1,201 research outputs found

    Multidisciplinary perspectives on Artificial Intelligence and the law

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    This open access book presents an interdisciplinary, multi-authored, edited collection of chapters on Artificial Intelligence (‘AI’) and the Law. AI technology has come to play a central role in the modern data economy. Through a combination of increased computing power, the growing availability of data and the advancement of algorithms, AI has now become an umbrella term for some of the most transformational technological breakthroughs of this age. The importance of AI stems from both the opportunities that it offers and the challenges that it entails. While AI applications hold the promise of economic growth and efficiency gains, they also create significant risks and uncertainty. The potential and perils of AI have thus come to dominate modern discussions of technology and ethics – and although AI was initially allowed to largely develop without guidelines or rules, few would deny that the law is set to play a fundamental role in shaping the future of AI. As the debate over AI is far from over, the need for rigorous analysis has never been greater. This book thus brings together contributors from different fields and backgrounds to explore how the law might provide answers to some of the most pressing questions raised by AI. An outcome of the Católica Research Centre for the Future of Law and its interdisciplinary working group on Law and Artificial Intelligence, it includes contributions by leading scholars in the fields of technology, ethics and the law.info:eu-repo/semantics/publishedVersio

    Conversations on Empathy

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    In the aftermath of a global pandemic, amidst new and ongoing wars, genocide, inequality, and staggering ecological collapse, some in the public and political arena have argued that we are in desperate need of greater empathy — be this with our neighbours, refugees, war victims, the vulnerable or disappearing animal and plant species. This interdisciplinary volume asks the crucial questions: How does a better understanding of empathy contribute, if at all, to our understanding of others? How is it implicated in the ways we perceive, understand and constitute others as subjects? Conversations on Empathy examines how empathy might be enacted and experienced either as a way to highlight forms of otherness or, instead, to overcome what might otherwise appear to be irreducible differences. It explores the ways in which empathy enables us to understand, imagine and create sameness and otherness in our everyday intersubjective encounters focusing on a varied range of "radical others" – others who are perceived as being dramatically different from oneself. With a focus on the importance of empathy to understand difference, the book contends that the role of empathy is critical, now more than ever, for thinking about local and global challenges of interconnectedness, care and justice

    LIPIcs, Volume 251, ITCS 2023, Complete Volume

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    LIPIcs, Volume 251, ITCS 2023, Complete Volum

    2023 SDSU Data Science Symposium Presentation Abstracts

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    This document contains abstracts for presentations and posters 2023 SDSU Data Science Symposium

    Less is More: Restricted Representations for Better Interpretability and Generalizability

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    Deep neural networks are prevalent in supervised learning for large amounts of tasks such as image classification, machine translation and even scientific discovery. Their success is often at the sacrifice of interpretability and generalizability. The increasing complexity of models and involvement of the pre-training process make the inexplicability more imminent. The outstanding performance when labeled data are abundant while prone to overfit when labeled data are limited demonstrates the difficulty of deep neural networks' generalizability to different datasets. This thesis aims to improve interpretability and generalizability by restricting representations. We choose to approach interpretability by focusing on attribution analysis to understand which features contribute to prediction on BERT, and to approach generalizability by focusing on effective methods in a low-data regime. We consider two strategies of restricting representations: (1) adding bottleneck, and (2) introducing compression. Given input x, suppose we want to learn y with the latent representation z (i.e. x→z→y), adding bottleneck means adding function R such that L(R(z)) < L(z) and introducing compression means adding function R so that L(R(y)) < L(y) where L refers to the number of bits. In other words, the restriction is added either in the middle of the pipeline or at the end of it. We first introduce how adding information bottleneck can help attribution analysis and apply it to investigate BERT's behavior on text classification in Chapter 3. We then extend this attribution method to analyze passage reranking in Chapter 4, where we conduct a detailed analysis to understand cross-layer and cross-passage behavior. Adding bottleneck can not only provide insight to understand deep neural networks but can also be used to increase generalizability. In Chapter 5, we demonstrate the equivalence between adding bottleneck and doing neural compression. We then leverage this finding with a framework called Non-Parametric learning by Compression with Latent Variables (NPC-LV), and show how optimizing neural compressors can be used in the non-parametric image classification with few labeled data. To further investigate how compression alone helps non-parametric learning without latent variables (NPC), we carry out experiments with a universal compressor gzip on text classification in Chapter 6. In Chapter 7, we elucidate methods of adopting the perspective of doing compression but without the actual process of compression using T5. Using experimental results in passage reranking, we show that our method is highly effective in a low-data regime when only one thousand query-passage pairs are available. In addition to the weakly supervised scenario, we also extend our method to large language models like GPT under almost no supervision --- in one-shot and zero-shot settings. The experiments show that without extra parameters or in-context learning, GPT can be used for semantic similarity, text classification, and text ranking and outperform strong baselines, which is presented in Chapter 8. The thesis proposes to tackle two big challenges in machine learning --- "interpretability" and "generalizability" through restricting representation. We provide both theoretical derivation and empirical results to show the effectiveness of using information-theoretic approaches. We not only design new algorithms but also provide numerous insights on why and how "compression" is so important in understanding deep neural networks and improving generalizability

