Welcome to the SOCIAL AI CDT
The UKRI Centre for Doctoral Training in Socially Intelligent Artificial Agents
The application process for entry in September 2021 is now closed, Round 2 applicants please check your inbox (and spam) for forthcoming communications from SOCIAL AI CDT.
The overarching goal of SOCIAL AI is to train the next generation of experts in Artificial Social Intelligence; the AI domain aimed at endowing artificial agents with social intelligence, the ability to deal appropriately with users’ attitudes intentions, feelings, personality and expectations.
The training programme covers the following main areas:
To outline principles and laws that govern social interactions between human and artificial agents – both embodied and virtual – at the level of cognitive, behavioural and physiological phenomena.
To improve the impact of artificial agents through their integration into wider and more complex technological systems and infrastructures.
To develop technological approaches – informed by the principles and laws outlined in 1 – that allow artificial agents to act as believable and effective partners in social interactions involving human users.
To investigate the human response to socially intelligent artificial agents in everyday life.
SOCIAL AI is based at the University of Glasgow.
It is a collaboration between the School of Computing Science, the School of Psychology, the Institute of Neuroscience and Psychology, the Adam Smith Business School, the School of Critical Studies, the School of Engineering, the Scottish Graduate School of the Social Sciences and 14 industrial partners.
Watch our series of recaps from @Social__AI's workshop on #AI and #mentalhealth First up, Prof Mohamed Chetouani discusses AI-based approaches for mental health analysis that can decode social interaction in Autism spectrum disorder (ASD) youtube.com/watch?v=ouWAQv…
Proud to have our research featured in @UKRI_News's recent newsletter!??? ?@Social__AI's @alevincia, @SABrewster & @ProfMinnis et. al. created a new #ml computational model to measure attachment in childhood Read in full: journals.plos.org/plosone/art…