Pub Date : 2023-01-01DOI: 10.1177/20539517231158635
Ingrid Metzler, Lisa-Maria Ferent, U. Felt
Biobanking involves the assembling, curating, and distributing of samples and data. While relations between samples and data are often taken as defining properties of biobanking, several studies have pointed to the challenges in relating them in practice. This article investigates how samples and data are curated, connected, and made mobile in practice. Building on an analysis of data collected at five hospital-based biobanks in Austria, the article describes and compares biobanking in three types of biobank collections: ‘departmental collections’, ‘project-specific collections’ and ‘hospital-wide collections’. It draws attention to the invisible work going into this infrastructure and highlights the central role of visions to make samples and data travel to a different location and thus support biomedical research. It shows that while visions of future travels are often epistemologically uncertain, they are informed by social ties and relationships between the collectives involved in the curation of samples and data on the one hand and the imagined users on the other. Finally, we point to the importance that policy actors in this domain consider the aspects we identified—and, in particular, reflect the temporalities inherent in such a research infrastructure.
{"title":"On samples, data, and their mobility in biobanking: How imagined travels help to relate samples and data","authors":"Ingrid Metzler, Lisa-Maria Ferent, U. Felt","doi":"10.1177/20539517231158635","DOIUrl":"https://doi.org/10.1177/20539517231158635","url":null,"abstract":"Biobanking involves the assembling, curating, and distributing of samples and data. While relations between samples and data are often taken as defining properties of biobanking, several studies have pointed to the challenges in relating them in practice. This article investigates how samples and data are curated, connected, and made mobile in practice. Building on an analysis of data collected at five hospital-based biobanks in Austria, the article describes and compares biobanking in three types of biobank collections: ‘departmental collections’, ‘project-specific collections’ and ‘hospital-wide collections’. It draws attention to the invisible work going into this infrastructure and highlights the central role of visions to make samples and data travel to a different location and thus support biomedical research. It shows that while visions of future travels are often epistemologically uncertain, they are informed by social ties and relationships between the collectives involved in the curation of samples and data on the one hand and the imagined users on the other. Finally, we point to the importance that policy actors in this domain consider the aspects we identified—and, in particular, reflect the temporalities inherent in such a research infrastructure.","PeriodicalId":47834,"journal":{"name":"Big Data & Society","volume":" ","pages":""},"PeriodicalIF":8.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46303992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1177/20539517231179197
Daniel Greene, Nate Beard, Tamara L. Clegg, E. Weight
Elite athletes are constantly tracked, measured, scored, and sorted to improve their performance. Privacy is sacrificed in the name of improvement. Athletes frequently do not know why particular personal data are collected or to what end. Our interview study of 23 elite US college athletes and 26 staff members reveals that their sports play is governed through information asymmetries. These asymmetries look different for different sports with different levels of investment, different racial and gender makeups, and different performance metrics. As large, data-intensive organizations with highly differentiated subgroups, university athletics are an excellent site for theory building in critical data studies, especially given the most consequential data collected from us, with the greatest effect on our lives, is frequently a product of collective engagement with specific organizational contexts like workplaces and schools. Empirical analysis reveals two key tensions in this data regime: Athletes in high-status sports, more likely to be Black men, have relatively less freedom to see or dispute their personal data, while athletes in general are more comfortable sharing personal data with people further away from them. We build from these findings to develop a theory of collective informational harm in bounded institutional settings such as the workplace. The quantified organization, as we term it, is concerned not with monitoring individuals but building data collectives through processes of category creation and managerial data relations of coercion and consent.
