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NORC at the University Chicago
NORC unlocks the full potential of AI through tailored, fit-for-purpose solutions that deliver insights and analysis that decision-makers trust.

NORC develops fit-for-purpose AI solutions to meet our clients’ needs. Our expertise covers the full AI lifecycle, from data quality assessment, record linkage, and confidentiality and privacy to computational algorithms, assessing and mitigating bias in AI models, user experience research, and multidisciplinary subject matter expertise. With such expertise, NORC is the trusted source in AI—tailoring solutions to clients’ specific needs.  

  • Methodological enhancement: Our data science experts use AI to expand the state of the art in fields like survey methodology and statistics, and to build innovative AI systems that help clients derive trustworthy insights from their data. 
  • More effective and wide-ranging data integration: With AI, NORC can help clients take advantage of non-traditional data, such as audio, images, video, and text, and extract even richer insights from traditional sources, such as surveys and administrative data.   
  • AI-ready data and infrastructure: NORC is a proven leader in helping organize data to be effectively leveraged by AI and in designing infrastructure to support AI research.   
  • Actionable, boundary-pushing research: In addition to using AI, NORC also conducts research about AI and its effects in different domains. NORC’s AI research helps clients understand the societal impacts of this consequential technology. 

Following the principles of human-centered AI, NORC is working to make AI research, products, and services more equitable by understanding and mitigating the bias that AI can introduce. This human-centered approach improves user experiences and results in insights that benefit society as a whole. 

Highlighted Projects

Artificial Intelligence for Enhancing Data Quality, Standardization & Integration

Applying innovative data science methods to create datasets that support evidence-based decision-making

Client:

National Center for Science and Engineering Statistics

Artificial Intelligence in Graduate STEM Education

Examining the use of artificial intelligence in STEM graduate programs and its effect on diversity, equity, and inclusion

Client:

Alfred P. Sloan Foundation

Clinical Decision Support Innovation Collaborative

Translating patient-centered outcomes research into effective practice

Client:

Agency for Healthcare Research and Quality

Data Concierge Models for a National Secure Data Service

Developing novel models and tools to assist federal data users

Client:

National Center for Science and Engineering Statistics

Data Usage Platform as a Federal Data Asset

User experience research and prototyping for a federal data usage platform

Client:

National Center for Science and Engineering Statistics

Developing a Supervised Model of Online COVID Vaccine Information

Examining AI biases in model development to accurately detect and classify online COVID-19 vaccine information

Client:

Amazon Web Services (AWS)

Graduate Research Fellowship Program Pilot Project

Innovating data collection methods to track National Science Foundation research fellowship outcomes

Client:

National Science Foundation

Health Communication AI

Combining the trust-building ability of digital opinion leaders with the scalability of AI to revolutionize health communication

Workforce Challenges & Technology Adoption for Health Information Professionals

Examining the current state of the health information workforce and the use of artificial intelligence

Client:

American Health Information Management Association

Our Insights

WATCH: Susan Paddock on AI & Equity

EquityCorps Video Series

In this interview, Susan Paddock sheds light on how artificial intelligence (AI) can help advance equity.
Susan-Paddock_cropped - 1

Like Parent, like Teen: AI Usage Patterns Reveal Striking Parallels Across Generations

NORC Education

A NORC Spotlight on Education survey powered by AmeriSpeak® finds that American teenagers use AI at about the same rate as adults under the age 60.
A horizontal stacked bar chart comparing AI usage across three age groups: teens, adult Gen Z/Millennials/Gen X, and adult Boomers. Teens and adult Gen Z/Millenials/Gen X have similar adoption rates (53% and 48% respectively) while adult boomers have lower adoption rates (18%)
opens in new tabDisinformation, AI and poll-worker problems: How elections this week could preview 2024

USA TODAY

opens in new tabWhat Are the Limits of Big Data?
opens in new tab5 Steps for Nonprofits to Begin Cloud-based Machine Learning

Publications

Publications on Artificial Intelligence

Artificial Intelligence Experts