1,891 research outputs found
Recalibrating machine learning for social biases: demonstrating a new methodology through a case study classifying gender biases in archival documentation
This thesis proposes a recalibration of Machine Learning for social biases to minimize harms from existing approaches and practices in the field. Prioritizing quality over quantity, accuracy over efficiency, representativeness over convenience, and situated thinking over universal thinking, the thesis demonstrates an alternative approach to creating Machine Learning models. Drawing on GLAM, the Humanities, the Social Sciences, and Design, the thesis focuses on understanding and communicating biases in a specific use case. 11,888 metadata descriptions from the University of Edinburgh Heritage Collections' Archives catalog were manually annotated for gender biases and text classification models were then trained on the resulting dataset of 55,260 annotations. Evaluations of the models' performance demonstrates that annotating gender biases can be automated; however, the subjectivity of bias as a concept complicates the generalizability of any one approach.
The contributions are: (1) an interdisciplinary and participatory Bias-Aware Methodology, (2) a Taxonomy of Gendered and Gender Biased Language, (3) data annotated for gender biased language, (4) gender biased text classification models, and (5) a human-centered approach to model evaluation. The contributions have implications for Machine Learning, demonstrating how bias is inherent to all data and models; more specifically for Natural Language Processing, providing an annotation taxonomy, annotated datasets and classification models for analyzing gender biased language at scale; for the Gallery, Library, Archives, and Museum sector, offering guidance to institutions seeking to reconcile with histories of marginalizing communities through their documentation practices; and for historians, who utilize cultural heritage documentation to study and interpret the past. Through a real-world application of the Bias-Aware Methodology in a case study, the thesis illustrates the need to shift away from removing social biases and towards acknowledging them, creating data and models that surface the uncertainty and multiplicity characteristic of human societies
LIPIcs, Volume 251, ITCS 2023, Complete Volume
LIPIcs, Volume 251, ITCS 2023, Complete Volum
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Gender Policy-as-Practice with Young Children: The Politics of Gender-Justice in Early Childhood Education
Trans and queer children are experiencing discrimination starting in the earliest years of schooling. In a paradoxical era of increased support for transgender and queer children on the one hand, and persistent gender violence on the other, this study examines how the New York City Department of Education (NYCDOE) gender policy is taken up in Early Childhood Education practice.
In particular, I ask: (a) What are early childhood teachers’ understanding of NYCDOE’s policy? (b) How do the larger social and material contexts, shape teachers’ enactments of the policy? (c) What do teachers’ understandings and enactments of NYC gender policy look like in their everyday classroom practices?
I use a critical policy-as-practice conceptual framework that does not take policy for granted but understands that embedded in all the policy processes, there is always a great deal of negotiation of power, where some stakeholders are empowered and other perspectives are silenced. Through semi-structured interviews with district policymakers, school administrators, and early childhood teachers, this study unveils how different actors took up NYCDOE’s gender policy in their practice, in accordance with their own ideas, motivations, and broader social and material contexts.
Findings indicate that the policy formation processes excluded the knowledge and perspectives of school communities and grassroots trans activist movements. Principals and teachers had little knowledge of the Guidelines on Gender and resources available, while several policy content and procedures reproduced gender and racial violence. Moreover, the sediment construct of childhood innocence shaped early childhood teachers’ gender-justice practices. Shifting understandings of gender, without revising understandings of childhood, this study concludes, hinders the possibility of transformative change
Image-based Decision Support Systems: Technical Concepts, Design Knowledge, and Applications for Sustainability
Unstructured data accounts for 80-90% of all data generated, with image data contributing its largest portion. In recent years, the field of computer vision, fueled by deep learning techniques, has made significant advances in exploiting this data to generate value. However, often computer vision models are not sufficient for value creation. In these cases, image-based decision support systems (IB-DSSs), i.e., decision support systems that rely on images and computer vision, can be used to create value by combining human and artificial intelligence. Despite its potential, there is only little work on IB-DSSs so far.
In this thesis, we develop technical foundations and design knowledge for IBDSSs and demonstrate the possible positive effect of IB-DSSs on environmental sustainability. The theoretical contributions of this work are based on and evaluated in a series of artifacts in practical use cases: First, we use technical experiments to demonstrate the feasibility of innovative approaches to exploit images for IBDSSs.
We show the feasibility of deep-learning-based computer vision and identify future research opportunities based on one of our practical use cases. Building on this, we develop and evaluate a novel approach for combining human and artificial intelligence for value creation from image data. Second, we develop design knowledge that can serve as a blueprint for future IB-DSSs. We perform two design science research studies to formulate generalizable principles for purposeful design — one for IB-DSSs and one for the subclass of image-mining-based decision support systems (IM-DSSs). While IB-DSSs can provide decision support based on single images, IM-DSSs are suitable when large amounts of image data are available and required for decision-making. Third, we demonstrate the viability of applying IBDSSs to enhance environmental sustainability by performing life cycle assessments for two practical use cases — one in which the IB-DSS enables a prolonged product lifetime and one in which the IB-DSS facilitates an improvement of manufacturing processes.
