We are living in strange times. I don’t think anyone could have predicted the COVID-19 pandemic, let alone its transmissibility and the seriousness of the illness. Being sheltered-in-place and working remotely is one thing — doing so because everyone’s life may depend on it is another. This got me to thinking about how the medical, scientific, and technological experts are battling this disease, and the vast resources of data they are using to do so. The good news is that amazing headway is being made in tackling this global contagion; the bad news is that there is one casualty from this pandemic that may take longer to heal (if at all) than you may think.
Whether you realize this or not, there are a great many technological tools used in battling such a pandemic. Believe it or not, one of the biggest ones is big data. More specifically, the confluence of artificial intelligence (AI), machine learning (ML), and analysis of big data. Think about it — it makes sense. First, the increases in the capability of AI over the past decade are resulting in vast capabilities to intelligently parse vast amounts of information. This is leading to the capability to review and analyze large quantities of public information in a way that not only helps track the propagation of COVID-19 and associated risks, but helps monitor and perhaps even predict future hotspots (more on predictive analytics in a future article). Given the vast amount of data available from news sources, social media feeds, third-party website commentary, and even official government information portals and feeds, it is not hard to see that with the proper algorithms and training, AI can see patterns within vast mountains of data not easily seen through other less technical means.
Moreover, this confluence is permitting AI/ML to draw inferences from vast information sources that will likely help research scientists in identifying effective treatments and drug regimes, as well as a likely vaccine. Think about it — scientists have already put together a large neural network called COVID-Net to process chest X-ray information to facilitate better testing from COVID-19. Although this convolutional neural network is more a research tool that has yet to be validated, the fact that this network has been made available to the public to help combat COVID-19 is a testament to the rapid progression of AI/ML tools. It is only a matter of time before such tools help find the necessary weaknesses in COVID-19 to help find not only an effective vaccine, but hopefully render this pandemic into a mere seasonal nuisance for future generations.
So what’s the problem? Well, it all boils down to the data itself. In an effort to combat this pandemic, Google has already released location tracking data to help governmental authorities determine which areas are complying to government-mandated stay-at-home orders. In fact, Google has also disabled its SameSite cookie support during the pandemic to avoid potential incompatibilities with some websites, opting to ensure continued website availability. This feature was a positive step toward personal information privacy because it prevents third-party domains from setting cookie data files when users are not on that third-party’s website — disabling the technology (although ostensibly temporary) is not a step in the right privacy direction. Simply put: the unforeseen casualty from the COVID-19 pandemic is the privacy of your personal information.
Please don’t misunderstand the point here — I fully recognize that extraordinary circumstances require equally extraordinary responses. I applaud the use of AI/ML on available open-source data, and fully understand that the possibility of saving lives warrants taking some liberties involving personal data collection and use. The risk-benefit analysis in that regard is a no-brainer. What I worry about is that the Herculean response to this virus and big data efforts to combat it will not be adjusted once COVID-19 is under control. Think about it — it’s not hard to imagine the use of location tracking data originally designed to address stay-at-home order compliance and contagion propagation continuing long after COVID-19 subsides, perhaps for purposes well outside of public health concerns. Whether under the guise of tracking vaccine efficacy or for other ostensible public health-related reasons, it’s not hard to fathom uses of such information for other purposes by third parties that may not be so easy for individuals to address or accept. It’s like a toll-road that has already paid for itself, and the tolls far exceed the cost of maintenance of the roadway. Although no longer absolutely necessary, the operator continues to collect the tolls, and being used to doing so, we remain willing to pay them just to ride on the toll road.
Like you, I pray for this pandemic to be over soon, and remain quite optimistic about the prospects of AI/ML helping accelerate the learning curve and effectuate a vaccine. That said, the pandemic has now made it abundantly clear that privacy legislation on the federal level will need to become a reality sooner rather than later. State efforts (such as the CCPA in California) are a step in the right direction, but as I have written previously, they will result in a patchwork of legislation that will not uniformly address the underlying next-level privacy issues. Just as with the COVID-19 pandemic, a powerful federal response along the lines of the EU General Data Protection Regulation may be necessary in the future. Let’s all hope that Congress can come up with the right legislative vaccine regarding the future privacy of your personal information. I know what you may be thinking, but the health of your personal information may likely depend on it.
Tom Kulik is an Intellectual Property & Information Technology Partner at the Dallas-based law firm of Scheef & Stone, LLP. In private practice for over 20 years, Tom is a sought-after technology lawyer who uses his industry experience as a former computer systems engineer to creatively counsel and help his clients navigate the complexities of law and technology in their business. News outlets reach out to Tom for his insight, and he has been quoted by national media organizations. Get in touch with Tom on Twitter (@LegalIntangibls) or Facebook (www.facebook.com/technologylawyer), or contact him directly at firstname.lastname@example.org.
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