[Submitted on 27 Jun 2023 (v1), last revised 22 Dec 2023 (this version, v2)] · arXiv.org

Authors:Xiang 'Anthony' Chen, Jeff Burke, Ruofei Du, Matthew K. Hong, Jennifer Jacobs, Philippe Laban, Dingzeyu Li, Nanyun Peng, Karl D. D. Willis, Chien-Sheng Wu, Bolei Zhou

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Abstract:Through iterative, cross-disciplinary discussions, we define and propose next-steps for Human-centered Generative AI (HGAI). We contribute a comprehensive research agenda that lays out future directions of Generative AI spanning three levels: aligning with human values; assimilating human intents; and augmenting human abilities. By identifying these next-steps, we intend to draw interdisciplinary research teams to pursue a coherent set of emergent ideas in HGAI, focusing on their interested topics while maintaining a coherent big picture of the future work landscape.
Subjects: Human-Computer Interaction (cs.HC); Computation and Language (cs.CL); Computer Vision and Pattern Recognition (cs.CV); Machine Learning (cs.LG)
Cite as: arXiv:2306.15774 [cs.HC]
  (or arXiv:2306.15774v2 [cs.HC] for this version)
  https://doi.org/10.48550/arXiv.2306.15774

arXiv-issued DOI via DataCite

Submission history

From: Xiang 'Anthony' Chen [view email]
[v1] Tue, 27 Jun 2023 19:54:30 UTC (602 KB)
[v2] Fri, 22 Dec 2023 17:53:02 UTC (898 KB)

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