WP4: Human AI collaboration

WP4 image Human AI collaboration


  • Enabling synergetic human-AI collaborations, including in the context of Hybrid AI


  • Human decision-making process cannot be fully captured by the computational model of Hybrid AI.
  • Human perception and cognitive capability are limited. Hybrid AI can augment human to improve critical decision making.


  • Interactive techniques to explore hybrid AI models for explainability
  • Conditional Generative Models for visual prediction of probable futures with uncertainties for different decision choices
  • Algorithms for joint multimodal learning from temporal data and multimodal reasoning with prior or external knowledge
  • Efficient techniques for machine learning models to recover from erroneous or malicious inputs


  • Behavioural experiments
  • Participatory design and evaluation methods
  • Computing systems performance measurement and optimization
  • Human-in-the-loop machine learning
  • Immersive visualization
  • Visual learning and reasoning
  • Bio-inspired computer vision

Team members


Lead PI SG: Wei Tsang OOI (NUS)

Christophe Jouffrais

Lead PI FR: Christophe JOUFFRAIS (CNRS)

Team PI Singapore

Brian LIM (NUS)

Jamie NG (A*STAR)

Lai Xing NG (A*STAR)


Shengdong ZHAO (NUS)

Team PI France




Christophe HURTER (ENAC)


WP4 focuses on how humans can interact with AI to (i) bring humanity aspects that cannot be computationally modeled into AI systems and algorithms, forming a hybrid AI with human interaction at its core, and (ii) allow hybrid AI to augment human perception and cognition (especially assisting humans in decision making). Within this WP, we propose to develop interaction and visualization techniques for collaboration between humans and AI towards building intelligent, explainable, and accountable AI. We will also explore how to improve the robustness of AI towards erroneous and malicious human inputs. Finally, we propose to investigate how hybrid AI can augment human perception and cognition. WP4 will provide inputs for WP1 (methods and techniques for interactive explainability), WP2 and WP3 (methods and techniques to put back humans in the loop of Machine Learning), WP8 and WP9 (methods and techniques to control a set of autonomous agents).

More links

This research is supported by the National Research Foundation, Prime Minister’s Office, Singapore under its Campus for Research Excellence and Technological Enterprise (CREATE) programme.

CREATE is an international collaboratory housing research centres set up by top universities. At CREATE, researchers from diverse disciplines and backgrounds work closely together to perform cutting-edge research in strategic areas of interest, for translation into practical applications leading to positive economic and societal outcomes for Singapore. The interdisciplinary research centres at CREATE focus on four areas of interdisciplinary thematic areas of research, namely human systems, energy systems, environmental systems and urban systems. More information on the CREATE programme can be obtained from www.create.edu.sg.

Visit the CNRS website here.