ICML 2022 Workshop on Human-Machine Collaboration and Teaming

July 23, 2022

Starting at 8:55am ET

This workshop will take place in-person but will be amenable to virtual participants. The workshop will be live streamed for all remote, registered attendees.

What types of algorithms and socio-computational paradigms are needed to design and support the next-generation of effective human-machine collaborations?

Machine learning (ML) approaches can support decision-making in key societal settings including healthcare and criminal justice, can empower creative discovery in mathematics and the arts, and can guide interventions in education and policy. However, deploying such human-machine teams raises critical questions, such as how learning algorithms know when to defer to a human teammate, and broader systemic questions, such as which tasks to allocate dynamically between humans and machines. Effective synergistic teaming necessitates a prudent eye towards explainability and complementarity. This offers exciting potential for interaction with human teammates, while considering real-world distribution shifts and avoiding automation bias. In light of these opportunities, our workshop offers a forum to focus and inspire core algorithmic developments from the ICML community towards efficacious human-machine teaming, and an open environment to advance critical discussions around the issues raised by human-AI collaboration in practice.

Speakers and Panelists

Collége de France

University of Cambridge

Unviersité Paris-Saclay

Makere University

Sunbird AI

The Institute of Human(ity)-centric AI

ELLIS Unit Alicante Foundation

University of Southern California


University of Cambridge

Harvard University


Harvard University




University of Illinois at Urbana- Champaign


University of Cambridge

The Alan Turing Institute

University of Cambridge

University of Texas at Austin

University College London

The Alan Turing Institute

University of Cambirdge

The Alan Turing Institute

Thank You to Our Program Commitee!

Kaarina Aho

Zahra Ashktorab

Serena Booth

Valerie Chen

Isabel Chien

Riccardo Fogliato

Ruijiang Gao

Katy Gero

Kenneth Holstein

Jennifer Hsia

Alon Jacovi

Anna Kawakami

Gavin Kerrigan

Satyapriya Krishna

Niklas Kuehl

David Madras

Hussein Mozannar

Keziah Naggita

Hellina Hailu Nigatu

Emma Pierson

Manuel Rodriguez

Jakob Schoeffer

Ming Yin

Joyce Zhou

Miri Zilk

Thank You to our Sponsors!

Call for Papers

We welcome submissions broadly focused on advancing human-machine collaboration and teaming. Specific topics of interest for the workshop include (but are not limited to) theoretical, empirical, or user study-driven works in:

Human-in-the-loop learning

Training of systems which complement humans (e.g., deferral-based systems)

• Design choices for decision support systems which enable improved measures of performance

• Visualization or other methods for better explainability to improve team performance

• Theoretical guarantees on human-AI complementarity

• Out-of-distribution generalization in real-world teaming applications

Position papers discussing the state-of-the-art and future of human-machine collaboration

We invite submissions of full papers as well as works-in-progress, position papers, and papers describing open problems and challenges. While original contributions are preferred, we also invite submissions of high-quality work that has recently been published in other venues or is concurrently submitted. If the work has previously been published, please state the venue and year when making your submission.

Papers should be 4 pages in length (excluding references and acknowledgments) formatted using the ICML template (in the blind non-accepted mode) and submitted online at https://easychair.org/conferences/?conf=hmcat2022. Some accepted papers will be selected for a short oral presentation.

Submission deadline: May 26, 2022 (23:59 AoE)

Notification: June 13, 2022

Workshop: July 23, 2022