This wiki complements the AI PTF marketing page on the main OMG website. It is intended as a place to keep the community (OMG members and non-members alike) informed of the activities derived from OMG's 2019 initiative on Artificial Intelligence, and consolidated into a new Platform Task Force chartered in September of that year. It is focused on how we operate as a Task Force.
The vision behind the AI PTF is to create and “animate” an OMG-based AI center, coordinating and complementing AI-related efforts in other groups (such as Ontology, Retail, Healthcare. and more) and especially considering aspects that can benefit from standardization – making OMG the place to come for AI technology standardization.
|Charter (adopted on 27 Sep 2019, revised on 13 Dec 2019)|
| OMG’s Artificial Intelligence Platform Task Force (AIPTF) will promote the adoption of specifications that standardize foundational capabilities of artificial intelligence.
Among the goals of the AIPTF is freeing AI technology suppliers as well as end users from interoperability and interchange limitations with respect to models, languages and data, and to enable them to focus instead on development of advanced AI applications.
In the context of this charter, Artificial Intelligence is defined broadly and includes, but is not limited to:
* Modeling of AI artifacts
* Machine learning, deep learning and neural networks
* Image understanding, speech recognition, and computer vision
* Robotic systems
* Virtual and augmented reality
* Autonomous and autonomic systems and agents
* Knowledge representations
* Natural language processing (NLP)
* Security, privacy, social and other ethical aspects of AI
The purpose of the AIPTF includes development of foundational specifications that support AI in the above broad sense.
The AIPTF may, when appropriate, generate discussion papers, RFIs or RFPs or recommend technologies for adoption. It will also collaborate with other OMG subgroups to identify and document use cases and interoperability requirements for AI, and identify the need for AI-related additions or revisions to those groups’ existing and emerging specifications. It will seek to identify external stakeholders, including other standards development organizations, and partner with them as needed.
The history of OMG's efforts related to AI can be summarized as follows:
The co-chairs are collectively reachable at the address firstname.lastname@example.org.
The purpose of this section is to keep track of organizations that have contacted us, or participated in meetings. This is obviously a list under construction. If needed, we'll make it into a separate page later. We're not showing people's e-mail addresses to avoid getting them spammed. If you wish to contact someone on this list, email the co-chairs.
We welcome great ideas, emerging AI technology, and new AI standards, bring your digital twin and join us!
An “AI metamodel” (this term has been critiqued, since it seems to be more of a taxonomy than a metamodel) of the range of technologies that are “in scope” for the AI PTF has been proposed and is shown below (click on the figure to enlarge it).
Links below appear in three different colors automatically generated by Dokuwiki. They are:
March 2020 AI PTF virtual meeting notes (to be published)
September 17, 2020 AI PTF regular quarterly meeting (See agenda). AI PTF members are also encouraged to attend the special event Understanding Ontologies and Knowledge Graphs scheduled for on September 15, 2020 (separate registration required).
Future meeting agenda ideas:
Unite.AI maintains a list of conferences and exhibits of potential interest to members. The scope of their calendar entries extends to robotics and data science
Note that any indications of a physical location in the coming months is highly subject to change until the COVID-19 pandemic is under control. Moreover, when an on-site conference is changed to a virtual one, the dates may also change.
Those who attend any external AI-related event are strongly encouraged to share their notes through our mailing list of for posting on this wiki.
Bibliography of links and papers shared by members; please send new entries to email@example.com.
Association for Computing Machinery (ACM): AI-powered Chatbots: recording and slides from a January 23, 2020 meetup in San Francisco.
The MP4 file at the top is the audiovisual recording of most of the event (86 minutes – and some questions at the end are cut off). The other files are the slides presented during the event.
Baudoin, Claude (cébé IT & Knowledge Management), Pete Rivett (Adaptive), Bobbin Teegarden (OntoAge) et al.: Analysis of Responses to NIST's AI Standards RFI.
Work in progress. Contains references, with hyperlinks, to the 98 responses received by NIST. We are seeking volunteers to provide short summaries of the responses, and an estimate of their usefulness to OMG's AI work. To obtain the right to edit this document, contact Claude Baudoin.
