Artificial intelligence vs COVID-19: limitations, constraints and pitfalls
By Wim Naudé. Ai & Society, 2020
309 citations recorded by the source corpus.
This paper provides an early evaluation of Artificial Intelligence (AI) against COVID-19. The main areas where AI can contribute to the fight against COVID-19 are discussed. It is concluded that AI has not yet been impactful against COVID-19. Its use is hampered by a lack of data, and by too much data. Overcoming these constraints will require a careful balance between data privacy and public health, and rigorous human-AI interaction. It is unlikely that these will be addressed in time to be of much help during the present pandemic. In the meantime, extensive gathering of diagnostic data on who is infectious will be essential to save lives, train AI, and limit economic damages.
Subfields: Health Informatics, Information Systems, Radiology, Nuclear Medicine and Imaging
View Paper: https://www.semanticscholar.org/paper/8e404c468452a0d76576f974159170e6c2480c6b
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In Health Informatics
In Information Systems
In Radiology, Nuclear Medicine and Imaging
Citations in the corpus
- Impact of COVID-19 pandemic on information management research and practice: Transforming education, work and life (2020, background): “It is not only due to a lack of historical training data but also problems with using “big data”, e.g., such as harvested from social media that contains huge amounts of noise needing to be filtered before meaningful trends can be discerned (Naudé, 2020).”