Artificial intelligence and predictive analytics could significantly transform the way elections are analysed, public policy is developed and universities prepare students for the future, a University of Fiji Press Club session has heard.
The University of Fiji Press Club hosted its August session on Monday, 10 August 2026, at the University of Fiji Suva Central Campus, featuring international governance and strategy specialist Mr David Elbourne.
The session focused on the provocative theme, “What If We Already Know Who Is Going to Win the Election? – The Case for Artificial Intelligence and the High-Value University.”
The presentation examined how artificial intelligence, machine learning and predictive analytics could be applied to journalism, political analysis, government decision-making and education.
UniFiji Vice Chancellor, Professor Shaista Shameem said ‘it was heartening to see the Press Club providing cutting edge opportunities to established journalists and journalism students at the same time, allowing total involvement of both in a symbiotic relationship’.
Mr Elbourne drew on his international experience in Australia and the United Kingdom, as well as his background in data analytics, artificial intelligence, machine learning, digital transformation and organisational strategy.
At the heart of the discussion was the question of whether available historical and contemporary data could be used to develop analytical models capable of forecasting election outcomes. Mr Elbourne explained that such models could examine political party performance, online visibility, controversies, funding and resources, candidate distribution, economic conditions, previous election results and other factors.
However, he stressed that predictive analytics should not be mistaken for certainty. “This model does not remove uncertainty. It measures it,” he said, highlighting the fact that elections remain influenced by factors that cannot be accurately predicted, including voter turnout, vote switching, party alliances, campaign effects, future events and individual voting decisions.
Mr Elbourne said the development of an effective predictive model begins with understanding what is already known and identifying the areas that remain uncertain. By assigning weightings to different factors and combining qualitative and quantitative information, analysts can develop a framework capable of producing probability-based assessments rather than absolute predictions.
He told students that the approach was not limited to elections and could potentially be applied to areas including climate change, economic development and infrastructure planning. “It’s not specifically only to elections,” he explained, noting that the same analytical approach could be adapted across different industries and areas of decision-making.
The presentation also introduced the relationship between predictive analytics, machine learning and artificial intelligence. Mr Elbourne described predictive analytics as part of machine learning, which in turn forms part of the broader field of artificial intelligence. He encouraged students to begin developing their own analytical frameworks and consider how university research and ideas could eventually become intellectual property.
The discussion also raised important questions about the ethical implications of using AI in elections and public life. The University of Fiji opening address noted that while AI can identify patterns, analyse large volumes of information and support evidence-based decision-making, it also raises concerns about data ownership, manipulation, public opinion and democratic participation. “Can we trust what AI tells us? Who controls the data? How do we distinguish information from manipulation?” the university representative asked. For journalism students, the implications are particularly significant.
The session emphasised that the growth of AI does not reduce the importance of journalists but instead places greater responsibility on them to verify information, understand data and exercise ethical judgement. The university noted that future journalists will require not only traditional reporting skills but also data literacy, critical thinking, ethical judgement and the ability to question information produced by technology.
The Press Club was also presented as an important platform for students to engage with issues beyond the classroom. Established as an initiative of the Journalism and Media Studies Programme, the club provides opportunities for students to interact with journalists, policymakers, academics, professionals and community leaders while developing practical knowledge and professional skills.
Mr Elbourne further argued that universities have an important role to play in helping Fiji move beyond simply adopting technologies developed elsewhere. He said universities could become engines of innovation by turning research into intellectual property, intellectual property into industries, and industries into employment, exports and national prosperity. A key message from the session was that data alone has limited value unless it is properly organised, interpreted and transformed into knowledge.
Mr Elbourne explained that the progression from data to information, knowledge and applied intelligence is essential if Fiji is to develop systems capable of supporting more informed decisions. The session concluded with a broader challenge to universities, journalists and students to prepare for a future in which AI will increasingly influence professional and social life.
Rather than viewing artificial intelligence simply as a technological development, the Press Club discussion framed it as an issue involving democracy, journalism, ethics, education, public trust and national development.
For Fiji, the message was clear: artificial intelligence may provide powerful tools for understanding the future, but the quality of the outcome will ultimately depend on the quality of the data, the people interpreting it and the ethical frameworks guiding its use.
