Global Struggle Over AI Surveillance


Report by the National Endowment for Democracy: “From cameras that identify the faces of passersby to algorithms that keep tabs on public sentiment online, artificial intelligence (AI)-powered tools are opening new frontiers in state surveillance around the world. Law enforcement, national security, criminal justice, and border management organizations in every region are relying on these technologies—which use statistical pattern recognition, machine learning, and big data analytics—to monitor citizens.

What are the governance implications of these enhanced surveillance capabilities?

This report explores the challenge of safeguarding democratic principles and processes as AI technologies enable governments to collect, process, and integrate unprecedented quantities of data about the online and offline activities of individual citizens. Three complementary essays examine the spread of AI surveillance systems, their impact, and the transnational struggle to erect guardrails that uphold democratic values.

In the lead essay, Steven Feldstein, a senior fellow at the Carnegie Endowment for International Peace, assesses the global spread of AI surveillance tools and ongoing efforts at the local, national, and multilateral levels to set rules for their design, deployment, and use. It gives particular attention to the dynamics in young or fragile democracies and hybrid regimes, where checks on surveillance powers may be weakened but civil society still has space to investigate and challenge surveillance deployments.

Two case studies provide more granular depictions of how civil society can influence this norm-shaping process: In the first, Eduardo Ferreyra of Argentina’s Asociación por los Derechos Civiles discusses strategies for overcoming common obstacles to research and debate on surveillance systems. In the second, Danilo Krivokapic of Serbia’s SHARE Foundation describes how his organization drew national and global attention to the deployment of Huawei smart cameras in Belgrade…(More)”.

Citizens of Worlds: Open-Air Toolkits for Environmental Struggle


Book by Jennifer Gabrys: “Modern environments are awash with pollutants churning through the air, from toxic gases and intensifying carbon to carcinogenic particles and novel viruses. The effects on our bodies and our planet are perilous. Citizens of Worlds is the first thorough study of the increasingly widespread use of digital technologies to monitor and respond to air pollution. It presents practice-based research on working with communities and making sensor toolkits to detect pollution while examining the political subjects, relations, and worlds these technologies generate. Drawing on data from the Citizen Sense research group, which worked with communities in the United States and the United Kingdom to develop digital-sensor toolkits, Jennifer Gabrys argues that citizen-oriented technologies promise positive change but then collide with entrenched and inequitable power structures. She asks: Who or what constitutes a “citizen” in citizen sensing? How do digital sensing technologies enable or constrain environmental citizenship? Spanning three project areas, this study describes collaborations to monitor air pollution from fracking infrastructure, to document emissions in urban environments, and to create air-quality gardens. As these projects show, how people respond to, care for, and struggle to transform environmental conditions informs the political subjects and collectives they become as they strive for more breathable worlds….(More)”.

Algorithmic monoculture and social welfare


Paper by Jon Kleinberg and Manish Raghavan: “As algorithms are increasingly applied to screen applicants for high-stakes decisions in employment, lending, and other domains, concerns have been raised about the effects of algorithmic monoculture, in which many decision-makers all rely on the same algorithm. This concern invokes analogies to agriculture, where a monocultural system runs the risk of severe harm from unexpected shocks. Here, we show that the dangers of algorithmic monoculture run much deeper, in that monocultural convergence on a single algorithm by a group of decision-making agents, even when the algorithm is more accurate for any one agent in isolation, can reduce the overall quality of the decisions being made by the full collection of agents. Unexpected shocks are therefore not needed to expose the risks of monoculture; it can hurt accuracy even under “normal” operations and even for algorithms that are more accurate when used by only a single decision-maker. Our results rely on minimal assumptions and involve the development of a probabilistic framework for analyzing systems that use multiple noisy estimates of a set of alternatives…(More)”.

Impediment of Infodemic on Disaster Policy Efficacy: Insights from Location Big Data


Paper by Xiaobin Shen, Natasha Zhang Foutz, and Beibei Li: “Infodemics impede the efficacy of business and public policies, particularly in disastrous times when high-quality information is in the greatest demand. This research proposes a multi-faceted conceptual framework to characterize an infodemic and then empirically assesses its impact on the core mitigation policy of a latest prominent disaster, the COVID-19 pandemic. Analyzing a half million records of COVID-related news media and social media, as well as .2 billion records of location data, via a multitude of methodologies, including text mining and spatio-temporal analytics, we uncover a number of interesting findings. First, the volume of the COVID information incurs an inverted-U-shaped impact on individuals’ compliance with the lockdown policy. That is, a smaller volume encourages the policy compliance, whereas an overwhelming volume discourages compliance, revealing negative ramifications of excessive information about a disaster. Second, novel information boosts policy compliance, signifying the value of offering original and distinctive, instead of redundant, information to the public during a disaster. Third, misinformation exhibits a U-shaped influence unexplored by the literature, deterring policy compliance until a larger amount surfaces, diminishing informational value, escalating public uncertainty. Overall, these findings demonstrate the power of information technology, such as media analytics and location sensing, in disaster management. They also illuminate the significance of strategic information management during disasters and the imperative need for cohesive efforts across governments, media, technology platforms, and the general public to curb future infodemics…(More)”.

