Browsing by Subject "algorithms"
Now showing items 1-20 of 20
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(2023)The rapid advancement of AI technologies has sparked inquiries across various legal domains, including intellectual property (IP) law. While the impact of AI on copyright and patents has received considerable attention, the influence of AI on EU trademark law is also anticipated. The World Intellectual Property Organization (WIPO) has acknowledged this impact cautiously, recognizing that AI may affect certain aspects of trademark 1law. One significant domain where AI will exert its influence on trademarks is online retail platforms. These platforms have already implemented various AI applications to provide consumers with highly personalized product recommendations. Moreover, AI-driven shopping experiences, facilitated by virtual assistants like Amazon's Alexa, have redefined the role of consumers in the purchasing process, diverging from traditional shopping practices. This thesis aims to explore how the emergence of AI technologies will impact fundamental doctrines of trademark law, including the functions of trademarks, the concept of the average consumer, and the assessment of trademark infringement. Additionally, it seeks to identify the types of AI applications deployed by e-commerce platforms and advocate for necessary actions that EU legislators must undertake to address these implications within trademark law. The findings of this thesis indicate that while many prominent doctrines of EU trademark law will remain relevant amidst the rise of AI technologies, some require re-examination in the context of advanced AI applications. The transformative nature of AI necessitates a comprehensive assessment and potential recalibration of these doctrines to ensure their efficacy in regulating AI-driven environments.
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(2023)The rapid advancement of AI technologies has sparked inquiries across various legal domains, including intellectual property (IP) law. While the impact of AI on copyright and patents has received considerable attention, the influence of AI on EU trademark law is also anticipated. The World Intellectual Property Organization (WIPO) has acknowledged this impact cautiously, recognizing that AI may affect certain aspects of trademark 1law. One significant domain where AI will exert its influence on trademarks is online retail platforms. These platforms have already implemented various AI applications to provide consumers with highly personalized product recommendations. Moreover, AI-driven shopping experiences, facilitated by virtual assistants like Amazon's Alexa, have redefined the role of consumers in the purchasing process, diverging from traditional shopping practices. This thesis aims to explore how the emergence of AI technologies will impact fundamental doctrines of trademark law, including the functions of trademarks, the concept of the average consumer, and the assessment of trademark infringement. Additionally, it seeks to identify the types of AI applications deployed by e-commerce platforms and advocate for necessary actions that EU legislators must undertake to address these implications within trademark law. The findings of this thesis indicate that while many prominent doctrines of EU trademark law will remain relevant amidst the rise of AI technologies, some require re-examination in the context of advanced AI applications. The transformative nature of AI necessitates a comprehensive assessment and potential recalibration of these doctrines to ensure their efficacy in regulating AI-driven environments.
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(2022)This thesis is a review of articles focusing on software assisted floor plan design for architecture. I group the articles into optimization, case based design, and machine learning, based on their use of prior examples. I then look into each category and further classify articles based on dimensions relevant to their overall approach. Case based design was a popular research field in the 1990s and early 2000s when several large research projects were conducted. However, since then the research has slowed down. Over the past 20 years, optimization methods to solve architectural floor plans have been researched extensively using a number of different algorithms and data models. The most popular approach is to use a stochastic optimization method such as a genetic algorithm or simulated annealing. More recently, a number of articles have investigated the possibility of using machine learning on architectural floor plans. The advent of neural networks and GAN models, in particular, has spurred a great deal of new research. Despite considerable research efforts, assisted floor plan design has not found its way into commercial applications. To aid industry adoption, more work is needed on the integration of computational design tools into the existing design workflows.
