Information and Schedule

  • Location: NeurIPS'23 Workshop, New Orleans, Louisiana, USA.
  • Date and time: 15 December 2023.
  • Schedule: Details to be added.
  • Paper submission deadline: 25 September 2023, 01:00 PM PDT (Pacific Daylight Time).
  • Author notification: 25 October 2023, 01:00 PM PDT (Pacific Daylight Time).
  • Paper submissions: See more information below in CFP.
  • Contact: For any questions, please email contact.gaied AT
  • Updates:
    • 2023-08-31: We have updated the list of invited speakers.
    • 2023-08-05: We have added details about paper submissions.
    • 2023-07-05: Initial website created for the NeurIPS'23 workshop.
    • Please refresh the page to ensure you have the latest content.


GAIED (pronounced "guide") aims to bring together researchers, educators, and practitioners to explore the potential of generative AI for enhancing education. Such an exploration, jointly as a community, is time critical: Recent advances in generative AI, in particular deep generative and large language models like ChatGPT, are bringing in transformational effects on the educational landscape. On the one hand, these advances provide unprecedented opportunities to enhance education by creating unique human-machine collaborative systems, e.g., these models could act as personalized digital tutors for students, as digital assistants for educators, and as digital peers to enable new collaborative learning scenarios. On the other hand, the advanced capabilities of these generative AI models have brought unexpected challenges for educators and policymakers worldwide, causing a chaotic disruption in universities and schools to design regulatory policies about the usage of these models. The workshop will investigate these opportunities and challenges in education by focusing the discussions along two thrusts:

  1. GAI→ED: Exploring how recent advances in generative AI provide new opportunities to drastically improve state-of-the-art educational technology.
  2. ED→GAI: Identifying unique challenges in education caused by these recent advances and how to tackle them by bringing in desired safeguards along with technical innovations in generative AI.

For us to fully realize these opportunities and tackle these challenges, it is crucial to build a community of researchers, educators, and practitioners that are "multilingual" with (a) technical expertise in the cutting-edge advances in generative AI, (b) first-hand experience of working with students in classrooms, and (c) know-how of building/deploying educational technology at scale. The goal of GAIED is to foster such a multilingual community. The workshop will bring together speakers and participants with diverse backgrounds ranging from researchers in human-computer interaction, learning sciences, natural language processing, and program synthesis to industry practitioners and educators directly involved in educational activities. Moreover, the workshop program, including two panels and breakout group discussions, is designed to facilitate new connections, inspire novel ideas, and create fruitful partnerships.

We will investigate the above-mentioned thrusts on GAI→ED and ED→GAI along several topics related, but not limited, to:

  • (GAI→ED) Sharing viewpoints, novel ideas, or field experiences about using generative AI in real-world educational settings.
  • (GAI→ED) Exploring the capabilities of generative AI and large-language models in novel educational scenarios, e.g., personalized content generation and grading.
  • (GAI→ED) Exploring novel human-machine collaborative systems where generative models play different roles, e.g., as digital tutors, assistants, or peers.
  • (ED→GAI) Sharing viewpoints, unique challenges, or field experiences about concerns among educators and policymakers in using generative AI.
  • (ED→GAI) Developing novel prompting and fine-tuning techniques to safeguard the outputs of generative AI and large-language models against biases and incorrect information.
  • (ED→GAI) Developing novel safeguarding techniques to validate the authenticity of content, e.g., to determine whether an assignment was written by students or generated by models.


Accepted Papers

List of accepted papers will be added here in October 2023.

Call for Papers and Participation

Details about papers submissions are provided below:

  • We invite submissions of research papers reporting new results and position papers reporting new viewpoints or field experiences. As per NeurIPS guidelines, previously published work or work that is presented at the NeurIPS conference is not acceptable as a workshop submission.
  • Submissions are limited to 6 pages of main content, including all figures and tables; additional pages containing references are allowed. If authors wish to put supplemental information in the paper (e.g., implementation details, proofs), they can use additional pages after the references to add appendices. Note that this supplemental information will not be used during the reviewing process, and reviewers should be able to judge your work based on the main content (up to 6 pages).
  • All submissions must be in PDF format based on the NeurIPS 2023 LaTeX style file.
  • The reviewing process is double-blind. All submissions should be anonymous.
  • Accepted papers will be made publicly available as non-archival reports.
  • We are using OpenReview to manage workshop submissions. All authors must have an OpenReview profile when submitting. The author list cannot be changed after the deadline.
  • Submission portal: NeurIPS'23 Workshop GAIED.
  • Paper submission deadline: 25 September 2023, 01:00 PM PDT (Pacific Daylight Time).
  • Author notification: 25 October 2023, 01:00 PM PDT (Pacific Daylight Time).

GAIED workshop welcomes participation from individuals who do not have something they'd like to submit but are interested in the workshop topics. The workshop aims to facilitate new connections, inspire novel ideas, and create fruitful partnerships.