Many government agencies, state and federal, have deployed a variety of algorithms to combat the COVID-19 pandemic. Given that these automated systems can take a myriad of forms, investigating them can also require a variety of approaches. In this way, COVID-related algorithms show how challenging reporting on automated decision-making systems can be: just as government algorithms in general, they are widespread and diverse, making them a challenging, but important topic for journalists to cover.
So, what kinds of algorithms are governments creating in response to the COVID pandemic? The COVID-related government algorithms that we found aim to track the virus, reduce its spread and soften the impacts of the pandemic in various ways. Many of these algorithms relate to state politics and health care. The Minnesota Department of Health, for example, published guidelines for Minnesota healthcare organizations to report COVID-19 cases to the state. Similarly, the Oregon Health Authority published recommendations for healthcare workers preventing and treating COVID-19. The State of Michigan created a web application to screen for COVID-19 based on users’ self-reported symptoms, and Carnegie Mellon University developed risk indices for Philadelphia counties to inform policymakers as they reopen the state economy.
Other algorithms address the virus in more unexpected ways. For instance, the Environmental Protection Agency published new animal carcass management guidelines in response to COVID-19; the Arizona Department of Child Safety published guidelines for virtual visits for foster caregivers; and the Center for Disease Control created an interactive map that informs users of the risks of traveling to different countries during the pandemic.
These algorithms may be useful, but they also present a number of risks. For example, the MI Symptoms App could raise privacy concerns as many other COVID-related government software have around the world. Although the MI Symptoms App is an online screening tool rather than a contact-tracing application, user information is not covered by HIPAA, can be shared with health departments and contributes to larger county and state data. Furthermore, though third-party organizations do not receive information from the MI Symptoms App, users can sign in with Google and Facebook. This could raise privacy concerns given the sensitive information collected by the software and how that information is handled by third-party services. This algorithm has the potential to affect a large number of people as the State of Michigan created and promoted this free application for employers to use in the daily screening protocol required by the state.
The Carnegie Mellon University Risk-Based Decision Support Tools similarly have the potential to affect many people. This algorithm creates risk evaluations that will influence Pennsylvania policymakers as they plan to reopen the economy, which will in turn impact the economic situation and safety of their constituents. This algorithm is also newsworthy given the general controversy surrounding reopening the economy, especially in Pennsylvania, which had some of the highest unemployment-compensation claims in the country as of late April and the tenth highest number of confirmed cases in the U.S. as of early July 2020. Although the risk indices are data-driven evaluations, the algorithm speaks to a political and divisive decision, so it is likely to be a topic of debate regardless of its output or whether policymakers act in accordance to its evaluations.
We’ll be on the lookout for more COVID-related algorithms moving forward. But even just with the ones we’ve already found, there’s more work to do. To investigate the MI Symptoms App, researchers and journalists could file a public records request with the State of Michigan to learn about the software. They could also request user agreements from the MI Symptoms App and connected third-party services to learn about user privacy. Reporters who are interested in looking at the Carnegie Mellon risk indices can search for updated project proposals from the university or dig into the details of its implementation. Investigations into other COVID-related government algorithms can begin with contacting relevant government agencies and health organizations. For instance, The Minnesota Department of Health or a Minnesota hospital could speak to the efficacy of state reporting guidelines. We hope that with additional research and reporting, the impact of these systems and algorithms for the public can be further clarified.