Big Data & Society最新文献_第8页

Expansive and extractive networks of Web3 Web3的扩展和提取网络

IF 8.5 1区社会学

Big Data & Society Pub Date : 2023-01-01 DOI: 10.1177/20539517231159629

Jathan Sadowski, Kaitlin Beegle

{"title":"Expansive and extractive networks of Web3","authors":"Jathan Sadowski, Kaitlin Beegle","doi":"10.1177/20539517231159629","DOIUrl":"https://doi.org/10.1177/20539517231159629","url":null,"abstract":"The self-proclaimed usurper of Web 2.0, Web3 quickly became the center of attention. Not long ago, the public discourse was saturated with projects, promises, and peculiarities of Web3. Now the spotlight has swung around to focus on the many faults, failures, and frauds of Web3. The cycles of technological trends and investment bubbles seem to be accelerating in such a way as to escape any attempt at observing them in motion before they crash, and then everybody moves on to the next thing. Importantly, Web3 was not an anomaly or curiosity in the broader tech industry. It articulates patterns that existed before Web3 and will exist after. Web3 should be understood as a case study of innovation within the dominant model of Silicon Valley venture capitalism. Our focus in this article is on understanding how the movement around Web3 formed through an interplay between (1) normative concepts and contestations related to ideas of “decentralization” and (2) political economic interests and operations related to the dynamics of fictitious capital. By offering a critical analysis of Web3, our goal is also to show how any even potentially progressive (or as we call them “expansive”) forms of Web3 development struggle for success, recognition, and attention due to the wild excesses of hype and investment devoted to “extractive” forms of Web3. In the process, they provide us a better view of how different arrangements of technopolitics can exist at the same time, side-by-side, in complicated ways.","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":"46524146","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}

引用次数: 4

Ecological ethics and the smart circular economy 生态伦理与智慧循环经济

IF 8.5 1区社会学

Big Data & Society Pub Date : 2023-01-01 DOI: 10.1177/20539517231158996

Rolien Hoyng

{"title":"Ecological ethics and the smart circular economy","authors":"Rolien Hoyng","doi":"10.1177/20539517231158996","DOIUrl":"https://doi.org/10.1177/20539517231158996","url":null,"abstract":"The corporate discourse on the circular economy holds that the growth of the electronics industry, driven by continuous innovation, does not imperil ecological sustainability. To achieve sustainable growth, its advocates propose optimizing recycling by means of artificial intelligence and sets of interrelated datacentric and algorithmic technologies. Drawing on critical data and algorithm studies, theories of waste, and empirical research, this paper investigates ecological ethics in the context of the datacentric and algorithmically mediated circular economy. It foregrounds the indeterminate and fickle material nature of waste as well as the uncertainties inherent in, and stemming from, datafication and computation. My question is: how do the rationalities, affordances, and dispositions of datacentric and algorithmic technologies perform and displace notions of corporate responsibility and transparency? In order to answer this question, I compare the smart circular economy to the informal recycling practices that it claims to replace, and I analyze relations between waste matter and data as well as distributions of agency. Specifically, I consider transitions and slippages between response-ability and responsibility. Conceptually, I bring process-relation or immanence-based philosophies such as Bergson's and Deleuze's into a debate about relations between waste matter and data and the ambition of algorithmic control over waste. My aim is not to demand heightened corporate responsibility enacted through control but to rethink responsibility in the smart circular economy along the lines of Amoore's cloud ethics to carve out a position of critique beyond either a deontological perspective that reinforces corporate agency or new-materialist denunciation of the concept.","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":"45912563","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}

引用次数: 1

Manipulative tactics are the norm in political emails: Evidence from 300K emails from the 2020 US election cycle 操纵策略是政治邮件中的常态:来自2020年美国选举周期的30万封电子邮件的证据

IF 8.5 1区社会学

Big Data & Society Pub Date : 2023-01-01 DOI: 10.1177/20539517221145371

Arunesh Mathur, Angelina Wang, Carsten Schwemmer, Maia Hamin, Brandon M Stewart, Arvind Narayanan

