Jun Zhao

Jun came to computing relatively late. While many of her classmates arrived at university already fluent in programming, she was starting from scratch. An early lecturer offered advice she still remembers: ‘Nobody can know everything about computing.’

Her early academic work did not focus on children or digital technology. During her PhD and the first decade of her research career, she worked in computational biology. Advances in genetic sequencing were generating enormous volumes of data, and Jun applied computational methods and AI algorithms to help biologists analyse and interpret those datasets.

‘I was working with biologists…applying AI algorithms to help them process the data and make sense of the data.’

Jun’s research direction shifted unexpectedly after she became a parent in 2015. Around that time, she and her colleagues began investigating how mobile applications collect and transmit data. Their initial work focused broadly on data traffic in freely available apps. What they discovered raised serious concerns. Even apps designed for toddlers learning the alphabet or practising counting were transmitting huge amounts of data to third parties without users’ knowledge or consent.

For Jun, the discovery was personal. ‘As a parent, I was outraged by what was happening to my children’s data.’ That moment marked the beginning of a new research direction that would shape the next decade of her work.

Ten years ago, very few people were talking about the impact of AI on children. Today, Jun leads research at the centre of those debates.

One thing has consistently surprised her throughout that work. ‘People always think children of this age group have very little understanding about technologies,’ she says of the seven-to-twelves at the centre of her research. ‘But I’m always amazed by how much they actually know.’ Watching children become more conscious of how technology affects their lives through her research interactions, she says, is the most rewarding part of the work.

The implications of that research reach well beyond academic publications. Digital platforms operate across borders while regulation develops at national levels: ‘there are no boundaries on the internet,’ as Jun puts it, and she has become increasingly involved in policy discussions as a result, working with international organisations to translate scientific evidence into practical guidance. ‘A lot of the policies are being launched in the global north,’ she notes, while many countries in the global south face different risks and challenges.

Looking ahead, she wants families to have real choices about the technologies they use and the alternatives available to them. Teachers and parents, she observes, often feel uncertain because technologies are evolving so quickly. ‘They are extremely anxious about not knowing what the harms or impacts are and how to support their children.’ Building stronger AI literacy, for children, parents and teachers alike, is central to what she hopes her research can achieve.

On diversity, she is equally direct and precise. It is not simply a matter of gender balance, she argues, but of the range of perspectives brought to the work itself. Within her own lab, where gender balance is close to equal and the demographics of students and researchers are deliberately varied, she has seen first-hand how different backgrounds surface questions that would otherwise go unasked. A colleague once pointed out that ‘agency,’ a concept central to her framework for ethical AI, is itself a Western idea, one that may not translate across cultures. ‘That is what makes diversity really critical in thinking about responsible innovation, to make sure that everything we are looking at is trying to be as inclusive as possible.’