    Searching for Themes in a Chamber full of Noise? How Language Affects United Nations’ Actions and Decisions

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    Against a scholarly mountain of literature on the United Nations, it is astounding how profoundly little we know about the decision-making processes of its most powerful and secretive body, the UN Security Council. In particular, no study has systematically investigated the rhetoric in the Council and assessed its impact on actions and decisions in authorized resolutions. Since diplomats, lawyers, and policymakers held almost 80,000 speeches in public debates between 1995 and 2018 alone, one has to wonder, do these speeches matter? Do they affect intergovernmental decision-making procedures? Do they amount to anything in world politics? And if so, what is their effect? The lack of answers to these questions shows the need for a theory-driven systematic, and rigorous empirical investigation of Council rhetoric

    Comparative genomics of recent adaptation in Candida pathogens

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    [eng] Fungal infections pose a serious health threat, affecting >1,000 million people and causing ~1.5 million deaths each year. The problem is growing due to insufficient diagnostic and therapeutic options, increased number of susceptible patients, expansion of pathogens partly linked to climate change and the rise of antifungal drug resistance. Among other fungal pathogens, Candida species are a major cause of severe hospital-acquired infections, with high mortality in immunocompromised patients. Various Candida pathogens constitute a public health issue, which require further efforts to develop new drugs, optimize currently available treatments and improve diagnostics. Given the high dynamism of Candida genomes, a promising strategy to improve current therapies and diagnostics is to understand the evolutionary mechanisms of adaptation to antifungal drugs and to the human host. Previous work using in vitro evolution, population genomics, selection inferences and Genome Wide Association Studies (GWAS) have partially clarified such recent adaptation, but various open questions remain. In the three research articles that conform this PhD thesis we addressed some of these gaps from the perspective of comparative genomics. First, we addressed methodological issues regarding the analysis of Candida genomes. Studying recent adaptation in these pathogens requires adequate bioinformatic tools for variant calling, filtering and functional annotation. Among other reasons, current methods are suboptimal due to limited accuracy to identify structural variants from short read sequencing data. In addition, there is a need for easy-to-use, reproducible variant calling pipelines. To address these gaps we developed the “personalized Structural Variation detection” pipeline (perSVade), a framework to call, filter and annotate several variant types, including structural variants, directly from reads. PerSVade enables accurate identification of structural variants in any species of interest, such as Candida pathogens. In addition, our tool automatically predicts the structural variant calling accuracy on simulated genomes, which informs about the reliability of the calling process. Furthermore, perSVade can be used to analyze single nucleotide polymorphisms and copy number-variants, so that it facilitates multi-variant, reproducible genomic studies. This tool will likely boost variant analyses in Candida pathogens and beyond. Second, we addressed open questions about recent adaptation in Candida, using perSVade for variant identification. On the one hand, we investigated the evolutionary mechanisms of drug resistance in Candida glabrata. For this, we used a large-scale in vitro evolution experiment to study adaptation to two commonly-used antifungals: fluconazole and anidulafungin. Our results show rapid adaptation to one or both drugs, with moderate fitness costs and through few mutations in a narrow set of genes. In addition, we characterize a novel role of ERG3 mutations in cross-resistance towards fluconazole in anidulafungin-adapted strains. These findings illuminate the mutational paths leading to drug resistance and cross-resistance in Candida pathogens. On the other hand, we reanalyzed ~2,000 public genomes and phenotypes to understand the signs of recent selection and drug resistance in six major Candida species: C. auris, C. glabrata, C. albicans, C. tropicalis, C. parapsilosis and C. orthopsilosis. We found hundreds of genes under recent selection, suggesting that clinical adaptation is diverse and complex. These involve species-specific but also convergently affected processes, such as cell adhesion, which could underlie conserved adaptive mechanisms. In addition, using GWAS we predicted known drivers of antifungal resistance alongside potentially novel players. Furthermore, our analyses reveal an important role of generally-overlooked structural variants, and suggest an unexpected involvement of (para)sexual recombination in the spread of resistance. Taken together, our findings provide novel insights on how Candida pathogens adapt to human-related environments and suggest candidate genes that deserve future attention. In summary, the results of this thesis improve our knowledge about the mechanisms of recent adaptation in Candida pathogens, which may enable improved therapeutic and diagnostic applications.