Contextual Intelligence – Short Explanation

Contextual intelligence refers to the ability to adapt and apply what has been learned, such as skills and knowledge, in different scenarios/situations.

A key phrase or saying, a hand gesture or look – all of these have different meanings based on where you live and work. The statement – context matters – cannot be emphasized enough. For anyone in business with international exposure, this is an almost self-evident truth. When it comes to the world of computers and AI, context is just as important.

How Contextual Intelligence Works in the World of AI

The term contextual intelligence has a very different meaning when it comes to the world of Artificial Intelligence (AI). AI is ubiquitous now and powers smart assistants like Alexa and Sira that we are all used to. However, while these devices are becoming increasingly smarter day-by-day, they frequently throw out answers that simply do not make sense in context to your question.

Contextual AI has learned from previous iterations of AI. Historically, AI was nothing more than a complex set of rules and algorithms. While sufficient to beat the world’s chess masters, the first iteration of AI was unable to understand and resolve problems in a manner similar to humans.

With the advent of deep learning and big data, the capabilities of AI expanded significantly. Now capable of being trained to recognize patterns and learn through training on large datasets, AI was considerably more useful. However, this “black box” approach did not engender trust as it was difficult to determine and understand exactly what the AI algorithm had learned.

This has led to the search for a new type of AI. Contextual AI offers an improved collaboration between man and machine algorithms, where the AI takes a more human-centric approach. With digital assistants continuing to grow in popularity and use, contextual AI is becoming ever more critical.