{"title":"The visible body and the invisible organization: Information asymmetry and college athletics data","authors":"Daniel Greene, Nate Beard, Tamara L. Clegg, E. Weight","doi":"10.1177/20539517231179197","DOIUrl":"https://doi.org/10.1177/20539517231179197","url":null,"abstract":"Elite athletes are constantly tracked, measured, scored, and sorted to improve their performance. Privacy is sacrificed in the name of improvement. Athletes frequently do not know why particular personal data are collected or to what end. Our interview study of 23 elite US college athletes and 26 staff members reveals that their sports play is governed through information asymmetries. These asymmetries look different for different sports with different levels of investment, different racial and gender makeups, and different performance metrics. As large, data-intensive organizations with highly differentiated subgroups, university athletics are an excellent site for theory building in critical data studies, especially given the most consequential data collected from us, with the greatest effect on our lives, is frequently a product of collective engagement with specific organizational contexts like workplaces and schools. Empirical analysis reveals two key tensions in this data regime: Athletes in high-status sports, more likely to be Black men, have relatively less freedom to see or dispute their personal data, while athletes in general are more comfortable sharing personal data with people further away from them. We build from these findings to develop a theory of collective informational harm in bounded institutional settings such as the workplace. The quantified organization, as we term it, is concerned not with monitoring individuals but building data collectives through processes of category creation and managerial data relations of coercion and consent.","PeriodicalId":47834,"journal":{"name":"Big Data & Society","volume":" ","pages":""},"PeriodicalIF":8.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43057794","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1177/20539517231163173
Astrid Mager
This article investigates how developers of alternative search engines challenge increasingly corporate imaginaries of digital futures by building out counter-imaginaries of search engines devoted to social values instead of mere profit maximization. Drawing on three in-depth case studies of European search engines, it analyzes how search engine developers counter-imagine hegemonic search, what social values support their imaginaries, and how they are intertwined with their sociotechnical practices. This analysis shows that notions like privacy, independence, and openness appear to be fluid, context-dependent, and changing over time, leading to a certain “value pragmatics” that allows the projects to scale beyond their own communities of practice. It further shows how European values, and broader notions of Europe as “unified or pluralistic,” are constructed and co-produced with developers’ attempts to counter-imagine and counteract hegemonic search. To conclude, I suggest three points of intervention that may help alternative search engine projects, and digital technologies more generally, to not only make their counter-imaginaries more powerful, but also acquire the necessary resources to build their technologies and infrastructures accordingly. I finally discuss how “European values,” in all their richness and diversity, can contribute to this undertaking.
{"title":"European Search? How to counter-imagine and counteract hegemonic search with European search engine projects","authors":"Astrid Mager","doi":"10.1177/20539517231163173","DOIUrl":"https://doi.org/10.1177/20539517231163173","url":null,"abstract":"This article investigates how developers of alternative search engines challenge increasingly corporate imaginaries of digital futures by building out counter-imaginaries of search engines devoted to social values instead of mere profit maximization. Drawing on three in-depth case studies of European search engines, it analyzes how search engine developers counter-imagine hegemonic search, what social values support their imaginaries, and how they are intertwined with their sociotechnical practices. This analysis shows that notions like privacy, independence, and openness appear to be fluid, context-dependent, and changing over time, leading to a certain “value pragmatics” that allows the projects to scale beyond their own communities of practice. It further shows how European values, and broader notions of Europe as “unified or pluralistic,” are constructed and co-produced with developers’ attempts to counter-imagine and counteract hegemonic search. To conclude, I suggest three points of intervention that may help alternative search engine projects, and digital technologies more generally, to not only make their counter-imaginaries more powerful, but also acquire the necessary resources to build their technologies and infrastructures accordingly. I finally discuss how “European values,” in all their richness and diversity, can contribute to this undertaking.","PeriodicalId":47834,"journal":{"name":"Big Data & Society","volume":" ","pages":""},"PeriodicalIF":8.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44558202","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1177/20539517231153803
M. Pedersen
Bringing together a motley crew of social scientists and data scientists, the aim of this special theme issue is to explore what an integration or even fusion between anthropology and data science might look like. Going beyond existing work on the complementarity between ‘thick’ qualitative and ‘big’ quantitative data, the ambition is to unsettle and push established disciplinary, methodological and epistemological boundaries by creatively and critically probing various computational methods for augmenting and automatizing the collection, processing and analysis of ethnographic data, and vice versa. Can ethnographic and other qualitative data and methods be integrated with natural language processing tools and other machine-learning techniques, and if so, to what effect? Does the rise of data science allow for the realization of Levi-Strauss’ old dream of a computational structuralism, and even if so, should it? Might one even go as far as saying that computers are now becoming agents of social scientific analysis or even thinking: are we about to witness the birth of distinctly anthropological forms of artificial intelligence? By exploring these questions, the hope is not only to introduce scholars and students to computational anthropological methods, but also to disrupt predominant norms and assumptions among computational social scientists and data science writ large.
