This article was published on Apr 25 in ExpressHealthcare (arm of Indian Express):

On Feb 17, 31st case of coronavirus surfaced in Daegu, South Korea. On outlining the tracks of this ‘Patient 31’, public health official ascertained that in the last ten days the patient had attended two worship services with over 1000 people. Within a week, a 30-fold increase occurred in the nation’s number of cases. Since then, extensive use of analytics and data science has been central to South Korea’s approach in successfully ‘flattening the curve’. South Korean government has been tracking on quarantined people through a mobile app which also aids patients’ communication with the local health authorities to report symptoms.

The utilisation of data analytics to understand the causes of the pandemic is reflective of the substantial transformation in the potential of organisations and governments to collect massive amount of data and use AI algorithms to harness them. In this battle, firms have been collecting and processing real-time data at an unprecedented pace and scale. Countries such as India, Singapore, China, Korea, Spain and Israel have successfully developed and deployed indigenous mobile apps to provide instant notifications if an exposure to a covid infected person has occurred. Government health officials and epidemiologists then uses such data sets to track down and screen the exposed individuals and create hot-spot zones where stern isolation is implemented.

Artificial Intelligence for Monitoring and Drug Development

Baidu, a Chinese tech giant, uses infrared sensor and Artificial Intelligence powered facial recognition technology to predict people’s temperature at various airports and railway stations. Drones powered with AI-based thermal screening are deployed in public places by various nations to detect fever. AI and cloud computing are being used extensively to identify potential drugs and augment the research for coronavirus vaccine development. IBM has offered its AI-powered virtual agent, Watson Assistant for Citizens, which helps governments deliver accurate information to their citizens. Microsoft had released chatbots that can help people self-identify the best action plan based on their symptoms. Tech  majors – Apple and Google – recently announced a collaboration for developing a decentralised contact tracing tool. Machine-learning tools have analysed millions of social media posts in China to help predict the spread.

The aforementioned examples clearly indicate that the striking advances in data analytics and AI-based algorithms have provided a strong fillip to global efforts in identifying communities at risk and arresting the contagion spread. BlueDot, a Canadian AI-based infectious disease surveillance system, spotted the coronavirus nine days before WHO released an alert for the virus’ emergence. Scientists at Carnegie Melon University have developed an AI based tool that can determine a covid infected case by analyzing the sound of a person’s breath and cough.

Active monitoring and contact tracing, and analyzing real-time data is pivotal to assuage the stark implications stemming of the pandemic. Countries such as Singapore, India, Taiwan, China, South Korea, Spain, Norway, Belgium etc. have successfully deployed these data-driven predictive mechanisms. Today, smart phones are laced with high-end technology which can easily enable in mapping the travel patterns of people, thereby offering real-time date to telecom providers and tech firms. Data from CCTV footage and ATM transaction records have been used for contact tracing in Singapore and South Korea. A portable surveillance device powered by machine learning, FluSense, can detect coughing in real time at public places, and then analyse the data to monitor trends.

Pressure on Privacy Protection

This massive tracking of consumer behaviour and data has invited severe rebuke from privacy law activists across the globe terming it as ‘privacy-infringement’. Doubters of AI and data science technology complain that this is a blatant attack on the civic liberties brought upon populations in the name of disease-surveillance. There is a growing fear of how this data will be used once the crisis is over and whether such data sets are truly anonymous. However, we should look at the data privacy guidelines from a different lens to facilitate the suppression of this pandemic as precious lives are being lost on daily basis.

Governments and regulators need to provide assurance that data-use and analysis will not endanger privacy rights. Greater transparency is required amongst governments, telecom providers and tech firms that such data sharing will not result in any future regulatory action. The data by telecom providers need to be in an anonymised and aggregated format. More ‘privacy-friendly’ alternatives should be wrought and use of tracking apps should be done on voluntarily basis and non-intrusive.

Such arduous situation necessitates a fine balance between governments, regulators, telecoms, and tech firms. We need to wisely analyse the trade-off between saving lives and civil liberties during this public health emergency. Ample evidence of AI and data science being effective tools against coronavirus should enable consumers to understand that some leeway could be given to the individual privacy laws. We all need to think and act unitedly to mitigate the impact and the methodical use of technological solutions can prove to be a formidable and potent warrior.

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