Dealing With Context in AI


By Imène Brigui

The notion of context, both vague and fascinating, makes sense when it comes to decision making. It caught tremendous interest in many studies from several disciplines of decision sciences, psychology or digital sciences and increasingly in artificial intelligence. But what do we really mean by context?

Context is key in everything we do : to understand, analyze a situation, project ourselves, put into perspective and act in an informed way. In other words, everything is context! For managers, approaching context is crucial, whether for forecasting, interpreting and justifying performance, negotiating, carrying out market analysis, etc.

The managerial dimension is not limited to the used tools and techniques to support managers’ decision-making but explores new horizons to better understand habits, preferences, consumption patterns … From a more concrete point of view, today we benefit from several technological advances which bring actual added value and that companies should consider at two main levels:

How to integrate context in decision-making process?

Everything becomes instrumentalized, connected and intelligent. Particularly due to hyperconnectivity with the explosion of IoT. You can get the exact situation of almost everything. One of the challenges in integrating context is to build sense by crossing several data coming from various channels, with different associated semantics and structures and at multiple levels. To get as close as possible to the reality of a certain situation, it is essential to have ubiquitous systems able to reach optimal perception of the moment and to make links between similar situations at different times and with different stakeholders.

How to connect context with Big Data?

Big data and all the associated collection and analysis tools have empowered today’s systems perception. We are now close to identify all the elements characterizing the state of objects, individuals or organizations. With Big Data, understanding the context has become a necessity. Big data has undoubtedly opened up new horizons in terms of data accessibility and processing, but also faces so many challenges of expressiveness and interpretability of these data. Companies must question data more and constantly push the boundaries of acquisition and appropriation of these data.

Understanding Big Data in a contextualized way leads to precise, relevant and accurate “Small Data”. To do this, the Micro customer-oriented context and the Macro market-oriented and environmental context must coexist and interact to create value through contextual AI. Thus, small changes at the level of elementary, local and isolated data (generated and collected automatically) crossed with Market data (Business Intelligence, market scanning, etc.) can significantly and very effectively support and guide the decision-making process.

connect context with Big Data

Human + Machine is the right equation

To conclude, more than ever, bridging Human Intelligence and Artificial Intelligence to seize context is important. The way humans act and interact with their environment is crucial to enhance factual and logical reasoning.

While machines are empowering decision makers with high computational abilities and short processing cycles, humans must empower machines by bringing subjectivity, expertise, nuance and by adding new relevant dimensions.

The right understanding of context couldn’t be achieved without setting the right equation Human + Machine and so empowering human abilities from one side and training and educating machines from the other side.

About the Author

Imène Brigui

Imène Brigui, associate professor and researcher at emlyon business school, holds a PhD in Computer Science from Paris Dauphine University. Her research areas focus on Artificial Intelligence and in particular Intelligent Agents. During more than 15 years’ experience in research and teaching, she has been involved in several research projects and pedagogical responsibilities. She is also engaged in multiple AI and Data communities in France and abroad. 


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