Baudoin, Claude (cébé IT & Knowledge Management): AI Meet & Greet Presentation. OMG document ai/19-12-02. Presented at OMG meeting in Long Beach, Calif., on December 9, 2019.
BDI (Bundesverband der Deutschen industrie): BDI Statement on EU White Paper on AI. English version via Dr. Karl Gosejacob. OMG document ai/20-06-03, June 2020.
Beechinor, Allan F. (Altada Group): Predictive Analytics in Healthcare. OMG document ai/19-06-03. Presented at the AI Platform SIG meeting in Amsterdam in June 2019.
Chen, Frank: AI, Deep Learning, and Machine Learning: A Primer. June 2016.
From types of machine intelligence to a tour of algorithms, Frank Chen, head of the Deal and Research team at Andreessen Horowitz (aka “a16z”) walks us through the basics (and beyond) of AI and deep learning in this narrated slide presentation. Watch time: 45 minutes.
Data Science Central: The State of AI Bias in 2019.
DataRobot surveyed more than 350 US- and UK-based CIOs, CTOs, VPs, and IT managers involved in AI and machine learning purchasing decisions to learn how AI is being used by businesses today, current perceptions of AI bias, and what is being done -– or should be done -– to enhance AI bias prevention efforts in the future.
Enterprise Knowledge Graph Foundation (EKGF): EKGF Launch Webinar. 23 June 2020, 55 minutes.
European Commission Independent High-Level Expert Group on Artificial Intelligence: Ethics Guidelines for Trustworthy AI. April 2019, 41 pages. Overview and versions in other EU languages available here.
Finin, Prof. Tim: Semantic Knowledge Graphs for Cybersecurity. OMG document ai/20-06-06, June 2020.
Gosejacob, Dr. Karl: Some Thoughts on Sampling with AI. OMG document ai/20-06-04, June 2020.
Hailey, Victoria: AI Ethics Standards Landscape. OMG document ai/20-06-07, June 2020.
Hall, Curt: Organizations Eye Smartbots and Intelligent Assistants for CX Initiatives. Cutter Consortium Advisor, January 2020.
IEEE Computer Society: Computing Edge, February 2020. Contains the following AI-related articles:
Johnston, Alan T.: ISO 18101 Interoperability with Digital Twins and AI. OMG document ai/20-06-01, June 2020.
Johnston, Alan T.: ISO TC 184/WG 6/N 8, Ontologies Position Paper. OMG document ai/20-06-02, June 2020.
Johnston, Alan T.: ISO TC 184 Ad Hoc Group on Data Architecture of the Digital Twin. OMG document ai/20-06-03, June 2020.
National Institute of Standards and Technology (NIST): U.S. Leadership in AI:A Plan for Federal Engagement in Developing Technical Standards and Related Tools. August 2019, 48 pages.
OMG: OMG AI Standards Strategy. OMG document omgi/19-09-03. Adopted by the OMG Board of Directors in September 2019.
OMG: OMG Response to NIST RFI on AI Standards. June 2019.
Perey, Christine (AREA): Augmented Reality Interoperability Requirements Workshop. OMG document ai/19-09-04, September 2019.
Poole, David L. and Alan K. Mackworth: Artificial Intelligence:Foundations of Computational Agents, 2nd Edition. Free e-book.
Shavit, Nir: Big Brain Burnout: What’s Wrong with AI Computing?. Neural Magic webinar, September 2020.
TopQuadrant: Knowledge Graphs vs. Property Graphs - Similarities, Differences and Some Guidance on Capabilities. 2020, 24 pages.
Vogel, Andreas (SAP): Reference Model for AI Ethics. OMG document ai/19-06-05, June 2019.
Zicari, Roberto (University of Frankfurt): Z-inspection - toward a Process to assess Ethical AI. September 2019.
Zicari, Roberto (University of Frankfurt): On AI for Insurance and Risk Management: An Interview with Sastry Durvasula. ODBMS Industry Watch, February 2020.