Welcome to Big Tech's'Age of Extraction' In his new book, antitrust scholar and former White House adviser Tim Wu argues that tech giants are bleeding you dry--and lays out a plan to stop them. Growing up in Toronto, Tim Wu had a classmate who was the progeny of Communist parents. His name was Cory Doctorow. Yes, the same guy who just published a book about enshittification . Though they shared a general world view, the boyhood pals also had arguments, with Wu typically taking a less radical stance than his buddy.

The COVID-19 pandemic underscored a critical need for intervention strategies that balance disease containment with socioeconomic stability. We approach this challenge by designing a framework for modeling and evaluating disease-spread prevention strategies. Our framework leverages multi-objective reinforcement learning (MORL) - a formulation necessitated by competing objectives - combined with a new stochastic differential equation (SDE) pandemic simulator, calibrated and validated against global COVID-19 data. Our simulator reproduces national-scale pandemic dynamics with orders of magnitude higher fidelity than other models commonly used in reinforcement learning (RL) approaches to pandemic intervention. Training a Pareto-Conditioned Network (PCN) agent on this simulator, we illustrate the direct policy trade-offs between epidemiological control and economic stability for COVID-19. Furthermore, we demonstrate the framework's generality by extending it to pathogens with different epidemiological profiles, such as polio and influenza, and show how these profiles lead the agent to discover fundamentally different intervention policies. To ground our work in contemporary policymaking challenges, we apply the model to measles outbreaks, quantifying how a modest 5% drop in vaccination coverage necessitates significantly more stringent and costly interventions to curb disease spread. This work provides a robust and adaptable framework to support transparent, evidence-based policymaking for mitigating public health crises.

For rapidly spreading diseases where many cases show no symptoms, swift and effective contact tracing is essential. While exposure notification applications provide alerts on potential exposures, a fully automated system is needed to track the infectious transmission routes. To this end, our research leverages large-scale contact networks from real human mobility data to identify the path of transmission. More precisely, we introduce a new Infectious Path Centrality network metric that informs a graph learning edge classifier to identify important transmission events, achieving an F1-score of 94%. Additionally, we explore bidirectional contact tracing, which quarantines individuals both retroactively and proactively, and compare its effectiveness against traditional forward tracing, which only isolates individuals after testing positive. Our results indicate that when only 30% of symptomatic individuals are tested, bidirectional tracing can reduce infectious effective reproduction rate by 71%, thus significantly controlling the outbreak.

Agent-based models have proven to be useful tools in supporting decision-making processes in different application domains. The advent of modern computers and supercomputers has enabled these bottom-up approaches to realistically model human mobility and contact behavior. The COVID-19 pandemic showcased the urgent need for detailed and informative models that can answer research questions on transmission dynamics. We present a sophisticated agent-based model to simulate the spread of respiratory diseases. The model is highly modularized and can be used on various scales, from a small collection of buildings up to cities or countries. Although not being the focus of this paper, the model has undergone performance engineering on a single core and provides an efficient intra- and inter-simulation parallelization for time-critical decision-making processes. In order to allow answering research questions on individual level resolution, nonpharmaceutical intervention strategies such as face masks or venue closures can be implemented for particular locations or agents. In particular, we allow for sophisticated testing and isolation strategies to study the effects of minimal-invasive infectious disease mitigation. With realistic human mobility patterns for the region of Brunswick, Germany, we study the effects of different interventions between March 1st and May 30, 2021 in the SARS-CoV-2 pandemic. Our analyses suggest that symptom-independent testing has limited impact on the mitigation of disease dynamics if the dark figure in symptomatic cases is high. Furthermore, we found that quarantine length is more important than quarantine efficiency but that, with sufficient symptomatic control, also short quarantines can have a substantial effect.

