Language variation, automatic speech recognition and algorithmic bias

In this thesis, I situate the impacts of automatic speech recognition systems in relation to sociolinguistic theory (in particular drawing on concepts of language variation, language ideology and language policy) and contemporary debates in AI ethics (especially regarding algorithmic bias and fairness). In recent years, automatic speech recognition systems, alongside other language technologies, have been adopted by a growing number of users and have been embedded in an increasing number of algorithmic systems. This expansion into new application domains and language varieties can be understood as an expansion into new sociolinguistic contexts. In this thesis, I am interested in how automatic speech recognition tools interact with this sociolinguistic context, and how they affect speakers, speech communities and their language varieties. Focussing on commercial automatic speech recognition systems for British Englishes, I first explore the extent and consequences of performance differences of these systems for different user groups depending on their linguistic background. When situating this predictive bias within the wider sociolinguistic context, it becomes apparent that these systems reproduce and potentially entrench existing linguistic discrimination and could therefore cause direct and indirect harms to already marginalised speaker groups. To understand the benefits and potentials of automatic transcription tools, I highlight two case studies: transcribing sociolinguistic data in English and transcribing personal voice messages in isiXhosa. The central role of the sociolinguistic context in developing these tools is emphasised in this comparison. Design choices, such as the choice of training data, are particularly consequential because they interact with existing processes of language standardisation. To understand the impacts of these choices, and the role of the developers making them better, I draw on theory from language policy research and critical data studies. These conceptual frameworks are intended to help practitioners and researchers in anticipating and mitigating predictive bias and other potential harms of speech technologies. Beyond looking at individual choices, I also investigate the discourses about language variation and linguistic diversity deployed in the context of language technologies. These discourses put forward by researchers, developers and commercial providers not only have a direct effect on the wider sociolinguistic context, but they also highlight how this context (e.g., existing beliefs about language(s)) affects technology development. Finally, I explore ways of building better automatic speech recognition tools, focussing in particular on well-documented, naturalistic and diverse benchmark datasets. However, inclusive datasets are not necessarily a panacea, as they still raise important questions about the nature of linguistic data and language variation (especially in relation to identity), and may not mitigate or prevent all potential harms of automatic speech recognition systems as embedded in larger algorithmic systems and sociolinguistic contexts

Exploring professional engineers' knowings-in-practice in an emerging industry: An Actor-Network Theory approach

This thesis presents a sociomaterial perspective on how everyday engineering work practices are being changed by the complexities and tensions prevalent in emerging industries. Presenting the wind energy industry, in the renewable energy sector, as a case, this study contends that current engineering education practices are not adequately preparing and supporting students and professionals for work in highly volatile, precarious industries. This study pays close attention to how engineers enact competent knowing and learning strategies to respond to, and navigate, these complexities and tensions. Traditional engineering education practices tend to frame engineering work as a bounded, stable, rational, and technical endeavor, where knowledge is regarded as a commodity to be acquired. Rather than treating professional knowledge as an independent reality of the engineering field, this thesis argues that education practices can be informed by making visible mundane and taken-for-granted aspects of engineers’ everyday work, and reconfiguring conceptualisations of engineering knowledge as situated, collective, on-going, and materially-mediated performances. To do so, this study draws on concepts of knowing-in-practice and Actor-Network Theory, which position engineering work as heterogeneous assemblages of social and material relations. An ethnographic methodology afforded the tracing of social and material relations between 13 participating engineers and the objects of their practice in a wind energy organisation located in a Scottish city. Following six months of observations and interviews, three activities that generated high intensity in the engineers' everyday work were analysed: securing a signature on a contract, the unfolding of a specific organising process, and implementing a new technology. Analysis revealed four tensions that needed to be constantly negotiated, which included balancing: commercial objectives and client needs with traditional engineering concerns; standardising practices with innovating practices; acceptable practice with allowable deviation; and visibility with invisibility. Emerging from the findings were clear indications that the multiple knowings-in-practice enacted to negotiate these tensions were interdependent, yet partial, fluid and multiple, sociomaterial performances. This thesis offers recommendations for education practices based on these findings, which challenge dominant representational and individualistic conceptualisations of engineering education and workplace learning. Furthermore, a ‘dynamic stability’ sensibility is offered as a pedagogical approach that encourages attunement to the performance of fluid and informal infrastructuring practices, which tolerate volatility and high-change in work practices

Generating intelligent tutoring systems for teaching reading: combining phonological awareness and thematic approaches

The objective of this thesis is to investigate the use of computers with artificial intelligence methods for the teaching of basic literacy skills to be applied eventually to the teaching of illiterate adults in Brazil.In its development many issues related to adult education have been considered, and two very significant approaches to the teaching of reading were focused on in detail: Phonological Awareness (PA) and Generative Themes. After being excluded from literacy curricula for a long time during the ascendancy of the "Whole Word" approaches, activities for the development of phonological awareness are currently being accepted as fundamental for teaching reading, and are being incorporated in most English literacy programmes. Generative Themes, in turn, were first introduced in Brazil in a massive programme for teaching reading to adults, and have since then been used successfully in a number of developing countries for the same purpose. However, these two approaches are apparently conflicting in their principles and emphasis, for the first (PA) is generally centred on the technical aspects of phonology, based on well controlled experiments and research, whereas the second is socially inspired and focused mainly on meaning and social relationships.The main question addressed in this research, consequently, is whether these two apparently conflicting approaches could be combined to create a method that would be technically PA oriented but at the same time could concentrate on meaning by using thematic vocabularies as stimuli for teaching. Would it be possible to find words to illustrate all the phonological features with which a PA method deals using a thematic vocabulary?To answer this question diverse concepts, languages and tools have been developed as part of this research, in order to allow the selection of thematic vocabularies, the description of PA curricula, the distribution of thematic words across PA curricula, the description of teaching activities and the definition of the teaching strategy rules to orient the teaching sequence.The resultant vocabularies have been evaluated and the outcomes of the research have been assessed by literacy experts. A prototype system for delivering experimental teaching activities through the Internet has also been developed and demonstrated