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(2023)Sequence alignment is widely studied problem in the field of bioinformatics. The exact solution takes quadratic time to compute, and thus is not practical for long sequences. A number of heuristic approaches have been developed to conquer the quadratic time-complexity. This thesis reviews the average-case time analysis of two such heuristics, banded alignment by Ganesh and Sy in ''Near-Linear Time Edit Distance for Indel Channels'' WABI 2020, and seed-chain-extend by Shaw and Yu in ''Proving sequence aligners can guarantee accuracy in almost O(m log n) time through an average-case analysis of the seed-chain-extend heuristic'' Genome Research 2023. These heuristics reduce the quadratic average-case time complexity of the sequence alignment to log-linear. The approach of the thesis reviews is to outline the proofs of the original analysis, and provide supporting materials to aid the reader in studying the analysis. The experiments of this thesis compare four different approaches to compute the exact match anchors of the seed-chain-extend sequence alignment heuristic. A Bi-Directional Burrows-Wheeler Transformation (BDBWT), suffix tree based Mummer and Minimap2 based exact match anchors are computed. The anchors are then given to a chaining algorithm, to compare the performance of each anchoring technique. The qualities of the chains are compared using a Jaccard index applied to the sequences. The highest Jaccard index is obtained for the maximal exact match and the unique maximal exact match anchors of Mummer and BDBWT approaches. An increasing minimum length of the exact matches seem to increase the Jaccard index and reduce the running time of the chaining algorithm.
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(2022)Automatic headline generation has the potential to significantly assist editors charged with head- lining articles. Approaches to automation in the headlining process can range from tools as creative aids, to complete end to end automation. The latter is difficult to achieve as journalistic require- ments imposed on headlines must be met with little room for error, with the requirements depending on the news brand in question. This thesis investigates automatic headline generation in the context of the Finnish newsroom. The primary question I seek to answer is how well the current state of text generation using deep neural language models can be applied to the headlining process in Finnish news media. To answer this, I have implemented and pre-trained a Finnish generative language model based on the Transformer architecture. I have fine-tuned this language model for headline generation as autoregression of headlines conditioned on the article text. I have designed and implemented a variation of the Diverse Beam Search algorithm, with additional parameters, to perform the headline generation in order to generate a diverse set of headlines for a given text. The evaluation of the generative capabilities of this system was done with real world usage in mind. I asked domain-experts in headlining to evaluate a generated set of text-headline pairs. The task was to accept or reject the individual headlines in key criteria. The responses of this survey were then quantitatively and qualitatively analyzed. Based on the analysis and feedback, this model can already be useful as a creative aid in the newsroom despite being far from ready for automation. I have identified concrete improvement directions based on the most common types of errors, and this provides interesting future work.
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(2022)AI-driven innovation offers numerous possibilities for the public sector. The potential of digital advancements is already palpable within the tax administrations. Automation is efficiently used for tax assessments, to perform compliance management, to enhance revenue collection and to provide services to taxpayers. A digital transformation encompassing Big Data, advanced analytics and ADM systems promises significant benefits and efficiencies for the tax administrations. It is essential that public organizations meet the necessary legal framework and safeguards to expand the use of these automated systems since its sources of information, technical capacity, and extent of application have evolved. Using Finland as a case study, this research assesses the use of automated decision-making systems within the public sector. Constitutional and administrative legal principles serve as guidelines and constraints for the administrative activity and decision-making. This study examines the lawfulness of the deployment of ADM systems in the field of taxation by looking its compatibility with long-standing legal principles. Focus if given to the principles of the rule of law, due process, good administration, access to information, official accountability, confidentiality, and privacy. Numerous public concerns have been raised regarding the use of ADM systems in the public sector. Scholars, academics and journalists have justifiably pointed out the risks and limitations of ADM systems. Despite the legal challenges posed by automation, this research suggests that ADM systems used to pursue administrative objectives can fit with long-standing legal principles with appropriate regulation, design and human capacity.
