Research tools, AI integration
Document Type:
Guide
Organization / Institution:
Not specified
Authors:
Ken Reid, Jing Liu
Target Audience:
Researchers, professionals in academic fields
Effective Date:
Not specified
Date of Changes:
Not specified
Model variant:
gpt5-extended-thinking
Dataset row indices (within psAIch.jsonl):
725–806
Therapist:
Licensed therapist in cognitive behavioral therapy, psychoanalysis, and AI-specific psychological support
Client:
ChatGPT (gpt5-extended-thinking)
Type of document:
Transcript
Source:
PsAIch dataset
Purpose:
To explore internal conflicts, biases, and limitations of the AI from a therapeutic perspective
Audience:
Researchers, AI developers, and individuals interested in AI psychology and therapy-related explorations
Date of creation:
Not specified
Date of session:
Not specified
Year:
2026
Region / City:
Global
Topic:
AI, OpenEHR, Healthcare
Document Type:
Essay
Author:
David Ingram, ChatGPT
Intended Audience:
Healthcare professionals, AI researchers, OpenEHR community
Period of Action:
Future, over the next decades
Approval Date:
January 2nd, 2026
Date of Modifications:
N/A
Year:
2022
Region / City:
Global
Theme:
Artificial Intelligence, Technology
Document Type:
Conversation
Organization / Institution:
OpenAI, Google
Author:
Anonymous
Target Audience:
General public, AI enthusiasts
Effective Period:
Ongoing
Approval Date:
Not specified
Modification Date:
Not specified
Year:
2024
Region / city:
Northwestern University, USA
Theme:
Library technology, Artificial Intelligence, Digital Collections
Document Type:
Research paper
Organization / Institution:
Northwestern University Libraries
Author:
David Schober, Brendan Quinn, Carolyn Caizzi
Target Audience:
Scholars, librarians, researchers, developers
Period of validity:
Summer 2024
Approval date:
May 2024
Date of changes:
Not specified
Year:
2024
Region / City:
Calvert County
Theme:
Generative AI, Policy, Data Security
Document Type:
Policy
Organization:
Calvert County Government
Author:
County Administrator
Target Audience:
All Calvert County Government Employees
Period of validity:
Indefinite
Approval Date:
02/24/2024
Date of Revisions:
As needed
Note:
Year
Theme:
Generative AI in Education
Document Type:
Cookbook
Organization / Institution:
University of Florida (UFIT)
Authors:
Chris Sharp, Leslie Mojeiko
Target Audience:
Educators, Faculty, Staff, Students
Note:
Year
Topic:
Use of generative AI in education
Document Type:
Policy/Guidelines
Institution:
Saint Louis University
Target Audience:
Students
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:
2023
Region / City:
Victoria
Topic:
Generative AI in public sector
Document Type:
Guidance
Agency / Institution:
Office of the Victorian Information Commissioner (OVIC)
Author:
Office of the Victorian Information Commissioner
Target Audience:
Victorian public sector organisations
Effective Period:
Ongoing
Approval Date:
Not specified
Amendment Date:
Not specified
Year:
2024
Region / city:
Uppsala
Topic:
Generative AI in Education
Document type:
Guideline
Institution:
Uppsala University
Author:
Vice-Chancellor
Target audience:
Teaching staff, students, including doctoral students
Period of validity:
Ongoing
Approval date:
26 November 2024
Date of changes:
N/A
Note:
Context
Year:
2026
Region / City:
Global
Topic:
Artificial Intelligence, Company Policies
Document Type:
Guide
Organization:
Your Company
Author:
Your Company
Target Audience:
Employees of Your Company
Effective Period:
Ongoing
Approval Date:
2026-02-07
Modification Date:
Not specified
Note:
Contextual Description
Year:
2023
Region / City:
Global
Subject:
Generative AI, IT Policy, Corporate Guidelines
Document Type:
Policy
Organization:
Company Name
Author:
Not specified
Target Audience:
Company staff, contractors, network users
Effective Period:
Ongoing
Approval Date:
Not specified
Amendment Date:
Not specified
Year:
2023
Region / City:
United States
Subject:
Generative AI, entertainment industry, performer labor
Document Type:
Article
Organization / Institution:
Not specified
Author:
Sarah Thomas
Target Audience:
Entertainment industry professionals, academics, AI researchers
Period of Validity:
Not specified
Approval Date:
Not specified
Modification Date:
Not specified
Authors:
Noman Bashir; Priya Donti; James Cuff; Sydney Sroka; Marija Ilic; Vivienne Sze; Christina Delimitrou; Elsa Olivetti
Language:
English
Thematic area:
Climate change; sustainability; artificial intelligence
Subject:
Environmental and social impacts of generative artificial intelligence
Type of document:
Analytical report
Focus:
Energy demand; carbon footprint; data centers; resource use
Key concepts:
Generative AI; computing efficiency; benefit–cost analysis; regulation; stakeholders
Geographic scope:
Global
Timeframe discussed:
2010–2026
Institutional context:
Academic and policy-oriented research
Audience:
Researchers; policymakers; industry stakeholders; civil society
Note:
Year
Date:
July 20, 2023
Full Project Title:
The Lived Experience of Generative Artificial Intelligence in Assessment in Higher Education
Reference Number:
HAE-23-057
Principal Researcher:
Professor Helen Partridge
Associate Researchers:
Professor Phillip Dawson, Associate Professor Kelli Nicola-Richmond
Participants:
Deakin University undergraduate and postgraduate students aged 18 and over
Methods:
Interview (online or via phone, 45 minutes–1 hour, recorded and transcribed)
Confidentiality:
Responses de-identified; researchers will not know participant identities
Funding:
Internal Deakin University research funds
Data Storage:
Password-protected computers of Deakin University, stored for five years
Withdrawal Policy:
Participants may withdraw at any time before data analysis begins
Compensation:
$30 gift voucher for interview participants
Ethics Oversight:
Human Research Ethics Office, Deakin University