Bridging Systems: Open Problems for Countering Destructive Divisiveness across Ranking, Recommenders, and Governance

Divisiveness appears to be increasing in much of the world, leading to concern about political violence and a decreasing capacity to collaboratively address large-scale societal challenges. In this working paper we aim to articulate an interdisciplinary research and practice area focused on what we call bridging systems: systems which increase mutual understanding and trust across divides, creating space for productive conflict, deliberation, or cooperation. We give examples of bridging systems across three domains: recommender systems on social media, collective response systems, and human-facilitated group deliberation. We argue that these examples can be more meaningfully understood as processes for attention-allocation (as opposed to "content distribution" or "amplification") and develop a corresponding framework to explore similarities - and opportunities for bridging - across these seemingly disparate domains. We focus particularly on the potential of bridging-based ranking to bring the benefits of offline bridging into spaces which are already governed by algorithms. Throughout, we suggest research directions that could improve our capacity to incorporate bridging into a world increasingly mediated by algorithms and artificial intelligence.Comment: 40 pages, 11 figures. See https://bridging.systems for more about this wor

Error in the Euclidean Preference Model

Spatial models of preference, in the form of vector embeddings, are learned by many deep learning and multiagent systems, including recommender systems. Often these models are assumed to approximate a Euclidean structure, where an individual prefers alternatives positioned closer to their "ideal point", as measured by the Euclidean metric. However, Bogomolnaia and Laslier (2007) showed that there exist ordinal preference profiles that cannot be represented with this structure if the Euclidean space has two fewer dimensions than there are individuals or alternatives. We extend this result, showing that there are realistic situations in which almost all preference profiles cannot be represented with the Euclidean model, and derive a theoretical lower bound on the expected error when using the Euclidean model to approximate non-Euclidean preference profiles. Our results have implications for the interpretation and use of vector embeddings, because in some cases close approximation of arbitrary, true ordinal relationships can be expected only if the dimensionality of the embeddings is a substantial fraction of the number of entities represented.Comment: 11 pages, 5 figures. Accepted as an Extended Abstract to AAMAS 202

SHAPE: A Framework for Evaluating the Ethicality of Influence

Agents often exert influence when interacting with humans and non-human agents. However, the ethical status of such influence is often unclear. In this paper, we present the SHAPE framework, which lists reasons why influence may be unethical. We draw on literature from descriptive and moral philosophy and connect it to machine learning to help guide ethical considerations when developing algorithms with potential influence. Lastly, we explore mechanisms for governing algorithmic systems that influence people, inspired by mechanisms used in journalism, human subject research, and advertising.Comment: An earlier version of this paper was accepted at EUMAS 202

Tools to Ease the Choice and Design of Protein Crystallisation Experiments

The process of macromolecular crystallisation almost always begins by setting up crystallisation trials using commercial or other premade screens, followed by cycles of optimisation where the crystallisation cocktails are focused towards a particular small region of chemical space. The screening process is relatively straightforward, but still requires an understanding of the plethora of commercially available screens. Optimisation is complicated by requiring both the design and preparation of the appropriate secondary screens. Software has been developed in the C3 lab to aid the process of choosing initial screens, to analyse the results of the initial trials, and to design and describe how to prepare optimisation screens

Online Handbook of Argumentation for AI: Volume 2

Editors: Federico Castagna, Francesca Mosca, Jack Mumford, Stefan Sarkadi and Andreas Xydis.This volume contains revised versions of the papers selected for the second volume of the Online Handbook of Argumentation for AI (OHAAI). Previously, formal theories of argument and argument interaction have been proposed and studied, and this has led to the more recent study of computational models of argument. Argumentation, as a field within artificial intelligence (AI), is highly relevant for researchers interested in symbolic representations of knowledge and defeasible reasoning. The purpose of this handbook is to provide an open access and curated anthology for the argumentation research community. OHAAI is designed to serve as a research hub to keep track of the latest and upcoming PhD-driven research on the theory and application of argumentation in all areas related to AI

The commercial food landscape: outdoor food advertising around primary schools in Australia

Objective: Food marketing is linked to childhood obesity through its influence on children’s food preferences, purchase requests and food consumption. We aimed to describe the volume and nature of outdoor food advertisements and factors associated with outdoor food advertising in the area surrounding Australian primary schools. Methods: Forty primary schools in Sydney and Wollongong were selected using random sampling within population density and socio-economic strata. The area within a 500m radius of each school was scanned and advertisements coded according to pre-defined criteria, including: food or non-food product advertisement, distance from the school, size and location. Food advertisements were further categorised as core foods, non-core foods and miscellaneous drinks (tea and coffee). Results: The number of advertisements identified was 9,151, of which 2,286 (25%) were for food. The number of non-core food advertisements was 1,834, this accounted for 80% of food advertisements. Soft drinks and alcoholic beverages were the food products most commonly advertised around primary schools (24% and 22% of food advertisements, respectively). Non-core food products were twice as likely to be advertised close to a primary school (95 non-core food advertisements per km2 within 250 m vs. 46 advertisements per km2 within 250-500 m). Conclusions: The density of non-core food advertisements within 500 m of primary schools, and the potential for repeated exposure of children to soft drink and alcoholic beverage advertisements in particular, highlights the need for outdoor food marketing policy intervention. Implications: Outdoor advertising is an important food marketing tool that should be considered in future debates on regulation of food marketing to children

