Artificial Intelligence

Dear Colleagues,

If it would be of interest to anyone dealing with AI, especially applied to smart energy, I am looking for a collaboration working on standards in applying AI to smart energy and particularly to smart PV systems.

If this theme coincides with your interests or professional activities (and especially if you are engaged in related themes of smart energy and smart grids standardisation in any capacity of engagement in SDOs/SSOs activities), please feel invited to join the EITCI hosted Smart Energy Standards Group at https://eitci.org/sesg (possibly also in an observer capacity). For ease of communication there is also a dedicated LinkedIn group at https://www.linkedin.com/groups/12498639/

The EITCI SESG group supports international SDOs in development of standards for AI assisted PV, as well as in smart energy in general. It brings together acedemics and practitioners in smart grids, PV & AI to jointly work on technical standards in overlap of these domains. The initiative aims at supporting the EU clean energy transition policies with smart energy standards development for digitization and artificial intelligence applications.

I'm looking forward to working together in the future.

Best regards,
Agnieszka

MPAI has published a book entitled: “Towards Pervasive and Trustworthy Artificial Intelligence: How standards can put a great technology at the service of humankind”.

With the printing industry sparing no efforts publishing books on Artificial Intelligence (AI), why should there be another that, in its title and subtitle, combines the overused words “AI” and “trustworthy”, with the alien words “standards” and “pervasive”?

The answer is that the book describes a solution that covers all the elements of the title: to effectively combine the AI and trustworthy words, but also to make AI pervasive. How? By developing standards for AI-based data coding.

Many industries need standards to run their business and used to have high respect for them. Users benefit from standards: MP3 put users in control of the content they wanted to enjoy, and the television – and now the video – experiences have little to do with how users used to approach audio-visual content 30 years ago.

At that time, the media industry was loath to invest in open standards. The successful MPEG standards development model, however, changed its attitude. Similarly, the AI industry has been slow in developing AI-based data coding standards making proprietary solutions their preferred route.

MPAI has shown that can take different types of data, encode them using AI and develop standards that make the technology and the benefits it brings with it pervasive. At the same time, MPAI standards can take a technology that may well be untrusted and make it trustworthy.

The MPAI book describes how MPAI develops standards that can also be used, how standards can make AI pervasive, and how MPAI gives users the means to make informed decisions about how to choose an implementation having the required level of trustworthiness.

This is the time to join the MPAI unique adventure. MPAI is open to those who want to make its vision real.

More info on MPAI at: https://mpai.community/

MPAI book available at: https://www.amazon.com/dp/B09NS4T6WN/

As (algorithmic) operations are becoming more complex, we realize that less and less we can continue relying on the methods of the past where Privacy Policy or ToC served (did they?) in building trust in the business. Moreover, it rarely helped any user to understand what’s going on with their data under the hood. “I agree, I understand, I accept.” — the big lies we told ourselves when clicking on the website’s cookie notice or when ticking the checkbox of one another digital platform. In the age of artificial intelligence, the privacy and cybersecurity risks remained, but now we’re observing the expansion of the risk profiles for every service to include bias and discriminatory issues. What should we do? A typical answer is a top-down regulation brought by national and cross-national entities. Countries and trade unions are now competing for AI ethics guidelines and standards. Good. What if you’re building an international business? As a business, you have to comply. Tons of digital paperwork (thanks, now it’s digital!) — and you could get settled in one single economic space. Once you’re there, there’s a chance you can move to another one by repeating the costly bureaucratic procedure. Unfortunately, this is not scalable. We call it the “cost of compliance”, and these costs are high. There is a possible way of avoiding the compliance scalability issue: disclosing the modus operandi once and matching it with existing requirements on each market. To make it possible we need a universally-accepted concept of product disclosure.

The complete article on Medium is available to learn more about disclosure and the transparency protocol to be used in conjunction with it.

https://lukianets.medium.com/why-algorithmic-transparency-needs-a-protocol-2b6d5098572f

Use of technologies based on Artificial Intelligence (AI) is extending to more and more applic­ations yielding one of the fastest-grow­ing markets in the data analysis and service sector.

However, industry must overcome hurdles for stakeholders to fully exploit this historical oppor­tunity: the current framework-based development model that makes applic­ation redep­loyment difficult, and monolithic and opaque AI applications that generate mistrust in users.

MPAI – Moving Picture, Audio and Data Coding by Artificial Intelligence – believes that univer­sally accessible standards can have the same positive effects on AI as digital media stan­dards and has identified data coding as the area where standards can foster development of AI tech­nologies, promote use of AI applications and contribute to the solution of existing problems.

MPAI defines data coding as the transformation of data from a given representation to an equiv­alent one more suited to a specific application. Examples are compression and semantics extraction.

