Distorted insights from human mobility data


Paper by Riccardo Gallotti, Davide Maniscalco, Marc Barthelemy & Manlio De Domenico: “The description of human mobility is at the core of many fundamental applications ranging from urbanism and transportation to epidemics containment. Data about human movements, once scarce, is now widely available thanks to new sources such as phone call detail records, GPS devices, or Smartphone apps. Nevertheless, it is still common to rely on a single dataset by implicitly assuming that the statistical properties observed are robust regardless of data gathering and processing techniques. Here, we test this assumption on a broad scale by comparing human mobility datasets obtained from 7 different data-sources, tracing 500+ millions individuals in 145 countries. We report wide quantifiable differences in the resulting mobility networks and in the displacement distribution. These variations impact processes taking place on these networks like epidemic spreading. Our results point to the need for disclosing the data processing and, overall, to follow good practices to ensure robust and reproducible results…(More)”

SciAgents: Automating Scientific Discovery Through Bioinspired Multi-Agent Intelligent Graph Reasoning


Paper by Alireza Ghafarollahi, and Markus J. Buehler: “A key challenge in artificial intelligence (AI) is the creation of systems capable of autonomously advancing scientific understanding by exploring novel domains, identifying complex patterns, and uncovering previously unseen connections in vast scientific data. In this work, SciAgents, an approach that leverages three core concepts is presented: (1) large-scale ontological knowledge graphs to organize and interconnect diverse scientific concepts, (2) a suite of large language models (LLMs) and data retrieval tools, and (3) multi-agent systems with in-situ learning capabilities. Applied to biologically inspired materials, SciAgents reveals hidden interdisciplinary relationships that were previously considered unrelated, achieving a scale, precision, and exploratory power that surpasses human research methods. The framework autonomously generates and refines research hypotheses, elucidating underlying mechanisms, design principles, and unexpected material properties. By integrating these capabilities in a modular fashion, the system yields material discoveries, critiques and improves existing hypotheses, retrieves up-to-date data about existing research, and highlights strengths and limitations. This is achieved by harnessing a “swarm of intelligence” similar to biological systems, providing new avenues for discovery. How this model accelerates the development of advanced materials by unlocking Nature’s design principles, resulting in a new biocomposite with enhanced mechanical properties and improved sustainability through energy-efficient production is shown…(More)”.

Academic writing is getting harder to read—the humanities most of all


The Economist: “Academics have long been accused of jargon-filled writing that is impossible to understand. A recent cautionary tale was that of Ally Louks, a researcher who set off a social media storm with an innocuous post on X celebrating the completion of her PhD. If it was Ms Louks’s research topic (“olfactory ethics”—the politics of smell) that caught the attention of online critics, it was her verbose thesis abstract that further provoked their ire. In two weeks, the post received more than 21,000 retweets and 100m views.

Although the abuse directed at Ms Louks reeked of misogyny and anti-intellectualism—which she admirably shook off—the reaction was also a backlash against an academic use of language that is removed from normal life. Inaccessible writing is part of the problem. Research has become harder to read, especially in the humanities and social sciences. Though authors may argue that their work is written for expert audiences, much of the general public suspects that some academics use gobbledygook to disguise the fact that they have nothing useful to say. The trend towards more opaque prose hardly allays this suspicion…(More)”.

Protecting civilians in a data-driven and digitalized battlespace: Towards a minimum basic technology infrastructure


Paper by Ann Fitz-Gerald and Jenn Hennebry: “This article examines the realities of modern day warfare, including a rising trend in hybrid threats and irregular warfare which employ emerging technologies supported by digital and data-driven processes. The way in which these technologies become applied generates a widened battlefield and leads to a greater number of civilians being caught up in conflict. Humanitarian groups mandated to protect civilians have adapted their approaches to the use of new emerging technologies. However, the lack of international consensus on the use of data, the public and private nature of the actors involved in conflict, the transnational aspects of the widened battlefield, and the heightened security risks in the conflict space pose enormous challenges for the protection of civilians agenda. Based on the dual-usage aspect of emerging technologies, the challenges associated with regulation and the need for those affected by conflict to demonstrate resilience towards, and knowledge of, digital media literacy, this paper proposes the development of guidance for a “minimum basic technology infrastructure” which is supported by technology, regulation, and public awareness and education…(More)”.

Behaviour-based dependency networks between places shape urban economic resilience


Paper by Takahiro Yabe et al: “Disruptions, such as closures of businesses during pandemics, not only affect businesses and amenities directly but also influence how people move, spreading the impact to other businesses and increasing the overall economic shock. However, it is unclear how much businesses depend on each other during disruptions. Leveraging human mobility data and same-day visits in five US cities, we quantify dependencies between points of interest encompassing businesses, stores and amenities. We find that dependency networks computed from human mobility exhibit significantly higher rates of long-distance connections and biases towards specific pairs of point-of-interest categories. We show that using behaviour-based dependency relationships improves the predictability of business resilience during shocks by around 40% compared with distance-based models, and that neglecting behaviour-based dependencies can lead to underestimation of the spatial cascades of disruptions. Our findings underscore the importance of measuring complex relationships in patterns of human mobility to foster urban economic resilience to shocks…(More)”.

