Article by By Hoppe, Travis et al : “Generative Artificial Intelligence (AI) is redefining how people interact with public information and shaping how public data are consumed. Recent advances in large language models (LLMs) mean that more Americans are getting answers from AI chatbots and other AI systems, which increasingly draw on public datasets. The federal statistical community can take action to advance the use of federal statistics with generative AI to ensure that official statistics are front-and-center, powering these AIdriven experiences.
The Federal Committee on Statistical Methodology (FCSM) developed the Framework for Data Quality to help analysts and the public assess fitness for use of data sets. AI-based queries present new challenges, and the framework should be enhanced to meet them. Generative AI acts as an intermediary in the consumption of public statistical information, extracting and combining data with logical strategies that differ from the thought processes and judgments of analysts. For statistical data to be accurately represented and trustworthy, they need to be machine understandable and be able to support models that measure data quality and provide contextual information.
FCSM is working to ensure that federal statistics used in these AI-driven interactions meet the data quality dimensions of the Framework including, but not limited to, accessibility, timeliness, accuracy, and credibility. We propose a new collaborative federal effort to establish best practices for optimizing APIs, metadata, and data accessibility to support accurate and trusted generative AI results…(More)”.
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