Co-Autor<\/strong><\/p>\n Dr. Patrik Feth The definition of AI is currently being discussed by the ISO\/IEC JTC 1\/SC 42<\/a> committee, for example. \u00bbEthics Guidelines for Trustworthy AI<\/a>\u00ab have been drawn up at the European level by a high-level expert group. These Guidelines proceed on the assumption that all legal rights and obligations that apply to the processes and activities involved in developing, deploying and using AI systems remain mandatory and must be duly observed (Seite 8<\/a>). These laws include the The current laws do not, however, make any concrete provisions regarding the development of safety-critical systems. It is only required by various means to comply with the state of the art and the state of the practice. This is where standards come into play, because standards should reflect this state in the best possible way. To be able to do so, they must be regularly updated in terms of new technological developments. Traditionally, such adjustments have rather been reactive in nature. Industry representatives agree on a minimum level that can be regarded as the current standard. Regarding the use of AI in safety-critical applications, however, a proactive approach is increasingly being taken. Safety experts from research and application jointly develop recommendations for action and application rules. In the following, we will focus on work and working groups using this proactive approach.<\/p>\n Here we list already published documents from standardization committees that concern AI and autonomous systems. At this time, many other documents are under preparation and will be published in the near future. Please see the list below for current initiatives. We will gladly extend the list with additional elements. Simply use the comment function below.<\/p>\n The list below does not contain any standards, but we believe that the included documents reflect the generally accepted state of the art quite well. We will gladly add additional elements to this list. Please use the comment function below for this.<\/p>\n Many organizations are undertaking activities to further develop the state of the art in science and technology, or to document this state of the art in standardization projects. We will gladly add further elements to this list. Simply use the comment function below for this purpose.<\/p>\n Looking for more information and input on that topic?<\/strong><\/p>\n <\/p>\n If you want to learn more about the state of the art and the challenges of using AI safely in autonomous systems<\/strong>, please feel free to attend our 4-day seminar to become a certified \u00bbData Scientist Specialized in Assuring Safety\u00ab<\/a>. The seminar also provides an up-to-date insight into the state of standardization.<\/p>\n <\/p>\n![\"Patrik](\"https:\/\/www.iese.fraunhofer.de\/blog\/wp-content\/uploads\/2020\/04\/Patrik_Feth_Blog-150x150.jpg\")
<\/strong><\/p>\n
\nCorporate Unit Functional Safety
\nSICK AG
\nPatrik.Feth@sick.de<\/a><\/p>\n<\/div>\nAre there already standards for autonomous systems?<\/h3>\n
\n(German) Product Safety Act<\/a> with the associated machinery directive, which are of particular importance in the context of safety.<\/p>\nAlready published standards for autonomous systems (including technical reports, DIN SPECs, DKE application rules, etc.)<\/h3>\n
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\nThe aim of DIN SPEC 92001 is to establish a quality-assuring and transparent lifecycle for AI modules. In the first part of the planned 92001 series, a framework is being set up for this.
\nhttps:\/\/www.din.de\/de\/wdc-beuth:din21:288723757<\/a><\/li>\n
\nUL4600 places the focus on setting up a safety case for autonomous systems and provides a framework for this. Fraunhofer IESE is on the review committee in order to provide support with its industry experience and its research expertise.
\nhttps:\/\/edge-case-research.com\/ul4600\/<\/a><\/li>\n
\n<\/strong> Developed for the automotive sector, this standard addresses the limits of meaningful usability of algorithms and sensor systems and considers the new error class of functional deficiencies.
\nhttps:\/\/www.iso.org\/standard\/70939.html<\/a>
\n<\/strong><\/li>\n
\nThis standard defines basic terminology for Big Data. However, the terms Artificial Intelligence or Machine Learning are not mentioned in this document.
\nhttps:\/\/www.iso.org\/standard\/68305.html<\/a><\/em><\/em><\/em><\/em><\/li>\n
\nThe 20547 series is intended to establish a reference architecture for Big Data. In this second part, use cases are listed.