{"title":"Manipulative tactics are the norm in political emails: Evidence from 300K emails from the 2020 US election cycle","authors":"Arunesh Mathur, Angelina Wang, Carsten Schwemmer, Maia Hamin, Brandon M Stewart, Arvind Narayanan","doi":"10.1177/20539517221145371","DOIUrl":"https://doi.org/10.1177/20539517221145371","url":null,"abstract":"We collect and analyze a corpus of more than 300,000 political emails sent during the 2020 US election cycle. These emails were sent by over 3000 political campaigns and organizations including federal and state level candidates as well as Political Action Committees. We find that in this corpus, manipulative tactics—techniques using some level of deception or clickbait—are the norm, not the exception. We measure six specific tactics senders use to nudge recipients to open emails. Three of these tactics—“dark patterns”—actively deceive recipients through the email user interface, for example, by formatting “from:” fields so that they create the false impression the message is a continuation of an ongoing conversation. The median active sender uses such tactics 5% of the time. The other three tactics, like sensationalistic clickbait—used by the median active sender 37% of the time—are not directly deceptive, but instead, exploit recipients’ curiosity gap and impose pressure to open emails. This can further expose recipients to deception in the email body, such as misleading claims of matching donations. Furthermore, by collecting emails from different locations in the US, we show that senders refine these tactics through A/B testing. Finally, we document disclosures of email addresses between senders in violation of privacy policies and recipients’ expectations. Cumulatively, these tactics undermine voters’ autonomy and welfare, exacting a particularly acute cost for those with low digital literacy. We offer the complete corpus of emails at https://electionemails2020.org for journalists and academics, which we hope will support future work.","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":"45283674","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}

引用次数: 13

‘I’ve left enough data’: Relations between people and data and the production of surveillance “我已经留下了足够的数据”:人与数据之间的关系以及监控的产生

IF 8.5 1区社会学

Big Data & Society Pub Date : 2023-01-01 DOI: 10.1177/20539517231173904

Hwankyung Janet Lee

{"title":"‘I’ve left enough data’: Relations between people and data and the production of surveillance","authors":"Hwankyung Janet Lee","doi":"10.1177/20539517231173904","DOIUrl":"https://doi.org/10.1177/20539517231173904","url":null,"abstract":"Exploring emergent relations between data-producing individuals and their data products, this study aims to contribute to the ongoing scholarly discussion on agencies in data practices. It focuses on shifts in surveillance structure in the era of Big Data, in which the individual becomes both a subject and an object in the production of data surveillance. Drawing on the concept of the ‘dividual’, the study analyses data practices for a tracing system invented by the South Korean government during the COVID-19 pandemic, with findings from field research conducted with 11 research participants in various urban sites in Seoul. Highlighting how the tracing system positioned surveillance ‘in the hands of citizens’, the study exposes the complexities of the relations that the participants formed with the data they produced, and how they reflexively reappropriated their practices through alterations and deflections on the basis of their tacit knowledge and imaginaries concerning digital data and their constituent positions in the knowledge production system. The resultant expression of surveillance was directly shaped by the evolving relationship between the producers (participants) and products (digital data). The study proposes that an intersectional focus on surveillance and critical data studies, with close attention to ordinary people's relations with data, has the capacity to inquire into the politics of data more fully.","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":"45576144","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}

引用次数: 0

Modeling COVID-19 with big mobility data: Surveillance and reaffirming the people in the data 用大流动数据建模COVID-19:监测和重申数据中的人员

IF 8.5 1区社会学

Big Data & Society Pub Date : 2023-01-01 DOI: 10.1177/20539517231164115

Thomas Walsh

引用次数: 2

Ground truth tracings (GTT): On the epistemic limits of machine learning 基本真理追踪（GTT）：关于机器学习的认识极限

