AI and Accuracy
AI is about Statistical Relationships, not Functional Relationships, Executives need to understand Accuracy to make business decisions around AI
By; J M Stadtmueller
As the story goes, when Newton observed an apple falling from a tree, he developed a functional relationship between force, mass, and acceleration due to gravity. With this relationship (F=ma), many things can be “determined” from that equation. AI does not work that way. In this scenario, with AI, thousands or millions of different types of things would be observed falling from different types of things and from different heights. Based on “seeing” all that happens (being trained) the AI system could then make predictions (inference) about how other things will fall. The AI system is statistical. Specifically, it will get some things right and some things wrong. The question that follows is how “accurate” is the AI system in making that prediction?
In business systems, the more important question is how accurate does the AI system need to be? In the current state of AI, it seems, that with more and more data and computing power, training an AI system can become more accurate. But, more and more data and computing power, and more specialized skills to “wrangle” that data comes at greater cost. So, a business executive needs to understand that not only does the objective need to be clearly identified, and the data needed to train to that objective identified, the required accuracy needs to be defined.
For instance, a business creating a fun system based on AI (i.e. recognizing dogs and cats) may not need to be that accurate. However, a system used by a veterinarian to determine a symptom in a dog should be more accurate. A self-driving car that can determine the difference between a dog and or some leaves in the road, needs to be exceedingly accurate. The accuracy required for a specific business system directly relates to data, training time, effort and computing power needed and so is a critical part of business cases.
When deciding your business case for using AI take into account how mission critical accuracy is to the project and take an educated, savvy approach to defining your needed outcomes.