Phase I clinical trial and pharmacodynamic evaluation of combination hydroxychloroquine and doxorubicin treatment in pet dogs treated for spontaneously occurring lymphoma

Autophagy is a lysosomal degradation process that may act as a mechanism of survival in a variety of cancers. While pharmacologic inhibition of autophagy with hydroxychloroquine (HCQ) is currently being explored in human clinical trials, it has never been evaluated in canine cancers. Non-Hodgkin lymphoma (NHL) is one of the most prevalent tumor types in dogs and has similar pathogenesis and response to treatment as human NHL. Clinical trials in canine patients are conducted in the same way as in human patients, thus, to determine a maximum dose of HCQ that can be combined with a standard chemotherapy, a Phase I, single arm, dose escalation trial was conducted in dogs with spontaneous NHL presenting as patients to an academic, tertiary-care veterinary teaching hospital. HCQ was administered daily by mouth throughout the trial, beginning 72 h prior to doxorubicin (DOX), which was given intravenously on a 21-d cycle. Peripheral blood mononuclear cells and biopsies were collected before and 3 d after HCQ treatment and assessed for autophagy inhibition and HCQ concentration. A total of 30 patients were enrolled in the trial. HCQ alone was well tolerated with only mild lethargy and gastrointestinal-related adverse events. The overall response rate (ORR) for dogs with lymphoma was 93.3%, with median progression-free interval (PFI) of 5 mo. Pharmacokinetic analysis revealed a 100-fold increase in HCQ in tumors compared with plasma. There was a trend that supported therapy-induced increase in LC3-II (the cleaved and lipidated form of microtubule-associated protein 1 light chain 3/LC3, which serves as a maker for autophagosomes) and SQSTM1/p62 (sequestosome 1) after treatment. The superior ORR and comparable PFI to single-agent DOX provide strong support for further evaluation via randomized, placebo-controlled trials in canine and human NHL

Tools to Ease the Choice and Design of Protein Crystallisation Experiments

The process of macromolecular crystallisation almost always begins by setting up crystallisation trials using commercial or other premade screens, followed by cycles of optimisation where the crystallisation cocktails are focused towards a particular small region of chemical space. The screening process is relatively straightforward, but still requires an understanding of the plethora of commercially available screens. Optimisation is complicated by requiring both the design and preparation of the appropriate secondary screens. Software has been developed in the C3 lab to aid the process of choosing initial screens, to analyse the results of the initial trials, and to design and describe how to prepare optimisation screens

Characterization of mitochondrial FOXRED1 in the assembly of respiratory chain complex I

Human mitochondrial complex I is the largest enzyme of the respiratory chain and is composed of 44 different subunits. Complex I subunits are encoded by both nuclear and mitochondrial (mt) DNA and their assembly requires a number of additional proteins. FAD-dependent oxidoreductase domain-containing protein 1 (FOXRED1) was recently identified as a putative assembly factor and FOXRED1 mutations in patients cause complex I deficiency; however, its role in assembly is unknown. Here, we demonstrate that FOXRED1 is involved in mid-late stages of complex I assembly. In a patient with FOXRED1 mutations, the levels of mature complex I were markedly decreased, and a smaller ∼475 kDa subcomplex was detected. In the absence of FOXRED1, mtDNA-encoded complex I subunits are still translated and transiently assembled into a late stage ∼815 kDa intermediate; but instead of transitioning further to the mature complex I, the intermediate breaks down to an ∼475 kDa complex. As the patient cells contained residual assembled complex I, we disrupted the FOXRED1 gene in HEK293T cells through TALEN-mediated gene editing. Cells lacking FOXRED1 had ∼10% complex I levels, reduced complex I activity, and were unable to grow on galactose media. Interestingly, overexpression of FOXRED1 containing the patient mutations was able to rescue complex I assembly. In addition, FOXRED1 was found to co-immunoprecipitate with a number of complex I subunits. Our studies reveal that FOXRED1 is a crucial component in the productive assembly of complex I and that mutations in FOXRED1 leading to partial loss of function cause defects in complex I biogenesis