Big Data & Society最新文献_第10页

Surface and Sublevel Hate 曲面和子层级仇恨

IF 8.5 1区社会学

Big Data & Society Pub Date : 2023-01-01 DOI: 10.1177/20539517221148136

Luke Munn

引用次数: 0

Disability data and its situational and contextual irrationalities in the Global South 全球发展中国家的残疾数据及其情境和背景的不合理性

IF 8.5 1区社会学

Big Data & Society Pub Date : 2023-01-01 DOI: 10.1177/20539517231160523

Abdul Rohman, Dyah Pitaloka, E. Erlina, Duy Dang, Ade Prastyani

引用次数: 1

Dislocated accountabilities in the “AI supply chain”: Modularity and developers’ notions of responsibility “AI供应链”中的错位责任：模块化与开发者的责任观念

IF 8.5 1区社会学

Big Data & Society Pub Date : 2022-09-20 DOI: 10.1177/20539517231177620

D. Widder, D. Nafus

{"title":"Dislocated accountabilities in the “AI supply chain”: Modularity and developers’ notions of responsibility","authors":"D. Widder, D. Nafus","doi":"10.1177/20539517231177620","DOIUrl":"https://doi.org/10.1177/20539517231177620","url":null,"abstract":"Responsible artificial intelligence guidelines ask engineers to consider how their systems might harm. However, contemporary artificial intelligence systems are built by composing many preexisting software modules that pass through many hands before becoming a finished product or service. How does this shape responsible artificial intelligence practice? In interviews with 27 artificial intelligence engineers across industry, open source, and academia, our participants often did not see the questions posed in responsible artificial intelligence guidelines to be within their agency, capability, or responsibility to address. We use Suchman's “located accountability” to show how responsible artificial intelligence labor is currently organized and to explore how it could be done differently. We identify cross-cutting social logics, like modularizability, scale, reputation, and customer orientation, that organize which responsible artificial intelligence actions do take place and which are relegated to low status staff or believed to be the work of the next or previous person in the imagined “supply chain.” We argue that current responsible artificial intelligence interventions, like ethics checklists and guidelines that assume panoptical knowledge and control over systems, could be improved by taking a located accountability approach, recognizing where relations and obligations might intertwine inside and outside of this supply chain.","PeriodicalId":47834,"journal":{"name":"Big Data & Society","volume":" ","pages":""},"PeriodicalIF":8.5,"publicationDate":"2022-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44303049","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: 14

The effectiveness of embedded values analysis modules in Computer Science education: An empirical study 嵌入式价值分析模块在计算机科学教育中的有效性：一项实证研究

IF 8.5 1区社会学

Big Data & Society Pub Date : 2022-08-10 DOI: 10.1177/20539517231176230

Matthew Kopec, Meica Magnani, Vance Ricks, R. Torosyan, John Basl, Nicholas Miklaucic, Felix Muzny, R. Sandler, Christopher D. Wilson, Adam Wisniewski-Jensen, Cora Lundgren, Ryan Baylon, Kevin Mills, Marcy Wells

{"title":"The effectiveness of embedded values analysis modules in Computer Science education: An empirical study","authors":"Matthew Kopec, Meica Magnani, Vance Ricks, R. Torosyan, John Basl, Nicholas Miklaucic, Felix Muzny, R. Sandler, Christopher D. Wilson, Adam Wisniewski-Jensen, Cora Lundgren, Ryan Baylon, Kevin Mills, Marcy Wells","doi":"10.1177/20539517231176230","DOIUrl":"https://doi.org/10.1177/20539517231176230","url":null,"abstract":"Embedding ethics modules within computer science courses has become a popular response to the growing recognition that computer science programs need to better equip their students to navigate the ethical dimensions of computing technologies such as artificial intelligence, machine learning, and big data analytics. However, the popularity of this approach has outpaced the evidence of its positive outcomes. To help close that gap, this empirical study reports positive results from Northeastern University's program that embeds values analysis modules into computer science courses. The resulting data suggest that such modules have a positive effect on students’ moral attitudes and that students leave the modules believing they are more prepared to navigate the ethical dimensions they will likely face in their eventual careers. Importantly, these gains were accomplished at an institution without a philosophy doctoral program, suggesting this strategy can be effectively employed by a wider range of institutions than many have thought.","PeriodicalId":47834,"journal":{"name":"Big Data & Society","volume":"10 1","pages":""},"PeriodicalIF":8.5,"publicationDate":"2022-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43917079","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: 3

Towards a political economy of technical systems: The case of Google 走向技术系统的政治经济学:b谷歌的案例

IF 8.5 1区社会学

Big Data & Society Pub Date : 2022-07-01 DOI: 10.1177/20539517221135162

Bernhard Rieder

引用次数: 6

Neither opaque nor transparent: A transdisciplinary methodology to investigate datafication at the EU borders 既不不透明也不透明：调查欧盟边境数据化的跨学科方法

