Trust in the Machine

The last two years has seen a massive increase in AI deployment. But alongside the opportunities, there are some big risks: including accuracy, bias and transparency. How can we ensure that AI systems not only perform effectively but also respect the heritage, values, and responsibilities that underpin ethical information stewardship?

In this session, I will discuss practical strategies for making AI systems transparent, fair, and aligned with human values; from designing explainable models and addressing data bias to implementing robust governance frameworks. I will also highlight how curating data with care and context is essential to building AI that can be trusted to serve the public good.

Importantly, this session emphasises the human dimension of AI trustworthiness. Trust cannot be programmed; it must be cultivated through openness, accountability, and sustained dialogue between technologists, information professionals, and the communities they serve