Subject Code & Name: AD25403 – Standards in Artificial Intelligence
Regulation: R-2025
Semester: IV (Fourth Semester)
Branch: B.Tech. Artificial Intelligence and Data Science (AI&DS)
Credits / L-T-P: 1 Credit | L-T-P: 1-0-0
Course Objectives
- The official syllabus gives no separate Course Objectives for this 1-credit course; it is listed under “Overview of Standards”.
Full Unit-wise Syllabus
The official PDF prints this content under “Basic concepts of standardization” and “International Standards in Artificial Intelligence”. It is split into short units below for readability; wording is unchanged.
Unit I – Basic Concepts of Standardization
Purpose of Standardization, marking and certification of articles and processes; Importance of standards to industry, policy makers, trade, sustainability and innovation. Objectives, roles and functions of BIS, Bureau of Indian Standards Act, ISO/IEC Directives; WTO Good Practices for Standardization. Important Indian and International Standards.
Unit II – International Standards in Artificial Intelligence – ISO Standards
Introduction – Importance of standards in IT – Overview of key international standards organizations. ISO Standards – ISO/IEC 23053:2022 Framework for AI systems using machine learning, ISO/IEC 42001:2023 AI management systems, ISO/IEC 23894:2023 AI – Guidance on risk management.
Unit III – IEEE Standards for AI
IEEE P3123™ – Standard for Artificial Intelligence and Machine Learning (AI/ML) Terminology and Data Formats, IEEE P7015™ – Standard for Data and Artificial Intelligence (AI) Literacy, Skills, and Readiness, IEEE P3198™ – Standard for Evaluation Method of Machine Learning Fairness, IEEE P1948.1™ – Standard for Artificial Intelligence Based Network Applications in 5G and Beyond Mobile Networks, IEEE 2801™-2022 – IEEE Recommended Practice for the Quality Management of Datasets for Medical Artificial Intelligence, IEEE 2941™-2021 – IEEE Standard for Artificial Intelligence (AI) Model Representation, Compression, Distribution, and Management, IEEE 2941.2™-2023 – IEEE Standard for Application Programming Interfaces (APIs) for Deep Learning (DL) Inference Engines, IEEE P2975.2™ – Standard for Model Verification & Validation of Industrial Artificial Intelligence Systems, IEEE P2976™ – Standard for XAI – eXplainable Artificial Intelligence – for Achieving Clarity and Interoperability of AI Systems Design, IEEE P3127™ – Guide for an Architectural Framework for Blockchain-based Federated Machine Learning, IEEE 3129™-2023 – IEEE Standard for Robustness Testing and Evaluation of Artificial Intelligence (AI)-based Image Recognition Service, IEEE 3333.1.3™-2022 – IEEE Standard for the Deep Learning-Based Assessment of Visual Experience Based on Human Factors, IEEE P3157™ – Recommended Practice for Vulnerability Test for Machine Learning Models for Computer Vision Applications, IEEE 3168™-2024 – IEEE Standard for Robustness Evaluation Test Methods for a Natural Language Processing Service That Uses Machine Learning, IEEE P3419™ – Standard for Large Language Model Evaluation, IEEE 7010™-2020 – IEEE Recommended Practice for Assessing the Impact of Autonomous and Intelligent Systems on Human Well-Being, IEEE P7018™ – Standard for Security and Trustworthiness Requirements in Generative Pretrained Artificial Intelligence (AI) Models, IEEE P7100™ – Standard for Measurement of Environmental Impacts of Artificial Intelligence Systems.
Unit IV – ACM Standards and Guidelines
ACM Code of Ethics and Professional Conduct – ACM Computing Classification System (CCS) and its role in standardization.
Course Outcomes (COs)
- The official syllabus does not list a CO table for this course.
Source: Official Anna University – B.Tech. Artificial Intelligence and Data Science R-2025 Syllabus
Last Updated: October 2026
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