Defining Digital Intelligence: No Small Task!
Defining DI is not a simple thing because the definition has evolved since 1960 (Buchanan, 2005). At the time, some algorithms could enter into a rather vague definition of DI, whereas today they are taught as part of classic problem-solving strategies and not as instances of DI (Rich, 1988).
DI is very far from replacing human intelligence today, and it is difficult to estimate the extent of DI development in the future. Projections range from a limited application of DI in the coming decades to achieving a technological singularity in the relatively near horizon. This singularity would be a point of no return where DI could develop itself exponentially, jeopardizing any human control over it.
However, it is not necessary to consider extreme scenarios for advances in DI, even from a conservative perspective, to deserve the attention of education stakeholders (Karsenti, 2018}). DI is creating new needs for a specialized workforce as well as a need for citizens to have a good grasp of the issues surrounding digital tools. Actors in the education community can react to or prepare for change.
In its simplest form, Digital Intelligence can be defined as a field of study aimed at the artificial reproduction of the cognitive faculties of human intelligence in order to create software or machines (robots, platforms, etc.).
Digital Intelligence is therefore also computer programs - or machines like robots - able to learn and apply the knowledge acquired to solve problems. DI is therefore able to solve problems by learning from data, patterns, and models. Digital Intelligence is found in several fields and applications in education (Sanchez & Lama, 2008). The point of DI is to relieve humans of certain, sometimes more complex, tasks by automating them.
It seems necessary to present some key concepts of this current field (Najafabadi at all, 2015).