{"title":"Editorial introduction: Towards a machinic anthropology","authors":"M. Pedersen","doi":"10.1177/20539517231153803","DOIUrl":"https://doi.org/10.1177/20539517231153803","url":null,"abstract":"Bringing together a motley crew of social scientists and data scientists, the aim of this special theme issue is to explore what an integration or even fusion between anthropology and data science might look like. Going beyond existing work on the complementarity between ‘thick’ qualitative and ‘big’ quantitative data, the ambition is to unsettle and push established disciplinary, methodological and epistemological boundaries by creatively and critically probing various computational methods for augmenting and automatizing the collection, processing and analysis of ethnographic data, and vice versa. Can ethnographic and other qualitative data and methods be integrated with natural language processing tools and other machine-learning techniques, and if so, to what effect? Does the rise of data science allow for the realization of Levi-Strauss’ old dream of a computational structuralism, and even if so, should it? Might one even go as far as saying that computers are now becoming agents of social scientific analysis or even thinking: are we about to witness the birth of distinctly anthropological forms of artificial intelligence? By exploring these questions, the hope is not only to introduce scholars and students to computational anthropological methods, but also to disrupt predominant norms and assumptions among computational social scientists and data science writ large.","PeriodicalId":47834,"journal":{"name":"Big Data & Society","volume":" ","pages":""},"PeriodicalIF":8.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44350115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1177/20539517231176228
Richard A. Rogers
Google results have been scrutinized over the years for what they privilege, be it the surface web, the powerful, optimized webpages, the personalized and/or their own properties. For some time now, another type of Google returns also has been the source of attention: the offensive result. The following revisits a selection of offensive and other problematic results found by journalists and researchers alike. In a technique termed ‘algorithmic probing’, the prompting queries are re-run to study what has come of these results in Google Web and Image Search but mainly in Google Autocompletion. The question concerns a different kind of privileging – Google's hierarchy of concerns – or the extent to which certain categories as well as languages are moderated and others less so. In all, it was found that Google heavily moderates religion, ethnicities and sexualities (albeit with gaps) but leaves alone stereotypes of gendered professions as well as ageism. It also moderates to a greater degree in English compared to southern European and Balkan languages. The article concludes with a discussion of the stakes of Google's moderation, including its uneven coverage.