[cat] Les infeccions fúngiques representen una greu amenaça per a la salut, afectant a més de 1.000 milions de persones i causant aproximadament 1,5 milions de morts cada any. El problema està augmentant a causa d’unes opcions terapèutiques i diagnòstiques insuficients, l'increment del nombre de pacients susceptibles, l'expansió dels patògens parcialment vinculada al canvi climàtic i l'augment de la resistència als fàrmacs antifúngics. D’entre diversos fongs patògens, els llevats del gènere Candida són una causa important d'infeccions nosocomials, amb una alta mortalitat en pacients immunodeprimits. Diverses espècies de Candida constitueixen un problema de salut pública, cosa que requereix més esforços per a desenvolupar nous medicaments, optimitzar els tractaments disponibles i millorar els diagnòstics. Tenint en compte el dinamisme genòmic d’aquests patògens, una estratègia prometedora per millorar les teràpies i diagnòstics actuals és comprendre els mecanismes evolutius d'adaptació als fàrmacs antifúngics i a l’hoste humà. Treballs anteriors utilitzant l'evolució in vitro, la genòmica de poblacions, les inferències de selecció i els estudis d'associació de genoma complet (GWAS, per les sigles en anglès) han aclarit parcialment aquesta adaptació recent, però encara hi ha diverses preguntes obertes. En els tres articles que conformen aquesta tesi doctoral, hem abordat algunes d'aquestes preguntes des de la perspectiva de la genòmica comparativa. En primer lloc, hem abordat qüestions metodològiques relatives a l'anàlisi dels genomes de les espècies Candida. L'estudi de l'adaptació recent en aquests patògens requereix eines bioinformàtiques adequades per a la detecció, filtratge i anotació funcional de variants genètiques. Entre altres raons, els mètodes actuals són subòptims a causa de la limitada precisió per identificar variants estructurals a partir de dades de seqüenciació amb lectures curtes. A més, hi ha una necessitat d’eines computacionals per a la detecció de variants que siguin senzilles d'utilitzar i reproduibles. Per abordar aquestes mancances, hem desenvolupat el mètode bioinformàtic "personalized Structural Variation detection" (perSVade), una eina que permet la detecció, filtratge i anotació de diversos tipus de variants, incloent-hi les variants estructurals, directament des de les lectures. PerSVade permet la identificació precisa de les variants estructurals en qualsevol espècie d'interès, com ara els patògens Candida. A més, la nostra eina prediu automàticament la precisió de la detecció d’aquestes variants en genomes simulats, la qual cosa informa sobre la fiabilitat del procés. Finalment, perSVade es pot utilitzar per analitzar altres tipus de variants, com els polimorfismes de nucleòtid únic o els canvis en el nombre de còpies, facilitant així estudis genòmics integrals i reproduibles. Aquesta eina probablement impulsarà les anàlisis genòmiques en els patògens Candida i també en altres espècies. En segon lloc, hem abordat algunes de les preguntes obertes sobre l'adaptació recent en els llevats Candida, utilitzant perSVade per a la identificació de variants. D'una banda, hem investigat els mecanismes evolutius de resistència als fàrmacs antifúngics en Candida glabrata. Per a això, hem utilitzat un experiment d'evolució in vitro a gran escala per estudiar l'adaptació a dos antifúngics comuns: el fluconazol i l’anidulafungina. Els nostres resultats mostren una adaptació ràpida a un o ambdós fàrmacs, amb un cost per al creixement moderat i a través de poques mutacions en un nombre reduït de gens. A més, hem caracteritzat un paper nou de les mutacions en ERG3 en la resistència creuada al fluconazol en soques adaptades a anidulafungina. Aquests descobriments aclareixen els processos mutacionals que condueixen a la resistència als fàrmacs i a la resistència creuada en els patògens Candida. D'altra banda, hem re-analitzat aproximadament 2.000 genomes i fenotips disponibles en repositoris públics per a comprendre els senyals genòmics de selecció recent i de resistència a fàrmacs antifúngics, en sis espècies rellevants de Candida: C. auris, C. glabrata, C. albicans, C. tropicalis, C. parapsilosis i C. orthopsilosis. Hem trobat centenars de gens sota selecció recent, suggerint que l'adaptació clínica és diversa i complexa. Aquests gens estan relacionats amb funcions específiques de cada espècie, però també trobem processos alterats de manera similar en diferents patògens, com per exemple l’adhesió cel·lular, cosa que indica fenòmens d’adaptació conservats. A part, utilitzant GWAS hem predit mecanismes esperats de resistència a antifúngics i també possibles nous factors. A més, les nostres anàlisis revelen un paper important de les variants estructurals, generalment poc estudiades, i suggereixen una implicació inesperada de la recombinació (para)sexual en la propagació de la resistència. En conjunt, els nostres descobriments proporcionen noves perspectives sobre com els patògens Candida s'adapten als entorns humans, i suggereixen gens candidats que mereixen investigacions futures. En resum, els resultats d’aquesta tesi milloren el nostre coneixement sobre els mecanismes d'adaptació recent en els patògens Candida, cosa que pot permetre el disseny de noves teràpies i diagnòstics

