In the last decade, the computational power of AI has grown exponentially – doubling every six months since 2010 for some well-known tools. This, in tandem with more sophisticated machine learning models and increases in available data, has opened up possibilities for research and discovery that would have been unthinkable even a few years ago.

But most academics are relatively new to using AI and thus have a long way to go to understand its many potential applications. Something that comes more naturally to some than to others.

To find out how researchers can get the most out of AI tools while managing the associated risks, this week, we speak to a leading computer scientist who has been developing AI tools for research for more than 20 years.

Karin Verspoor is dean of the School of Computing Technologies at RMIT University in Melbourne, Australia. Her research focuses on the use of AI to support biological discovery and clinical decision making by analysing biomedical text and clinical records.

She has held previous posts as director of health technologies and deputy head of the School of Computing and Information Systems at the University of Melbourne, as the scientific director of health and life sciences at NICTA Victoria Research Laboratory.

Listen to Karin’s take on the good, the bad and the best way forward for AI in academic research.

And if you want more practical advice and insight on how to best apply GenAI to augment your own research, check out our latest spotlight guide: GenAI as a research assistant.