Showing papers in "Big Data & Society in 2020"
TL;DR: It is shown that even ‘well optimized’ moderation systems could exacerbate, rather than relieve, many existing problems with content policy as enacted by platforms, as it is demonstrated these systems remain opaque, unaccountable and poorly understood.
Abstract: As government pressure on major technology companies builds, both firms and legislators are searching for technical solutions to difficult platform governance puzzles such as hate speech and misinf...
271 citations
TL;DR: Even if the authors could effectively automate content moderation, it is not clear that they should, because of the immense scale of the data, the relentlessness of the violations, and the need for human judgments without wanting humans to have to make them.
Abstract: AI seems like the perfect response to the growing challenges of content moderation on social media platforms: the immense scale of the data, the relentlessness of the violations, and the need for h...
137 citations
TL;DR: In late March of 2020, a new hashtag, #FilmYourHospital, made its first appearance on social media as discussed by the authors, which encouraged people to visit local hospitals to take pictures and videos of empty hospi...
Abstract: In late March of 2020, a new hashtag, #FilmYourHospital, made its first appearance on social media. The hashtag encouraged people to visit local hospitals to take pictures and videos of empty hospi...
125 citations
TL;DR: In this article, the authors examine four models of data governance emerging in the current platform society, while major attention is currently given to the dominant model of corporate platforms collecting and ec...
Abstract: The article examines four models of data governance emerging in the current platform society. While major attention is currently given to the dominant model of corporate platforms collecting and ec...
110 citations
TL;DR: In this paper, the authors argue that "ethics has powerful teeth, but these are barely being used in the ethics of AI today" and it is no wonder the Ethics of AI is then blamed for having no teeth.
Abstract: Ethics has powerful teeth, but these are barely being used in the ethics of AI today – it is no wonder the ethics of AI is then blamed for having no teeth. This article argues that ‘ethics’ in the ...
92 citations
TL;DR: This paper examines folk theories of algorithmic recommendations on Spotify to make visible the cultural specificities of data assemblages in the global South and argues that folk theories offer a productive way to broaden understanding of what agency means in relation to algorithms.
Abstract: This paper examines folk theories of algorithmic recommendations on Spotify in order to make visible the cultural specificities of data assemblages in the global South. The study was conducted in C...
73 citations
TL;DR: This article presents two critical cases on digital surveillance technologies implemented during the Covid-19 pandemic and delineates the privacy implications thereof and raises the question of whether there is a way to have expedited privacy assessments that could anticipate and help mitigate adverse privacy implications these may have on society.
Abstract: The global Covid-19 pandemic has resulted in social and economic disruption unprecedented in the modern era. Many countries have introduced severe measures to contain the virus, including travel re...
60 citations
TL;DR: Through the lens of micro-work, this paper prefigure the policy implications of a future in which data technologies do not replace human workforce but imply its marginalization and precariousness.
Abstract: This paper sheds light on the role of digital platform labour in the development of today’s artificial intelligence, predicated on data-intensive machine learning algorithms. Focus is on the specif...
59 citations
TL;DR: In this article, the authors explore how digital marketers think about marketing in the age of Big Data surveillance, automatic computational analyses, and algorithmic shaping of choice contexts, and explore the role of context in the decision process.
Abstract: In this article, we explore how digital marketers think about marketing in the age of Big Data surveillance, automatic computational analyses, and algorithmic shaping of choice contexts. Our starti...
55 citations
TL;DR: In this article, the authors describe how environments are increasingly becoming technologized sites of data production, from smart cities to smart forests, digital networks are analyzing and joining up environmental processes.
Abstract: Environments are increasingly becoming technologized sites of data production. From smart cities to smart forests, digital networks are analyzing and joining up environmental processes. This commen...
55 citations
TL;DR: There exists a limited window of opportunity to societally agree principles of practice regarding privacy and the use of data about emotions, according to a weak consensus among social stakeholders on the need for privacy.
