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Data Justice Lab Seminar Series: 

Delivering Effective Risk Communication Using Interactive Informatics Tools to Facilitate Environment Literacy, Health and Equities

Nov 11, 2024

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Location: Blocker 220

Bio

Dr Carolyn A. Lin is a Professor of Communication at the University of Connecticut. Her research integrates specific multimedia narratives—tailored to target different audience segments— with digital informatics and data science tools to achieve effective communication outcomes. Her research has been funded by NSF, NIH, EPA, U.S. Department of Education, and State of Connecticut. She is a fellow of the International Communication Association and the founder of the Communication Technology Division for the Association for Education in Journalism & Mass Communication.

Abstract

The major barriers of developing and delivering effective risk communication messages reflect the reality that our audiences have diverse demographic backgrounds, sociocultural values and political ideologies, in addition to low health and environmental literacy. Other barriers can be attributed to the widespread misinformation, disinformation and conspiracy theories about public health and environmental issues that are commonly seen and believed by selected segments of the public.

Data-science-driven informatic tools can be developed to facilitate the desired risk communication objectives. For instance, these tools can be designed to allow users—to 1) process information with ease, 2) learn the health and environmental protection techniques in a real-world scenario, and 3) apply these techniques in an immersive environment—to help improve environmental literacy, health and equity.

The challenges of environmental health and equity issues will continue to burden our economy, security, health, safety, and quality of life. For this reason, we need to remain vigilant about designing data tools such as machine-learning algorithms and generative AI to present science-based facts to counter the spread of pseudo-science misinformation through data manipulation.

The seminar talk is available to watch at the following link: https://youtu.be/0EvW4G-sq1s?si=jAjFqSpL9dYe0Hio

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