Timezone: »

 
Workshop
Workshop on Human-Machine Collaboration and Teaming
Umang Bhatt · Katie Collins · Maria De-Arteaga · Bradley Love · Adrian Weller

Sat Jul 23 05:55 AM -- 02:00 PM (PDT) @ Ballroom 4
Event URL: https://sites.google.com/view/icml-2022-hmcat/home »

Machine learning (ML) approaches can support decision-making in key societal settings including healthcare and criminal justice, empower creative discovery in mathematics and the arts, and guide educational interventions. However, deploying such human-machine teams in practice raises critical questions, such as how a learning algorithm may know when to defer to a human teammate and broader systemic questions of when and which tasks to dynamically allocate to a human versus a machine, based on complementary strengths while avoiding dangerous automation bias. Effective synergistic teaming necessitates a prudent eye towards explainability and offers exciting potential for personalisation in interaction with human teammates while considering real-world distribution shifts. 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.

Author Information

Umang Bhatt (University of Cambridge)
Katie Collins (MIT)
Maria De-Arteaga (University of Texas at Austin)
Bradley Love (University College London)
Adrian Weller (University of Cambridge, Alan Turing Institute)
Adrian Weller

Adrian Weller is Programme Director for AI at The Alan Turing Institute, the UK national institute for data science and AI, and is a Turing AI Fellow leading work on trustworthy Machine Learning (ML). He is a Principal Research Fellow in ML at the University of Cambridge, and at the Leverhulme Centre for the Future of Intelligence where he is Programme Director for Trust and Society. His interests span AI, its commercial applications and helping to ensure beneficial outcomes for society. Previously, Adrian held senior roles in finance. He received a PhD in computer science from Columbia University, and an undergraduate degree in mathematics from Trinity College, Cambridge.

More from the Same Authors