{"title":"Algorithmic probing: Prompting offensive Google results and their moderation","authors":"Richard A. Rogers","doi":"10.1177/20539517231176228","DOIUrl":"https://doi.org/10.1177/20539517231176228","url":null,"abstract":"Google results have been scrutinized over the years for what they privilege, be it the surface web, the powerful, optimized webpages, the personalized and/or their own properties. For some time now, another type of Google returns also has been the source of attention: the offensive result. The following revisits a selection of offensive and other problematic results found by journalists and researchers alike. In a technique termed ‘algorithmic probing’, the prompting queries are re-run to study what has come of these results in Google Web and Image Search but mainly in Google Autocompletion. The question concerns a different kind of privileging – Google's hierarchy of concerns – or the extent to which certain categories as well as languages are moderated and others less so. In all, it was found that Google heavily moderates religion, ethnicities and sexualities (albeit with gaps) but leaves alone stereotypes of gendered professions as well as ageism. It also moderates to a greater degree in English compared to southern European and Balkan languages. The article concludes with a discussion of the stakes of Google's moderation, including its uneven coverage.","PeriodicalId":47834,"journal":{"name":"Big Data & Society","volume":" ","pages":""},"PeriodicalIF":8.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46166854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1177/20539517231155064
Karin van Es, Daan van der Weijden, Jeroen Bakker
Data centers are material structures that take up space, use resources like water and energy, and possess a large carbon footprint. This paper examines the broader long-term discussion around data centers during the period 2020–2022 in the Dutch Twittersphere. Through an analysis of tweets and images, it identifies and reflects on the communities active in the discussion and the range of visions and imaginaries of data centers they produce. Unpacking these tweets and images over time traces not only the emergence of a ‘reactive imaginary’, critical of the promises of information technology (IT) industry and (local) governments, but also the blind spots of the discussion. It furthermore reveals an important role for journalism in the discussion by questioning the claims of the industry and contributing to a ‘visibility expansion’ of data center’s impact on Earth's resources. The paper shows the multifaceted and situated nature of imaginaries and their role in shaping decision-making and policy.
{"title":"The multifaceted and situated data center imaginary of Dutch Twitter","authors":"Karin van Es, Daan van der Weijden, Jeroen Bakker","doi":"10.1177/20539517231155064","DOIUrl":"https://doi.org/10.1177/20539517231155064","url":null,"abstract":"Data centers are material structures that take up space, use resources like water and energy, and possess a large carbon footprint. This paper examines the broader long-term discussion around data centers during the period 2020–2022 in the Dutch Twittersphere. Through an analysis of tweets and images, it identifies and reflects on the communities active in the discussion and the range of visions and imaginaries of data centers they produce. Unpacking these tweets and images over time traces not only the emergence of a ‘reactive imaginary’, critical of the promises of information technology (IT) industry and (local) governments, but also the blind spots of the discussion. It furthermore reveals an important role for journalism in the discussion by questioning the claims of the industry and contributing to a ‘visibility expansion’ of data center’s impact on Earth's resources. The paper shows the multifaceted and situated nature of imaginaries and their role in shaping decision-making and policy.","PeriodicalId":47834,"journal":{"name":"Big Data & Society","volume":" ","pages":""},"PeriodicalIF":8.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48577553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1177/20539517231159002
K. Nabben
The term ‘Web3’ refers to the practices of participating in digital infrastructures through the ability to read, write and coordinate digital assets. Web3 is hailed as an alternative to the failings of big tech, offering a participatory mode of digital self-organizing and shared ownership of digital infrastructure through software-encoded governance rules and participatory practices. Yet, very few analytical frameworks have been presented in academic literature by which to approach Web3. This piece draws on the theoretical lens of infrastructure studies to offer an analytical framework to approach the emergent field of Web3 as an exploration in ‘how to infrastructure’ through prefigurative self-infrastructuring. Drawing on qualitative examples from digital ethnographic methods, I demonstrate how the origins of Web3 reveal the intentions of its creators as a political tool of prefiguration, yet its practices reveal the inherent tension of expressing these ideals in coherent technical and institutional infrastructure. Thus, I argue that one of the fundamental challenges Web3 is negotiating through technical and governance experiments is ‘how to self-infrastructure?’.
