BTG AEGIS AI™ Crash Course – Ethical Artificial Intelligence (2025 Edition)

The BTG AEGIS AI Crash Course – Ethical Artificial Intelligence (2025 Edition) provides a structured, practical framework for building and governing responsible AI systems. Recognised under CERN Zenodo and OpenAIRE EU, this program combines international AI ethics guidelines — including the EU AI Act, UNESCO’s Recommendation on the Ethics of AI, and IEEE’s Ethically Aligned Design — to train learners in identifying, mitigating, and managing ethical risks in artificial intelligence. Participants explore real-world issues of bias, transparency, accountability, and human oversight while learning to design AI governance frameworks and ethical audit processes. The course culminates in an Ethical AI Design Proposal, preparing graduates to act as certified BTG AEGIS Ethical AI Practitioners capable of integrating fairness and compliance into innovation. Author: Santosh Sunar – Founder, BeTheGuide® | UZB BUZ AI | ExoAnsion Pvt Ltd (India) Community: BTG AEGIS AI – Global Ethical AI Research Community Recognition: CERN Zenodo & OpenAIRE EU Background & References: This crash course builds upon the author’s earlier research in the BTG AEGIS AI Series, both published and recognised under CERN Zenodo and OpenAIRE EU: 1. BTG AEGIS AI – The Ethical AI-as-a-Service Framework for Global Governance (Zenodo DOI: https://doi.org/10.5281/zenodo.17459356) 2. BTG AEGIS AI – Prototype Edition (Zenodo DOI: (https://doi.org/10.5281/zenodo.17459356)

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-11-04
DOI
https://doi.org/10.5281/zenodo.17522229
Citations
1
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
2.37
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

BTG AEGIS AI™ Crash Course – Ethical Artificial Intelligence (2025 Edition)

1 citations
Zenodo (CERN European Organization for Nuclear Research)
Ethics and Social Impacts of AI
2.37
article

BTG AEGIS AI™ Crash Course – Ethical Artificial Intelligence (2025 Edition)

article en
1 citations

Abstract

The BTG AEGIS AI Crash Course – Ethical Artificial Intelligence (2025 Edition) provides a structured, practical framework for building and governing responsible AI systems. Recognised under CERN Zenodo and OpenAIRE EU, this program combines international AI ethics guidelines — including the EU AI Act, UNESCO’s Recommendation on the Ethics of AI, and IEEE’s Ethically Aligned Design — to train learners in identifying, mitigating, and managing ethical risks in artificial intelligence. Participants explore real-world issues of bias, transparency, accountability, and human oversight while learning to design AI governance frameworks and ethical audit processes. The course culminates in an Ethical AI Design Proposal, preparing graduates to act as certified BTG AEGIS Ethical AI Practitioners capable of integrating fairness and compliance into innovation. Author: Santosh Sunar – Founder, BeTheGuide® | UZB BUZ AI | ExoAnsion Pvt Ltd (India) Community: BTG AEGIS AI – Global Ethical AI Research Community Recognition: CERN Zenodo & OpenAIRE EU Background & References: This crash course builds upon the author’s earlier research in the BTG AEGIS AI Series, both published and recognised under CERN Zenodo and OpenAIRE EU: 1. BTG AEGIS AI – The Ethical AI-as-a-Service Framework for Global Governance (Zenodo DOI: https://doi.org/10.5281/zenodo.17459356) 2. BTG AEGIS AI – Prototype Edition (Zenodo DOI: (https://doi.org/10.5281/zenodo.17459356)

Zenodo (CERN European Organization for Nuclear Research)
Bühler (United Kingdom) (GB), Bethel University (US)
Openalex Percentile: Top 7%
Ethics and Social Impacts of AI
2.37
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.