How to Code Algorithms to Favor Public Goods Over Private Ones

Abstract

The world has become too complex to entrust management only to flesh-and-blood human governance, which such complexification disarms. Facing this multiplication of threatening complexities, we are accepting more and more to be helped by ubiquitous algorithmic assistances. Often these algorithms treat their user through dedicated focus, in a privileged way, as if they were the only ones in the world. While we might accept such algorithmic orientation and very focused targeting for some specific domains of our life, decisions that impact our public goods are of a complete different nature (like it is well known for long in economic science). In this paper, to mainly convey the idea and for sake of pedagogy, I will use the example of GPS and automatic navigation systems that make an important use of shortest path algorithm to connect the departure and the destination points in complex road networks and in a way that is supposed to maximally satisfy the users. Taking for granted that most of these algorithms run in an individualistic manner, I will show how departing from such an individualistic version of them, it is possible, through a succession of iterations and the definition of a cost function that takes into account the cumulated collective impact of the previous iterations, to gradually reach a much more satisfactory solution for the collective whole. I will finally discuss who should be in charge of the writing of these algorithms once they are dedicated to the public goods and by definition escape the private sector.