This article was contributed by Slater Victoroff, founder and CTO of Indico Data. There is a belief, built out of science fiction and a healthy fear of math, that AI is some infallible judge of objective truth. We tell ourselves that AI algorithms divine truth from data, and that there is no truth higher than the righteous residual of a regression test. For others, the picture is simple: logic is objective, math is logic, AI is math; thus AI is objective. This is not a benign belief.

Lets imagine for a moment that the horse you see in the image below is sick and dying.

Each year, nearly 120 million units of donated blood flow from donor veins into storage bags at collection centers around the world. The fluid is packed, processed and reserved for later use. But once outside the body, stored red blood cells (RBCs) undergo continuous deterioration. By day 42 in most countries, the products are no longer usable. For years, labs have used expert microscopic examinations to assess the quality of stored blood.

Car accidents can be the tragic byproducts of any number of factors, each more unpredictable than the next: a sudden thunderstorm, a busy intersection, or even perhaps, gravel on the road. These are just a few examples of the great deal of uncertainty government officials must deal with every day. Even the colours used in a heatmap can sway decisions, says Mansour Raad, a subject matter expert on Advanced Analytics, BigData and AI at Esri, the leading GIS company. However, policies must always be made on accurate facts rather than human subjectivity. We look at how sensors, artificial intelligence, and geospatial technologies can help officials dig out underlying causes, identify patterns, and ultimately, make informed decisions. Government officials are now able to gather an extensive amount of data from the environment and infrastructures using ubiquitous sensors.