Фильтр :
Стандарт и/или проект находящийся в компетенции ISO/IEC JTC 1/SC 42 Секретариата | Этап | ICS |
---|---|---|
Information technology — Artificial intelligence — Assessment of machine learning classification performance |
60.60 | |
Artificial intelligence — Data quality for analytics and machine learning (ML) — Part 1: Overview, terminology, and examples |
40.60 | |
Artificial intelligence — Data quality for analytics and machine learning (ML) — Part 2: Data quality measures |
40.20 | |
Artificial intelligence — Data quality for analytics and machine learning (ML) — Part 3: Data quality management requirements and guidelines |
40.60 | |
Artificial intelligence — Data quality for analytics and machine learning (ML) — Part 4: Data quality process framework |
40.60 | |
Artificial intelligence — Data quality for analytics and machine learning (ML) — Part 5: Data quality governance |
30.99 | |
Artificial intelligence — Data quality for analytics and machine learning (ML) — Part 6: Visualization framework for data quality |
30.00 |
|
Information technology — Artificial intelligence — AI system life cycle processes |
50.20 | |
Information technology — Artificial intelligence — Guidance for AI applications |
50.00 | |
Information technology — Artificial intelligence — Reference architecture of knowledge engineering |
40.99 | |
Artificial intelligence — Functional safety and AI systems |
50.00 | |
Information technology — Artificial intelligence — Objectives and approaches for explainability of ML models and AI systems |
30.60 | |
Information technology — Artificial intelligence — Data life cycle framework |
60.60 | |
Information technology — Artificial intelligence — Controllability of automated artificial intelligence systems |
30.60 | |
Information technology — Artificial intelligence — Treatment of unwanted bias in classification and regression machine learning tasks |
50.00 | |
Information technology — Artificial intelligence — Transparency taxonomy of AI systems |
30.60 | |
Information technology — Artificial intelligence — Verification and validation analysis of AI systems |
20.00 |
|
Information technology — Artificial intelligence — Overview of machine learning computing devices |
30.60 | |
Artificial intelligence — Application of AI technologies in health informatics |
20.00 |
|
Information technology — Artificial intelligence — Environmental sustainability aspects of AI systems |
20.00 |
|
Information technology — Big data — Overview and vocabulary |
60.60 | |
Information technology — Big data reference architecture — Part 1: Framework and application process |
60.60 | |
Information technology — Big data reference architecture — Part 2: Use cases and derived requirements |
60.60 | |
Information technology — Big data reference architecture — Part 3: Reference architecture |
60.60 | |
Information technology — Big data reference architecture — Part 5: Standards roadmap |
60.60 | |
Information technology – Artificial intelligence – Beneficial AI systems |
20.00 |
|
Artificial intelligence — Functional safety and AI systems — Requirements |
20.00 |
|
Information technology — Artificial intelligence — Guidance on addressing societal concerns and ethical considerations |
20.00 |
|
Information technology — Artificial intelligence — Artificial intelligence concepts and terminology |
60.60 | |
Framework for Artificial Intelligence (AI) Systems Using Machine Learning (ML) |
60.60 | |
Information technology — Artificial intelligence — Guidance on risk management |
60.60 | |
Information technology — Artificial intelligence (AI) — Bias in AI systems and AI aided decision making |
60.60 | |
Information technology — Artificial intelligence — Overview of trustworthiness in artificial intelligence |
60.60 | |
Artificial Intelligence (AI) — Assessment of the robustness of neural networks — Part 1: Overview |
60.60 | |
Artificial intelligence (AI) — Assessment of the robustness of neural networks — Part 2: Methodology for the use of formal methods |
60.60 | |
Artificial intelligence (AI) — Assessment of the robustness of neural networks — Part 3: Methodology for the use of statistical methods |
20.00 |
|
Information technology — Artificial intelligence (AI) — Use cases |
90.92 | |
Information technology — Artificial intelligence (AI) — Use cases |
30.99 | |
Information technology — Artificial intelligence — Overview of ethical and societal concerns |
60.60 | |
Information technology — Artificial intelligence (AI) — Overview of computational approaches for AI systems |
60.60 | |
Information technology — Artificial intelligence — Process management framework for big data analytics |
60.60 | |
Systems and software engineering — Systems and software Quality Requirements and Evaluation (SQuaRE) — Guidance for quality evaluation of artificial intelligence (AI) systems |
50.20 | |
Software engineering — Systems and software Quality Requirements and Evaluation (SQuaRE) — Quality model for AI systems |
60.60 | |
Software and systems engineering — Software testing — Part 11: Testing of AI systems |
20.00 |
|
Information technology — Governance of IT — Governance implications of the use of artificial intelligence by organizations |
60.60 | |
Information technology — Artificial intelligence — Management system |
50.00 | |
Information technology — Artificial intelligence — AI system impact assessment |
30.60 | |
Information technology — Artificial intelligence — Requirements for bodies providing audit and certification of artificial intelligence management systems |
40.00 | |
Information technology — Artificial intelligence — Taxonomy of AI system methods and capabilities |
20.00 |
|
Information technology — Artificial intelligence — Overview of synthetic data in the context of AI systems |
20.00 |
|
Information technology — Artificial intelligence — Guidance for human oversight of AI systems |
20.00 |
|
Information technology — Artificial intelligence — Overview of differentiated benchmarking of AI system quality characteristics |
20.00 |
|
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