Talk:Human-Centered Artificial Intelligence

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Notability[edit]

The article has been tagged for notability but has a substantial amount of citations, seems like it fulfills GNG. Can someone elaborate on the issue here? 22:33, 28 February 2022 (UTC)— Preceding unsigned comment added by PigeonChickenFish (talkcontribs)

The growing literature on Human-Centered AI indicates the vitality of the is topic. (benbendc) — Preceding unsigned comment added by 70.79.147.42 (talkcontribs)
Many of the citations on the page didn't really mention this topic at all (they're mostly being used to support WP:OR), and the rest either trace back to a very small group of people or are just simple mentions as titles of conference presentations. These are not the kind of sources (or the kind of content) that supports an encylopedia article, particularly one that is a very poorly differentiated fork of Human-centered computing. I've redirected it accordingly. - MrOllie (talk) 01:13, 3 May 2022 (UTC)[reply]

The importance of creating Human-Centered Artificial Intelligence.[edit]

I would like to add a new section on the content page called "Importance of HCAI" or "Significance of HCAI" by providing some examples to show not using HCAI could cause serious issues regarding on fairness. --Kj0361 (talk) 03:30, 24 March 2022 (UTC)[reply]

What does it mean for artificial intelligence and machine learning to be human-centered?[edit]

I want to edit the page and add a couple of sources that talk about interpretability and explainability. Other changes will include discussions on when and if an artificial intelligence solution should be applied. Some of the sources I'd like to discuss include the following:

How to make Machine Learning more Human Centered: Importance of Unbiased Datasets[edit]

I would like to add a section regarding the roles datasets play in machine learning algorithms, and how datasheets for datasets can help consumers use data in a more informed way. Some of the sources I will use to supplement this section include the following:

  • Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna Wallach, Hal Daumé III, and Kate Crawford. 2021. Datasheets for datasets. Commun. ACM 64, 12 (December 2021), 86–92. DOI:https://doi.org/10.1145/3458723
  • Nithya Sambasivan, Shivani Kapania, Hannah Highfill, Diana Akrong, Praveen Kumar Paritosh, & Lora Mois Aroyo (2021). "Everyone wants to do the model work, not the data work": Data Cascades in High-Stakes AI. https://research.google/pubs/pub49953/

NotunKiba (talk) 17:32, 24 March 2022 (UTC)[reply]