The idea of replicating human decision making with computers has been around for nearly as long as the information technology industry has been in existence. Artificial Intelligence (AI) and more recently what has been termed Machine Learning (ML) are topics that have been of enduring interest in the international research community. Albeit that the popularity of AI has waxed and waned despite its potential to replace human beings in hazardous working environments, such as those that face firefighters every day.

Today the subjects of AI and ML are going through another renaissance with the ever-increasing speed of contemporary computing technologies, guided by Moore’s Law, and the emerging insights from the relatively new developments in data science. This is sometimes referred to as ‘big data’.

The latest resurgence of interest in AI has been driven in part by the emergence of ML techniques and the ability to use a technique known as ‘reinforcement learning’ to fine tune the ability of the algorithms to improve their ability to replicate human decision making. This is the ultimate goal of AI. While this dream has yet to be fully realised the most recent developments have taken the field of AI to a new level.

Given these recent developments it is appropriate to ask a number of questions. These include: to what extent might AI and ML techniques have some relevance to the emergency services community? What applications of AI might prove beneficial? How robust would those solutions be? Will AI ever be able to think creatively? Will a human always be involved in supervising the decision making in the foreseeable?

Before addressing these questions, it is worthwhile reflecting on some of the historical perspectives that have emerged from research over the last few decades. Of these perhaps the most enduring application of AI technologies outside the military research sphere has been in the medical world.


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