By Luca Nannini, PhD at Indra, Minsait.

Benjamin Mueller, Senior Policy Analyst at Center for Data Innovation, sat down with Luca Nannini, a PhD student in AI at the University of Santiago de Compostela and data analyst at Minsait, INDRA. Mr. Nannini discussed his work on explainable AI, including the various technical and social dimensions of explainability. He highlighted the importance of thinking about the user when designing explainable systems and offered his thoughts on how explainability principles should inform thinking on future AI development.

Benjamin Mueller is a senior policy analyst at the Center for Data Innovation, focusing on AI and technology governance. Prior to joining the Center he was chief of staff at a financial technology company in London. Dr. Mueller studied Politics, Philosophy and Economics at the University of Oxford, and completed his PhD in International Relations at the London School of Economics.

Headed by Daniel Castro, the Center for Data Innovation is the leading think tank studying the intersection of data, technology, and public policy. With staff in Washington, DC and Brussels, the Center formulates and promotes pragmatic public policies designed to maximize the benefits of data-driven innovation in the public and private sectors. It educates policymakers and the public about the opportunities and challenges associated with data, as well as technology trends such as open data, artificial intelligence, and the Internet of Things..


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