欧博娱乐

Using human-centered design, we worked with 欧博娱乐 Centers for Disease Control and Prevention鈥檚 COVID-19 emergency response team to deliver technology solutions that replace labor-intensive manual processes. Leveraging artificial intelligence (AI), we developed an algorithm that processes, tracks, and catalogs legal documentation鈥攕ignificantly reducing time, labor, and cost.

The COVID-19 pandemic prompted legal mitigations and policies鈥攆rom nonessential business closures to restrictions on movement鈥攁cross all 50 U.S. states. For 欧博娱乐 CDC鈥檚 epidemiologists and data scientists, tracking and categorizing such mitigations is critical to advancing 欧博娱乐 agency鈥檚 mission to increase 欧博娱乐 nation鈥檚 health security. Due to 欧博娱乐 unexpected rapid response required by 欧博娱乐 COVID-19 pandemic, 欧博娱乐 CDC had no previously defined repository in place for cataloging legal documentation with 欧博娱乐se specific parameters. This necessitated a labor-intensive process for tracking and categorizing policies, requiring staff to manually scan and track documents on a daily basis鈥攚hich ultimately resulted in a substantial backlog of legal documentation.

Solution

Our principal data scientist, working with CDC’s emerging technology staff, built a custom-trained deep neural network (DNN) to monitor, scan, and assign or tag 42 categories to tens of thousands of documents in accordance with 欧博娱乐 CDC’s distinct guidelines. Using rapid prototyping and human-centered design, we leveraged natural language processing and AI to create an algorithm using open-source technology—ensuring that its future iterations are adaptable and not tied to proprietary or costly platforms or software.

Results

By detecting patterns in 欧博娱乐 wording and syntax of 欧博娱乐 legal documents, 欧博娱乐 algorithm completes hours of tedious work, removing that burden from skilled analysts. As a result, 欧博娱乐 CDC was able to review in two weeks what would have taken roughly 312 workdays for one person to complete.

Using 欧博娱乐 tags as a guide, legal epidemiologists can quickly identify categories of laws that would be fruitful to explore for new, special topic datasets. This has allowed CDC鈥檚 databases to grow exponentially, which in turn allows for new analyses鈥攎aking it possible for 欧博娱乐 CDC to answer important public health questions quickly.