Alexander J. Gates, Rion Brattig Correia, Xuan Wang, and Luis M. Rocha

PNAS March 23, 2021 118 (12) e2022598118

Many biological networks are modeled with multivariate discrete dynamical systems. Current theory suggests that the network of interactions captures salient features of system dynamics, but it misses a key aspect of these networks: some interactions are more important than others due to dynamical redundancy and nonlinearity. This unequivalence leads to a canalized dynamics that differs from constraints inferred from network structure alone. To capture the redundancy present in biochemical regulatory and signaling interactions, we present the effective graph, an experimentally validated mathematical framework that synthesizes both structure and dynamics in a weighted graph representation of discrete multivariate systems. Our results demonstrate the ubiquity of redundancy in biology and provide a tool to increase causal explainability and control of biochemical systems.

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Gordon Pennycook, Ziv Epstein, Mohsen Mosleh, Antonio A. Arechar, Dean Eckles & David G. Rand
Nature (2021)

In recent years, there has been a great deal of concern about the proliferation of false and misleading news on social media1–4. Academics and practitioners alike have asked why people share such misinformation, and sought solutions to reduce the sharing of misinformation5–7. Here, we attempt to address both of these questions. First, we find that the veracity of headlines has little effect on sharing intentions, despite having a large effect on judgments of accuracy. This dissociation suggests that sharing does not necessarily indicate belief. Nonetheless, most participants say it is important to share only accurate news. To shed light on this apparent contradiction, we carried out four survey experiments and a field experiment on Twitter; the results show that subtly shifting attention to accuracy increases the quality of news that people subsequently share. Together with additional computational analyses, these findings indicate that people often share misinformation because their attention is focused on factors other than accuracy—and therefore they fail to implement a strongly held preference for accurate sharing. Our results challenge the popular claim that people value partisanship over accuracy8,9, and provide evidence for scalable attention-based interventions that social media platforms could easily implement to counter misinformation online. Surveys and a field experiment with Twitter users show that prompting people to think about the accuracy of news sources increases the quality of the news that they share online.

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Avi Wigderson and László Lovász won for their work developing complexity theory and graph theory, respectively, and for connecting the two fields.

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Distinguishing excessive doubt from excessive belief can help inform how to bring a conspiracy theorist back to reality.

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Michael Batty

To explore the impact of the pandemic on the form and function of cities, we propose to simulate the forces of centralisation and decentralisation for different urban futures which we encapsulate in the spatial interaction patterns linking places of work to residence. Because the current pandemic has distorted locational patterns in current cities so radically, we first build a hypothetical city on a square grid that we then proceed to lock down in terms of the percentage of the population no longer at their traditional places of work but working from home. We explore various pictures under different levels of lockdown showing how non-locked down activity responds to the changing urban landscape. We add some randomness to provide a greater degree of diversity and this partially breaks the symmetry of the idealised system. We then introduce different patterns of deterrence which imply different average trip lengths exploring a range of forms from highly centralised to decentralised. We illustrate how the system moves to different forms as we release the lockdown and let the system react to the continually changing urban landscape which produces a series of highly concentrated equilibria. This generates different patterns that we then perturb by adding a degree of randomness in the size of locations and we conclude by scaling the city from its 11×11 grid to one of 41×41 more illustrative of the diversity and degree of asymmetry in large cities like London. To progress this approach, we need to adapt our hypothetical model to real cities and continue such speculation through

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