{"title":"Web3 as ‘self-infrastructuring’: The challenge is how","authors":"K. Nabben","doi":"10.1177/20539517231159002","DOIUrl":"https://doi.org/10.1177/20539517231159002","url":null,"abstract":"The term ‘Web3’ refers to the practices of participating in digital infrastructures through the ability to read, write and coordinate digital assets. Web3 is hailed as an alternative to the failings of big tech, offering a participatory mode of digital self-organizing and shared ownership of digital infrastructure through software-encoded governance rules and participatory practices. Yet, very few analytical frameworks have been presented in academic literature by which to approach Web3. This piece draws on the theoretical lens of infrastructure studies to offer an analytical framework to approach the emergent field of Web3 as an exploration in ‘how to infrastructure’ through prefigurative self-infrastructuring. Drawing on qualitative examples from digital ethnographic methods, I demonstrate how the origins of Web3 reveal the intentions of its creators as a political tool of prefiguration, yet its practices reveal the inherent tension of expressing these ideals in coherent technical and institutional infrastructure. Thus, I argue that one of the fundamental challenges Web3 is negotiating through technical and governance experiments is ‘how to self-infrastructure?’.","PeriodicalId":47834,"journal":{"name":"Big Data & Society","volume":" ","pages":""},"PeriodicalIF":8.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44627299","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1177/20539517231172424
Sahana Udupa, Antonis Maronikolakis, Axel Wisiorek
In this article, we present new empirical evidence to demonstrate the severe limitations of existing machine learning content moderation methods to keep pace with, let alone stay ahead of, hateful language online. Building on the collaborative coding project “AI4Dignity” we outline the ambiguities and complexities of annotating problematic text in AI-assisted moderation systems. We diagnose the shortcomings of the content moderation and natural language processing approach as emerging from a broader epistemological trapping wrapped in the liberal-modern idea of “the human”. Presenting a decolonial critique of the “human vs machine” conundrum and drawing attention to the structuring effects of coloniality on extreme speech, we propose “ethical scaling” to highlight moderation process as political praxis. As a normative framework for platform governance, ethical scaling calls for a transparent, reflexive, and replicable process of iteration for content moderation with community participation and global parity, which should evolve in conjunction with addressing algorithmic amplification of divisive content and resource allocation for content moderation.
{"title":"Ethical scaling for content moderation: Extreme speech and the (in)significance of artificial intelligence","authors":"Sahana Udupa, Antonis Maronikolakis, Axel Wisiorek","doi":"10.1177/20539517231172424","DOIUrl":"https://doi.org/10.1177/20539517231172424","url":null,"abstract":"In this article, we present new empirical evidence to demonstrate the severe limitations of existing machine learning content moderation methods to keep pace with, let alone stay ahead of, hateful language online. Building on the collaborative coding project “AI4Dignity” we outline the ambiguities and complexities of annotating problematic text in AI-assisted moderation systems. We diagnose the shortcomings of the content moderation and natural language processing approach as emerging from a broader epistemological trapping wrapped in the liberal-modern idea of “the human”. Presenting a decolonial critique of the “human vs machine” conundrum and drawing attention to the structuring effects of coloniality on extreme speech, we propose “ethical scaling” to highlight moderation process as political praxis. As a normative framework for platform governance, ethical scaling calls for a transparent, reflexive, and replicable process of iteration for content moderation with community participation and global parity, which should evolve in conjunction with addressing algorithmic amplification of divisive content and resource allocation for content moderation.","PeriodicalId":47834,"journal":{"name":"Big Data & Society","volume":" ","pages":""},"PeriodicalIF":8.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43134080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1177/20539517231177621
D. Curran
Zuboff's The Age of Surveillance Capitalism provides a powerful analysis of the emergence of surveillance capitalism as a particular type of informational capitalism. Many of the important impacts of this project of creating larger and more integrated systems of ‘behavioural surplus’ are captured powerfully by Zuboff; yet as different risk and organisational scholars such as Beck, Perrow, and Vaughan have argued, integrated systems often do not function as intended. While the imperfection of these systems may raise the possibility that surveillance capitalism may not be as bad as Zuboff suggests, there is also a way in which these systems not functioning as intended can make surveillance capitalism an even more dystopian possibility. In this vein, this paper asks: what are the consequences when the tools of a surveillance capitalist society break down? This paper argues that it is by thinking through Zuboff's framework that we can identify the systemic fragility of a surveillance capitalist society. This systemic fragility emerges through how surveillance capitalism generates imperatives towards the maximal collection of data for exploitation, which in turn generates a corresponding imperative to connect all aspects of life. Both of these imperatives, of collect and connect, in turn create an immensely fragile digital system, which has vast ramifications throughout social life, such that small imperfections and gaps in the system can magnify risk throughout society.