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(2022)AI-driven innovation offers numerous possibilities for the public sector. The potential of digital advancements is already palpable within the tax administrations. Automation is efficiently used for tax assessments, to perform compliance management, to enhance revenue collection and to provide services to taxpayers. A digital transformation encompassing Big Data, advanced analytics and ADM systems promises significant benefits and efficiencies for the tax administrations. It is essential that public organizations meet the necessary legal framework and safeguards to expand the use of these automated systems since its sources of information, technical capacity, and extent of application have evolved. Using Finland as a case study, this research assesses the use of automated decision-making systems within the public sector. Constitutional and administrative legal principles serve as guidelines and constraints for the administrative activity and decision-making. This study examines the lawfulness of the deployment of ADM systems in the field of taxation by looking its compatibility with long-standing legal principles. Focus if given to the principles of the rule of law, due process, good administration, access to information, official accountability, confidentiality, and privacy. Numerous public concerns have been raised regarding the use of ADM systems in the public sector. Scholars, academics and journalists have justifiably pointed out the risks and limitations of ADM systems. Despite the legal challenges posed by automation, this research suggests that ADM systems used to pursue administrative objectives can fit with long-standing legal principles with appropriate regulation, design and human capacity.
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High-Performance k-mer Membership Queries over Spectral Burrows-Wheeler Transform with GPU computing (2023)The volume of data generated by high-throughput DNA sequencing has grown to a magnitude that leads to substantial computational challenges in storing and searching the data. To tackle this problem, various computational methodologies have been developed in recent years to space-efficiently index collections of data sets and enable efficient searches. One of the most recent indexing methods, Spectral Burrows-Wheeler Transform (SBWT), presents all distinct k-mers of a DNA sequence using only 4 bits and a small additional space for the rank data structures per k-mer. In addition to being space-efficient, it also enables k-mer membership queries in linear time relative to k, and constant time relative to the number of distinct k-mers in the sequence. The queries rely on rank queries over bit vectors. Experiments run on a single CPU thread have shown that in one second, hundreds of thousands of k-mer membership queries can be performed over SBWT. By parallelizing the queries on a CPU, it is possible to execute millions of queries per second. However, Graphic Processing Units (GPUs) have much more parallelization potential. The main contribution of the thesis is an implementation of the k-mer membership queries over SBWT with GPU computing. Optimizing the queries to be performed on a GPU made it possible to perform over a billion queries per second. Furthermore, the thesis presents a new enhancement for the queries over SBWT called presearching, which doubles the speed of the original SBWT search query. The rank query needed for the membership queries is implemented using space-efficient poppy rank data structures, and its derivative cumulative-poppy data structure which is one of the contributions of the thesis.
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(2024)There are two primary types of quantum computers: quantum annealers and circuit model computers. Quantum annealers are specifically designed to tackle particular problems, as opposed to circuit model computers, which can be viewed as universal quantum computers. Substantial efforts are underway to develop quantum-based algorithms for various classical computational problems. The objective of this thesis is to implement algorithms for solving graph problems using quantum annealer computers and analyse these implementations. The aim is to contribute to the ongoing development of algorithms tailored for this type of machine. Three distinct types of graph problems were selected: all pairs shortest path, graph isomorphism, and community detection. These problems were chosen to represent varying levels of computational complexity. The algorithms were tested using the D-Wave quantum annealer Advantage system 4.1, equipped with 5760 qubits. D-Wave provides a cloud platform called Leap and a Python library, Ocean tools, through which quantum algorithms can be designed and run using local simulators or real quantum computers in the cloud. Formulating graph problems to be solved on quantum annealers was relatively straightforward, as significant literature already contains implementations of these problems. However, running these algorithms on existing quantum annealer machines proved to be challenging. Even though quantum annealers currently boast thousands of qubits, algorithms performed satisfactorily only on small graphs. The bottleneck was not the number of qubits but rather the limitations imposed by topology and noise. D-Wave also provides hybrid solvers that utilise both the Quantum Processing Unit (QPU) and CPU to solve algorithms, which proved to be much more reliable than using a pure quantum solver.
