Draft:Artificial Intelligence, Data, and Analytics User Group

Submission declined on 27 September 2023 by Qcne (talk).

This draft's references do not show that the subject qualifies for a Wikipedia article. In summary, the draft needs multiple published sources that are:

in-depth (not just brief mentions about the subject or routine announcements)
reliable
secondary
strictly independent of the subject

Make sure you add references that meet all four of these criteria before resubmitting. Learn about mistakes to avoid when addressing this issue. If no additional references exist, the subject is not suitable for Wikipedia.

If you would like to continue working on the submission, click on the "Edit" tab at the top of the window.
If you have not resolved the issues listed above, your draft will be declined again and potentially deleted.
If you need extra help, please ask us a question at the AfC Help Desk or get live help from experienced editors.
Please do not remove reviewer comments or this notice until the submission is accepted.

Where to get help

If you need help editing or submitting your draft, please ask us a question at the AfC Help Desk or get live help from experienced editors. These venues are only for help with editing and the submission process, not to get reviews.
If you need feedback on your draft, or if the review is taking a lot of time, you can try asking for help on the talk page of a relevant WikiProject. Some WikiProjects are more active than others so a speedy reply is not guaranteed.

How to improve a draft

Wikipedia:Contributing to Wikipedia – a basic overview on how to edit Wikipedia.
Help:Wikitext – how to use the markup
Help:Referencing for beginners – how to include references
Wikipedia:Article development – how to develop your article
Wikipedia:Writing better articles – how to improve your article
Wikipedia:Verifiability – make sure your article includes reliable third-party sources

You can also browse Wikipedia:Featured articles and Wikipedia:Good articles to find examples of Wikipedia's best writing on topics similar to your proposed article.

Improving your odds of a speedy review

To improve your odds of a faster review, tag your draft with relevant WikiProject tags using the button below. This will let reviewers know a new draft has been submitted in their area of interest. For instance, if you wrote about a female astronomer, you would want to add the Biography, Astronomy, and Women scientists tags.

Add tags to your draft

Editor resources

Easy tools: Citation bot (help) | Advanced: Fix bare URLs

Declined by Qcne 13 months ago. Last edited by UtherSRG 5 months ago. Reviewer: Inform author.

Resubmit

Please note that if the issues are not fixed, the draft will be declined again.

Comment: Does not yet pass WP:NORG as all your sources are primary (other than source #2, which seems irrelevant?).
Please also remove the external links from the body of the text, see WP:EXTERNAL. Qcne (talk) 18:39, 27 September 2023 (UTC)

Artificial Intelligence, Data, and Analytics User Group (AIDAUG)^[1] is a not-for-profit association that aims to educate and engage its members, and to develop thought leadership and best practices around the fields of Artificial Intelligence (AI) and Data Analytics..

History

AIDAUG was founded in 2021 by a group of data analytics experts and associates from within the IBM Champions community.

Background

Major advances in Artificial Intelligence technology such as ChatGPT, Bard and Watsonx, have generated consumer-driven demand for the practical application of a rapidly evolving set of technologies, as well as implementation guidance^[2]. The groundswell of interest served to catalyze discussions around preparing for the inevitable mainstream adoption of AI from related intersecting domains, including data governance, cloud platform engineering, and even ethics.

AIDAUG was created in response to this market-driven momentum, in part to link practitioners and perspectives from these correlated technology practice areas, with the general objective of guiding the multidisciplinary development of standards, guidelines and best practices around AI and data analytics.

While the group itself is a self-managed association not directly affiliated with or funded by IBM, several of the original founding members of AIDAUG had deep expertise with IBM Cognos Analytics and related technologies, and structured the association in conformance with the unofficial IBM template for user group governance.

Notable Projects

AIDAUG oversees the development of the Open Data Contract Standard (ODCS). The ODCS proposes a mechanism to encode data governance rules and other facets of an operational exchange between data producers and consumers^[3].

Mission and Purpose

As stated on the group's website and other literature, their mission is to "share knowledge, connect people, and provide guidance through this next era of computing while embracing peace and the highest levels of ethics"^[4]

AIDAUG enumerates its purpose as follows:

To promote education and exchange of information concerning data, analytics, and artificial intelligence within the meaning of Section 501(c)(6) of the Internal Revenue Code of 1986, as amended.
To establish channels for the education and communication of information to and from members in the field of artificial intelligence, data, and analytics.
To conduct conferences, meetings, discussion groups, forums, panels, lectures, and other programs concerned with developing and exchanging information among members.
To encourage and strengthen the participation of all qualified members.
To promote the acceptance of artificial intelligence and other best data practices.
To encourage the development of products embedding and using artificial intelligence, data, and analytics.
To provide a forum for the promotion of excellence in information processing by recognizing those individuals who, judged by their peers, put forth the highest effort and ethical standards and succeed in best-utilizing data, analytics, and artificial intelligence within their organizations.
To provide a safe and unbiased way of discussing the ethical ramifications of the use of artificial intelligence, data, and analytics across a broad range of industries and humanity.

External Links

References

^ https://aidausergroup.org/
^ "25 Artificial Intelligence Statistics [2023]: Key Facts About AI And The AI Industry". Zippia. 2022-11-09. Retrieved 2023-09-29.
^ "Open Data Contract Standard". GitHub.
^ "About AIDA User Group". AIDAUG Website (Mission).

[1] ttps://aidausergroup.org/

[2] "25 Artificial Intelligence Statistics [2023]: Key Facts About AI And The AI Industry". Zippia. 2022-11-09. Retrieved 2023-09-29.

[3] "Open Data Contract Standard". GitHub.

[4] "About AIDA User Group". AIDAUG Website (Mission).

[1]

[2]

[3]

[4]