My research is on socio-technical systems that seamlessly combine artificial, human, and collective intelligence. I’m interested in emergent and augmented intelligence as we often experience it on open, decentralised digital platforms, like on social networks and in online communities.
I work on mechanisms, algorithms, and tools to describe and anticipate qualities of technical artifacts within such systems, and the links to the social environment in which they were created. In the past five years, I’ve worked on these topics in the context of smart cities (building human-in-the-loop smart transport infrastructures), citizen science (understanding motivations, incentives, and behaviours of volunteers) and knowledge communities (developing methods to assess the quality of knowledge graphs as a function of their social fabric). The systems I build or study are primarily digital, so many of the research methods I work with use digital traces of such platforms as a means to understand behaviour, design interventions, and suggest areas of improvement.
I am excited about the applications of large language models and other similar AI technologies if used in a thoughtful way. They could change all areas I’ve researched in, from writing code and working with data to accessing and sharing knowledge. At the same time, I think it’s going to take some time to understand how we could create the best user experience for these technologies for non-experts, and how to make sure they are used responsibly.