{"title":"Surveillance capitalism and systemic digital risk: The imperative to collect and connect and the risks of interconnectedness","authors":"D. Curran","doi":"10.1177/20539517231177621","DOIUrl":"https://doi.org/10.1177/20539517231177621","url":null,"abstract":"Zuboff's The Age of Surveillance Capitalism provides a powerful analysis of the emergence of surveillance capitalism as a particular type of informational capitalism. Many of the important impacts of this project of creating larger and more integrated systems of ‘behavioural surplus’ are captured powerfully by Zuboff; yet as different risk and organisational scholars such as Beck, Perrow, and Vaughan have argued, integrated systems often do not function as intended. While the imperfection of these systems may raise the possibility that surveillance capitalism may not be as bad as Zuboff suggests, there is also a way in which these systems not functioning as intended can make surveillance capitalism an even more dystopian possibility. In this vein, this paper asks: what are the consequences when the tools of a surveillance capitalist society break down? This paper argues that it is by thinking through Zuboff's framework that we can identify the systemic fragility of a surveillance capitalist society. This systemic fragility emerges through how surveillance capitalism generates imperatives towards the maximal collection of data for exploitation, which in turn generates a corresponding imperative to connect all aspects of life. Both of these imperatives, of collect and connect, in turn create an immensely fragile digital system, which has vast ramifications throughout social life, such that small imperfections and gaps in the system can magnify risk throughout society.","PeriodicalId":47834,"journal":{"name":"Big Data & Society","volume":" ","pages":""},"PeriodicalIF":8.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47233959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1177/20539517231171051
Geri L. Dimas, Lauri Goldkind, R. Konrad
The social services sector, comprised of a constellation of programs meeting critical human needs, lacks the resources and infrastructure to implement data science tools. As the use of data science continues to expand, it has been accompanied by a rise in interest and commitment to using these tools for social good. This commentary examines overlooked, and under-researched limitations of data science applications in the social sector—the volume, quality, and context of the available data that currently exists in social service systems require unique considerations. We explore how the presence of small data within the social service contexts can result in extrapolation; if not properly considered, data science can negatively impact the organizations data scientists are trying to assist. We conclude by proposing three ways data scientists interested in working within the social services sector can enhance their contributions to the field: refining and leveraging available data, improving collaborations, and respecting data limitations.
{"title":"Big ideas, small data: Opportunities and challenges for data science and the social services sector","authors":"Geri L. Dimas, Lauri Goldkind, R. Konrad","doi":"10.1177/20539517231171051","DOIUrl":"https://doi.org/10.1177/20539517231171051","url":null,"abstract":"The social services sector, comprised of a constellation of programs meeting critical human needs, lacks the resources and infrastructure to implement data science tools. As the use of data science continues to expand, it has been accompanied by a rise in interest and commitment to using these tools for social good. This commentary examines overlooked, and under-researched limitations of data science applications in the social sector—the volume, quality, and context of the available data that currently exists in social service systems require unique considerations. We explore how the presence of small data within the social service contexts can result in extrapolation; if not properly considered, data science can negatively impact the organizations data scientists are trying to assist. We conclude by proposing three ways data scientists interested in working within the social services sector can enhance their contributions to the field: refining and leveraging available data, improving collaborations, and respecting data limitations.","PeriodicalId":47834,"journal":{"name":"Big Data & Society","volume":" ","pages":""},"PeriodicalIF":8.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43073458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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