\nhttps:\/\/www.iso.org\/standard\/71276.html<\/a><\/li>\n
\nThe fifth part of the 20547 series provides an overview of standards that are relevant for Big Data, both existing standards and standards currently in development.
\nhttps:\/\/www.iso.org\/standard\/72826.html<\/a><\/li>\n<\/ul>\nWhitepapers, reports, and similar documents<\/h3>\n
\n
\nThese guidelines set out a framework for achieving trustworthy AI. Three elementary components are identified here: The AI should be lawful, ethical, and robust. Under the aspect of robustness, safety is mentioned explicitly. The document contains an assessment list for trustworthy AI.
\nhttps:\/\/ec.europa.eu\/digital-single-market\/en\/high-level-expert-group-artificial-intelligence<\/a><\/li>\n
\nThe Data Ethics Commission was commissioned by the German Federal Government with the development of ethical standards, guidelines, and concrete recommendations for action aimed at protecting the individual, preserving social coexistence, and safeguarding and promoting prosperity in the information age. This document summarizes the results. [only available in German]
\nhttp:\/\/s.fhg.de\/mcz<\/a><\/li>\n
\nIn this document, the IEEE summarizes its recommendations aimed at designing the development of standards, certification, regulation, and legislation for the development of autonomous and intelligent systems in such a way that this benefits societal well-being holistically.
\nhttps:\/\/ethicsinaction.ieee.org\/<\/a><\/li>\n
\nHaving emerged from a working group of the Safety-Critical System Club, this document lists objectives for the validation of autonomous systems at different levels of abstraction.
\nhttps:\/\/scsc.uk\/ga<\/a><\/li>\n
\nIn this cross-industry whitepaper, Daimler together with Aptiv, Audi, Baidu, BMW, Continental, Fiat Chrysler Automobiles, HERE, Infineon, Intel, and Volkswagen examines the topic of safety for automated driving in accordance with SAE Level 3 and Level 4. It also addresses the use of AI methods (Machine Learning) required for automated driving.
\nhttps:\/\/newsroom.intel.com\/wp-content\/uploads\/sites\/11\/2019\/07\/Intel-Safety-First-for-Automated-Driving.pdf<\/a><\/li>\n
\nWe have included this publication because it offers a good overview of technical, ethical, and legal safety-related issues and their interfaces.
\nhttps:\/\/www.sciencedirect.com\/science\/article\/abs\/pii\/S0004370219301109?dgcid=rss_sd_all<\/a><\/li>\n
\nWe have included this technical report from NASA because it summarizes what needs to be considered when technical systems take over safety-critical tasks that had previously been solved by humans with their \u201cintelligence\u201d.
\nhttps:\/\/ntrs.nasa.gov\/archive\/nasa\/casi.ntrs.nasa.gov\/20180006312.pdf<\/a><\/li>\n<\/ul>\nOngoing Initiatives in Research and Standardization<\/h3>\n
Standardization Initiatives<\/h4>\n
\n
\nDIN and DKE are collaborating with the German Federal Government and representatives from industry, research, and civil society to draw up a standardization roadmap on Artificial Intelligence. This also includes standardization with regard to safety.
\nhttps:\/\/din.one\/pages\/viewpage.action?pageId=33620030<\/a><\/li>\n
\nThe Standardization Council<\/a> has the task to coordinate standardization and regulation work in the field of Industrie4.0 in Germany and beyond. It represents the interests of industry in the field of national, European and international standardization in the context of the digitization of industry and actively promotes international cooperation. Fraunhofer IESE and SICK are in the working group „safe trustworthy AI-systems“. Fraunhofer IESE is additionally in the working groups „Human and AI“ as well as „Data modelling and semantics“.<\/li>\n
\nWorking group 1 of the SC42 is concerned with the fundamentals of AI standardization, such as terminology, concepts, and frameworks.
\nhttps:\/\/www.iso.org\/committee\/6794475.html<\/a><\/li>\n
\nWorking group 2 of the SC42 emerged from a formerly independent SC on the topic of \u201cBig Data\u201d. Here, topics concerning data and data quality continue to be worked on.
