The operationalisation of ethical principles, current and emerging legalisation, and the understanding and mitigation of potential consequences to individuals and society are key challenges in the design, development and deployment of Artificial Intelligence (AI) driven systems. Organisations developing AI solutions as a service or innovating novel applications will need to openly address ethical principles such as bias, fairness, explainability, transparency, data privacy, accountability, and safety through AI Governance.   In this talk I will briefly first overview ethical issues and emerging/current legalisation related to AI systems and the impact on people and society. Responsible innovation and ethical tech are essential to build public trust and meet legal obligations, yet how can researchers harness People Power through participatory AI (co-design, co-production and public engagement).  I will give some examples of projects that bridge the gap between academia and people including the EPSRC funded PEAs in PODs and the Peoples Panel for Artificial Intelligence.

Research using linked data is both time- and cost-effective compared with performing de-novo longitudinal studies, as it maximises the use of available data and makes it feasible to follow-up entire populations over extended periods. In addition, it enables retrospective studies to be conducted many years after exposure to an agent or policy, and largely eliminates limitations due to sample size, response or recall bias, and loss to follow-up. It also allows empirical investigation of even marginal shifts in policy and practice in real-world settings.

Over the last decade, linked data systems have proliferated globally with many countries now having robust whole-population data platforms capable of linking health and social sector data at both the individual and genealogical level. My presentation will overview the data linkage landscape in Australia, and abroad, providing examples of linked data research that has informed social and health policy and practice. It will also explore emerging opportunities for the application of newer data science and analytical techniques to linked routine databases.