Deploying Artificial Intelligence to Combat Covid-19 Misinformation on Social Media: Technological and Ethical Considerations
56th Annual Hawaii International Conference on System Sciences, HICSS 2023
; 2023-January:2140-2149, 2023.
Article
in English
| Scopus | ID: covidwho-2292966
ABSTRACT
This paper reports on AI research into online misinformation pertaining to the COVID-19 pandemic within the Canadian context. This is part of our longer-term goal, i.e., development of a 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 on predictive accuracies accomplished by applying a combination of technologies, including a custom-designed web-crawler, The Dark Crawler, the Posit toolkit, and four different machine-learning models based on Naïve Bayes, Support Vector Machines, LibLinear and LibShortText. Overall, we found that Posit and LibShortText models showed higher levels of correlation to the pre-determined (manual and machine-driven) data classifications than the other machine-learning algorithms tested. 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. © 2023 IEEE Computer Society. All rights reserved.
COVID-19; machine-learning; misinformation; social media; Ethical technology; Learning algorithms; Learning systems; Social networking (online); Support vector machines; Web crawler; Ethical considerations; Learning tool; Long-term goals; On-line service; Service governments; Service provider; Social media platforms
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Collection:
Databases of international organizations
Database:
Scopus
Language:
English
Journal:
56th Annual Hawaii International Conference on System Sciences, HICSS 2023
Year:
2023
Document Type:
Article
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