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(2020)NP-hard optimization problems can be found in various real-world settings such as scheduling, planning and data analysis. Coming up with algorithms that can efficiently solve these problems can save various rescources. Instead of developing problem domain specific algorithms we can encode a problem instance as an instance of maximum satisfiability (MaxSAT), which is an optimization extension of Boolean satisfiability (SAT). We can then solve instances resulting from this encoding using MaxSAT specific algorithms. This way we can solve instances in various different problem domains by focusing on developing algorithms to solve MaxSAT instances. Computing an optimal solution and proving optimality of the found solution can be time-consuming in real-world settings. Finding an optimal solution for problems in these settings is often not feasible. Instead we are only interested in finding a good quality solution fast. Incomplete solvers trade guaranteed optimality for better scalability. In this thesis, we study an incomplete solution approach for solving MaxSAT based on linear programming relaxation and rounding. Linear programming (LP) relaxation and rounding has been used for obtaining approximation algorithms on various NP-hard optimization problems. As such we are interested in investigating the effectiveness of this approach on MaxSAT. We describe multiple rounding heuristics that are empirically evaluated on random, crafted and industrial MaxSAT instances from yearly MaxSAT Evaluations. We compare rounding approaches against each other and to state-of-the-art incomplete solvers SATLike and Loandra. The LP relaxation based rounding approaches are not competitive in general against either SATLike or Loandra However, for some problem domains our approach manages to be competitive against SATLike and Loandra.
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(2023)The two-dimensional path-planning problem involves determining the shortest path between two points on a plane while adhering to a set of polygonal constraints. In this thesis, we show how the path-planning problem in dynamically updated environments gives rise to a need for an edge-flipping based line-segment insertion procedure for constrained Delaunay triangulations, and present an efficient algorithm for the problem. The algorithm operates on convex vertices situated along the boundary of the channel of triangles that intersect with the edge that is to be inserted. We show that such vertices can be removed from the channel using a finite series of edge-flip operations, and that the repeated application of the vertex removal procedure results in the insertion of the requested edge in the triangulation. Furthermore, we present a working sample implementation of the resulting algorithm.
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(2023)The scholarship allotment problem describes the goal of strategically offering scholarships to prospective students of a university in a way that optimises the expected return for that investment. The goal of this thesis is to formulate the scholarship allotment problem in multiple variations of increasing complexity while also introducing algorithms to solve those variations optimally as efficiently as possible. The thesis also offers some insight into the way more complex variations and generalisations heighten the difficulty of finding an optimal solution in a reasonable amount of time. The main focus and the main tool used to tackle these problems is the classic knapsack algorithm and different variations of it, like multiple-choice knapsack and multidimensional knapsack. In addition to the theoretical side, the thesis contains an empirical study into the performance and feasibility of the algorithms introduced. Concrete implementations of the algorithms discussed are all available on a public GitHub repository online: https://github.com/SirVeggie/scholarship-allotment.
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(2022)Inverted indices is a core index structure for different low-level structures, like search engines and databases. It stores a mapping from terms, numbers etc. to list of location in document, set of documents, database, table etc. and allows efficient full-text searches on indexed structure. Mapping location in the inverted indicies is usually called a postings list. In real life applications, scale of the inverted indicies size can grow huge. Therefore efficient representation of it is needed, but at the same time, efficient queries must be supported. This thesis explores ways to represent postings lists efficiently, while allowing efficient nextGEQ queries on the set. Efficient nextGEQ queries is needed to implement inverted indicies. First we convert postings lists into one bitvector, which concatenates each postings list's characteristic bitvector. Then representing an integer set efficiently converts to representing this bitvector efficiently, which is expected to have long runs of 0s and 1s. Run-length encoding of bitvector have recently led to promising results. Therefore in this thesis we experiment two encoding methods (Top-k Hybrid coder, RLZ) that encode postings lists via run-length encodes of the bitvector. We also investigate another new bitvector compression method (Zombit-vector), which encodes bitvectors by finding redundancies of runs of 0/1s. We compare all encoding to current state-of-the-art Partitioned Elisa-Fano (PEF) coding. Compression results on all encodings were more efficient than the current state-of-the-art PEF encoding. Zombit-vector nextGEQ query results were slighty more efficient than PEF's, which make it more attractive with bitvectors that have long runs of 0s and 1s. More work is needed with Top-k Hybrid coder and RLZ, so that those encodings nextGEQ can be compared to Zombit-vector and PEF.
