Location Surveillance to Counter COVID-19: Efficacy Is What Matters


Susan Landau at Lawfare: “…Some government officials believe that the location information that phones can provide will be useful in the current crisis. After all, if cellphone location information can be used to track terrorists and discover who robbed a bank, perhaps it can be used to determine whether you rubbed shoulders yesterday with someone who today was diagnosed as having COVID-19, the respiratory disease that the novel coronavirus causes. But such thinking ignores the reality of how phone-tracking technology works.

Let’s look at the details of what we can glean from cellphone location information. Cell towers track which phones are in their locale—but that is a very rough measure, useful perhaps for tracking bank robbers, but not for the six-foot proximity one wants in order to determine who might have been infected by the coronavirus.

Finer precision comes from GPS signals, but these can only work outside. That means the location information supplied by your phone—if your phone and that of another person are both on—can tell you if you both went into the same subway stop around the same time. But it won’t tell you whether you rode the same subway car. And the location information from your phone isn’t fully precise. So not only can’t it reveal if, for example, you were in the same aisle in the supermarket as the ill person, but sometimes it will make errors about whether you made it into the store, as opposed to just sitting on a bench outside. What’s more, many people won’t have the location information available because GPS drains the battery, so they’ll shut it off when they’re not using it. Their phones don’t have the location information—and neither do the providers, at least not at the granularity to determine coronavirus exposure.

GPS is not the only way that cellphones can collect location information. Various other ways exist, including through the WiFi network to which a phone is connected. But while two individuals using the same WiFi network are likely to be close together inside a building, the WiFi data would typically not be able to determine whether they were in that important six-foot proximity range.

Other devices can also get within that range, including Bluetooth beacons. These are used within stores, seeking to determine precisely what people are—and aren’t—buying; they track peoples’ locations indoors within inches. But like WiFi, they’re not ubiquitous, so their ability to track exposure will be limited.

If the apps lead to the government’s dogging people’s whereabouts at work, school, in the supermarket and at church, will people still be willing to download the tracking apps that get them get discounts when they’re passing the beer aisle? China follows this kind of surveillance model, but such a surveillance-state solution is highly unlikely to be acceptable in the United States. Yet anything less is unlikely to pinpoint individuals exposed to the virus.

South Korea took a different route. In precisely tracking coronavirus exposure, the country used additional digital records, including documentation of medical and pharmacy visits, history of credit card transactions, and CCTV videos, to determine where potentially exposed people had been—then followed up with interviews not just of infected people but also of their acquaintances, to determine where they had traveled.

Validating such records is labor intensive. And for the United States, it may not be the best use of resources at this time. There’s an even more critical reason that the Korean solution won’t work for the U.S.: South Korea was able to test exposed people. The U.S. can’t do this. Currently the country has a critical shortage of test kits; patients who are not sufficiently ill as to be hospitalized are not being tested. The shortage of test kits is sufficiently acute that in New York City, the current epicenter of the pandemic, the rule is, “unless you are hospitalized and a diagnosis will impact your care, you will not be tested.” With this in mind, moving to the South Korean model of tracking potentially exposed individuals won’t change the advice from federal and state governments that everyone should engage in social distancing—but employing such tracking would divert government resources and thus be counterproductive.

Currently, phone tracking in the United States is not efficacious. It cannot be unless all people are required to carry such location-tracking devices at all times; have location tracking on; and other forms of information tracking, including much wider use of CCTV cameras, Bluetooth beacons, and the like, are also in use. There are societies like this. But so far, even in the current crisis, no one is seriously contemplating the U.S. heading in that direction….(More)”.

Milwaukee’s Amani Neighborhood Uses Data to Target Traffic Safety and Build Trust


Article by Kassie Scott: “People in Milwaukee’s Amani neighborhood are using data to identify safety issues and build relationships with the police. It’s a story of community-engaged research at its best.

In 2017, the Milwaukee Police Department received a grant under the federal Byrne Criminal Justice Innovation program, now called the Community Based Crime Reduction Program, whose purpose is to bridge the gap between practitioners and researchers and advance the use of data in making communities safer. Because of its close ties in the Amani neighborhood, the Dominican Center was selected to lead this initiative, known as the Amani Safety Initiative, and they partnered with local churches, the district attorney’s office, LISC-Milwaukee, and others. To support the effort with data and coaching, the police department contracted with Data You Can Use.

Together with Data You Can Use, the Amani Safety Initiative team first implemented a survey to gauge perceptions of public safety and police legitimacy. Neighborhood ambassadors were trained (and paid) to conduct the survey themselves, going door to door to gather the information from nearly 300 of their neighbors. The ambassadors shared these results with their neighborhood during what they called “data chats.” They also printed summary survey results on door hangers, which they distributed throughout the neighborhood.

