Mary Gray Discusses How Human-Centered Tech Can Beat COVID-19

By TAP Staff Blogger

Posted on April 23, 2020


Tech companies such as Apple and Google want to help individuals take contact tracing into their own hands. They, and many others, want to equip anyone with a cell phone to anonymously text their COVID-19 infection status or receive text alerts if they come close to someone infected with the virus. As two computer scientists and a physician who is involved in standing up the contact tracing program in Massachusetts, we share deep reservations about the effectiveness and equity of this particular tech approach to contact tracing. - from “How Human-Centered Tech Can Beat COVID-19 Through Contact Tracing” by Mary Gray, Margaret Bourdeaux, and Barbara Grosz (The Hill, April 21, 2020)


Contact tracing is the process of finding and reaching out to the contacts of someone who tests positive for an infectious pathogen. Those contacts are then quarantined or monitored, and if any of them are also positive, the process is repeated with their contacts, and on and on, until the chain of transmission is halted.


The Centers for Disease Control and Prevention (CDC) is developing a contract-tracing plan that will enable the U.S. to safely scale back on the social distancing orders currently in place. According to CDC Director Robert Redfield, the plan relies on ramped-up testing and "very aggressive" contact tracing of those who do test positive for the coronavirus. (See NPR story, “CDC Director: 'Very Aggressive' Contact Tracing Needed For U.S. To Return To Normal.”)


Professor Mary L. Gray, Senior Researcher at Microsoft Research and Fellow at Harvard University’s Berkman Klein Center for Internet and Society, raises concerns over Apple and Google’s project to “embed a feature in iPhones and Android devices to enable users to track infected people they’d come close to.” In “How Human-Centered Tech Can Beat COVID-19 Through Contact Tracing,” an opinion piece coauthored with colleagues Margaret Bourdeaux and Barbara Grosz (both with Harvard), Professor Gray expresses reservations surrounding the inequitable use of cell phones as well as the aspects of contact tracing that digital devices are incapable of.


Below are a few excerpts from “How Human-Centered Tech Can Beat COVID-19 Through Contact Tracing.”


Cell Phone Data


Cell phone data may help, but it is only a partial solution. It will miss, for example, data from an infected person who leaves their cell phone behind when they go grocery shopping. It will also miss the millions of Americans who don’t have their own cell phones or live in rural parts of the country with limited cellular or internet access. More crucially, cell phone tracking alone cannot accurately report the nature of contacts. High risk contacts range from being within six feet of an infected person without a mask for longer than 15 minutes to touching the same surface many hours or even days apart. Successful contact tracing involves patiently helping people recall with whom they have interacted in the preceding weeks and assessing the risk associated with each of these interactions. Irrelevant contact data will needlessly consume precious human contact tracer time.


Most problematic, however, is assuming that locating people is all that contact tracing requires.


Human Contact Tracers


To succeed, contact tracing programs require that people trust the entity to whom they are reporting. Trust is built on empathy, patience and the ability to help someone who has just been exposed to a life-threatening disease. Human contact tracers need to guide a rattled parent to think through who their child might have played with at a neighborhood potluck two weeks ago or an undocumented immigrant find support and care should they fall ill. They also need to understand and help people marshal the resources they will need to sustain a 14-day quarantine after they have been exposed. Thus, contact tracing hinges on deeply human exchanges. There is no app for that.


Human and Technology Collaboration


Digital technologies do have a role to play. They will be crucial to successful contact tracing programs. But they must be intentionally built to assist, rather than replace the people in the health care loop vital to success.


Ultimately, the best technological interventions to fight COVID-19 will be the ones designed in collaboration with contact tracers to enable them to do their best work and integrated into the planning processes of these programs. Human-centered tech can combine the power of data with the irreplaceable compassion of frontline contact tracers to help us keep COVID-19 at bay until we have a vaccine. In fact, doing anything less misses the opportunity of our lifetimes to unleash the deeply social potential of technologies.


Read the full article from The Hill, “How Human-Centered Tech Can Beat COVID-19 Through Contact Tracing” by Mary Gray, Margaret Bourdeaux, and Barbara Grosz.


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Mary L. Gray is a Senior Researcher at Microsoft Research and Fellow at Harvard University’s Berkman Klein Center for Internet and Society. She maintains a faculty position in the School of Informatics, Computing, and Engineering with affiliations in Anthropology, Gender Studies and the Media School at Indiana University. Professor Gray is a leading expert in the emerging field of AI and ethics, particularly research methods at the intersections of computer and social sciences.


Margaret Bourdeaux, MD, MPH, is the policy liaison for Partners in Health COVID-19 Contact Tracing Program, and holds appointments at Harvard Medical School, Brigham and Women’s Hospital, and the Belfer Center for Science and International Affairs at Harvard Kennedy School of Government.


Barbara Grosz is Higgins Research Professor of Natural Sciences in the Paulson School of Engineering and Applied Sciences at Harvard University and external faculty at the Santa Fe Institute. Her research in Artificial Intelligence (AI) aims to develop the capabilities needed for computer-agent systems to function as intelligent, helpful team members over the long term and in uncertain, dynamic environments.