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(2020)In my MA thesis I explore the Finnish people’s relationship to technology and especially to information communication technology by discussing technological imaginaries. Imaginaries guide attention toward collective sense making while they convey shared social values, norms and identities that are performed in different speech acts. Everyday algorithms are the starting point of my thesis. I framed the topic of algorithms and the technological imaginaries they produce with the theoretical discussion of datafication and dataveillance. As the influence of technology is only growing in our Western society, I am interested in observing its potential sociopolitical impact. My research question is how technological imaginaries affect the society. I am interested in questions how a technology-related future narrative exists and how these narratives are constructed—and what they tell about the Finnish society. My goal is to create holistic understanding of living with quantified data and to analyze what values technological imaginaries might reveal. The research approach is anthropology of technology. The ethnographic focus is in Helsinki, Finland and the ethnographic material consists of 39 semi-structured interviews, which are divided between two reference groups, which I named as ‘everyday algorithms’ and ‘digital marketers.’ The interviews were conducted in 2017 and 2018 and the ethnographic material was systematically analyzed with content analysis. The interviewees’ affective and analytical responses depended on the topic at hand and from the different perspectives the interviewees saw them through. Technological determinism and dataism, which represent faith in technology as the source of progress and faith in data as objective, rational and good, were themes that emerged in the interviews. What became apparent is that technology is viewed to mediate social utopias, such as social equality, even when actual technology mediated practices might not support those desires.
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(2020)In my MA thesis I explore the Finnish people’s relationship to technology and especially to information communication technology by discussing technological imaginaries. Imaginaries guide attention toward collective sense making while they convey shared social values, norms and identities that are performed in different speech acts. Everyday algorithms are the starting point of my thesis. I framed the topic of algorithms and the technological imaginaries they produce with the theoretical discussion of datafication and dataveillance. As the influence of technology is only growing in our Western society, I am interested in observing its potential sociopolitical impact. My research question is how technological imaginaries affect the society. I am interested in questions how a technology-related future narrative exists and how these narratives are constructed—and what they tell about the Finnish society. My goal is to create holistic understanding of living with quantified data and to analyze what values technological imaginaries might reveal. The research approach is anthropology of technology. The ethnographic focus is in Helsinki, Finland and the ethnographic material consists of 39 semi-structured interviews, which are divided between two reference groups, which I named as ‘everyday algorithms’ and ‘digital marketers.’ The interviews were conducted in 2017 and 2018 and the ethnographic material was systematically analyzed with content analysis. The interviewees’ affective and analytical responses depended on the topic at hand and from the different perspectives the interviewees saw them through. Technological determinism and dataism, which represent faith in technology as the source of progress and faith in data as objective, rational and good, were themes that emerged in the interviews. What became apparent is that technology is viewed to mediate social utopias, such as social equality, even when actual technology mediated practices might not support those desires.
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(2023)This thesis is an exploration of food delivery couriers’ everyday experiences, practices and sensemaking processes through a posthumanist and sociomaterial approach that highlights the idea that technology and society are mutually shaping one another, and that considers the agency of non-human entities such as algorithms, transcendental. Moreover, by adopting a sociomaterial perspective, we can have a better understanding of how social and technological systems, as well as human and non-human beings, are interrelated, how they shape, and are shaped by one another. This work’s aims are threefold: First, it explores couriers’ experiences at work and describes their daily practices in order to understand the enactment of agency from a sociomaterial and post-humanist philosophical tradition. Second, it explores the material implications of algorithmic management in couriers’ lives, and finally, it explores the way couriers perform their work in context, both through the tethered geographical elements of the city, and amidst the platform’s multiple entanglements and spatiotemporal arrangements. The research design of this thesis has a strong qualitative research methodology, including methods such as walk-along interviews, semi-structured interviews, ethnographic reporting techniques, and the author’s 3-month work experience as a food delivery courier. The findings of this work suggest that we should acknowledge the platform as a constant becoming entity where couriers’ sensemaking processes are produced at the intersection of their experience of the city and their relationship with the managing algorithms of the platform. A performative sociomaterial practice that constantly produces knowledge that is used by couriers to negotiate their participation in the platform. This thesis expands previous understandings of digital workers’ experiences of algorithmic management by incorporating a sociomaterial and performative approach in the analysis of couriers’ sensemaking processes. Furthermore, by considering the relationships and interactions between human and nonhuman agencies in the food delivery platform industry, this work contributes not only to the understanding of agency within digital platforms but also to a broader understanding of agency in our increasingly digitally mediated societies.
