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)”.

New Orleans has declared a state of emergency after a cyberattack


MIT Technology Review: “The city told its employees to shut down their computers as a precaution this weekend after an attempted cyberattack on Friday.

The news: New Orleans spotted suspicious activity in its networks at around 5 a.m. on Friday, with a spike in the attempted attacks at 8 a.m. It detected phishing attempts and ransomware, Kim LaGrue, the city’s head of IT, later told reporters. Once they were confident the city was under attack, the team shut down its servers and computers. City authorities then filed a declaration of a state of emergency with the Civil District Court, and pulled local, state, and federal authorities into a (still pending) investigation of the incident. The city is still working to recover data from the attack but will be open as usual from this morning, Mayor LaToya Cantrell said on Twitter.

Was it ransomware? The nature of the attack is still something of a mystery. Cantrell confirmed that ransomware had been detected, but the city hasn’t received any demands for ransom money.

The positives: New Orleans was at least fairly well prepared for this attack, thanks to training for this scenario and its ability to operate many of its services without internet access, officials told reporters.

A familiar story: New Orleans is just the latest government to face ransomware attacks, after nearly two dozen cities in Texas were targeted in August, plus Louisiana in November (causing the governor to declare a state of emergency). The phenomenon goes beyond the US, too: in October Johannesburg became the biggest city yet to face a ransomware attack.…(More)”.

A World With a Billion Cameras Watching You Is Just Around the Corner


Liza Lin and Newley Purnell at the Wall Street Journal: “As governments and companies invest more in security networks, hundreds of millions more surveillance cameras will be watching the world in 2021, mostly in China, according to a new report.

The report, from industry researcher IHS Markit, to be released Thursday, said the number of cameras used for surveillance would climb above 1 billion by the end of 2021. That would represent an almost 30% increase from the 770 million cameras today. China would continue to account for a little over half the total.

Fast-growing, populous nations such as India, Brazil and Indonesia would also help drive growth in the sector, the report said. The number of surveillance cameras in the U.S. would grow to 85 million by 2021, from 70 million last year, as American schools, malls and offices seek to tighten security on their premises, IHS analyst Oliver Philippou said.

Mr. Philippou said government programs to implement widespread video surveillance to monitor the public would be the biggest catalyst for the growth in China. City surveillance also was driving demand elsewhere.

“It’s a public-safety issue,” Mr. Philippou said in an interview. “There is a big focus on crime and terrorism in recent years.”

The global security-camera industry has been energized by breakthroughs in image quality and artificial intelligence. These allow better and faster facial recognition and video analytics, which governments are using to do everything from managing traffic to predicting crimes.

China leads the world in the rollout of this kind of technology. It is home to the world’s largest camera makers, with its cameras on street corners, along busy roads and in residential neighborhoods….(More)”.

Artificial Intelligence and National Security


CRS Report: “Artificial intelligence (AI) is a rapidly growing field of technology with potentially significant implications for national security. As such, the U.S. Department of Defense (DOD) and other nations are developing AI applications for a range of military functions. AI research is underway in the fields of intelligence collection and analysis, logistics, cyber operations, information operations, command and control, and in a variety of semiautonomous and autonomous vehicles.

Already, AI has been incorporated into military operations in Iraq and Syria. Congressional action has the potential to shape the technology’s development further, with budgetary and legislative decisions influencing the growth of military applications as well as the pace of their adoption.

AI technologies present unique challenges for military integration, particularly because the bulk of AI development is happening in the commercial sector. Although AI is not unique in this regard, the defense acquisition process may need to be adapted for acquiring emerging technologies like AI. In addition, many commercial AI applications must undergo significant modification prior to being functional for the military.

A number of cultural issues also challenge AI acquisition, as some commercial AI companies are averse to partnering with DOD due to ethical concerns, and even within the department, there can be resistance to incorporating AI technology into existing weapons systems and processes.

Potential international rivals in the AI market are creating pressure for the United States to compete for innovative military AI applications. China is a leading competitor in this regard, releasing a plan in 2017 to capture the global lead in AI development by 2030. Currently, China is primarily focused on using AI to make faster and more well-informed decisions, as well as on developing a variety of autonomous military vehicles. Russia is also active in military AI development, with a primary focus on robotics.

Although AI has the potential to impart a number of advantages in the military context, it may also introduce distinct challenges. AI technology could, for example, facilitate autonomous operations, lead to more informed military decisionmaking, and increase the speed and scale of military action. However, it may also be unpredictable or vulnerable to unique forms of manipulation. As a result of these factors, analysts hold a broad range of opinions on how influential AI will be in future combat operations. While a small number of analysts believe that the technology will have minimal impact, most believe that AI will have at least an evolutionary—if not revolutionary—effect….(More)”.