Year: 2026
Type: article
Abstract: Artificial intelligence systems increasingly influence critical societal decisions, from healthcare resource distribution to criminal justice evaluations. While John Rawls’ theory of justice, especially his “veil of ignorance,” has become a prominent framework for promoting algorithmic fairness, this paper reveals a fundamental paradox in its use: unchanging principles of justice, when applied in evolving AI systems, can sustain or worsen existing inequalities. We demonstrate how algorithmic systems that meet initial Rawlsian fairness standards can create growing disparities through feedback loops and systemic biases. Our healthcare case study shows how seemingly neutral resource allocation algorithms can systematically harm vulnerable groups even when they meet formal fairness criteria.
Author: Dwayne Woods
Institution: Purdue University West Lafayette
Language: English
Subfield: Safety Research
Field: Social Sciences
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid: $2,390
OpenAlex ID: W7135090965