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(2022)This thesis examines the social interaction and media ideologies of Finnish TikTok users and how they are different from the discourses about TikTok in Finnish news media. My aim is to understand how TikTok is seen as a social media platform and what kind of social interaction and face-work users do when encountered with differing views of their media ideologies. I use Gershon’s framework of media ideologies to understand the implied and explicit opinions of Finnish TikTok users of the proper ways of using the medium and to compare those views to Finnish news media’s representations of the app and its use. By analysing discourses of the online news of Finnish Public Broadcasting Company (YLE) and the online news of Finland’s biggest newspaper Helsingin Sanomat (HS), I identify main categories of discourse about TikTok and its use. To understand the users’ perspective, I have conducted online ethnography in TikTok with two separate user accounts to collect data from videos, comments and video replies. From this data, I identify multiple media ideologies voiced out among the users of TikTok. Lastly, I compare these two data sets to see where they overlap and where they live separate lives. In order to understand the social phenomena related to the debates over different media ideologies, I utilise Erving Goffman’s concept of face and face-work. By exploring these questions with these methods and theoretical frameworks I wish to contribute to the discussion of how young users might adopt new ways of interacting and expressing themselves within a new medium, and how that might be different from the views of the people outside that medium. The goal of my thesis is to create an analytical overview on social interaction and media ideologies in TikTok, especially among Finnish TikTokers and how that differs from the discourses represented in Finnish news media
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(2022)This thesis examines the social interaction and media ideologies of Finnish TikTok users and how they are different from the discourses about TikTok in Finnish news media. My aim is to understand how TikTok is seen as a social media platform and what kind of social interaction and face-work users do when encountered with differing views of their media ideologies. I use Gershon’s framework of media ideologies to understand the implied and explicit opinions of Finnish TikTok users of the proper ways of using the medium and to compare those views to Finnish news media’s representations of the app and its use. By analysing discourses of the online news of Finnish Public Broadcasting Company (YLE) and the online news of Finland’s biggest newspaper Helsingin Sanomat (HS), I identify main categories of discourse about TikTok and its use. To understand the users’ perspective, I have conducted online ethnography in TikTok with two separate user accounts to collect data from videos, comments and video replies. From this data, I identify multiple media ideologies voiced out among the users of TikTok. Lastly, I compare these two data sets to see where they overlap and where they live separate lives. In order to understand the social phenomena related to the debates over different media ideologies, I utilise Erving Goffman’s concept of face and face-work. By exploring these questions with these methods and theoretical frameworks I wish to contribute to the discussion of how young users might adopt new ways of interacting and expressing themselves within a new medium, and how that might be different from the views of the people outside that medium. The goal of my thesis is to create an analytical overview on social interaction and media ideologies in TikTok, especially among Finnish TikTokers and how that differs from the discourses represented in Finnish news media
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(2020)Algorithms are effective data processing programs, which are being applied in an increasing amount of contexts and areas of our lives. One such context is that of our working lives, where algorithms are being adapted to take over tasks previously performed by human workers. This has sparked the discussion about capabilities and agency of algorithmic technology, and also whether or not technology will be replacing the human workforce. Public discussion has actively taken part in constructing both opportunities and fears related to algorithmic technology, but very little research exists about the impact of algorithmic technology at work. A lot of discussion has also centered around the agency of algorithms, as due to the advances in technology, agency is no longer something only only assigned to, or possessed by human actors. While some research has been done on the construction of algorithm agency, very little research has been conducted to explore the phenomena in the context of work. Research about adapting algorithms in companies is very scarce, and the gap in this research is especially crucial due to its lack of research from a social scientific perspective. The purpose of this thesis is to