Artificial Intelligence

Check out this position paper on the needs, benefits and risks of NLP standardization: Is NLP Ready for Standardization?

Part of this work has been conducted through a StandICT Fellowship.

Teaser: Both CEN-CENELEC and ISO-IEC are currently taking new steps towards NLP standardization, with more groups and more projects about to start. More news to come in the upcoming weeks!

This DIN SPEC is currently under development with an expected publication date in September 2023.

For further information see Business plans (din.de) or feel free to reach out to me.

What would be the requirements of an AI algorithm service to be made available to the public?

Answer (anonymously) these 3 questions here https://algorithmclassification.org/

1.- What would you make you trust an algorithm applied to your data?

2.- What is your major concern about an algorithm applied to your data?

3.- What would be a possible solution to trust AI algorithms?

Thanks

---

My project has the goal to provide an important basis for further work on standards that incorporate in particular ethical considerations. The focus of the project lies on one particular application of AI, namely automated vehicles (AVs). As the acceptance and use of AVs is contingent upon the trust people build in this technology, it is of utmost importance that technology is developed that is human-centred and trustworthy. At the same time this should also be reflected in the development of the standards on AVs.

ISO/IEC CD 5392 Information technology — Artificial intelligence — Reference architecture of knowledge engineering

Under development

https://www.iso.org/standard/81228.html

AI (and more specifically ML) can produce hard-to-explain/understand outputs (e.g., non-linear prediction functions), thus increasing the "black-box" perception that humans have about these systems. To address that, there is an ongoing discussion on the integration of simulators and digital twins to assist the operation of AI systems. The usage of simulators is expected to improve the trustworthiness and reliability of AI. However, there are still a lot of questions to be addressed and a lot of standardization work to be done. 

Dear colleagues,

The IEEE standard on the Fuzzy Markup Language, is under revision. 

Several extensions are under development to include other systems, e.g., type-2 , learning.

Abstract of the previous standard:

Dear colleagues,

The IEEE SA, has an ongoing work onfor XAI – eXplainable Artificial Intelligence

Abstract of the work:

"This standard defines mandatory and optional requirements and constraints that need to be satisfied for an AI method, algorithm, application or system to be recognized as explainable. Both partially explainable and fully or strongly explainable methods, algorithms and systems are defined. XML Schema are also defined."

Please consider to join the effort: https://sagroups.ieee.org/2976/