• Content Type

IEEE 7001

IEEE Standard for Transparency of Autonomous Systems

Last updated: 11 May 2023

Development Stage




4 Mar 2022


New IEEE Standard – Active. Measurable, testable levels of transparency, so that autonomous systems can be objectively assessed, and levels of compliance determined, are described in this standard. © Copyright 2022 IEEE


This standard is broadly applicable to all autonomous systems, including both physical and non-physical systems. Examples of the former include vehicles with automated driving systems or assisted living (care) robots. Examples of the latter include medical diagnosis (recommender) systems or chatbots. Of particular interest to this standard are autonomous systems that have the potential to cause harm. Safety-critical systems are therefore within scope. This standard considers systems that have the capacity to directly cause either physical, psychological, societal, economic or environmental, or reputational harm, as within scope. Harm might also be indirect, such as unauthorized persons gaining access to confidential data or a victimless crime that affect no-one in particular yet have an impact upon society or the environment. Intelligent autonomous systems that use machine learning are also within scope. The data sets used to train such systems are also within the scope of this standard when considering the transparency of the system as a whole. This standard provides a framework to help developers of autonomous systems both review and, if needed, design features into those systems to make them more transparent. The framework sets out requirements for those features, the transparency they bring to a system, and how they would be demonstrated in order to determine conformance with this standard. Future standards may choose to focus on specific applications or technology domains. This standard is intended as an umbrella standard from which domain-specific standards might develop (for instance, standards for transparency in autonomous vehicles, medical or healthcare technologies, etc.). This standard does not provide the designer with advice on how to design transparency into their system. Instead, it defines a set of testable levels of transparency and a standard set of requirements that shall be met in order to satisfy each of these levels. Transparency cannot be assumed. An otherwise well-designed system may not be transparent. Many well-designed systems are not transparent. Autonomous systems, and the processes by which they are designed, validated, and operated, will only be transparent if this is designed into them. In addition, methods for testing, measuring, and comparing different levels of transparency in different systems are needed. Note that system-system transparency (transparency of one system to another) is out of scope for this standard. However, this document does address the transparency of the engineering process. Transparency regarding how subsystems within an autonomous system interact is also within the scope of this standard. © IEEE 2022 All rights reserved.


The purpose of this standard is to set out measurable, testable levels of transparency for autonomous systems. The general principle behind this standard is that it should always be possible to understand why and how the system behaved the way it did. Transparency is one of the eight General Principles set out in IEEE Ethically Aligned Design [B21]. The basis of a particular autonomous and intelligent system decision should always be discoverable A working group tasked with drafting this standard was set up in direct response to a recommendation in the general principles section of IEEE Ethically Aligned Design. © IEEE 2022 All rights reserved.

Let the community know


Domain: Horizontal

Key Information

Organisation: IEEE
Free to access: Yes
  • Author
  • Up

    Share your thoughts on this standard with the AI Standards Hub community here.

You must be logged in to contribute to the discussion

Rated 0 out of 5
0 out of 5 stars (based on 0 reviews)
5 star0%
4 star0%
3 star0%
2 star0%
1 star0%

Post a review