The Danger of Misinformation in the COVID-19 Crisis.

By T. Nelson, N. Kagan, C. Critchlow, Alan Hillard, Albert Hsu. 2020

71 citations recorded by the source corpus.

Subfields: Natural Language Processing, Safety, Robustness & Interpretability

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Natural Language Processing

1. Alexandra Sasha Luccioni
2. Dylan Baker
3. Margaret Mitchell
4. Zeerak Talat
5. Su Lin Blodgett
6. Irene Solaiman
7. Yacine Jernite
8. William Agnew

In Safety, Robustness & Interpretability

1. Irene Solaiman
2. Su Lin Blodgett
3. Dylan Baker
4. Zeerak Talat
5. Marie-Therese Png
6. Yacine Jernite
7. William Agnew
8. Alexandra Sasha Luccioni

Citations in the corpus

• Evaluating the Social Impact of Generative AI Systems in Systems and Society (2023, background): “This can have devastating real world impacts, from attempting dangerous COVID-19 treatments [160], to inciting violence [146], and the loss of trust in mainstream news [95].”
• Synthetic Lies: Understanding AI-Generated Misinformation and Evaluating Algorithmic and Human Solutions (2023, background): “Examples of such efects include mortality and hospital admissions [20, 48], public fear and anxiety [79, 107], eroded trust in health institutions [87], and exacerbated racial discrimination and stigma [41, 48].”