Reduced liberty may be the price we need to pay for increased security.
In a March 2020 Pew Research Center survey, the American public named the spread of infectious diseases as the greatest threat to the country. For the first time, this surpassed the threat of terrorism: 79 percent of Americans named outbreaks of disease as a major threat to the country, compared to 73 percent of Americans who saw terrorism as a major threat. Counterterrorism measures nonetheless provide an important context for examining the trade-offs between reduced civil liberties and increased security. Following high-impact events such as terrorist attacks, public concerns regarding government intrusions on privacy tend to decrease. After the terrorist attacks in Paris, France, and San Bernardino, California, in 2015, for example, a national survey by Pew Research Center found that the American public was less concerned that anti-terrorism policies restricted civil liberties: such concerns fell to their lowest level in five years (to 28 percent), with twice as many people (56 percent) stating that their greater concern was that policies had not gone far enough to adequately protect the country.
Where does our data go, and what is it used for? Data mining, the process of extracting trends from large amounts of data using techniques such as pattern recognition and machine learning, has been used to understand and prevent terrorist activity and fraudulent behavior, often as part of a broader knowledge discovery process. A 2002 op-ed published by The New York Times detailed new plans for a program within the Defense Advanced Research Project Agency (DARPA) to create a centralized database containing information on citizens that could be used to data-mine for various purposes, including security concerns. The article led to the creation of a blue-ribbon committee around privacy concerns, the Technology and Privacy Advisory Committee, and the eventual cancellation of the program.
As countries ease lockdown restrictions imposed in response to the coronavirus, a trade-off for the liberty of free movement may be greater accessibility of civilian data. In at least twenty-three countries, dozens of ‘digital contact tracing’ apps have been downloaded more than fifty million times. Authorities in the UK and other countries, meanwhile, have deployed drones with video equipment and temperature sensors to track those who have broken lockdown restrictions by being outside their homes. In the United States, a task force of data mining start-ups and technology companies is currently working with the White House to develop a range of tracking and surveillance technologies to fight the coronavirus. Other ideas being considered include geolocation tracking of people using data from their phones, and facial recognition systems to determine who has come into contact with individuals later tested positive for the virus.
Such methods have raised concerns around “surveillance creep,” where intrusive powers are expanded or data is used to prosecute for a range of crimes. Data used to build predictive or preventative computer models around the coronavirus outbreak, therefore, comes with various issues, the most important of which surround privacy and accuracy. In the future, similar data collection techniques may be employed in the sharing of information between countries on potential individuals who are carrying disease, or who may be at risk due to their travel. Unlike in the context of terrorism, where countries are working to share information against a foreign entity or actor (under United Nations Security Council Resolution 2396, for example), countries will be required to collaborate in order to contain the spread of disease. Concerns around the accuracy of data shared by China and other countries in the early stages of the pandemic, however, raise issues around this initiative, and a new international body may need to ensure that some countries avoid the temptation to coast while hoping that other countries will pick up the slack. It would also be useful for countries who have employed surveillance techniques to sign a code of practice to ensure that data analysis has sufficient oversight.