How can data stop homelessness before it starts?


Article by Andrea Danes and Jessica Chamba: “When homelessness in Maidstone, England, soared by 58% over just five years, the Borough Council sought to shift its focus from crisis response to building early-intervention and prevention capacity. Working with EY teams and our UK technology partner, Xantura, the council created and implemented a data-focused tool — called OneView — that enabled the council to tackle their challenges in a new way.

Specifically, OneView’s predictive analytic and natural language generation capabilities enabled participating agencies in Maidstone to bring together their data to identify residents who were at risk of homelessness, and then to intervene before they were actually living on the street. In the initial pilot year, almost 100 households were prevented from becoming homeless, even as the COVID-19 pandemic took hold and grew. And, overall, the rate of homelessness fell by 40%. 

As evidenced by the Maidstone model, data analytics and predictive modeling will play an indispensable role in enabling us to realize a very big vision — a world in which everyone has a reliable roof over their heads.

Against that backdrop, it’s important to stress that the roadmap for preventing homelessness has to contain components beyond just better avenues for using data. It must also include shrewd approaches for dealing with complex issues such as funding, standards, governance, cultural differences and informed consent to permit the exchange of personal information, among others. Perhaps most importantly, the work needs to be championed by organizational and governmental leaders who believe transformative, systemic change is possible and are committed to achieving it.

Introducing the Smart Safety Net

To move forward, human services organizations need to look beyond modernizing service delivery to transforming it, and to evolve from integration to intuitive design. New technologies provide opportunities to truly rethink and redesign in ways that would have been impossible in the past.

A Smart Safety Net can shape a bold new future for social care. Doing so will require broad, fundamental changes at an organizational level, more collaboration across agencies, data integration and greater care co-ordination. At its heart, a Smart Safety Net entails:

  • A system-wide approach to addressing the needs of each individual and family, including pooled funding that supports coordination so that, for example, users in one program are automatically enrolled in other programs for which they are eligible.
  • Human-centered design that genuinely integrates the recipients of services (patients, clients, customers, etc.), as well as their experiences and insights, into the creation and implementation of policies, systems and services that affect them.
  • Data-driven policy, services, workflows, automation and security to improve processes, save money and facilitate accurate, real-time decision-making, especially to advance the overarching priority of nearly every program and service; that is, early intervention and prevention.
  • Frontline case workers who are supported and empowered to focus on their core purpose. With a lower administrative burden, they are able to invest more time in building relationships with vulnerable constituents and act as “coaches” to improve people’s lives.
  • Outcomes-based commissioning of services, measured against a more holistic wellbeing framework, from an ecosystem of public, private and not-for-profit providers, with government acting as system stewards and service integrators…(More)”.

Use of science in public policy: Lessons from the COVID-19 pandemic efforts to ‘Follow the Science’


Paper by Barry Bozeman: “The paper asks: ‘What can we learn from COVID-19 pandemic about effective use of scientific and technical information (STI) in policymaking and how might the lessons be put to use?’ The paper employs the political rhetoric of ‘follow the science’ as a lens for examining contemporary concerns in the use of STI, including (1) ‘Breadth of Science Products’, the necessity of a broader concept of STI that includes by-products science, (2) ‘Science Dynamism’, emphasizing the uncertainty and impeachability of science, (3) ‘STI Urgency’ suggesting that STI use during widespread calamities differs from more routine applications, and (4) ‘Hyper-politicization of Science’, arguing that a step-change in the contentiousness of politics affects uses and misuses of STI. The paper concludes with a discussion, STI Curation, as a possible ingredient to improving effective use. With more attention to credibility and trust of STI and to the institutional legitimacy of curators, it should prove possible to improve the effective use of STI in public policy….(More)”.

Serving citizens: measuring the performance of services for a better user experience


OECD Report: “Measuring the performance of services and making effective use of the results are critical for designing and delivering policies to improve people’s lives. Improving user satisfaction with public services is an objective in many OECD countries and is one of the indicators in the 2030 Sustainable Development Goal 16 of “Building effective, accountable and inclusive institutions at all levels”. This paper explores the use of satisfaction indicators to monitor citizens’ and users’ experience with public services. It finds that satisfaction indicators provide an accurate aggregate account of the factors driving service performance. At the same time, it shows that additional measures are needed to monitor the access, responsiveness and quality of public services, as well as to identify concrete areas of improvement. This paper provides examples of how countries use performance data in decision making (both subjective users’ experience and objective service outputs). It also highlights common challenges and good practices to strengthen performance measurement and management…(More)”.

Toolkit on Digital Transformation for People-Oriented Cities and Communities


Toolkit by the ITU: “The Toolkit on Digital Transformation for People-Oriented Cities and Communities supports strategizing and planning the digital transformation of cities and communities to promote sustainable, inclusive, resilient and improved quality of life for residents in cities and communities.