MPAI considers AI module (AIM) and its interfaces as the AI building block. The syntax and semantics of interfaces determine what AIMs should per­form, not how. AIMs can be implemented in hardware or software, with AI or Machine Learning legacy Data Processing.

MPAI’s AI framework enabling creation, execution, com­pos­ition and update of AIM-based work­flows (MPAI-AIF) is the cornerstone of MPAI standardisation because it enables building high-com­plexity AI solutions by interconnecting multi-vendor AIMs trained to specific tasks, operating in the standard AI framework and exchanging data in standard formats.

MPAI standards will address many of the problems mentioned above and benefit various actors:

• Technology providers will be able to offer their conforming AIMs to an open market
• Application developers will find on the open market the AIMs their applications need
• Innovation will be fuelled by the demand for novel and more performing AIMs
• Consumers will be offered a wider choice of better AI applications by a competitive market
• Society will be able to lift the veil of opacity from large, monolithic AI-based applications.

Focusing on AI-based data coding will also allow MPAI to take advantage of the results of emer­ging and future research in representation learning, transfer learning, edge AI, and reproducibility of perfor­mance.

MPAI is mindful of IPR-related problems which have accompanied high-tech standardisation. Unlike standards developed by other bodies, which are based on vague and contention-prone Fair, Reasonable and Non-Discriminatory (FRAND) declarations, MPAI standards are based on Frame­work Licences where IPR holders set out in advance IPR guidelines.

Finally, although it is a technical body, MPAI is aware of the revolutionary impact AI will have on the future of human society. MPAI pledges to address ethical questions raised by its technical work with the involvement of high-profile external thinkers. The initial significant step is to enable the understanding of the inner working of complex AI systems.

MORE INFO at https://mpai.community/

The Open Ethics Transparency Protocol (OETP) describes the creation and exchange of voluntary ethics Disclosures for IT products. It is brought as a solution to increase the transparency of how IT products are built and deployed. The scope of the Protocol covers Disclosures for systems such as Software as a Service (SaaS) Applications, Software Applications, Software Components, Application Programming Interfaces (API), Automated Decision-Making (ADM) systems, and systems using Artificial Intelligence (AI). The IETF I-D document provides details on how disclosures for data collection and data processing practice are formed, stored, validated, and exchanged in a standardized and open format.

OETP provides facilities for:

• Informed consumer choices : End-users able to make informed choices based on their own ethical preferences and product disclosure.
• Industrial-scale monitoring : Discovery of best and worst practices within market verticals, technology stacks, and product value offerings.
• Legally-agnostic guidelines : Suggestions for developers and product-owners, formulated in factual language, which are legally-agnostic and could be easily transformed into product requirements and safeguards.
• Iterative improvement : Digital products, specifically, the ones powered by artificial intelligence could receive nearly real-time feedback on how their performance and ethical posture could be improved to cover security, privacy, diversity, fairness, power balance, non-discrimination, and other requirements.
• Labeling and certification : Mapping to existing and future regulatory initiatives and standards.

Please feel free to join the discussion here and in the GitHub repository
 

IETF datatracker link: https://datatracker.ietf.org/doc/draft-lukianets-open-ethics-transparency-protocol/

IEEE 7007 WG created a unique standard that will contribute to the development of new technologies ethically aligned to human values. The IEEE 7007 Standard has an ontological representation which facilitates the investigation of the domain; and a formal language that adds precision to the knowledge and data collected during this investigation. The nature of the ontologies allows this ontological representation to be used in a wide variety of applications across all AIS domain.

The IEEE 7007 WG elaborated a formal representation, using formal Logics, for the following domains: Norms and Ethical Principles, Data Privacy and Protection, Transparency and Accountability, and Ethical Violation Management. In addition, during the elaboration of 7007 Standard, IEEE 7007 WG developed its own methodology to deal with the complexity of the Ethics of AI domain. It is based on agile methodology and can be used in heterogenous and spatially distributed groups like the IEEE 7007 WG.

The link to the standard: https://standards.ieee.org/standard/7007-2021.html

The EU-funded, StandICT.Eu 2023  Project, ICT Standardisation Observatory and Support Facility in Europe,  has just published the first of a series of Landscape Reports on ICT standards, Landscape Of AI Standards[1] a palpable, go-to reference, providing an overview of the diverse array of global standardisation work underway in Artificial Intelligence and the various organisations behind it. This information will be continuously updated and evolve via the “EUOS – Observatory For ICT Standardisation” a database powered by StandICT.eu 2023 to cover the wide-range of topics identified in the Rolling Plan For ICT Standardisation, and will ultimately result in the release of a dedicated Gaps Analysis Report for each theme.

