César Rentería, Public Administration and IT

Information Technologies in Government

Policymaking innovation: focusing on improving information capacity and AI integration.

César Rentería
César Rentería
Associate Professor, CIDE

I am a Centro de Investigación y Docencia Económicas (CIDE) professor in Mexico City and hold a Ph.D. in Public Administration and Policy from the State University of New York. I am a member of the Technical Committee Specialized in Government Information for the National Institute for Statistics, Geography and Informatics (INEGI, by its acronym in Spanish); have been a visiting researcher at Columbia University and the National University of Ireland; and have served as consultant for Inter-American Development Bank, Development Bank of Latin America, United Arab Emirates, Tinkler Foundation, Ministry of Communications and Transport, and National Institute of Telecommunications, among others. I was awarded the Digital Governance Junior Scholar Award by the American Society for Public Administration and the Research Grant for Young Researchers Amy Mahan by the International Development Research Centre.

I specialize in information technologies in organizations. As we all know, emergent technologies are transforming how we produce, use, and share information in our personal lives and jobs. Understanding and mastering the application of these tools can help us transform how governments operate. For example, how governments relate with their citizens, design and implement public policies, or deliver public services. Currently, I focus on three topics in this area: how governments can consolidate their information capacity (that is, their ability to produce, process, and use information), how we can harness the benefits of artificial intelligence in the public sector, and how new approaches for policymaking can help to renovate the way public policies address old problems.

These lines of research require digging deep into cases (of success or failure in using information technologies), documenting and systematizing lessons from pilot projects, and developing hypotheses of the mechanics of information technologies put into practice. I enjoy the process of clarifying my understanding of these mechanics so that I can later contribute to the community of practice in information systems management with descriptions, explanations, or recommendations of how emergent technologies can improve government performance; I also enjoy sharing my ideas with colleagues and learning from their ideas and expertise. Sometimes, it is enough to read the literature to clarify my mind. Still, other times, I need to talk to people, look at data and statistics, and analyze documents to understand this field better. Connecting those insights with the literature is one of the things I like the most about my research.

For example, I am trying to understand better information capacity and artificial intelligence, two very connected topics. Data quality determines—to a great extent—the quality of an AI application in the public sector. However, data quality is still a loose concept that depends very much on knowledge domains and theoretical frameworks. Understanding how a public organization can attain data of high quality is even more difficult, as socio-technical processes are involved across different stages of the information cycle. We also must keep an eye on the rapid adoption of AI in society and better understand how these applications impact (for better or worse) the government's performance—not only on efficiency and effectiveness but also in its compliance with public values. Therefore, with my research, I also seek to contribute to a better understanding of the processes, development, and deployment of AI applications in the public sector and the organizational capacities governments need to attain the ethical use and sustainability of such applications.