Neighbors and community organizations were surprised by the survey results. Though violent crime and mistrust in the police were commonly thought to be the biggest issues, the data showed that residents were most concerned about traffic safety. Ultimately, residents decided to post slow-down signs in intersections.

This project stands out for letting the people in the neighborhood lead the way. Neighbors collected data, shared results, and took action. The partnership between neighbors, police, and local organizations shows how people can drive decision-making for their neighborhood.

The larger story is one of social cohesion and mutual trust. Through participating in the initiative and learning more about their neighborhood, Amani neighbors built stronger relationships with the police. The police began coming to neighborhood community meetings, which helped them build relationships with people in the community and understand the challenges they face….(More).

Facial Recognition Software requires Checks and Balances


David Eaves,  and Naeha Rashid in Policy Options: “A few weeks ago, members of the Nexus traveller identification program were notified that Canadian Border Services is upgrading its automated system, from iris scanners to facial recognition technology. This is meant to simplify identification and increase efficiency without compromising security. But it also raises profound questions concerning how we discuss and develop public policies around such technology – questions that may not be receiving sufficiently open debate in the rush toward promised greater security.

Analogous to the U.S. Customs and Border Protection (CBP) program Global Entry, Nexus is a joint Canada-US border control system designed for low-risk, pre-approved travellers. Nexus does provide a public good, and there are valid reasons to improve surveillance at airports. Even before 9/11, border surveillance was an accepted annoyance and since then, checkpoint operations have become more vigilant and complex in response to the public demand for safety.

Nexus is one of the first North America government-sponsored services to adopt facial recognition, and as such it could be a pilot program that other services will follow. Left unchecked, the technology will likely become ubiquitous at North American border crossings within the next decade, and it will probably be adopted by governments to solve domestic policy challenges.

Facial recognition software is imperfect and has documented bias, but it will continue to improve and become superior to humans in identifying individuals. Given this, questions arise such as, what policies guide the use of this technology? What policies should inform future government use? In our headlong rush toward enhanced security, we risk replicating the justification the used by the private sector in an attempt to balance effectiveness, efficiency and privacy.

One key question involves citizens’ capacity to consent. Previously, Nexus members submitted to fingerprint and retinal scans – biometric markers that are relatively unique and enable government to verify identity at the border. Facial recognition technology uses visual data and seeks, analyzes, and stores identifying facial information in a database, which is then used to compare with new images and video….(More)”.

Federal Agencies Use Cellphone Location Data for Immigration Enforcement


Byron Tau and Michelle Hackman at the Wall Street Journal: “The Trump administration has bought access to a commercial database that maps the movements of millions of cellphones in America and is using it for immigration and border enforcement, according to people familiar with the matter and documents reviewed by The Wall Street Journal.

The location data is drawn from ordinary cellphone apps, including those for games, weather and e-commerce, for which the user has granted permission to log the phone’s location.

The Department of Homeland Security has used the information to detect undocumented immigrants and others who may be entering the U.S. unlawfully, according to these people and documents.

U.S. Immigration and Customs Enforcement, a division of DHS, has used the data to help identify immigrants who were later arrested, these people said. U.S. Customs and Border Protection, another agency under DHS, uses the information to look for cellphone activity in unusual places, such as remote stretches of desert that straddle the Mexican border, the people said.

The federal government’s use of such data for law enforcement purposes hasn’t previously been reported.

Experts say the information amounts to one of the largest known troves of bulk data being deployed by law enforcement in the U.S.—and that the use appears to be on firm legal footing because the government buys access to it from a commercial vendor, just as a private company could, though its use hasn’t been tested in court.

“This is a classic situation where creeping commercial surveillance in the private sector is now bleeding directly over into government,” said Alan Butler, general counsel of the Electronic Privacy Information Center, a think tank that pushes for stronger privacy laws.

According to federal spending contracts, a division of DHS that creates experimental products began buying location data in 2017 from Venntel Inc. of Herndon, Va., a small company that shares several executives and patents with Gravy Analytics, a major player in the mobile-advertising world.

In 2018, ICE bought $190,000 worth of Venntel licenses. Last September, CBP bought $1.1 million in licenses for three kinds of software, including Venntel subscriptions for location data. 

The Department of Homeland Security and its components acknowledged buying access to the data, but wouldn’t discuss details about how they are using it in law-enforcement operations. People familiar with some of the efforts say it is used to generate investigative leads about possible illegal border crossings and for detecting or tracking migrant groups.

