To Örebro University

The successful application, usability, and social emancipation of AI technologies necessitates that the design and implementation of technical systems be founded on human-centred principles, be it cognitive or behavioural, social, ethical etc. Towards this objective, this thesis develops an interdisciplinary methodology for embedding cognitive behavioural principles in the design and development of next-generation human-centred AI technologies that aim to assist and empower humans in everyday life.

The interdisciplinary methodology developed in this research categorically focusses on two key aspects pertaining to human-centred technology design and engineering: (1) human behavioural precedents; and (2) cognitively founded representational and computational modalities:

• Human behavioural precedents are established by systematically analysing human visuo-locomotive experience during everyday activities involving (embodied) multimodal interactions. We conduct naturalistic behavioural experiments focusing on aspects of visual perception (e.g., inattention blindness) and spatial cognition (e.g., orientation, navigation) in diverse settings of everyday mobility. As specific -in-the-wild- experimental contexts, we focus on behavioural aspects involved in everyday (human) navigation and driving.
• Representational and computational modalities are developed based on cognitively-driven articulation of behavioural precedents. Particularly, a cognitive model of visuospatial complexity for grounding embodied multimodal interactions is developed by incorporating behavioural precedents pertaining to representations of space, motion, and interaction. Furthermore, precedents concerning human preferences are used as a basis for semantically-driven computational synthesis (e.g. in the generation and manipulation of spatial morphologies), and in the articulation of human-centred evaluation and standardisation of AI systems.

As case studies we demonstrate the developed methodology in the backdrop of two application domains: (a) design assistance technologies, and (b) autonomous driving. More broadly, this thesis emphasises the need for embedding ecologically valid behavioural knowledge within the development of "human-centred" technologies.  Furthermore, this research paves the way for the development of systems that understand, interpret and anticipate human behaviour under ecologically valid naturalistic circumstances.