Landscape of Artificial Intelligence Standards is the fruit of the dedicated Technical Working Group (TWG AI) set-up to harness expert advice and stimulate discussion among SDOs, public bodies, academic institutions and acclaimed specialists to provide an expert overview of documents and activities relevant to standardisation in this field. Ultimately, the TWG AI will pinpoint gaps where additional activity and investment can strengthen Europe’s position and also help create

“a structured dialogue between the EC, Member States and standardisation organisations to stay at the forefront of artificial intelligence through the twin objectives of Europe in adopting a European approach to excellence in AI and a European approach to trust in AI”,as Kilian Gross, the EC’s Head of Unit in Artificial Intelligence at DG Connect, states in his foreword of the Report.

The Report provides an encompassing compilation of standardisation efforts underway in the framework of European SDOs, such as CEN and ETSI, Government, Public Bodies and Agencies, such as the European Commission, the European Data Portal, European Parliament and the HLEG-AI and JRC, Global SDOs and initiatives, such as IEC, IEEE, ISO/IEC, ITU-T, WEF, W3C, as well as non-EU, country-specific contributions including China, Germany, Japan, UK and USA and relevant contributions from other organisations (BDVA, G20, Khronos, OECD, SAE International).

Since its start, StandICT.eu 2023 has launched 6 other such Technical Working Groups in Blockchain (TWG BLOCK), Big Data Spaces and Data Interoperability (TWG BDDI), Cybersecurity (TWG Cyber), Smart Cities (TWG CITIES), Trusted Information (TWG TRUSTI) and Standards Education (TWG ACADEMY) where further Landscape and Gap Analysis Reports will be published as part of the series.

In parallel, StandICT.eu 2023 is providing 3M EURO to fund European ICT experts through a series of (10) Open Calls to participate in international Standardisation Developing Organisations' working groups across the wide-range of topics identified in the EC Rolling Plan for ICT Standardisation..

From the Authors:

“This overview provides an easy “look up” regarding what AI standardisation is happening in various organisations and brief information on the organisations themselves. There is no attempt to say here which documents are more fit-for-purpose than others: that will be considered in the next step, in a Gaps Analysis Report. This document is just one possible output from a multi-dimensional database; we look forward to extending, filtering, discussing, mindmapping and collaborating to benefit standards experts and users globally.”  Lindsay Frost, Chief Standardisation Engineer, NEC, Editor, TWG AI Chair

“The ICT Standardization landscape is an every changing, living and dynamic ecosystem of ecosystems where new technologies, tools, techniques, components, products and services are being innovated and disrupted on a constant basis. To remain current, regular standardization landscape research exercises like this AI Landscape Report are crucial to capture the latest state-of-the-art.” Ray Walshe, StandICT.eu 2023 EAG Chair & EUOS Director, Series Editor 

“Having such a thorough and detailed reference document that provides this bird’s eye view on all AI standardisation will allow us to provide our Standardisation Developing Organisations SDOs and Funding Agencies with the mechanisms to help intertwine efforts collectively which is the purpose of the StandICT.eu ecosystem “      Silvana Muscella, CEO Trust-It and StandICT.eu 2023 Project Coordinator, Series Editor

Edge AI is rapidly gaining momentum with growing investments and awareness of its benefits, such as reducing costs and latency times for improved user experience and increased levels of security in terms of data privacy through local processing. 

Yet its full potential has yet to be realised. One way to achieve this is by combining various execution platforms for ubiquitous and seamless execution computing environments for a complete cloud continuum. As a result, application developers will have greater control over computing, network and data infrastructures and services and end-users will benefit from seamless access to continuous service environments. 

AI-SPRINT is a newly funded initiative under Europe’s Horizon 2020 programme aiming to drive innovations in AI and edge computing.

On the 30.03.2021 at 10:00 CEST the initiative is organising the first in a series of AI-SPRINT webinars, AI-SPRINT: An EU Perspective on the Future of AI and Edge Computing,  analysing challenges and needs from an AI and Edge computing perspective and giving practical solutions that we’re developing in the context of the AI-SPRINT as we embark on our R&I journey.

Lightning talks from key partners will give examples of new AI applications in edge and cloud environments, top challenges that need addresses and real-world scenarios aimed at proving competitive edge and replicability. 

The panel discussion brings together members of the AI-SPRINT Alliance and project experts for a deep-dive into the challenges, needs and future trends of AI and edge computing from various viewpoints. Participants will also get a chance to learn about the Alliance designed for small SW houses and EU cloud providers to support the AI and edge computing ecosystem while the interactive polls will capture viewpoints from the audience. 

Full programme, speakers and registration are available at the following link: https://ai-sprint-project.eu/events/ai-sprint-eu-perspective-future-ai-and-edge-computing

We do look forward to meeting you online on the 30.03.2021 at 10:00 CEST