Machine Learning for a Better World

We live in a world in which the economic process works from the aggregation of millions of individual, and to great extent independent, decisions that look for the maximization of private profit. This economic basis is proven to be the source of increasing inequalities contradictorily with the fact that it is able to constantly produce better goods with an increasing productivity potentially satisfying human needs. On top of this, we have to bear in mind the damaging environmental footprint of such an economic basis.

More than ever before, it is urgent rethinking the economic process to be based on a rational planning approach that is optimized towards the satisfaction of human needs and according to goals that are democratically decided. The impressive advancements over the last decades in different areas like communications, computer science and artificial intelligence make it possible to resume the work of brilliant mathematicians like Victor Glushkov in order to deploy an efficient and rationally planned economic process. Of course, machine learning would play an important role by, e.g., helping to optimize production in real-time towards consumers' preferences.