This thesis seeks to identify the increasing apparency of discriminatory behavior in the decision-making processes of artificial intelligence algorithms and identify which states are best prepared to prevent this new discrimination – both in terms of artificial intelligence readiness and responsible deployment. Through comparative analyses between the infrastructures of OECD states leading the way in artificial intelligence development and deployment, it seeks to explain why those states that

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... ve the greatest capacity and readiness for artificial intelligence may not necessarily be the states most apt at responsibly preventing artificial intelligence discrimination moving forward. From these analyses, it is argued that several clear patterns can be identified: states with smaller and less developed private technology sectors have a stronger focus on responsible development over large-scale deployment and states with a pre-existing prioritization for human rights and privacy infrastructure are more prepared to enact stronger protections against automated discrimination. Upon further case study analysis between the United States and Estonia, it is argued that these trends are indicative of a greater dichotomy between states that prioritize private sector innovation and those that prioritize responsible, equitable artificial intelligence applications in public sector services.