Nordic Centre for Sustainable and Trustworthy Artificial Intelligence Research (NordSTAR) is a Centre of Research Excellence in modern Artificial Intelligence (AI). The centre aims to establish a new paradigm in AI basic research, so-called sustainable and trustworthy AI.
Artificial intelligence demand massive computing power and energy, and is also threatened by a lack of trust. NordSTAR aims to establish a new paradigm in the research on these challenges. This will be done by developing AI tools, which embed all key aspects related to sustainability and trustworthiness. To do this the centre has established five research areas:
Security, safety and reliability:
This research area will address data security, humans physical safety, and reliability of the communication at the level of AI methods design. Ahmed Elmokashfi from SimulaMet leads the research area.
Human factors in AI: We will incorporate the fundamental legal and moral norms underlying social behavior and consider them in the design of Sustainable and Trustworthy AI tools. Elena Parmiggiani from the Norwegian University of Science and Technology (NTNU) leads this research area.
Quantum AI: The aim of this area is to bridge the gap between the growing number of theoretical suggestions on design and application of quantum AI and the present lack of quantitative practical results. Sergiy Denysov from OsloMet leads the research area.
Biologically-inspired computational systems: They will incorporate fundamental aspects of natural intelligence in AI models, with the motivation of approaching the efficiency of biological neural systems. Stefano Nichele from OsloMet leads this research area.
Understandable and explainable models: This research area is going to quantify the uncertainty in AI decisions and develop tools for better understanding of the different components of AI models and for explaining why specific AI decisions are obtained. Hugo Lewi Hammer from OsloMet leads this research area.