IF 8.5 1区社会学

Big Data & Society Pub Date : 2023-01-01 DOI: 10.1177/20539517221146122

Edward B. Kang

{"title":"Ground truth tracings (GTT): On the epistemic limits of machine learning","authors":"Edward B. Kang","doi":"10.1177/20539517221146122","DOIUrl":"https://doi.org/10.1177/20539517221146122","url":null,"abstract":"There is a gap in existing critical scholarship that engages with the ways in which current “machine listening” or voice analytics/biometric systems intersect with the technical specificities of machine learning. This article examines the sociotechnical assemblage of machine learning techniques, practices, and cultures that underlie these technologies. After engaging with various practitioners working in companies that develop machine listening systems, ranging from CEOs, machine learning engineers, data scientists, and business analysts, among others, I bring attention to the centrality of “learnability” as a malleable conceptual framework that bends according to various “ground-truthing” practices in formalizing certain listening-based prediction tasks for machine learning. In response, I introduce a process I call Ground Truth Tracings to examine the various ontological translations that occur in training a machine to “learn to listen.” Ultimately, by further examining this notion of learnability through the aperture of power, I take insights acquired through my fieldwork in the machine listening industry and propose a strategically reductive heuristic through which the epistemological and ethical soundness of machine learning, writ large, can be contemplated.","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":"43497044","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}

引用次数: 8

The importance of algorithm skills for informed Internet use 算法技能对知情互联网使用的重要性

IF 8.5 1区社会学

Big Data & Society Pub Date : 2023-01-01 DOI: 10.1177/20539517231168100

Jonathan Gruber, E. Hargittai

{"title":"The importance of algorithm skills for informed Internet use","authors":"Jonathan Gruber, E. Hargittai","doi":"10.1177/20539517231168100","DOIUrl":"https://doi.org/10.1177/20539517231168100","url":null,"abstract":"Using the Internet means encountering algorithmic processes that influence what information a user sees or hears. Existing research has shown that people's algorithm skills vary considerably, that they develop individual theories to explain these processes, and that their online behavior can reflect these understandings. Yet, there is little research on how algorithm skills enable people to use algorithms to their own benefit and to avoid harms they may elicit. To fill this gap in the literature, we explore the extent to which people understand how the online systems and services they use may be influenced by personal data that algorithms know about them, and whether users change their behavior based on this understanding. Analyzing 83 in-depth interviews from five countries about people's experiences with researching and searching for products and services online, we show how being aware of personal data collection helps people understand algorithmic processes. However, this does not necessarily enable users to influence algorithmic output, because currently, options that help users control the level of customization they encounter online are limited. Besides the empirical contributions, we discuss research design implications based on the diversity of the sample and our findings for studying algorithm skills.","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":"41901578","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}

引用次数: 2

The world wide web of carbon: Toward a relational footprinting of information and communications technology's climate impacts 全球碳网：信息和通信技术对气候影响的关系足迹

IF 8.5 1区社会学

Big Data & Society Pub Date : 2023-01-01 DOI: 10.1177/20539517231158994

A. Pasek, Hunter Vaughan, Nicole Starosielski

{"title":"The world wide web of carbon: Toward a relational footprinting of information and communications technology's climate impacts","authors":"A. Pasek, Hunter Vaughan, Nicole Starosielski","doi":"10.1177/20539517231158994","DOIUrl":"https://doi.org/10.1177/20539517231158994","url":null,"abstract":"The climate impacts of the information and communications technology sector—and Big Data especially—is a topic of growing public and industry concern, though attempts to quantify its carbon footprint have produced contradictory results. Some studies argue that information and communications technology's global carbon footprint is set to rise dramatically in the coming years, requiring urgent regulation and sectoral degrowth. Others argue that information and communications technology's growth is largely decoupled from its carbon emissions, and so provides valuable climate solutions and a model for other industries. This article assesses these debates, arguing that, due to data frictions and incommensurate study designs, the question is likely to remain irresolvable at the global scale. We present six methodological factors that drive this impasse: fraught access to industry data, bottom-up vs. top-down assessments, system boundaries, geographic averaging, functional units, and energy efficiencies. In response, we propose an alternative approach that reframes the question in spatial and situated terms: A relational footprinting that demarcates particular relationships between elements—geographic, technical, and social—within broader information and communications technology infrastructures. Illustrating this model with one of the global Internet's most overlooked components—subsea telecommunication cables—we propose that information and communications technology futures would be best charted not only in terms of quantified total energy use, but in specifying the geographical and technical parts of the network that are the least carbon-intensive, and which can therefore provide opportunities for both carbon reductions and a renewed infrastructural politics. In parallel to the politics of (de)growth, we must also consider different network forms.","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":"46213167","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}

