Generative AI 101: How Survey Researchers Can Apply AI
November 8, 2024 at 11:30am CT
Claire Kelley and Sarah Kelley
Child Trends
How can generative AI be used to support survey research? In this introductory webinar we will provide a primer on how generative AI works and how it can be used for survey research. This course will cover a (math free) introduction to how generative AI models are built, and introduce core concepts such as API’s, transformers, prompt engineering, few-shot learning, and fine-tuning. We will provide a brief overview of how generative AI is currently used in survey research with a focus on how learners can apply these concepts to their own research.
Registration to this webinar gives you access to the live webinar as well as access to the recording for one price. The cost for MAPOR members is $10, $40 for non-members, and FREE for students with a valid .edu email address.
 | Claire Kelley is a co-program area director of data science and senior data scientist at Child Trends, where she conducts and supports research across all program areas. Her primary research interests focus on the intersection of machine learning and social science, particularly in the domains of health and education. In her work, Claire blends traditional quantitative methods with machine learning and software engineering. Some of her recent projects include using computer vision to assess bias in news articles, co-authoring an open source software package for fitting mixed effects models with complex survey weights, and creating an interactive JavaScript-based data story about algebra enrollment. In addition to writing software and conducting research, Claire is passionate about creating a community of practice around data science for social research. She regularly presents her research and teaches professional development courses at data science and social science conferences including PyData, the American Association for Public Opinion Research, and the American Education Research Association. Prior to joining Child Trends, Claire worked as a data scientist at the American Institutes for Research (AIR) and at Merck. At AIR, Claire worked on a variety of data engineering and data science projects and led the data visualization and reporting working group. At Merck, she worked on e-commerce data science, including developing a parallelized system for generating product recommendations and using time series models for forecasting product demand. She holds a bachelor’s degree in statistics from Yale University and a master’s degree in quantitative methods from Columbia University. |
 | Sarah Kelley is a co-program area director of data science and senior data scientist whose research focuses on applying data science techniques— especially natural language processing, computer vision, and machine learning—to answer questions related to social science and education. She has worked on a diverse set of social science problems, from using social media data to explore public conversations around child abuse in Haiti, to using big data and geospatial statistics to understand drivers of the opioid crisis, to using natural language processing to gain insight into political polarization online. Sarah is particularly excited about the potential of data science methods to augment traditional research methods. She seeks to make her work accessible to general audiences through data visualization. She also hopes to support quantitative researchers by using data science methods to create and integrate rich data sets, providing data access through application programming interfaces, and linking data sets using machine learning methods. Previously, Sarah was a data scientist at the American Institutes for Research, where she led projects focused on applying computer vision algorithms in education contexts, developing large-scale data processing pipelines, and using machine learning techniques to improve predictive modeling. She holds a bachelor’s degree in sociology from Yale University and a master’s degree in data science from the University of California, Berkeley. |