Location
Online
Event Website
https://hicss.hawaii.edu/
Start Date
3-1-2023 12:00 AM
End Date
7-1-2023 12:00 AM
Description
This paper reports on research into online misinformation pertaining to the COVID-19 pandemic using artificial intelligence. This is part of our longer-term goal, i.e., the development of an artificial intelligence (machine-learning) tool to assist social media platforms, online service providers and government agencies in identifying and responding to misinformation on social media. We report herein on the predictive accuracy accomplished by applying a combination of technologies, including a custom-designed web-crawler, The Dark Crawler (TDC) and the Posit toolkit, a text-reading software solution designed by George Weir of University of Strathclyde. Overall, we found that performance of models based upon Posit-derived textual features showed high levels of correlation to the pre-determined (manual and machine-driven) data classifications. We further argue that the harms associated with COVID-19 misinformation — e.g., the social and economic damage, and the deaths and severe illnesses — outweigh the right to personal privacy and freedom of speech considerations.
Recommended Citation
Cartwright, Barry; Frank, Richard; Weir, George; Padda, Karmvir; and Strange, Sarah-May, "Deploying Artificial Intelligence to Combat Covid-19 Misinformation on Social Media: Technological and Ethical Considerations" (2023). Hawaii International Conference on System Sciences 2023 (HICSS-56). 5.
https://aisel.aisnet.org/hicss-56/dsm/data_analytics/5
Deploying Artificial Intelligence to Combat Covid-19 Misinformation on Social Media: Technological and Ethical Considerations
Online
This paper reports on research into online misinformation pertaining to the COVID-19 pandemic using artificial intelligence. This is part of our longer-term goal, i.e., the development of an artificial intelligence (machine-learning) tool to assist social media platforms, online service providers and government agencies in identifying and responding to misinformation on social media. We report herein on the predictive accuracy accomplished by applying a combination of technologies, including a custom-designed web-crawler, The Dark Crawler (TDC) and the Posit toolkit, a text-reading software solution designed by George Weir of University of Strathclyde. Overall, we found that performance of models based upon Posit-derived textual features showed high levels of correlation to the pre-determined (manual and machine-driven) data classifications. We further argue that the harms associated with COVID-19 misinformation — e.g., the social and economic damage, and the deaths and severe illnesses — outweigh the right to personal privacy and freedom of speech considerations.
https://aisel.aisnet.org/hicss-56/dsm/data_analytics/5