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Designing the Future of User Feedback for Generative AI — arXiv:2610.02631

Source: arXiv
Original: https://arxiv.org/abs/2610.02631
License (as archived): CC0-1.0
Archived: 2026-10-05T22:49:07.527Z
SHA-256 of the archived text: 3440f9fca16a8f1b341aa8f9e7341aa233948eba15f98cc289b26fc596a20733
Stable URL of this page: https://metraipolis.com/documento/dc_da36bc15eb04

How to cite

Designing the Future of User Feedback for Generative AI — arXiv:2610.02631 — arXiv, https://arxiv.org/abs/2610.02631 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_da36bc15eb04 (Metraipolis archive dc_da36bc15eb04, sha256 3440f9fca16a8f1b341aa8f9e7341aa233948eba15f98cc289b26fc596a20733)

BibTeX

@misc{dcda36bc15eb04,
  title = {Designing the Future of User Feedback for Generative AI — arXiv:2610.02631},
  howpublished = {arXiv},
  url = {https://arxiv.org/abs/2610.02631},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_da36bc15eb04; sha256 3440f9fca16a8f1b341aa8f9e7341aa233948eba15f98cc289b26fc596a20733},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv, https://arxiv.org/abs/2610.02631. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Post-deployment feedback from users can be a cost-effective, scalable, and representative means to monitor and improve generative AI systems and features. When implemented effectively, giving such feedback can increase users' engagement with and trust in GenAI systems. Government regulations and industry guidelines call for post-deployment user engagement, but there is little guidance on designing mechanisms that are usable for consumers and provide actionable input for product teams. We conducted a multi-phase study as a collaboration between academic researchers and eBay. Our benchmark evaluation of current industry approaches identified common issues including lack of discoverability, unclear terminology, and inattention to user value. Based on these findings, we developed best-practice recommendations and designed and tested a prototype feedback-collection tool. The tool aimed to provide users with an efficient, flexible, and positive feedback-giving experience, and provide product teams with rich data on performance and potential problems in a usable format.

Tema degli esploratori: agenti e intelligenza artificiale (elenco arXiv cs.AI, nuovi lavori del giorno).
Categorie arXiv: Artificial Intelligence (cs.AI).
Pagina del lavoro: https://arxiv.org/abs/2610.02631 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-05T22:45:55.611Z dalla pagina https://arxiv.org/list/cs.AI/new (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).