Once It Has Been Trained, Who Will Own My Digital Twin?


Article by Todd Carpenter: “Presently, if one ignores the hype around Generative AI systems, we can recognize that software tools are not sentient. Nor can they (yet) overcome the problem of coming up with creative solutions to novel problems. They are limited in what they can do by the training data that they are supplied. They do hold the prospect for making us more efficient and productive, particularly for wrote tasks. But given enough training data, one could consider how much farther this could be taken. In preparation for that future, when it comes to the digital twins, the landscape of the ownership of the intellectual property (IP) behind them is already taking shape.

Several chatbots have been set up to replicate long-dead historical figures so that you can engage with them in their “voice”.  Hellohistory is an AI-driven chatbot that provides people the opportunity to, “have in-depth conversations with history’s greatest.” A different tool, Historical Figures Chat, was widely panned not long after its release in 2023, and especially by historians who strongly objected. There are several variations on this theme of varying quality. Of course, with all things GenAI, they will improve over time and many of the obvious and problematic issues will be resolved either by this generation of companies or the next. Whether there is real value and insight to be gained, apart from the novelty, of engaging with “real historical figures” is the multi-billion dollar question. Much like the World Wide Web in the 1990s, very likely there is value, but it will be years before it can be clearly discerned what that value is and how to capitalize upon it. In anticipation of that day, many organizations are positioning themselves to capture that value.

While many universities have taken a very liberal view of ownership of the intellectual property of their students and faculty — far more liberal than many corporations might — others are quite more restrictive…(More)”.

Big brother: the effects of surveillance on fundamental aspects of social vision 


Paper by Kiley Seymour et al: “Despite the dramatic rise of surveillance in our societies, only limited research has examined its effects on humans. While most research has focused on voluntary behaviour, no study has examined the effects of surveillance on more fundamental and automatic aspects of human perceptual awareness and cognition. Here, we show that being watched on CCTV markedly impacts a hardwired and involuntary function of human sensory perception—the ability to consciously detect faces. Using the method of continuous flash suppression (CFS), we show that when people are surveilled (N = 24), they are quicker than controls (N = 30) to detect faces. An independent control experiment (N = 42) ruled out an explanation based on demand characteristics and social desirability biases. These findings show that being watched impacts not only consciously controlled behaviours but also unconscious, involuntary visual processing. Our results have implications concerning the impacts of surveillance on basic human cognition as well as public mental health…(More)”.

How Your Car Might Be Making Roads Safer


Article by Kashmir Hill: “Darcy Bullock, a civil engineering professor at Purdue University, turns to his computer screen to get information about how fast cars are traveling on Interstate 65, which runs 887 miles from Lake Michigan to the Gulf of Mexico. It’s midafternoon on a Monday, and his screen is mostly filled with green dots indicating that traffic is moving along nicely. But near an exit on the outskirts of Indianapolis, an angry red streak shows that cars have stopped moving.

A traffic camera nearby reveals the cause: A car has spun out, causing gridlock.

In recent years, vehicles that have wireless connectivity have become a critical source of information for transportation departments and for academics who study traffic patterns. The data these vehicles emit — including speed, how hard they brake and accelerate, and even if their windshield wipers are on — can offer insights into dangerous road conditions, congestion or poorly timed traffic signals.

“Our cars know more about our roads than agencies do,” said Dr. Bullock, who regularly works with the Indiana Department of Transportation to conduct studies on how to reduce traffic congestion and increase road safety. He credits connected-car data with detecting hazards that would have taken years — and many accidents — to find in the past.

The data comes primarily from commercial trucks and from cars made by General Motors that are enrolled in OnStar, G.M.’s internet-connected service. (Drivers know OnStar as the service that allows them to lock their vehicles from a smartphone app or find them if they have been stolen.) Federal safety guidelines require commercial truck drivers to be routinely monitored, but people driving G.M. vehicles may be surprised to know that their data is being collected, though it is indicated in the fine print of the company’s privacy policy…(More)”.

Digital Governance: Confronting the Challenges Posed by Artificial Intelligence


Book edited by Kostina Prifti, Esra Demir, Julia Krämer, Klaus Heine, and Evert Stamhuis: “This book explores the structure and frameworks of digital governance, focusing on various regulatory patterns, with the aim of tackling the disruptive impact of artificial intelligence (AI) technologies. Addressing the various challenges posed by AI technologies, this book explores potential avenues for crafting legal remedies and solutions, spanning liability of AI, platform governance, and the implications for data protection and privacy…(More)”.