dr. Lize Alberts

Assistant Professor, Faculty of Science, Computer Science

Assistant Professor, Network Institute

Personal information

Lize has an interdisciplinary background spanning artificial intelligence, computational linguistics, behavioural psychology, analytic philosophy, social anthropology, and cognitive science. She obtained her DPhil in Computer Science from the University of Oxford, focusing on the ethics of human-AI social interaction. Her master’s applied principles from embodied cognition and cognitive linguistics to critically assess multi-modal grounded language learning approaches in AI.

During her doctorate, Lize worked at Google London as a Student Researcher on contextualising the alignment of social AI agents, laying the groundwork for the field now termed socioaffective alignment, and contributed to a Google DeepMind whitepaper on the ethics of advanced AI assistants.

Research

Lize Alberts is an Assistant Professor in the Department of Computer Science. Her research centres on building AI systems that understand users’ complex sets of needs and long-term goals and support them in personalised ways that foster autonomy, integration, and enduring self-determination.

She works in the VU's AI & Behaviour lab and is affiliated with the Network Institute and Hybrid Intelligence Centre. She holds a research associate position at the Unit for the Ethics of Technology at Stellenbosch University, and is associate editor of the Cambridge University Press Elements book series on AI Ethics & Society, in affiliation with the Leverhulme Centre for the Future of Intelligence.

Teaching

Lize co-designed and teaches three courses of the VU's BSc Artificial Intelligence programme.

Modelling Human Behaviour integrates perspectives from cognitive science, behavioural psychology, social network analysis, and computational modelling to give first year students a strong interdisciplinary foundation for understanding and modelling human behaviour. It covers the full model development pipeline: from the theoretical and ethical frameworks that underpin why and how we model behaviour, to practical implementation across multiple modelling tools and methods, including agent-based modelling in NetLogo, social network analysis in Python, and behavioural design principles for digital platforms. Students engage critically with the strengths, limitations, and risks of contemporary approaches to predicting and influencing behaviour, and consider the implications of applying these in AI and computing systems.

Research Design for AI guides students through the full research cycle of their final thesis project: formulating research questions, conducting literature reviews, selecting appropriate methodologies, handling data ethically, and communicating findings clearly and critically. The course runs alongside the BSc AI Project, supporting students with the timely and succesful completion of each thesis milestone.

Project Socially Aware Computing is a project-based course in which students conduct independent research to build, analyse, and critically report on an agent-based simulation of a phenomenon involving social interaction in the NetLogo environment.

Ancillary activities