CBP has said it has privacy protections and limits on how it uses the location information. The agency says that it accesses only a small amount of the location data and that the data it does use is anonymized to protect the privacy of Americans….(More)”

Artificial intelligence, geopolitics, and information integrity


Report by John Villasenor: “Much has been written, and rightly so, about the potential that artificial intelligence (AI) can be used to create and promote misinformation. But there is a less well-recognized but equally important application for AI in helping to detect misinformation and limit its spread. This dual role will be particularly important in geopolitics, which is closely tied to how governments shape and react to public opinion both within and beyond their borders. And it is important for another reason as well: While nation-state interest in information is certainly not new, the incorporation of AI into the information ecosystem is set to accelerate as machine learning and related technologies experience continued advances.

The present article explores the intersection of AI and information integrity in the specific context of geopolitics. Before addressing that topic further, it is important to underscore that the geopolitical implications of AI go far beyond information. AI will reshape defense, manufacturing, trade, and many other geopolitically relevant sectors. But information is unique because information flows determine what people know about their own country and the events within it, as well as what they know about events occurring on a global scale. And information flows are also critical inputs to government decisions regarding defense, national security, and the promotion of economic growth. Thus, a full accounting of how AI will influence geopolitics of necessity requires engaging with its application in the information ecosystem.

This article begins with an exploration of some of the key factors that will shape the use of AI in future digital information technologies. It then considers how AI can be applied to both the creation and detection of misinformation. The final section addresses how AI will impact efforts by nation-states to promote–or impede–information integrity….(More)”.

The Gray Spectrum: Ethical Decision Making with Geospatial and Open Source Analysis


Report by The Stanley Center for Peace and Security: “Geospatial and open source analysts face decisions in their work that can directly or indirectly cause harm to individuals, organizations, institutions, and society. Though analysts may try to do the right thing, such ethically-informed decisions can be complex. This is particularly true for analysts working on issues related to nuclear nonproliferation or international security, analysts whose decisions on whether to publish certain findings could have far-reaching consequences.

The Stanley Center for Peace and Security and the Open Nuclear Network (ONN) program of One Earth Future Foundation convened a workshop to explore these ethical challenges, identify resources, and consider options for enhancing the ethical practices of geospatial and open source analysis communities.

This Readout & Recommendations brings forward observations from that workshop. It describes ethical challenges that stakeholders from relevant communities face. It concludes with a list of needs participants identified, along with possible strategies for promoting sustaining behaviors that could enhance the ethical conduct of the community of nonproliferation analysts working with geospatial and open source data.

Some Key Findings

  • A code of ethics could serve important functions for the community, including giving moral guidance to practitioners, enhancing public trust in their work, and deterring unethical behavior. Participants in the workshop saw a significant value in such a code and offered ideas for developing one.
  • Awareness of ethical dilemmas and strong ethical reasoning skills are essential for sustaining ethical practices, yet professionals in this field might not have easy access to such training. Several approaches could improve ethics education for the field overall, including starting a body of literature, developing model curricula, and offering training for students and professionals.
  • Other stakeholders—governments, commercial providers, funders, organizations, management teams, etc.—should contribute to the discussion on ethics in the community and reinforce sustaining behaviors….(More)”.

Predictive Policing Theory


Paper by Andrew Guthrie Ferguson: “Predictive policing is changing law enforcement. New place-based predictive analytic technologies allow police to predict where and when a crime might occur. Data-driven insights have been operationalized into concrete decisions about police priorities and resource allocation. In the last few years, place-based predictive policing has spread quickly across the nation, offering police administrators the ability to identify higher crime locations, to restructure patrol routes, and to develop crime suppression strategies based on the new data.

This chapter suggests that the debate about technology is better thought about as a choice of policing theory. In other words, when purchasing a particular predictive technology, police should be doing more than simply choosing the most sophisticated predictive model; instead they must first make a decision about the type of policing response that makes sense in their community. Foundational questions about whether we want police officers to be agents of social control, civic problem-solvers, or community partners lie at the heart of any choice of which predictive technology might work best for any given jurisdiction.

This chapter then examines predictive policing technology as a choice about policing theory and how the purchase of a particular predictive tool becomes – intentionally or unintentionally – a statement about police role. Interestingly, these strategic choices map on to existing policing theories. Three of the traditional policing philosophies – hot spot policing , problem-oriented policing, and community-based policing have loose parallels with new place-based predictive policing technologies like PredPol, Risk Terrain Modeling (RTM), and HunchLab. This chapter discusses these leading predictive policing technologies as illustrative examples of how police can choose between prioritizing additional police presence, targeting environmental vulnerabilities, and/or establishing a community problem-solving approach as a different means of achieving crime reduction….(More)”.

