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Research

Behavioural Data Science research combines techniques from the behavioral sciences and data science to better model, understand and predict human, algorithmic, and systems behavior in various contexts.

The field of Behavioural Data Science combines techniques from behavioural science, decision theory, and social psychology with computational approaches to better understand and predict human behaviour, algorithmic behaviour, and systems behaviour.

 

This interdisciplinary field addresses a wide range of issues, including how to improve people's well-being, how to build flexible supply chains, and how to understand machine behaviour and algorithmic behaviour.

 

The field's future aims to establish ways to embed human values into AI systems and to ensure they operate in the service of successful, democratic, digitally empowered yet human-centred communities. 

The goal of the Behavioural Data Science research is to address theoretical and empirical challenges related to human, algorithmic, and systems behaviour through the development of innovative, impactful, and responsible approaches.  Behavioural Data Science research has an ambitious goal to transform the world by:

  • Understanding how AI, data science, and behavioural science can form synergies and develop tangible and effective methodologies in order to map, analyse, and help alleviate major behavioural issues societies are facing today

  • Providing valuable advice to businesses and policy makers about building happier, safer, more successful organisations and communities using behavioural data science insights

  • Training new generation of scientists who will work at the forefront of behavioural data science and behavioural artificial intelligence in the future


To learn more about Behavioural Data Science research, please, check Publications and Impact pages of this website.

You may find the following interview material of interest:

 

Delivering Package
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