Algorithmic Bias

[Technical Overview] Meta’s recent decision to dismantle its Diversity, Equity, and Inclusion (DEI) programs signifies a significant shift in corporate strategy, with potential ramifications for the tech industry. The core technical concept at play here isn’t just about hiring quotas, but also about how algorithmic fairness and ethical AI development are approached within organizations. Companies like Meta, which heavily rely on machine learning models, have a responsibility to proactively mitigate bias in these systems....

[Technical Overview] The increasing use of artificial intelligence (AI) and machine learning (ML) in tenant screening raises significant concerns about algorithmic bias, transparency, and fairness. Traditionally, tenant screening involved manual review of credit reports and rental history. However, with the advent of AI, automated systems are now used to generate risk scores based on complex algorithms. These algorithms often rely on historical data, which can inadvertently perpetuate existing societal biases. This can lead to discriminatory outcomes, where applicants from certain demographics are disproportionately denied housing opportunities without a clear understanding of the reasons behind the decisions....