A few months ago, I was invited to give a lecture at the workshop “decentralized insurance and risk sharing” organized the day before the Insurance: Mathematics & Economics conference , in Chicago, on fairness and networks. I took me some time (and a sabbatical) to write down some parts of my lectures that were not published. A short article is now available, entitled “Perceived Fairness in Networks” (this can be related to the recent papier Linear Risk Sharing on Networks we uploaded with Philipp Ratz).
The usual definitions of algorithmic fairness focus on population-level statistics, such as demographic parity or equal opportunity. However, in many social or economic contexts, fairness is not perceived globally, but locally, through an individual’s peer network and comparisons. We propose a theoretical model of perceived fairness networks, in which each individual’s sense of discrimination depends on the local topology of interactions. We show that even if a decision rule satisfies standard criteria of fairness, perceived discrimination can persist or even increase in the presence of homophily or assortative mixing. We propose a formalism for the concept of fairness perception, linking network structure, local observation, and social perception. Analytical and simulation results highlight how network topology affects the divergence between objective fairness and perceived fairness, with implications for algorithmic governance and applications in finance and collaborative insurance.
As a mention in my slides, my point is that group fairness is based on global statistics. But locally, individuals cannot observe everyone’s outcome, they might see only the outcome of their neighbors (in the network terminology)

This topology gives very different concept, e.g., the variance

or the covariance

If the variable of interest x is independent of the position on the network, then the topology of the network has no real impact. But if there is a correlation between x and the degrees d, those two concepts are different. This is the difference between “real variance” and “perceived variance”.

In “Perceived Fairness in Networks“, I show that if there is homophily in the network, then individuals might a perception of important discrimination, even if globally, there is no discrimination.




































Demand for gas in gas stations in Britanny, and demand for maternity in France (with border correction)
In addition to this paper we released a 