IF 8.5 1区社会学

Big Data & Society Pub Date : 2022-07-01 DOI: 10.1177/20539517221124586

Ana Valdivia, Claudia Aradau, Tobias Blanke, S. Perret

{"title":"Neither opaque nor transparent: A transdisciplinary methodology to investigate datafication at the EU borders","authors":"Ana Valdivia, Claudia Aradau, Tobias Blanke, S. Perret","doi":"10.1177/20539517221124586","DOIUrl":"https://doi.org/10.1177/20539517221124586","url":null,"abstract":"In 2020, the European Union announced the award of the contract for the biometric part of the new database for border control, the Entry Exit System, to two companies: IDEMIA and Sopra Steria. Both companies had been previously involved in the development of databases for border and migration management. While there has been a growing amount of publicly available documents that show what kind of technologies are being implemented, for how much money, and by whom, there has been limited engagement with digital methods in this field. Moreover, critical border and security scholarship has largely focused on qualitative and ethnographic methods. Building on a data feminist approach, we propose a transdisciplinary methodology that goes beyond binaries of qualitative/quantitative and opacity/transparency, examines power asymmetries and makes the labour of coding visible. Empirically, we build and analyse a dataset of the contracts awarded by two European Union agencies key to its border management policies – the European Agency for Large-Scale Information Systems (eu-LISA) and the European Border and Coast Guard Agency (Frontex). We supplement the digital analysis and visualisation of networks of companies with close reading of tender documents. In so doing, we show how a transdisciplinary methodology can be a device for making datafication ‘intelligible’ at the European Union borders.","PeriodicalId":47834,"journal":{"name":"Big Data & Society","volume":" ","pages":""},"PeriodicalIF":8.5,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41974968","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: 7

Taking a critical look at the critical turn in data science: From “data feminism” to transnational feminist data science 批判性地看待数据科学的批判性转向：从“数据女权主义”到跨国女权主义数据科学

IF 8.5 1区社会学

Big Data & Society Pub Date : 2022-07-01 DOI: 10.1177/20539517221112901

Z. Tacheva

引用次数: 3

Learning accountable governance: Challenges and perspectives for data-intensive health research networks 学习负责任的治理：数据密集型健康研究网络面临的挑战和前景

IF 8.5 1区社会学

Big Data & Society Pub Date : 2022-07-01 DOI: 10.1177/20539517221136078

Sam H A Muller, M. Mostert, J. V. van Delden, Thomas Schillemans, G. V. van Thiel

{"title":"Learning accountable governance: Challenges and perspectives for data-intensive health research networks","authors":"Sam H A Muller, M. Mostert, J. V. van Delden, Thomas Schillemans, G. V. van Thiel","doi":"10.1177/20539517221136078","DOIUrl":"https://doi.org/10.1177/20539517221136078","url":null,"abstract":"Current challenges to sustaining public support for health data research have directed attention to the governance of data-intensive health research networks. Accountability is hailed as an important element of trustworthy governance frameworks for data-intensive health research networks. Yet the extent to which adequate accountability regimes in data-intensive health research networks are currently realized is questionable. Current governance of data-intensive health research networks is dominated by the limitations of a drawing board approach. As a way forward, we propose a stronger focus on accountability as learning to achieve accountable governance. As an important step in that direction, we provide two pathways: (1) developing an integrated structure for decision-making and (2) establishing a dialogue in ongoing deliberative processes. Suitable places for learning accountability to thrive are dedicated governing bodies as well as specialized committees, panels or boards which bear and guide the development of governance in data-intensive health research networks. A continuous accountability process which comprises learning and interaction accommodates the diversity of expectations, responsibilities and tasks in data-intensive health research networks to achieve responsible and effective governance.","PeriodicalId":47834,"journal":{"name":"Big Data & Society","volume":" ","pages":""},"PeriodicalIF":8.5,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46307312","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

Toward a sociology of machine learning explainability: Human–machine interaction in deep neural network-based automated trading 走向机器学习的社会学解释：基于深度神经网络的自动交易中的人机交互

IF 8.5 1区社会学

Big Data & Society Pub Date : 2022-07-01 DOI: 10.1177/20539517221111361

C. Borch, Bo Hee Min

引用次数: 9

Social data governance: Towards a definition and model 社会数据治理:走向定义和模型

IF 8.5 1区社会学

Big Data & Society Pub Date : 2022-07-01 DOI: 10.1177/20539517221111352

Jun Liu

{"title":"Social data governance: Towards a definition and model","authors":"Jun Liu","doi":"10.1177/20539517221111352","DOIUrl":"https://doi.org/10.1177/20539517221111352","url":null,"abstract":"With the surge in the number of data and datafied governance initiatives, arrangements, and practices across the globe, understanding various types of such initiatives, arrangements, and their structural causes has become a daunting task for scholars, policy makers, and the public. This complexity additionally generates substantial difficulties in considering different data(fied) governances commensurable with each other. To advance the discussion, this study argues that existing scholarship is inclined to embrace an organization-centric perspective that primarily concerns factors and dynamics regarding data and datafication at the organizational level at the expense of macro-level social, political, and cultural factors of both data and governance. To explicate the macro, societal dimension of data governance, this study then suggests the term “social data governance” to bring forth the consideration that data governance not only reflects the society from which it emerges but also (re)produces the policies and practices of the society in question. Drawing on theories of political science and public management, a model of social data governance is proposed to elucidate the ideological and conceptual groundings of various modes of governance from a comparative perspective. This preliminary model, consisting of a two-dimensional continuum, state intervention and societal autonomy for the one, and national cultures for the other, accounts for variations in social data governance across societies as a complementary way of conceptualizing and categorizing data governance beyond the European standpoint. Finally, we conduct an extreme case study of governing digital contact-tracing techniques during the pandemic to exemplify the explanatory power of the proposed model of social data governance.","PeriodicalId":47834,"journal":{"name":"Big Data & Society","volume":" ","pages":""},"PeriodicalIF":8.5,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47421750","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: 9