We live in an era of information overload that impairs objective decision making, especially in time-sensitive contexts. Information Visualization (InfoVis) systems have been used to mitigate information overload, yet they have not yet unlocked their potential in critical decision-making scenarios. From emergency rooms and autonomous cars to operational command centres, a clear understanding and rapid assessment based on the available data can make the difference between life and death. SYMBIOTIK envisions an effortless interaction dialogue between human and InfoVis systems to support decision making processes, inspired by known biological principles and guided by artificial intelligence (AI). Critically, this dialogue requires AI solutions with context awareness, emotion sensing, and expressing capabilities. We propose a novel framework where both the human and the machine cooperate towards a common goal and evolve together. The overall objectives of the project are:
1. Support a natural dialogue between AI agents and humans following symbiosis principles.
2. Develop human-centric perception analysis methods and tools for situation/time-sensitive tasks in InfoVis systems.
3. Facilitate a novice-to-expert transition in InfoVis systems by means of context-aware self-adaptive graphical user interfaces.
Awareness principles will allow us to engineer complex systems, making them more resilient and more human-centric. We will define an integrative approach for awareness engineering and propose a specific open source implementation. Finally, we will demonstrate and validate the role and added-value of such an awareness framework in two scenarios: supporting novice-to-expert transitions and critical decision making. The awareness principles to be developed in this project can support learning, adaptation, and self-development of intelligent systems over long periods of time, not only in the InfoVis domain. Therefore, SYMBIOTIK has potential to achieve the real breakthroughs needed to bring awareness and emotional intelligence for decision-making tasks in computing systems. The results of the project will benefit a range of stakeholders, from human vision and brain researchers, computer scientists, citizens, as well as research funding bodies and policy makers.
