Rayid Ghani
Machine Learning Department and Heinz College of Information Systems and Public Policy
Office: Gates Hillman 8023
Email: rayid at cmu dot edu

Primary Appointment: Distinguished Career Professor, Joint Appointment in Machine Learning Department (School of Computer Science) and Public Policy (Heinz College).

Other CMU Affiliations:

Co-Lead, CMU Responsible AI Initiative
Software and Societal Systems Department, CMU
Block Center for Technology and Society
CMU-NIST AI Measurement Science & Engineering Cooperative Research Center (AIMSEC)
Carnegie Mellon Institute for Strategy & Technology

I am a Distinguished Career Professor at Carnegie Mellon University, with joint appointments in the Machine Learning Department (School of Computer Science) and Heinz College of Information Systems and Public Policy. I lead the Data Science for Social Good Lab and the DSSG Fellowship Program and co-lead CMU’s Responsible AI Initiative.

What I do

My work focuses on designing, developing, deploying, and evaluating Machine Learning and AI systems that improve real-world outcomes in public and social settings with an explicit focus on fairness and equity. I work closely with governments and organizations to build AI systems that are used in practice and produce measurable impact in areas such as public health, human services, criminal justice, and workforce development. I advise governments on AI governance, procurement, and evaluation, and have testified before the U.S. Senate and Congress on responsible AI and bias in automated systems.

Research and Practice

I work at the intersection of machine learning, public policy, and human decision-making, with a focus on:

  • “Human-centered” AI system design, including issues around explainability and interpretability
  • Evaluation of AI systems and real-world impact
  • Fairness, accountability, and governance of AI and ML Systems
  • AI for public sector decision-making

My work spans domains including human services, public health, criminal justice, housing, workforce development, and public safety.

Programs and Initiatives

I founded the Data Science for Social Good Summer Fellowship at the University of Chicago and continue to lead the program at Carnegie Mellon University. The program trains data scientists to work on high-impact social and policy problems in collaboration with governments and nonprofits.

I also develop and teach experiential training programs for students and professionals in government, nonprofit, and industry settings.

Policy and AI Governance

My work includes advising governments on the responsible use of AI, including issues related to procurement, evaluation, and bias.

Selected testimony:

Areas of Expertise

  • Machine Learning, AI, and Data Science
  • Human–AI Collaboration and Decision Systems
  • Evaluation of AI Systems and Real-World Impact
  • Responsible AI: fairness, accountability, and governance
  • Public policy applications of AI

Application Domains

  • Human services
  • Public health and clinical healthcare
  • Criminal justice and public safety
  • Housing and homelessness prevention
  • Workforce and economic development
  • Transportation and urban infrastructure

Recently (and reluctantly) added buzzwords: Artificial Intelligence, Data Science (not so recently)

Older buzzwords that are trendy now: Machine Learning

Not-so-old buzzwords that are not trendy now: Data Mining, Big Data, Analytics

Selected Experience

Before Carnegie Mellon University:

  • Founder and Director, Center for Data Science and Public Policy, University of Chicago
  • Faculty in the Department of Computer Science, and a Senior Fellow at the Harris School of Public Policy at the University of Chicago.
  • Chief Scientist, Obama for America (2012), leading data science efforts
  • Senior Research Scientist and Director of Analytics Research, Accenture Labs

I have led applied research and deployment efforts in machine learning and data science across sectors, including healthcare, financial services, retail & CPG, manufacturing, and government.

Additional Work

In my ample free time, I advise startups, nonprofits, and public sector organizations on the design and deployment of AI systems. I regularly speak at academic, industry, and policy forums and publish in machine learning, AI, and public policy venues.