AI@Strathclyde

Description

The Human Centric AI Research Group sets itself apart through its commitment to prioritising human needs in AI advancements. The belief central to the group is that AI technologies can only realise their full potential, and receive widespread societal acceptance, if their evolution is driven by the needs of the ultimate beneficiaries - the humans. This conviction necessitates not only the development of new AI technologies, but also demands that these technologies' applications in a human context are at the heart of their development.

Key strengths of the group include:

• Development of innovative AI-based problem-solving approaches that are explainable, trusted and acceptable.
• A shift in focus to ensure AI integrates into human-centric decision systems.
• Bridging the gap between humans and AI-systems, notably enhancing human intelligence areas where current AI-systems underperform.
• Construction of persistently autonomous systems that act sensibly and robustly in real-time, challenging environments.

The group conducts extensive research in areas such as:

• Human Centric AI for Healthcare: The group envisages fostering a transformative human-centric paradigm in AI for healthcare, where computers act as active collaborators rather than mere tools. The research themes within this include Trusted Data, Trusted AI, and Trust in Human Factors.
• AI and Software Engineering: The research explores how AI techniques can support the process of software engineering, and conversely, how AI systems should be engineered. Themes include Test Data Generation, Test Outcome Classification, Fault Localisation, and Autonomous Systems Evolution.
• AI and Animal Health: Research in this area involves interpreting novel sensor/IoT sources, machine learning in noisy environments, agent-based modelling, and M-Health in LIMC.
• AI and Video Coding, National Grid and E-Learning: The research here includes developing an AI solution for the National Grid ESO, a machine learning solution for FAIR E-Learning, new concepts in video coding for machines, and real-time video streaming in automated driving applications.
• AI and Multimodal Speech Communication: This field involves lipreading and speech recognition, explainable image features, and emotion recognition from video data.
• Robust Reasoning for Intelligent Agents: The aim here is to develop long-lasting autonomous systems that are robust and trusted, capable of reacting robustly and safely in dynamic and challenging environments, and working within mixed teams of humans and machines.

Offers funding

No, this infrastructure does not provide funding.

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University affiliation(s)

University of Strathclyde
Glasgow