№ lp_2_3_02457
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This research paper investigates the productivity impact of GitHub Copilot, a generative AI tool for software development, through field experiments at Microsoft and Accenture.
Year:
2023
Region / City:
Microsoft, Accenture
Topic:
Generative AI, productivity, software development
Document Type:
Research Paper
Organization / Institution:
Microsoft, Accenture
Authors:
Kevin Zheyuan Cui, Mert Demirer, Sonia Jaffe, Leon Musolff, Sida Peng, Tobias Salz
Target Audience:
Researchers, software developers, AI practitioners
Period of Validity:
September 2022 - ongoing
Approval Date:
N/A
Modification Date:
N/A
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Year:
2023
Region / City:
USA
Subject:
GitHub usage in software development
Document Type:
Technology Standard
Organization:
VA (Department of Veterans Affairs)
Author:
VA OIT
Target Audience:
VA software development teams
Action Period:
Ongoing
Approval Date:
Not specified
Modification Date:
Not specified
Tableau Portfolio GitHub Capstone Project and Professional Experience of Sr. Data Engineer Jyotsna.M
Year:
2023–Present
Location:
Richmond, Virginia, USA
Field:
Data Engineering / Data Science
Document Type:
Professional Portfolio / Resume
Organization:
W.R. Berkley Corporation, [email protected]
Author:
Jyotsna.M
Education:
Masters in IT (Data Science), Saint Peter’s University, GPA 3.9
Certifications:
AWS, Snowflake SnowPro, PSM-1, Azure, AINS-101, GCP, PSPO-1, Databricks Certified Data Engineer Associate and Professional
Skills:
Data Warehousing, PySpark, Spark SQL, Scala, Azure Data Factory, Azure Data Lake, SQL Server, Tableau, Power BI, Agile Methodology, Python
Professional Experience:
Data Engineer in Property & Casualty Insurance, involved in ETL pipelines, data integration, migration to Azure, and visualization
Technologies Used:
Azure Synapse Analytics, Azure Blob, Databricks, Snowflake, Apache Airflow, CI/CD tools (Jenkins, GitLab, Azure DevOps)
Year:
2023
Region / City:
Victoria
Subject:
Privacy and Data Protection
Document Type:
Public Statement
Organization / Institution:
Office of the Victorian Information Commissioner (OVIC)
Author:
Acting Information Commissioner
Target Audience:
Public sector organizations in Victoria
Effective Period:
From 1 November 2023
Approval Date:
Not specified
Amendment Date:
Not specified
Privacy Considerations:
Information Privacy Principles (IPPs)
Privacy Impact Assessment:
Required
Risk Assessment:
Required
Data Sharing:
Disabled with Microsoft platforms such as Power Platform and Dynamics 365
Year:
2026
Region / City:
N/A
Topic:
Copilot Agents Voucher Service Agreement Verification
Document Type:
Instructional Guide
Organization / Institution:
Microsoft
Author:
N/A
Target Audience:
Partners, Customers
Effective Period:
N/A
Approval Date:
January 14, 2026
Modification Date:
N/A
Year:
2026
Platform:
Legal Talk Network
Type of document:
Podcast transcript
Hosts:
Zach, Chad
Guest:
Ben Shor
Topic:
Application of AI tools in legal practice
Episode number:
598
Duration:
Approximately 8 minutes (partial transcript)
Language:
English
Audience:
Legal professionals and podcast listeners interested in AI in law
Year:
2023
Region / City:
Not specified
Topic:
Academic research, AI tools, academic papers
Document type:
Instructional guide
Organization / Institution:
Not specified
Author:
Not specified
Target audience:
Researchers, postdoctoral researchers, PhD students
Period of validity:
Not specified
Approval date:
Not specified
Modification date:
Not specified
Contextual description:
Instructional guide for using Perplexity AI, focusing on its academic research features, including CoPilot and AI model settings.
Year:
2023
Region / City:
Calgary, Canada
Topic:
Clinical/Adjunct/Research Promotions
Document Type:
Instructional Guide
Institution:
University of Calgary
Author:
Microsoft
Target Audience:
University of Calgary faculty members
Promotion Criteria Period:
Ongoing
Approval Date:
N/A
Date of Last Update:
N/A
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