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Increasingly, laws are being proposed and passed by governments around theworld to regulate Artificial Intelligence (AI) systems implemented into thepublic and private sectors. Many of these regulations address the transparencyof AI systems, and related citizen-aware issues like allowing individuals tohave the right to an explanation about how an AI system makes a decision thatimpacts them. Yet, almost all AI governance documents to date have asignificant drawback: they have focused on what to do (or what not to do) withrespect to making AI systems transparent, but have left the brunt of the workto technologists to figure out how to build transparent systems. We fill thisgap by proposing a novel stakeholder-first approach that assists technologistsin designing transparent, regulatory compliant systems. We also describe areal-world case-study that illustrates how this approach can be used inpractice.

Think About the Stakeholders First! Towards an Algorithmic Transparency Playbook for Regulatory Compliance