Risk management Archives - Page 4 of 17

This document establishes concepts and principles for Information Governance. This document applies to the governance of the organisation’s past, current and future information assets. It…

Published

Last Updated: 18 Jul 2024

IEEE 7000-2021

IEEE Standard Model Process for Addressing Ethical Concerns during System Design

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Horizontal AI-enabling - Project management AI-enabling - Risk management Accountability

Bias and discrimination Explainability and transparency Privacy Project management Risk management Stakeholder engagement and communication Sustainability Process, management and governance

A set of processes by which organizations can include consideration of ethical values throughout the stages of concept exploration and…

Published

Last Updated: 19 Jul 2024

ANSI/RIA R 15.08-1

Industrial Mobile Robots – Safety Requirements – Part 1: Requirements for the Industrial Mobile Robot

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Manufacturing AI-enabling - Non-intelligent robotics and autonomous systems AI-enabling - Risk management Risk management

Safety Robotics and autonomous systems Product and performance requirements

Specifies safety requirements for industrial mobile robots (IMRs). It describes basic hazards associated with IMRs in an industrial environment (See…

Published

Last Updated: 18 Jul 2024

IEEE 2813-2020

IEEE Standard for Big Data Business Security Risk Assessment

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General business applications AI-enabling - Cybersecurity AI-enabling - Data AI-enabling - Risk management

Data protection Risk management Security and resilience Process, management and governance

New IEEE Standard – Active. This standard can be applied to internet-based business scenarios, and can also be served serve…

Published

Last Updated: 18 Jul 2024

IEEE 7010-2020

IEEE Recommended Practice for Assessing the Impact of Autonomous and Intelligent Systems on Human Well-Being

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Horizontal AI-specific Accuracy and performance Human rights

Risk management System lifecycle Measurement and test methods

New IEEE Standard – Active. The impact of artificial intelligence or autonomous and intelligent systems (A/IS) on humans is measured…

Published

Last Updated: 19 Jul 2024

PAS 277:2015 from BSI

Health and wellness apps. Quality criteria across the life cycle. Code of practice

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Healthcare and medicine AI-enabling Project management Risk management

System lifecycle System quality Process, management and governance

What is PAS 277 – Health and wellness apps – Code of practise with quality standards for all stages of…

Published

Last Updated: 18 Jul 2024

ANSI/CTA 2096

Guidelines for Developing Trustworthy Artificial Intelligence Systems

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Horizontal AI-specific Accountability Accuracy and performance

Bias and discrimination Data protection Explainability and transparency Human-centred design Privacy Risk management Safety Security and resilience Stakeholder engagement and communication Process, management and governance

This recommended practice will describe things developers of artificial intelligence (AI) systems should consider for their systems to be considered…

Published

Last Updated: 18 Jul 2024

Content Type

Information technology – Artificial intelligence – Verification and validation analysis of AI systems

Information technology – Artificial intelligence – Risk management

Information technology – Artificial intelligence – Process management framework for big data analytics

Information technology – Artificial intelligence – Overview of trustworthiness in artificial intelligence

Information security, cybersecurity and privacy protection. Governance of information security

IEEE Standard Model Process for Addressing Ethical Concerns during System Design

Industrial Mobile Robots – Safety Requirements – Part 1: Requirements for the Industrial Mobile Robot

IEEE Standard for Big Data Business Security Risk Assessment

IEEE Recommended Practice for Assessing the Impact of Autonomous and Intelligent Systems on Human Well-Being

Health and wellness apps. Quality criteria across the life cycle. Code of practice

Guidelines for Developing Trustworthy Artificial Intelligence Systems

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