A multiagent system can be viewed as a society of autonomous agents, whose interactions can be effectively regulated via social norms. In general, the norms of a society are not hardcoded but emerge from the agents' interactions. Specifically, how the agents in a society react to each other's behavior and respond to the reactions of others determines which norms emerge in the society. We think of these reactions by an agent to the satisfactory or unsatisfactory behaviors of another agent as communications from the first agent to the second agent. Understanding these communications is a kind of social intelligence: these communications provide natural drivers for norm emergence by pushing agents toward certain behaviors, which can become established as norms. Whereas it is well-known that sanctioning can lead to the emergence of norms, we posit that a broader kind of social intelligence can prove more effective in promoting cooperation in a multiagent system. Accordingly, we develop Nest, a framework that models social intelligence in the form of a wider variety of communications and understanding of them than in previous work. To evaluate Nest, we develop a simulated pandemic environment and conduct simulation experiments to compare Nest with baselines considering a combination of three kinds of social communication: sanction, tell, and hint. We find that societies formed of Nest agents achieve norms faster; moreover, Nest agents effectively avoid undesirable consequences, which are negative sanctions and deviation from goals, and yield higher satisfaction for themselves than baseline agents despite requiring only an equivalent amount of information.

Chengdu, China – Sitting at the entrance of Chengdu's East Railway Station, Fu Guobin stared at a screen displaying infrared images of people passing through the station's gates. As each person entered, a number popped up next to their image indicating their body temperature. "This is making my life much easier," the station employee said as he sat in his booth. "Before this, I'd have to test everyone's temperature with an ear thermometer. And sometimes that doesn't work – I think this new system is much better."

Valerie Johnson is an avid traveler who loves the outdoors. Next on her list is a trip to Walden Pond, in Massachusetts. But the 27-year-old Texan won't need a plane ticket; all she'll need is a video game. Johnson was recently diagnosed with idiopathic intracranial hypertension, a neurological disorder that can cause headaches, impaired vision, and joint pain. These symptoms make travel--particularly to the outdoors--daunting.

An expansive compound of buildings covering the equivalent of 46 football pitches was recently erected on the outskirts of Guangzhou, China's bustling southern metropolis. The sprawling complex of three-storey buildings contains some 5,000 rooms and is the first of what is expected to be a chain of quarantine centres built by the Chinese government to house people arriving from overseas as it forges ahead with its zero-tolerance approach to COVID. The compound is equipped with "5G communication technology and artificial intelligence" infrastructure, and each room, which can host only one person at a time, has cameras at its door and a robot delivery system to "minimise human contact and the risk of cross-infection", according to the introduction to the centre put out by the Guangzhou government. It took the construction team less than three months to finish the project – in an echo of the Huoshenshan and Leishenshan temporary hospitals that were built in record time in the central city of Wuhan as COVID-19 took hold in early 2020. But while those hospitals were greeted with relief, the appearance of the quarantine centre nearly two years after the trauma of Wuhan has left some wondering why China is not relaxing its virus strategy now that the vast majority of its one billion people have been fully vaccinated. They're building more facilities but there is no indication the authorities plan to ease the restrictions that have effectively ended international travel for people in China.

Soon there will be no need for a passenger of the Moscow subway to pause in front of the turnstiles and frantically search their pockets for a transit card or ticket. Starting from Oct. 15, a glance at the camera will open the pay gate. On Wednesday, Moscow Mayor Sergei Sobyanin announced that the Face Pay system will soon be available at all subway stations (about 300). To be able to use it, commuters register in the Moscow subway app, upload a photo of their face, and attach their bank card. Once the user approaches turnstiles, the camera recognizes the face (even if the person is wearing a mask), the fare is debited from their account, and the pay gate opens.

The government of South Australia has implemented a new policy requiring Australians to use an app with facial recognition software and geolocation to prove that they are abiding by a 14-day quarantine for travel within the country. While a conservative policy expert described the policy as "Orwellian," he told Fox News that it represents an improvement over the current COVID-19 policy. Australia has banned international travel unless residents have a permit to leave the country. The country has also severely restricted travel between the six states of Australia. Residents must spend 14 days in quarantine upon return.