From Network Inequality to Network Fairness: A Perspective on Responsible Decision-Making
Social networks shape how individuals make decisions and how opportunities are distributed. However, the mechanisms that generate these networks often reflect pre-existing inequalities, and technologies that rely on network-derived signals risk further amplifying such disparities. Algorithmic fairness research largely treats networks as a fixed background, grounding analysis almost exclusively in distributive justice and overlooking how network structures systematically bias decision-making. In this Perspective, we identify ten network effects and trace how they create structural biases in the relationship between what we intend to measure and what we observe. Using academic hiring as an ...
| Authors | Lisette Espín-Noboa, Tina Eliassi-Rad, Pak-Hang Wong et al. |
|---|---|
| Primary category | cs.SI |
| Published | 12 September 2026 |
| Last updated at source | 12 September 2026 |
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