Editing AI-complete (section)

==AI-complete problems==
AI-complete problems have been hypothesized to include:

* AI [[peer review]]<ref>{{Cite magazine |last=Stockton |first=Nick |title=If AI Can Fix Peer Review in Science, AI Can Do Anything |url=https://www.wired.com/2017/02/ai-can-solve-peer-review-ai-can-solve-anything/ |access-date=2024-04-27 |magazine=Wired |language=en-US |issn=1059-1028}}</ref> (composite [[natural-language understanding|natural language understanding]], [[automated reasoning]], [[automated theorem proving]], [[Formalism (philosophy of mathematics)|formalized]] [[logic]] [[expert system]])
* [[Bongard problem]]s<ref name="Sekrst2020">{{Citation |last=Šekrst |first=Kristina |title=AI-Completeness: Using Deep Learning to Eliminate the Human Factor |date=2020 |work=Guide to Deep Learning Basics: Logical, Historical and Philosophical Perspectives |pages=117–130 |editor-last=Skansi |editor-first=Sandro |url=https://doi.org/10.1007/978-3-030-37591-1_11 |access-date=2024-04-05 |place=Cham |publisher=Springer International Publishing |language=en |doi=10.1007/978-3-030-37591-1_11 |isbn=978-3-030-37591-1|url-access=subscription }}</ref>
* [[Computer vision]] (and subproblems such as [[object recognition]])<ref>{{Cite journal |last1=Strat |first1=Thomas M. |last2=Chellappa |first2=Rama |last3=Patel |first3=Vishal M. |date=2020 |title=Vision and robotics |journal=AI Magazine |volume=42 |issue=2 |pages=49–65 |doi=10.1609/aimag.v41i2.5299 |s2cid=220687545 |via=ABI/INFORM Collection|doi-access=free }}</ref>
* [[Natural-language understanding|Natural language understanding]] (and subproblems such as [[text mining]],<ref>{{Cite book |last1=Krestel |first1=Ralf |last2=Aras |first2=Hidir |last3=Andersson |first3=Linda |last4=Piroi |first4=Florina |last5=Hanbury |first5=Allan |last6=Alderucci |first6=Dean |title=Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval |chapter=3rd Workshop on Patent Text Mining and Semantic Technologies (PatentSemTech2022) |date=2022-07-06 |chapter-url=https://dl.acm.org/doi/10.1145/3477495.3531702 |language=en |location=Madrid Spain |publisher=ACM |pages=3474–3477 |doi=10.1145/3477495.3531702 |isbn=978-1-4503-8732-3 |s2cid=250340282 |access-date=2023-04-15 |archive-date=2023-04-15 |archive-url=https://web.archive.org/web/20230415213932/https://dl.acm.org/doi/10.1145/3477495.3531702 |url-status=live }}</ref> [[machine translation]],<ref>{{Citation |last=Orynycz |first=Petro |title=Say It Right: AI Neural Machine Translation Empowers New Speakers to Revitalize Lemko |date=2022 |url=https://link.springer.com/10.1007/978-3-031-05643-7_37 |work=Artificial Intelligence in HCI |series=Lecture Notes in Computer Science |volume=13336 |pages=567–580 |editor-last=Degen |editor-first=Helmut |access-date=2023-04-15 |place=Cham |publisher=Springer International Publishing |language=en |doi=10.1007/978-3-031-05643-7_37 |isbn=978-3-031-05642-0 |editor2-last=Ntoa |editor2-first=Stavroula|url-access=subscription }}</ref> and [[word-sense disambiguation]]<ref>{{Cite journal |last1=Ide |first1=N. |last2=Veronis |first2=J. |year=1998 |title=Introduction to the special issue on word sense disambiguation: the state of the art |journal=Computational Linguistics |volume=24 |issue=1 |pages=2–40|url=https://www.aclweb.org/anthology/J/J98/J98-1001.pdf |archive-url=https://ghostarchive.org/archive/20221009/https://www.aclweb.org/anthology/J/J98/J98-1001.pdf |archive-date=2022-10-09 |url-status=live}}</ref>)
* [[Autonomous driving]]<ref>{{cite interview |last=Musk |first=Elon |subject-link=Elon Musk |interviewer=[[Chris_Anderson_(entrepreneur)]] |title=Elon Musk talks Twitter, Tesla and how his brain works — live at TED2022 |work=[[TED (conference)]] |location=Vancouver |date=April 14, 2022 |url=https://www.youtube.com/watch?v=cdZZpaB2kDM |access-date=December 15, 2022 |archive-date=December 15, 2022 |archive-url=https://web.archive.org/web/20221215004220/https://www.youtube.com/watch?v=cdZZpaB2kDM |url-status=live }}</ref>
* Dealing with unexpected circumstances while solving any real world problem,<ref>{{Citation |last=Šekrst |first=Kristina |title=Guide to Deep Learning Basics |date=2020 |work= |editor-last=Skansi |editor-first=Sandro |url=https://philarchive.org/archive/EKRAUD |chapter=Chapter 11 - AI-Completeness: Using Deep Learning to Eliminate the Human Factor |publisher=Springer |language=en |isbn=978-3-030-37591-1}}</ref> whether [[robotic mapping|navigation]], [[automated planning and scheduling|planning]], or even the kind of [[reasoning]] done by [[expert system]]s.{{citation needed|date=February 2021}}