Abstract: By the early 2020s, emotional artificial intelligence (emotional AI) will become increasingly present in everyday objects and practices such as assistants, cars, games, mobile phones, wearables, to...
TL;DR: In this article, the authors consider the data practices associated with COVID-19 responses and their implicatio- fatio- ing in new ways as responses to the COVID19 pandemic emerge.
Abstract: Home, digital technologies and data are intersecting in new ways as responses to the COVID-19 pandemic emerge. We consider the data practices associated with COVID-19 responses and their implicatio...
TL;DR: This work proposes two strategical pathways for the future use of mobile Big data for societal impact assessment, addressing access to both raw mobile Big Data as well as aggregated data products, and requires careful considerations of privacy issues, harmonized and transparent methodologies, and attention to the representativeness, reliability and continuity of data.
Abstract: The mobility restrictions related to COVID-19 pandemic have resulted in the biggest disruption to individual mobilities in modern times. The crisis is clearly spatial in nature, and examining the geographical aspect is important in understanding the broad implications of the pandemic. The avalanche of mobile Big Data makes it possible to study the spatial effects of the crisis with spatiotemporal detail at the national and global scales. However, the current crisis also highlights serious limitations in the readiness to take the advantage of mobile Big Data for social good, both within and beyond the interests of health sector. We propose two strategical pathways for the future use of mobile Big Data for societal impact assessment, addressing access to both raw mobile Big Data as well as aggregated data products. Both pathways require careful considerations of privacy issues, harmonized and transparent methodologies, and attention to the representativeness, reliability and continuity of data. The goal is to be better prepared to use mobile Big Data in future crises.
TL;DR: In the age of Big Data, companies and governments are increasingly using algorithms to inform hiring decisions, employee management, policing, credit scoring, insurance pricing, and many more aspec... as discussed by the authors.
Abstract: In the age of Big Data, companies and governments are increasingly using algorithms to inform hiring decisions, employee management, policing, credit scoring, insurance pricing, and many more aspec...
TL;DR: It is suggested that the economic relation that develops as a result of a digital gift offering not only masks the structural asymmetry between giver and gifted but also permits the creation of the new commodity of personal data, obfuscates its true value, and naturalizes its private appropriation.
Abstract: The harvesting of data about people, organizations, and things and their transformation into a form of capital is often described as a process of “accumulation by dispossession,” a pervasive loss o...
TL;DR: The use of algorithmic prediction in insurance is regarded as the beginning of a new era, because it promises to personalise insurance policies and premiums on the basis of individual behaviour and... as mentioned in this paper.
Abstract: The use of algorithmic prediction in insurance is regarded as the beginning of a new era, because it promises to personalise insurance policies and premiums on the basis of individual behaviour and...
TL;DR: This article explores, via the ‘value-chain’ approach, the evolution of digital governance research, and aligns it with current developments associated with data analytics, often referred to as ‘Big Data’.
Abstract: The emergence of Big Data has added a new aspect to conceptualizing the use of digital technologies in the delivery of public services and for realizing digital governance. This article explores, v...
TL;DR: In this paper, the authors draw on the sociology of expectations to examine the construction of expectations of ethical AI and consider the implications of these expectations for communication governance, and propose a set of expectations for ethical AI.
Abstract: This article draws on the sociology of expectations to examine the construction of expectations of ‘ethical AI’ and considers the implications of these expectations for communication governance. We...
TL;DR: The aim of this article is to assess the impact of Big Data technologies for insurance ratemaking, with a special focus on motor products, and how this conceptually contradicts the collective basis of insurance.
Abstract: The aim of this article is to assess the impact of Big Data technologies for insurance ratemaking, with a special focus on motor products.The first part shows how statistics and insurance mechanism...
TL;DR: In the last decade, much has been written about data politics as discussed by the authors, which has generated myriad concepts such as "surveillance capitalism", "gig economy", "quantified self", and "algorithmic governmentality".
