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This is an old revision of this page, as edited by Lavarball13 (talk | contribs) at 03:29, 18 October 2022 (→Peer Review: new section). The present address (URL) is a permanent link to this revision, which may differ significantly from the current revision.

Template:Vital article

Narrow != Weak

Narrow AI may well be what is defined in the article, but the weak/strong AI distinction is VERY different. See https://en.wikipedia.org/wiki/Chinese_room#Strong_AI

ALso Ray Kurzeuil and all the sigularity thing is interesting and entertaining, but is NOT reality, but speculation.

With respect, I call for a return to the version before 149.254.58.203's edits.

DISCUSS.

Samfreed (talk) 14:51, 23 October 2014 (UTC)[reply]


Altho speculative now, the future is a real thing and it's coming here soon. I suggest that where the first sentence says: real-world, 

All real-world systems labeled "artificial intelligence" of any sort are weak AI at most.   
It could say: present day world.  173.225.148.173 (talk) 17:30, 29 December 2015 (UTC)[reply]
I was about to say something similar. Siri is NOT weak AI, it is at best an extremely narrow and brittle attempt on AI. Jeblad (talk) 11:51, 24 November 2019 (UTC)[reply]

I've just made lots of edits to improve the article.

Here are some links I didn't use:


— Preceding unsigned comment added by 149.254.181.50 (talk) 21:42, 17 February 2014 (UTC)[reply]

— Preceding unsigned comment added by 149.254.58.203 (talk) 17:19, 16 February 2014 (UTC)[reply]

Possible confusion with weak methods in AI

The article should mention that this has nothing to do with the concept of using 'weak methods' in AI. This was made popular Newell in the the late 1960s (Newell, A. Heuristic programming: Ill-structured problems. In Aronofsky, J. (Ed.), Progress in Operations Research, III. New York: Wiley, 1969). See also:

weak methods

1. problem-solving techniques based on general principles rather than specific, domain-relevant knowledge. Such methods can be applied to a wide variety of problems but may be inefficient in many cases.

2. in artificial intelligence, programs based on general principles that do not take into account knowledge specific to any particular application or domain. Compare strong methods. — Preceding unsigned comment added by Finin (talk • contribs) 14:26, 7 February 2019 (UTC)[reply]

Seeking to improve

I would like to improve this article, and here is what I plan to do: I will add more reliable sources including ones from the UC Berkeley library. I also plan on explaining more about the differences between narrow and weak AI. Furthermore, I will talk about how weak AI exists in the real world today, and how it can be an issue to our current society. This article does not have an picture with a caption on the right side, so if I can figure out how to do that, I would also like to add one.

Here and at the bottom of the page are the sources I plan on using: [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] 

SkyradBear (talk) 04:08, 20 September 2022 (UTC)[reply]

References

  1. ^ Chandler, Daniel (2020). A dictionary of media and communication. Rod Munday (3rd ed.). Oxford. ISBN 978-0-19-187796-4. OCLC 1142344965.
  2. ^ Colman, Andrew M. (2015). A dictionary of psychology (4th ed.). Oxford. ISBN 978-0-19-965768-1. OCLC 896901441.
  3. ^ Szocik, Konrad; Jurkowska-Gomułka, Agata (2021-12-16). "Ethical, Legal and Political Challenges of Artificial Intelligence: Law as a Response to AI-Related Threats and Hopes". World Futures: 1–17. doi:10.1080/02604027.2021.2012876. ISSN 0260-4027.
  4. ^ Bartneck, Christoph; Lütge, Christoph; Wagner, Alan; Welsh, Sean (2021). An Introduction to Ethics in Robotics and AI. SpringerBriefs in Ethics. Cham: Springer International Publishing. doi:10.1007/978-3-030-51110-4. ISBN 978-3-030-51109-8.
  5. ^ Liu, Bin (2021-03-28). ""Weak AI" is Likely to Never Become "Strong AI", So What is its Greatest Value for us?". arXiv:2103.15294 [cs].
  6. ^ Kuleshov, Andrey; Prokhorov, Sergei (September 2019). "Domain Dependence of Definitions Required to Standardize and Compare Performance Characteristics of Weak AI Systems". 2019 International Conference on Artificial Intelligence: Applications and Innovations (IC-AIAI). Belgrade, Serbia: IEEE: 62–623. doi:10.1109/IC-AIAI48757.2019.00020. ISBN 978-1-7281-4326-2.
  7. ^ Kerns, Jeff (February 15, 2017). "What's the Difference Between Weak and Strong AI?". ProQuest.
  8. ^ LaPlante, Alice; Maliha, Balala (2018). Solving Quality and Maintenance Problems with AI. O'Reilly Media, Inc. ISBN 9781491999561.
  9. ^ Earley, Seth (2017). "The Problem With AI". IT Professional. 19 (4): 63–67. doi:10.1109/MITP.2017.3051331. ISSN 1520-9202.
  10. ^ Anirudh, Koul; Siddha, Ganju; Meher, Kasam (2019). Practical Deep Learning for Cloud, Mobile, and Edge. O'Reilly Media. ISBN 9781492034865.

Peer Review

I think this is a really good start, especially considering that you are drafting a brand new article. I really like the specific, well-divided sections along with the table of contents. Furthermore, your sources look reliable (maybe add a few more if you can?). Although weak artificial intelligence may be a part of civic tech itself, there is still somewhat a lack of a connection between weak and/or strong ai with civic tech. Also, you could really expand on the "impact" section as that is really what the heart of the article could be. Other than that which you probably already had in mind to add on, looks good. Lavarball13 (talk) 03:29, 18 October 2022 (UTC)[reply]

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