The Covid-19 outbreak has overwhelmed health systems around the world. At a point, bed spaces and ventilators for patients as well as protective gear for health workers were not enough to go around. This meant that health systems, especially in developed countries, had to employ certain technologies to allocate resources efficiently. AI is one of those and its importance in the fight against coronavirus continues to grow.
An app, developed by researchers at New York University, which uses AI and big data to predict the severity of Covid-19 cases is a good example of how the technology helps in resource allocation, at least in theory. The researchers used patient data from 160 hospitals in Wuhan, China to identify four biomarkers that were significantly higher in patients who died of the virus versus those who recovered. Based on the data fed into the AI model, the app assigns a severity score for patients, which a clinician can use to make informed care and resource allocation decisions.
Despite the positive impact that AI could bring to the coronavirus battlefield, the flaws in the underlying data being employed could deepen the inequities that already exist across gender and racial groups, wrote Genevieve Smith and Ishita Rustagi, both of the Center for Equity, Gender and Leadership at the UC Berkeley Haas School of Business, in an article published in the Stanford Social Innovation Review.
Interestingly, these data reliability concerns aren’t native to the coronavirus era. In fact, AI, along with its subsets of machine learning and deep learning, just to name a few, is plagued by the data bias and data quality conundrum.
The main discussion here is about how blockchain could help in tackling thes...