investigate how algorithmic agency (or lack thereof) is constructed in the discourse of five employees of an IT company that has applied an algorithm in their operations. I further want to investigate what consequences these constructs have on the work of the employees and the flow of agency in the company. The theoretical and methodological framework is rooted in social constructionism and discursive psychology and the analysis focuses on the construction of accounts of agency in the context. In order to answer the research questions I have conducted a semi-structured focused interview with each of the recruited employees. The results show that algorithmic agency is constructed in multifaceted ways and several constructs of agency coexist in the discourse of the employees. The agency is constructed as an independent actor with agency, but that this agency is also restricted by its human developers and operational staff intervening in its decisions. While accounts for algorithmicx agency exist, agency is also constructed as something possessed by the developers and company, who develop the algorithm in order to reach certain goals. The results also show that the algorithm is constructed as an enabler and restrictor to human agency, but that the adaptation of the algorithm has also created new flows of agency, where agency flows from human to algorithm and vice versa. This thesis contributes to previous research on agency, algorithms and work by taking a contemporary, employee-centric perspective on agency, not yet taken by previous research. In order to take into account the dynamic processes of agency when adapting algorithmic technology in companies, an extensive social scientific perspective is needed to inform organizational change. In order to achieve this, more qualitative research is needed to further understand the impact of automation on agency and other interpersonal dynamics.
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(2020)Algorithms are effective data processing programs, which are being applied in an increasing amount of contexts and areas of our lives. One such context is that of our working lives, where algorithms are being adapted to take over tasks previously performed by human workers. This has sparked the discussion about capabilities and agency of algorithmic technology, and also whether or not technology will be replacing the human workforce. Public discussion has actively taken part in constructing both opportunities and fears related to algorithmic technology, but very little research exists about the impact of algorithmic technology at work. A lot of discussion has also centered around the agency of algorithms, as due to the advances in technology, agency is no longer something only only assigned to, or possessed by human actors. While some research has been done on the construction of algorithm agency, very little research has been conducted to explore the phenomena in the context of work. Research about adapting algorithms in companies is very scarce, and the gap in this research is especially crucial due to its lack of research from a social scientific perspective. The purpose of this thesis is to investigate how algorithmic agency (or lack thereof) is constructed in the discourse of five employees of an IT company that has applied an algorithm in their operations. I further want to investigate what consequences these constructs have on the work of the employees and the flow of agency in the company. The theoretical and methodological framework is rooted in social constructionism and discursive psychology and the analysis focuses on the construction of accounts of agency in the context. In order to answer the research questions I have conducted a semi-structured focused interview with each of the recruited employees. The results show that algorithmic agency is constructed in multifaceted ways and several constructs of agency coexist in the discourse of the employees. The agency is constructed as an independent actor with agency, but that this agency is also restricted by its human developers and operational staff intervening in its decisions. While accounts for algorithmicx agency exist, agency is also constructed as something possessed by the developers and company, who develop the algorithm in order to reach certain goals. The results also show that the algorithm is constructed as an enabler and restrictor to human agency, but that the adaptation of the algorithm has also created new flows of agency, where agency flows from human to algorithm and vice versa. This thesis contributes to previous research on agency, algorithms and work by taking a contemporary, employee-centric perspective on agency, not yet taken by previous research. In order to take into account the dynamic processes of agency when adapting algorithmic technology in companies, an extensive social scientific perspective is needed to inform organizational change. In order to achieve this, more qualitative research is needed to further understand the impact of automation on agency and other interpersonal dynamics.
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