\nhttps:\/\/www.iso.org\/committee\/6794475.html<\/a><\/li>\n
\nThe focal topic of working group 3 of the SC42 is trustworthiness. Here, standards on risk management, on robustness of neural networks, as well as on ethical and social topics related to AI are being prepared.
\nhttps:\/\/www.iso.org\/committee\/6794475.html<\/a><\/li>\n
\nArbeitsgruppe 4 des SC42 sammelt Use Cases rund um KI.
\nhttps:\/\/www.iso.org\/committee\/6794475.html<\/a><\/li>\n
\n<\/strong>Working group 5 of the SC42 is the youngest group on the panel and has the mandate to deal with computational aspects and characteristics of AI.
\nhttps:\/\/www.iso.org\/committee\/6794475.html<\/a><\/li>\n
\nIn this working group of DKE, in which both Fraunhofer IESE and SICK are active, an application rule for the development of autonomous\/cognitive systems is currently being drawn up. The focus in this application rule is on the execution of a trustworthiness analysis and the establishment of a trustworthiness assurance case. It is planned to publish a first version of this application rule in 2020.
\nhttps:\/\/www.dke.de\/de\/news\/2019\/referenzmodell-vertrauenswuerdige-ki-vde-anwendungsregel<\/a><\/li>\n
\nIn the shortened procedure of an SPEC, DIN is currently making efforts to publish additional standards on the topic of AI. An
\noverview<\/a> includes those SPECs, where free downloadable drafts exists like DIN SPEC 13266<\/a> „Guideline for the development of deep learning image recognition systems“ [in German] and DIN SPEC 92001-1<\/a> „Artificial Intelligence – Life Cycle Processes and Quality Requirements – Part 1: Quality Meta Model“.<\/li>\n
\n<\/strong>This WG<\/a> is working on „A Formal Model for Safety Considerations in Automated Vehicle Decision Making“. <\/b>The purpose of this standard is to define a parameterized formal model for automated vehicle decision making that enables industry and government alike to align on a common definition of what it means for an automated vehicle to drive safely balancing safety and practicability.<\/li>\n
\n<\/strong>The FG-AI4AD<\/a> supports standardization activities for services and applications enabled by AI systems in autonomous and assisted driving. The FG aims to create international harmonization on the definition of a minimal performance threshold for these AI systems (such as AI as a Driver).<\/li>\n<\/ul>\nFurther Initiatives<\/h4>\n
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\nThis initiative led by the University of York is explicitly concerned with the assurance and regulation of robotics and autonomous systems. Currently, a freely accessible Body of Knowledge is being built up here, which is to become the reference source on this topic in the future. The \u201cAssuring Autonomy\u201d program is thematically very close to the Autonomous Systems<\/a> program of Fraunhofer IESE. In order to create synergies, a strategic collaboration is currently being prepared.
\nhttps:\/\/www.york.ac.uk\/assuring-autonomy\/<\/a><\/li>\n
\n<\/strong>Fraunhofer IESE is member of the working group Autonomous Systems of the Safety-Critical Systems Club. The group aims to produce clear guidance on how autonomous systems and autonomy technologies should be managed in a safety related context, in a way that reflects emerging best practice.
\nhttps:\/\/scsc.uk\/ga<\/a><\/li>\n
\nAn initiative led from the USA that identifies the use of safety-critical applications as the first of its thematic pillars. The partners comprise more than 90 organizations, including Amazon, Apple, Facebook, Google, and Microsoft. Companies from traditional safety-critical domains are not represented to date.
\nhttps:\/\/www.partnershiponai.org\/<\/a><\/li>\n
\n<\/strong>The Autonomous<\/a> is an open platform that brings together the autonomous mobility ecosystem to align on relevant safety subjects. Besides an annual event in Vienna, the Autonomous is hosting Chapter Events and Workshops throughout the year to work on global reference solutions on Safety from Architecture, Security, AI, and Regulation standpoint.<\/li>\n<\/ul>\n