We hope this thesis will contribute to expand the use and effectiveness of imagebased decision support systems in practice and will provide directions for future research
Optimisation for Optical Data Centre Switching and Networking with Artificial Intelligence
Cloud and cluster computing platforms have become standard across almost every domain of business, and their scale quickly approaches servers in a single warehouse. However, the tier-based opto-electronically packet switched network infrastructure that is standard across these systems gives way to several scalability bottlenecks including resource fragmentation and high energy requirements. Experimental results show that optical circuit switched networks pose a promising alternative that could avoid these.
However, optimality challenges are encountered at realistic commercial scales. Where exhaustive optimisation techniques are not applicable for problems at the scale of Cloud-scale computer networks, and expert-designed heuristics are performance-limited and typically biased in their design, artificial intelligence can discover more scalable and better performing optimisation strategies.
This thesis demonstrates these benefits through experimental and theoretical work spanning all of component, system and commercial optimisation problems which stand in the way of practical Cloud-scale computer network systems. Firstly, optical components are optimised to gate in and are demonstrated in a proof-of-concept switching architecture for optical data centres with better wavelength and component scalability than previous demonstrations. Secondly, network-aware resource allocation schemes for optically composable data centres are learnt end-to-end with deep reinforcement learning and graph neural networks, where less networking resources are required to achieve the same resource efficiency compared to conventional methods. Finally, a deep reinforcement learning based method for optimising PID-control parameters is presented which generates tailored parameters for unseen devices in . This method is demonstrated on a market leading optical switching product based on piezoelectric actuation, where switching speed is improved with no compromise to optical loss and the manufacturing yield of actuators is improved. This method was licensed to and integrated within the manufacturing pipeline of this company. As such, crucial public and private infrastructure utilising these products will benefit from this work
Towards responsible quantum technology, safeguarding, engaging and advancing Quantum R&D
The expected societal impact of quantum technologies (QT) urges us to proceed
and innovate responsibly. This article proposes a conceptual framework for
Responsible QT that seeks to integrate considerations about ethical, legal,
social, and policy implications (ELSPI) into quantum R&D, while responding to
the Responsible Research and Innovation dimensions of anticipation, inclusion,
reflection and responsiveness. After examining what makes QT unique, we argue
that quantum innovation should be guided by a methodological framework for
Responsible QT, aimed at jointly safeguarding against risks by proactively
addressing them, engaging stakeholders in the innovation process, and continue
advancing QT (SEA). We further suggest operationalizing the SEA-framework by
establishing quantum-specific guiding principles. The impact of quantum
computing on information security is used as a case study to illustrate (1) the
need for a framework that guides Responsible QT, and (2) the usefulness of the
SEA-framework for QT generally. Additionally, we examine how our proposed
SEA-framework for responsible innovation can inform the emergent regulatory
landscape affecting QT, and provide an outlook of how regulatory interventions
for QT as base-layer technology could be designed, contextualized, and tailored
to their exceptional nature in order to reduce the risk of unintended
counterproductive effects of policy interventions. Laying the groundwork for a
responsible quantum ecosystem, the research community and other stakeholders
are called upon to further develop the recommended guiding principles, and
discuss their operationalization into best practices and real-world
applications. Our proposed framework should be considered a starting point for
these much needed, highly interdisciplinary efforts
The University of Montana: A History Through the Lens of Physical Culture, PE, Health, Athletics, and Recreation 1897-2019: The Evolution of a Department
https://scholarworks.umt.edu/burns/1000/thumbnail.jp
Male Clients' Perspective Of Their Experience Of Counselling In Prisons Stephen Brian Fauguel
The use of psycho-therapeutic interventions within prisons in recent years has been widespread. In order to improve the results of therapy, it is necessary to measure the effectiveness of the outcome (Castonguay, 2013). However, the measurement of outcomes is difficult to gauge, in particular because of the hostile environment within prison, which encourages the client to enter a state in which life is stripped of purpose and responsibility. Heidegger (1927) explains his philosophical view of the awareness of existence with his statement of ‘Dasein’ (being there) (Heidegger, 1927). Incarceration in a prison excludes the possibility that individuals experience and express themselves in an open manner without fear, as Sartre explained as ‘existential anxiety’ (Sartre, 1945), the feeling of anxiety emerging within a prisoner creating a feeling of loss of freedom of choice.Considering the prisoner’s choices within prison, for example,the counsellor of their own choice, accessto counselling appointments, unrestrictivecounselling facilities, and counselling venues are issues that arise more frequently in prison than in any other therapeutic contexts. The focus of this research is on the male client’s perspective of counselling in prison.The purpose of the study is three-fold:to gainanunderstanding of how the male prisoners’experience counselling; to explore what is useful and what is notusefulabout counselling;and to further improve knowledge of counselling therapy,so thatcounselling may be enhancedfor the benefit of prison clients.Thisstudyis qualitative,adopting the theoretical framework of Interpretive Phenomenological Analysis (IPA). Male prisoners who have had counselling in prison have spoken of their experience of being counselled in prison and this has filled the gap in the literature.Thisstudy makes a unique contribution to the existing knowledge base regardinghow male clients perceive counselling and may improvethe effectiveness of counselling in prisonsbyensuringthat future counselling of men in prison will become more effective and appropriate to their need
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