The resources contained in this Toolkit include international standards and guidance, the latest research and projections, and cutting-edge reports on a variety of timely topics relevant to the digital transformation of cities and communities. The Toolkit can universally benefit cities and communities, as well as regions and countries regardless of their level of smart or digital development, or their geographical or economic status. ​

The Toolkit is:​

  • A one-stop guide containing latest international standards and other ITU and UN resources, publications and reports.​
  • An endeavour to identify the challenges faced by cities as well as potential solutions that they can leverage for maximum positive impact.​
  • A comprehensive, yet non-exhaustive collation of information that is meant to inspire and support progress toward the SDGs, especially SDG 11, at the local level.​..(More)”

Facial Expressions Do Not Reveal Emotions


Lisa Feldman Barrett at Scientific American: “Do your facial movements broadcast your emotions to other people? If you think the answer is yes, think again. This question is under contentious debate. Some experts maintain that people around the world make specific, recognizable faces that express certain emotions, such as smiling in happiness, scowling in anger and gasping with widened eyes in fear. They point to hundreds of studies that appear to demonstrate that smiles, frowns, and so on are universal facial expressions of emotion. They also often cite Charles Darwin’s 1872 book The Expression of the Emotions in Man and Animals to support the claim that universal expressions evolved by natural selection.

Other scientists point to a mountain of counterevidence showing that facial movements during emotions vary too widely to be universal beacons of emotional meaning. People may smile in hatred when plotting their enemy’s downfall and scowl in delight when they hear a bad pun. In Melanesian culture, a wide-eyed gasping face is a symbol of aggression, not fear. These experts say the alleged universal expressions just represent cultural stereotypes. To be clear, both sides in the debate acknowledge that facial movements vary for a given emotion; the disagreement is about whether there is enough uniformity to detect what someone is feeling.

This debate is not just academic; the outcome has serious consequences. Today you can be turned down for a job because a so-called emotion-reading system watching you on camera applied artificial intelligence to evaluate your facial movements unfavorably during an interview. In a U.S. court of law, a judge or jury may sometimes hand down a harsher sentence, even death, if they think a defendant’s face showed a lack of remorse. Children in preschools across the country are taught to recognize smiles as happiness, scowls as anger and other expressive stereotypes from books, games and posters of disembodied faces. And for children on the autism spectrum, some of whom have difficulty perceiving emotion in others, these teachings do not translate to better communication….Emotion AI systems, therefore, do not detect emotions. They detect physical signals, such as facial muscle movements, not the psychological meaning of those signals. The conflation of movement and meaning is deeply embedded in Western culture and in science. An example is a recent high-profile study that applied machine learning to more than six million internet videos of faces. The human raters, who trained the AI system, were asked to label facial movements in the videos, but the only labels they were given to use were emotion words, such as “angry,” rather than physical descriptions, such as “scowling.” Moreover there was no objective way to confirm what, if anything, the anonymous people in the videos were feeling in those moments…(More)”.

Citizen power mobilized to fight against mosquito borne diseases


GigaBlog: “Just out in GigaByte is the latest data release from Mosquito Alert, a citizen science system for investigating and managing disease-carrying mosquitoes, and is part of our WHO-sponsored series on vector borne human diseases. Presenting 13,700 new database records in the Global Biodiversity Information Facility (GBIF) repository, all linked to photographs submitted by citizen volunteers and validated by entomological experts to determine if it provides evidence of the presence of any of the mosquito vectors of top concern in Europe. This is the latest of a new special issue of papers presenting biodiversity data for research on human diseases health, incentivising data sharing to fill important particular species and geographic gaps. As big fans of citizen science (and Mosquito Alert), its great to see this new data showcased in the series.

Vector-borne diseases account for more than 17% of all infectious diseases in humans. There are large gaps in knowledge related to these vectors, and data mobilization campaigns are required to improve data coverage to help research on vector-borne diseases and human health. As part of these efforts, GigaScience Press has partnered with the GBIF; and has been supported by TDR, the Special Programme for Research and Training in Tropical Diseases, hosted at the World Health Organization. Through this we launched this “Vectors of human disease” thematic series. Incentivising the sharing of this extremely important data, Article Processing Charges have been waived to assist with the global call for novel data. This effort has already led to the release of newly digitised location data for over 600,000 vector specimens observed across the Americas and Europe.

While paying credit to such a large number of volunteers, creating such a large public collection of validated mosquito images allows this dataset to be used to train machine-learning models for vector detection and classification. Sharing the data in this novel manner meant the authors of these papers had to set up a new credit system to evaluate contributions from multiple and diverse collaborators, which included university researchers, entomologists, and other non-academics such as independent researchers and citizen scientists. In the GigaByte paper these are acknowledged through collaborative authorship for the Mosquito Alert Digital Entomology Network and the Mosquito Alert Community…(More)”.