Abstract: Much has been written about data politics in the last decade, which has generated myriad concepts such as ‘surveillance capitalism’, ‘gig economy’, ‘quantified self’, ‘algorithmic governmentality’,...
TL;DR: In the context of global uncertainty, numbers, indicators, categorizations, and comparisons are central to governmental and popular response to global uncertainty as discussed by the authors, which is particularly seductive in times of global uncertainties.
Abstract: Quantification is particularly seductive in times of global uncertainty. Not surprisingly, numbers, indicators, categorizations, and comparisons are central to governmental and popular response to ...
TL;DR: The authors argue that dominant norms of demographic data are insufficient for accounting for the complexities that characterize many lesbians, gay, bisexual, transgender, and queer (LGBTQ,... ) individuals.
Abstract: In this article, we argue that dominant norms of demographic data are insufficient for accounting for the complexities that characterize many lesbian, gay, bisexual, transgender, and queer (LGBTQ, ...
TL;DR: Based on six months of ethnographic fieldwork with a corporate data science team, how actors involved in a corporate project negotiated what work the system should do, how it should work, and how to assess whether it works is described.
Abstract: How are data science systems made to work? It may seem that whether a system works is a function of its technical design, but it is also accomplished through ongoing forms of discretionary work by ...
TL;DR: The prevalence of sarcastic and ironic language within social media posts is assessed and the need for future research studies to rethink their approach to data preparation and a more careful interpretation of sentiment analysis is highlighted.
Abstract: As the use of automated social media analysis tools surges, concerns over accuracy of analytics have increased. Some tentative evidence suggests that sarcasm alone could account for as much as a 50...
TL;DR: The FTC’s response to the Cambridge Analytica–Facebook scandal concludes that the scandal focuses attention on the need to explore the potential for embedding due process-type inquiries and protections within the enforcement actions by regulatory agencies such as the FTC.
Abstract: The Cambridge Analytica–Facebook scandal led to widespread concern over the methods deployed by Cambridge Analytica to target voters through psychographic profiling algorithms, built upon Facebook ...
TL;DR: These projects offer tutorials and tools for both dataviz practitioners and their publics to encourage critical thinking about how COVID-19 data is sourced and modeled—and to consider which subjects are not interpellated in those data sets, and why not.
Abstract: In response to the ubiquitous graphs and maps of COVID-19, artists, designers, data scientists, and public health officials are teaming up to create counter-plots and subaltern maps of the pandemic...
TL;DR: The Nordic countries aim to have a unique place within the European and global health data economy as discussed by the authors, and they have extensive nationally maintained and centralized health data records, as well as numerou...
Abstract: The Nordic countries aim to have a unique place within the European and global health data economy. They have extensive nationally maintained and centralized health data records, as well as numerou...
TL;DR: In this paper, the intervention attempts to engage critically with the Smittestopp app as a specifically Norwegian technofix, arguing that "culturally and politically, much of the Covid-19 response and the success of social di...
Abstract: The intervention attempts to engage critically with the Smittestopp app as a specifically Norwegian technofix. Culturally and politically, much of the Covid-19 response and the success of social di...
TL;DR: An adversarial public artificial intelligence system could enhance dynamic transparency, facilitate an alternative public articulation of social values using machine learning systems, and restore societal power to deliberate and determine social tradeoffs.
Abstract: In recent years, artificial intelligence has been deployed by online platforms to prevent the upload of allegedly illegal content or to remove unwarranted expressions. These systems are trained to ...
TL;DR: It is argued that the dynamics of prospecting are pervasive in, even characteristic of, data science and thus prospecting is a key driver of data science’s ongoing formation as a universal(izing) science.
Abstract: Data science is characterized by engaging heterogeneous data to tackle real world questions and problems. But data science has no data of its own and must seek it within real world domains. We call...