COVID-19

After 9/11, governments enacted new AI-powered (Artificial Inteligence) surveillance technology laws to locate existing and budding terrorists without success. Now, with COVID-19, governments are also weighing surveillance tools to locate vectors of infections and prevent the next pandemic. While terrorism and viruses originate from different sources, following the same 9/11 surveillance approach to prevent the next virus might catch the wrong individuals and violate civil rights and worse, impede the search for the real vectors of infections. Also, the Google Flu Trend venture to “nowcast” the flu based on big data trends in search engines was also wildly inaccurate. At the peak of the 2013 flu season, it missed the mark by 140 percent. Why did these programs fail? Because these technologies weren’t audited for proper context and assessed within a legal framework. 

The Covid-19 pandemic is ushering in a new era of digital surveillance and rewiring the world’s sensibilities about data privacy. As serious as COVID-19 is, we need to balance efforts to combat with the need to protect privacy rights. Excessive collection of highly sensitive data under the guise of helping to combat the pandemic is opportunistic. If privacy is not at the forefront of the plans and offerings, privacy rights will erode.

As we’ve seen with COVID-19, when present data suddenly stops looking like past data, AI-powered algorithms can’t cope. That means the algorithm won’t perform as expected and render inaccurate recommendations or predictions. Inaccuracies in predictive AI models for public health surveillance do not serve global citizens. Cultivating an understanding of contextual relationships, dependencies, actors, assessing risk while engaging the community all yield a more robust AI-powered technology.

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