引用次数: 6

Fact signalling and fact nostalgia in the data-driven society 数据驱动社会中的事实信号和事实怀旧

IF 8.5 1区社会学

Big Data & Society Pub Date : 2023-01-01 DOI: 10.1177/20539517231164118

Sun-ha Hong

{"title":"Fact signalling and fact nostalgia in the data-driven society","authors":"Sun-ha Hong","doi":"10.1177/20539517231164118","DOIUrl":"https://doi.org/10.1177/20539517231164118","url":null,"abstract":"Post-truth tells the story of a public descending into unreason, aided and abetted by platforms and other data-driven systems. But this apparent collapse of epistemic consensus is, I argue, also dominated by loud and aggressive commitment to the idea of facts and Reason – a site where an imagined modern past is being pillaged for vestigial legitimacy. This article identifies two common practices of such reappropriation and mythologisation. (1) Fact signalling involves performative invocations of facts and Reason, which are then weaponised to discredit communicative rivals and establish affective solidarity. This is often closely tied to (2) fact nostalgia: the cultivation of an imagined past when ‘facts were facts’ and we, the good liberal subjects, could recognise facts when we saw them. Both tendencies are underwritten by a myth of connection: the still enduring narrative that maximising the circulation of information regardless of provenance or meaning will eventually yield a more rational public – even as data-driven systems tend to undermine the very conditions for such a public. Drawing on examples from YouTube-amplified ‘alternative influencers’ in the American right, and the normative discourses around fact-checking practices, I argue that this continued reliance on the vestigial authority of the modern past is a pernicious obstacle in normative debates around data-driven publics, keeping us stuck on the same dead-end scripts of heroically suspicious individuals and ignorant, irrational masses.","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":"46642136","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}

引用次数: 2

Ethical assessments and mitigation strategies for biases in AI-systems used during the COVID-19 pandemic COVID-19大流行期间使用的人工智能系统中偏见的伦理评估和缓解策略

IF 8.5 1区社会学

Big Data & Society Pub Date : 2023-01-01 DOI: 10.1177/20539517231179199

A. de Manuel, Janet Delgado, Iris Parra Jounou, T. Ausín, D. Casacuberta, Maite Cruz, Ariel Guersenzvaig, Cristian Moyano, D. Rodríguez-Arias, J. Rueda, Á. Puyol

{"title":"Ethical assessments and mitigation strategies for biases in AI-systems used during the COVID-19 pandemic","authors":"A. de Manuel, Janet Delgado, Iris Parra Jounou, T. Ausín, D. Casacuberta, Maite Cruz, Ariel Guersenzvaig, Cristian Moyano, D. Rodríguez-Arias, J. Rueda, Á. Puyol","doi":"10.1177/20539517231179199","DOIUrl":"https://doi.org/10.1177/20539517231179199","url":null,"abstract":"The main aim of this article is to reflect on the impact of biases related to artificial intelligence (AI) systems developed to tackle issues arising from the COVID-19 pandemic, with special focus on those developed for triage and risk prediction. A secondary aim is to review assessment tools that have been developed to prevent biases in AI systems. In addition, we provide a conceptual clarification for some terms related to biases in this particular context. We focus mainly on non-racial biases that may be less considered when addressing biases in AI systems in the existing literature. In the manuscript, we found that the existence of bias in AI systems used for COVID-19 can result in algorithmic justice and that the legal frameworks and strategies developed to prevent the apparition of bias have failed to adequately consider social determinants of health. Finally, we make some recommendations on how to include more diverse professional profiles in order to develop AI systems that increase the epistemic diversity needed to tackle AI biases during the COVID-19 pandemic and beyond.","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":"44023224","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}

引用次数: 0