
By: Joseph Boyer (Dublin City University Law & Tech Research Cluster)
Picture a world where algorithms, not people, decide your financial future. This is already happening in some countries, where algorithmic lending offers the promise of efficiency but also raises serious concerns about fairness and discrimination.
While algorithmic lending can improve access to credit and streamline the process, it also introduces significant risks. Biased algorithms, trained on historical data, can reinforce existing social inequalities, leading to unfair treatment and fewer opportunities for marginalized groups. Research has shown that certain racial and gender groups are often disproportionately denied loans as a result.
This post draws from Joseph Boyer’s master’s dissertation, “Algorithmic Creditworthiness: A Legal Dissection,” which thoroughly explores the effectiveness of legal frameworks in tackling algorithmic bias in AI-driven lending…
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