    Current issues of the management of socio-economic systems in terms of globalization challenges

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    The authors of the scientific monograph have come to the conclusion that the management of socio-economic systems in the terms of global challenges requires the use of mechanisms to ensure security, optimise the use of resource potential, increase competitiveness, and provide state support to economic entities. Basic research focuses on assessment of economic entities in the terms of global challenges, analysis of the financial system, migration flows, logistics and product exports, territorial development. The research results have been implemented in the different decision-making models in the context of global challenges, strategic planning, financial and food security, education management, information technology and innovation. The results of the study can be used in the developing of directions, programmes and strategies for sustainable development of economic entities and regions, increasing the competitiveness of products and services, decision-making at the level of ministries and agencies that regulate the processes of managing socio-economic systems. The results can also be used by students and young scientists in the educational process and conducting scientific research on the management of socio-economic systems in the terms of global challenges

    Impacts of childhood psychological maltreatment on adult mental health

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    Previous studies have shown the negative impacts of child abuse on mental health in later life. Compared to physical and sexual abuse, psychological maltreatment has received less attention. Emerging literature has explored the associations between psychological maltreatment on adult mental health. However, no systematic review or meta-analysis focuses on the associations between childhood psychological maltreatment and adult mental health while controlling for other adverse childhood experiences. In addition, there is a lack of measures in China that focus on assessing childhood psychological maltreatment in all its relevant dimensions. Further, limited studies have explored the associations between different types and profiles of childhood psychological maltreatment and its associations with adult mental health. Therefore, this thesis aims to fill these gaps by reviewing previous literature on childhood psychological maltreatment and adult mental health, translating and validating a measure that focuses on childhood psychological maltreatment for use in China, assessing the associations between different types of childhood psychological maltreatment and adult mental health, and exploring different profile patterns in Chinese and the UK populations of childhood psychological maltreatment and its associations on mental well-being. Chapter 1 provides a brief background to the existing literature on childhood psychological maltreatment and its associations with adult mental health outcomes. It also presents an overview of frequently used measures assessing childhood psychological maltreatment in China and the UK. In addition, this chapter demonstrates the key gaps in the previous literature. Chapter 2 uses a systematic review approach to review the previous literature on childhood psychological maltreatment and various adult mental health outcomes (i.e., depression and anxiety, eating disorders, personality disorders, suicidal ideation and attempts, substance abuse, and other psychological symptoms). It also reviews the comparison of the mental health outcomes between clinical populations and the general population on the prevalence of childhood psychological abuse and neglect. Meta-analyses are conducted on several themes (i.e., depression and anxiety, suicidal ideation, and clinical population) to explore the effects sizes of childhood psychological abuse on these mental health outcomes. Chapter 3 introduces, translates, and validates the Psychological Maltreatment Review (PMR) for the Chinese population. Factorial validity, internal consistency, convergent and divergent validity, and gender measurement invariance are assessed. Chapter 4, which builds on Chapters 2 and 3, uses the higher-order model to examine the associations between childhood psychological abuse, neglect, and non-support and various mental health outcomes (i.e., depression, anxiety, anger, hostility, and physical aggression). This chapter explores whether different types of childhood psychological maltreatment are more harmful than others, whether the harms associated with different types of psychological maltreatment are generalised or specific to particular domains of psychopathology, and whether there are gender invariances in these associations. Building on Chapter 4, which compares sub-dimensions of childhood psychological maltreatment, Chapter 5 explores the effects of different profiles of psychological maltreatment in the Chinese and the UK population. Various mental health outcomes, such as depression, anxiety, and aggression, and broader well-being, such as self-esteem, are assessed. Lastly, Chapter 6 provides a general summary of the results from Chapters 2 – 5 and an overall discussion. In conclusion, this thesis contributes to understanding the associations between childhood psychological maltreatment and adult mental health. The empirical findings of this thesis emphasise the need to have policies that prevent psychological maltreatment and interventions that can address its psychological harms
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