Our TANGO project partners, University of TRENTO (IT), university of pisa (IT), university of sussex (UK) and Centre for European Policy Studies (CEPS) in Brussels, are pleased to announce the call for papers for the HLDM 2024 Second workshop on Hybrid Human-Machine Learning and Decision Making, which will take place, September 9th or 13th, 2024 in Vilnius, Lithuania.
The goal of our workshop is to bring together researchers with diverse backgrounds and expertise to explore effective hybrid machine learning and decision making. This will include approaches that explicitly consider the human-in-the-loop and the downstream goals of the human-machine system, as well as decision making strategies and HCI principles that promote rich and diverse interactions between humans and machines. Additionally, cognitive and legal aspects will be considered to identify potential pitfalls and ensure that trustworthy and ethical hybrid decision-making systems are developed.
Key Dates:
- Paper Submission Deadline: 15 June 2024
- Paper Author Notification: 15 July 2024
- Workshop date: 9 or 13 September 2024
Call for Papers
Following the success of the first edition, the HLDM 2024 workshop aims at gathering together a diverse set of researchers addressing the different aspects that characterize effective hybrid decision making. These range from machine learning approaches that explicitly account for the human-in-the-loop and the downstream goal of the human-machine system, to decision making strategies and HCI principles encouraging a rich and diverse interaction between the human and the machine, to cognitive aspects pinpointing potential pitfalls, misunderstandings and sub-optimal behaviour, legal and regulatory aspects highlighting requirements and constraints that trustworthy and ethical hybrid decision making systems should satisfy. The workshop will feature invited talks, a poster session, presentations of the best contributions and a final discussion.
We invite submissions on a broad range of topics revolving around hybrid human-machine learning and decision making, including but not limited to:
- learning to defer
- learning to complement
- selective classification
- cost-sensitive learning
- active learning
- calibration of learning models
- interactive machine learning
- human-in-the-loop machine learning
- trustworthy hybrid decision making
- cognitive aspects in hybrid decision making
- hybrid decision-making interfaces
- hybrid decision-making strategies
- hybrid decision-making applications
- regulation of hybrid decision-making systems
- assessment of hybrid decision-making systems
- ethics of hybrid decision-making
- legal aspects of decision support systems
More details about the submissions available at: HLDM’24 (unitn.it) and hldm-workshop@unitn.it