research published in Frontiers in Robotics and AI

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frontiersin.org·frontiersin.org/articles/10.3389/frobt.2021.665729/full

A peer-reviewed IEEE standardization proposal offering a concrete, stakeholder-differentiated framework for transparency in AI and robotics; relevant to governance and accountability discussions in AI safety.

Metadata

Importance: 62/100journal articleprimary source

Summary

This paper presents IEEE P7001, a draft standard that operationalizes transparency in autonomous systems as a measurable, testable property rather than a vague ethical principle. It defines five distinct stakeholder groups and specifies graduated transparency levels appropriate for each, illustrated through worked examples of fictional autonomous systems for both specification and assessment purposes.

Key Points

•Argues transparency should be a measurable, testable property with defined metrics, not merely an abstract ethical aspiration.
•Identifies five stakeholder groups: users, general public/bystanders, safety certification agencies, accident investigators, and legal experts.
•Defines graduated 'levels' of transparency appropriate to each stakeholder group's needs and expertise.
•Demonstrates practical application via worked examples of fictional autonomous systems using System Transparency Assessment (STA) and Specification (STS) frameworks.
•Provides a standardization framework intended to guide both developers specifying transparency requirements and regulators assessing compliance.

Cited by 1 page

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AI Standards Development	Concept	69.0

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Frontiers | IEEE P7001: A Proposed Standard on Transparency 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 ORIGINAL RESEARCH article

 Front. Robot. AI , 26 July 2021 

 Sec. Ethics in Robotics and Artificial Intelligence

 Volume 8 - 2021 | https://doi.org/10.3389/frobt.2021.665729 

 Published in Frontiers in Robotics and AI 

 Ethics in Robotics and Artificial Intelligence

 
 3 impact factor
 7.3 citescore
 Part of a Research Topic

 Responsible Robotics: Identifying and Addressing Issues of Ethics, Fairness, Accountability, Transparency, Privacy and Employment

 147k views
 11 articles
 Editor & Reviewers

 Edited by

 M M Masoumeh Mansouri

 University of Birmingham, United Kingdom

 Reviewed by

 B K Benjamin Kuipers

 University of Michigan, United States

 P J Pablo Jiménez-Schlegl

 Spanish National Research Council (CSIC), Spain

 Outline 

 Figures and Tables TABLE 1

 Transparency levels for end users. 

 View in article 
 TABLE 2

 Transparency levels for accident investigators. 

 View in article 
 TABLE 3

 Outline system transparency assessment (STA) for RoboTED. 

 View in article 
 TABLE 4

 Outline system transparency specification (STS) for nextVac. 

 View in article 
 ORIGINAL RESEARCH article

 Front. Robot. AI , 26 July 2021 

 Sec. Ethics in Robotics and Artificial Intelligence

 Volume 8 - 2021 | https://doi.org/10.3389/frobt.2021.665729 

 IEEE P7001: A Proposed Standard on Transparency 

 A F Alan F. T. Winfield 1 * 

 
 S B Serena Booth 2 

 
 L A Louise A. Dennis 3 

 
 T E Takashi Egawa 4 

 
 H H Helen Hastie 5 

 
 N J Naomi Jacobs 6 

 
 R I Roderick I. Muttram 7 

 
 J I Joanna I. Olszewska 8 

 
 F R Fahimeh Rajabiyazdi 9 

 
 A T Andreas Theodorou 10 

 
 M A Mark A. Underwood 11 

 
 R H Robert H. Wortham 12 

 
 +4 more 
 E W Eleanor Watson 13 

 
 
 1. Bristol Robotics Laboratory, UWE Bristol, Bristol, United Kingdom

 2. Computer Science and AI Laboratory (CSAIL), MIT, Cambridge, MA, United States

 3. Department of Computer Science, University of Manchester, Manchester, United Kingdom

 4. NEC Corporation, Tokyo, Japan

 5. Department of Computer Science, Heriot-Watt University, Edinburgh, United Kingdom

 6. ImaginationLancaster, Lancaster Institute for Contemporary Arts, University of Lancaster, Lancaster, United Kingdom

 7. Fourth Insight Ltd, Ewhurst, United Kingdom

 8. School of Computing and Engineering, University of the West of Scotland, Paisley, United Kingdom

 9. Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, ON, Canada

 10. Department of Computing Science, Umeå University, Umeå, Sweden

 11. Synchrony Financial, Stamford, CT, United States

 12. Department of Electronic and Electrical Engineering, University of Bath, Bath, United Kingdom

 13. Nell Watson Ltd., Carrickfergus, United Kingdom

 See mor

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Resource ID: 2156ef1b9e1946b4 | Stable ID: ZjU1MGVjZD