How digital sleuths unravelled the mystery of Iran’s plane crash


Chris Stokel-Walker at Wired: “The video shows a faint glow in the distance, zig-zagging like a piece of paper caught in an underdraft, slowly meandering towards the horizon. Then there’s a bright flash and the trees in the foreground are thrown into shadow as Ukraine International Airlines flight PS752 hits the ground early on the morning of January 8, killing all 176 people on board.

At first, it seemed like an accident – engine failure was fingered as the cause – until the first video showing the plane seemingly on fire as it weaved to the ground surfaced. United States officials started to investigate, and a more complicated picture emerged. It appeared that the plane had been hit by a missile, corroborated by a second video that appears to show the moment the missile ploughs into the Boeing 737-800. While military and intelligence officials at governments around the world were conducting their inquiries in secret, a team of investigators were using open-source intelligence (OSINT) techniques to piece together the puzzle of flight PS752.

It’s not unusual nowadays for OSINT to lead the way in decoding key news events. When Sergei Skripal was poisoned, Bellingcat, an open-source intelligence website, tracked and identified his killers as they traipsed across London and Salisbury. They delved into military records to blow the cover of agents sent to kill. And in the days after the Ukraine Airlines plane crashed into the ground outside Tehran, Bellingcat and The New York Times have blown a hole in the supposition that the downing of the aircraft was an engine failure. The pressure – and the weight of public evidence – compelled Iranian officials to admit overnight on January 10 that the country had shot down the plane “in error”.

So how do they do it? “You can think of OSINT as a puzzle. To get the complete picture, you need to find the missing pieces and put everything together,” says Loránd Bodó, an OSINT analyst at Tech versus Terrorism, a campaign group. The team at Bellingcat and other open-source investigators pore over publicly available material. Thanks to our propensity to reach for our cameraphones at the sight of any newsworthy incident, video and photos are often available, posted to social media in the immediate aftermath of events. (The person who shot and uploaded the second video in this incident, of the missile appearing to hit the Boeing plane was a perfect example: they grabbed their phone after they heard “some sort of shot fired”.) “Open source investigations essentially involve the collection, preservation, verification, and analysis of evidence that is available in the public domain to build a picture of what happened,” says Yvonne McDermott Rees, a lecturer at Swansea University….(More)”.

Lack of guidance leaves public services in limbo on AI, says watchdog


Dan Sabbagh at the Guardian: “Police forces, hospitals and councils struggle to understand how to use artificial intelligence because of a lack of clear ethical guidance from the government, according to the country’s only surveillance regulator.

The surveillance camera commissioner, Tony Porter, said he received requests for guidance all the time from public bodies which do not know where the limits lie when it comes to the use of facial, biometric and lip-reading technology.

“Facial recognition technology is now being sold as standard in CCTV systems, for example, so hospitals are having to work out if they should use it,” Porter said. “Police are increasingly wearing body cameras. What are the appropriate limits for their use?

“The problem is that there is insufficient guidance for public bodies to know what is appropriate and what is not, and the public have no idea what is going on because there is no real transparency.”

The watchdog’s comments came as it emerged that Downing Street had commissioned a review led by the Committee on Standards in Public Life, whose chairman had called on public bodies to reveal when they use algorithms in decision making.

Lord Evans, a former MI5 chief, told the Sunday Telegraph that “it was very difficult to find out where AI is being used in the public sector” and that “at the very minimum, it should be visible, and declared, where it has the potential for impacting on civil liberties and human rights and freedoms”.

AI is increasingly deployed across the public sector in surveillance and elsewhere. The high court ruled in September that the police use of automatic facial recognition technology to scan people in crowds was lawful.

Its use by South Wales police was challenged by Ed Bridges, a former Lib Dem councillor, who noticed the cameras when he went out to buy a lunchtime sandwich, but the court held that the intrusion into privacy was proportionate….(More)”.

The Economics of Violence: How Behavioral Science Can Transform our View of Crime, Insurgency, and Terrorism


Book by Gary M. Shiffman: “How do we understand illicit violence? Can we prevent it? Building on behavioral science and economics, this book begins with the idea that humans are more predictable than we like to believe, and this ability to model human behavior applies equally well to leaders of violent and coercive organizations as it does to everyday people. Humans ultimately seek survival for themselves and their communities in a world of competition. While the dynamics of ‘us vs. them’ are divisive, they also help us to survive. Access to increasingly larger markets, facilitated through digital communications and social media, creates more transnational opportunities for deception, coercion, and violence. If the economist’s perspective helps to explain violence, then it must also facilitate insights into promoting peace and security. If we can approach violence as behavioral scientists, then we can also better structure our institutions to create policies that make the world a more secure place, for us and for future generations….(More)”.