Data-driven innovations offer enormous opportunities to advance important societal goals. However, to take advantage of these opportunities, individuals must have access to high-quality data about themselves and their communities. If certain groups routinely do not have data collected about them, their problems may be overlooked and their communities held back in spite of progress elsewhere. Given this risk, policymakers should begin a concerted effort to address the “data divide”—the social and economic inequalities that may result from a lack of collection or use of data about individuals or communities.
Daniel Castro
Daniel Castro is president of the Information Technology and Innovation Foundation (ITIF), the world’s top-ranked think tank for science and technology policy, where he leads the organization’s work shaping debates on critical issues at the intersection of technological innovation and public policy. He is a prolific writer and respected public speaker on issues ranging from Internet policy and digital governance to artificial intelligence and other emerging technologies. Castro also founded and is director of ITIF’s Center for Data Innovation, a leading voice on open data, artificial intelligence, and digital transformation. He has played a key role in advancing the OPEN Government Data Act and has long worked on the policy and economic impact of data-driven innovation. His work on AI spans a broad range of policy issues, including adoption and diffusion, privacy and security, intellectual property, deepfakes and information integrity, and the economic and competitive dynamics of AI, as well as global competition and governance—particularly in China and Europe.
