A Review of Bias and Discrimination In Digital Platforms

Abstract

Digital bias and discrimination have become major concerns around the world, prompting developed and developing countries to set up a legal framework to address the issues; recent articles revealed that Nigeria took a step in this establishment. Users of digital platforms are treated unfairly, unethically, and partially discriminated against based on personal data that is automatically processed by an algorithm. This study used a mixed methods research design. This included conducting a literature search, conducting a systematic literature review by assessing the literature, and analyzing studies on digital discrimination. Digital discrimination often replicates offline discrimination, either by inheriting the biases of previous decision makers or simply reflecting societal prejudices. It may also worsen existing inequalities by giving less weight to historically disadvantaged groups. This review examines this difficult problem, existing solutions, and their limitations from a legal and computer science standpoint. An empirical Study of Apparent Gender-Based Discrimination in the Display of STEM Career Ads is featured in the review to highlight algorithmic bias. It concludes with a road map of outstanding issues for mitigating these constraints. Keywords: Digital Discrimination, algorithmic bias, Machine Learning, AI, Online advertisement