Cho + Greenstein Analytics

We provide technical solutions for social scientists by connecting AI tools with human-centered practices. Our work helps to make sense of large amounts of complex or unstructured data, whether textual or numerical, and to make findings more accessible to the world. We aim to help our clients build capacity, develop flexible tools, and explore emerging technologies.

Principles

Technologies like AI can make new kinds of work in social science possible, but they must be used thoughtfully. Without due care, studies show that issues can arise with ethics, equity, and human oversight. We believe in a shared duty to adopt AI tools responsibly, and we believe that doing so requires deep understanding of both the technology and the specific research context. To meet this challenge, our work at Cho + Greenstein Analytics is rooted firmly in both human-centered practices and technological expertise. Each project we undertake begins with a co-created foundation of ethics, equity, and human participation. This way, we help our clients use emerging tools to do exciting new things, while remaining in control, informed, and fully aligned with their values.

Services

Understanding large amounts of textual information with AI assistance

  • Qualitative coding or categorization of lengthy implementation reports
  • Summarization or thematic analysis of large numbers of interviews

Analyzing messy, complex, or unpredictable data using AI tools

  • Crawling the web for insights into where a program is offered or how it is described
  • Building a cohesive dataset based on tables found across thousands of PDFs

Building custom tools for dissemination and open access

  • An AI-assisted research navigator to help readers find the answers they need from a library of reports
  • An AI chatbot that helps convey technical information in a more accessible way

Safeguarding for ethical and equitable AI use in new and existing systems

  • Quantitative vetting to ensure a new AI tool is free from algorithmic bias
  • Stakeholder engagement to assess privacy concerns and select appropriate protections

Creating efficiencies in quantitative analysis, particularly impact evaluations

  • An AI-enhanced system that can assist quasi-experimental design by helping balance treatment and comparison groups for regression
  • Assisting the creation and editing of literature reviews

Developing data pipelines to support AI and modernized analysis workflows

  • An AI-enhanced tool to detect anomalies in incoming data
  • Analysis code connected to a secure data repository

Compliance and process management

  • Bringing an AI tool into alignment with organizational IT security policies
  • Education and outreach about responsible AI use

Visualizing data

  • Live visuals built into internal data pipelines
  • Automated reporting systems to help social scientists access the information they need
Contact Us