Workshop Overview

Artificial intelligence (AI) and Human-Computer Interaction (HCI) share common roots: early work on conversational agents has laid the foundation for both fields. Despite sharing a common history, economic and political influences have driven these fields to remain separate in subsequent decades. The recent rise of data-centric methods in machine learning has propelled few-shot emergent AI capabilities, resulting in a raft of practical tools. In particular, modern AI techniques now power new ways for machines and humans to interact. Recently, a wave of HCI tasks has been proposed to the machine learning community, which direct AI research by contributing new datasets and benchmarks, and challenging existing modeling techniques, learning methodologies, and evaluation protocols. Machine learning techniques have been developed for a variety of tasks, including user-interface understanding, UI generation, accessibility, and reinforcement learning from human feedback. This workshop offers a forum for researchers to discuss these new research directions, identify important challenges, showcase new computational and scientific ideas that can be applied, share datasets/tools that are already available, or propose those that should be further developed. Bridging AI and HCI is a vibrant topic across research fields and has been discussed by researchers in a variety of venues, including our previous workshop at CHI 2020. This year at ICML, we aim to deepen the discussion in the technical realm of machine learning. The workshop will be in-person. If you cannot come in person due to visa or travel issues, please email us at aihci@googlegroups.com. 

We invite researchers both in academia as well as industry who work in the areas including but not limited to: 

• User interface modeling for understanding and generation

• Reinforcement learning with human feedback (RLHF)

• Explainable and interpretable machine learning methods

• Generative AI and creativity tools

• Human evaluation methods

• Personalizable and correctable machine learning models

• Novel human interactions with models

• Active learning and human-in-the-loop systems

• Ethics and fairness-based models, interactions, and evaluations

• Tools and datasets to accelerate works at the intersection of HCI and AI

• Challenges in working at the intersection of AI and HCI

Please visit the Call for Participation page for detail on the contributions solicited.

Submission Portal is now open on OpenReview.

Important Dates

Paper Submission Deadline:  May 26th, 2023. 

Decision Notification Date:  June 19th, 2023 [UPDATED DATE]