Algorithmic transparency is the basis of machine accountability and the cornerstone of policy frameworks that regulate the use of artificial intelligence techniques. The goal of algorithmic transparency is to ensure accuracy and fairness in decisions concerning individuals.AI techniques replicate bias, and as these techniques become more complex, bias becomes more difficult to detect. But the principle of algorithmic transparency remains important across a wide range of sectors. Credit determinations, employment assessments, educational tracking, as well as decisions about government benefits, border crossings, communications surveillance and even inspections in sports stadiums increasingly rely on black box techniques that produce results that are unaccountable, opaque, and often unfair. Even the organizations that rely on these methods often do not fully understand their impact or their weaknesses.