Meet the Harvard CID faculty affiliates harnessing technology and data science to drive innovation, inform policy, and accelerate progress around the world.
Advances in technology and data science are transforming economies—enabling smarter solutions, fueling innovation, and driving sustainable growth.
For many, digital tools are transforming opportunities in work, education, and entrepreneurship. Yet challenges such as the digital divide, ethical risks, and inadequate data infrastructure remain. At CID, our research in technology and data science explores how artificial intelligence, machine learning, data analytics, and digital platforms can be harnessed to solve real-world development challenges.
Faculty affiliates from across Harvard investigate how technology can enhance decision-making, empower communities, and scale impact. From analyzing the role of big data and automation to studying how innovation fuels inclusive progress, CID researchers are generating insights to guide data-driven, equitable development.
Harvard CID Faculty Affiliates Advancing Research on Technology & Data Science
Thomas S. Murphy Professor of Business Administration, Harvard Business School
Clarence James Gamble Professor of Biostatistics, Population, and Data Science, Harvard T.H. Chan School of Public Health
Ricardo Hausmann
Ricardo Hausmann
Rafik Hariri Professor of the Practice of International Political Economy, Harvard Kennedy School
Gordon McKay Professor of Computer Science; Director of Center for Research on Computation and Society at Harvard University, Harvard John A. Paulson School of Engineering and Applied Sciences
Cahners-Rabb Professor of Business Administration, Harvard Business School
Associate Professor in the Department of Global Health and Population, Harvard Medical School
Featured Research on Technology & Data Science
CID faculty research insights look at publications by Harvard faculty that have shaped current understanding of technology and data science. These summaries distill complex findings into accessible takeaways for practitioners, policymakers, and researchers.
CID Faculty Publications
Read the latest research from CID faculty affiliates on technology and data science, exploring areas such as artificial intelligence, machine learning, data analytics, innovation, and digital transformation. These publications provide evidence-based insights to advance decision-making, solve complex problems, and promote inclusive technological growth.
Data-intensive Innovation and the State: Evidence from AI Firms in China
Data-intensive Innovation and the State: Evidence from AI Firms in China
Developing AI technology requires data. In many domains, government data far exceeds in magnitude and scope data collected by the private sector, and AI firms often gain access to such data when providing services to the state. We argue that such access can stimulate commercial AI innovation in part because data and trained algorithms are shareable across government and commercial uses.
CID Faculty Affiliate:
Deep Learning for Economists
Deep Learning for Economists
Deep learning provides powerful methods to impute structured information from large-scale, unstructured text and image datasets. For example, economists might wish to detect the presence of economic activity in satellite images, or to measure the topics or entities mentioned in social media, the congressional record, or firm filings. This review introduces deep neural networks, covering methods such as classifiers, regression models, generative AI, and embedding models.
CID Faculty Affiliate:
The Challenges of Scaling up Effective Child-Rearing Practices Using Technology in Developing Settings: Experimental Evidence From India
The Challenges of Scaling up Effective Child-Rearing Practices Using Technology in Developing Settings: Experimental Evidence From India
A study of 2,400 caregivers in India tested parenting advice via phone calls. Despite high participation, the tech-based program didn’t boost child development—and even slightly raised parental anxiety. Simple tech alone may not replicate the impact of hands-on support.
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Explore research from CID faculty affiliates on how technology and data science innovations drive problem-solving, informed decisions, and economic growth.