Outputs

Final conference

The final conference of the project “V-Data - The value of digital data: enhancing citizens’ awareness and voice about surveillance capitalism”, funded by Fondazione Cariplo, will take place 7-8 September 2023 at the University of Pavia (https://web-en.unipv.it/about-us/), Department of Political and Social Sciences, Italy. The event will comprise panel presentations and one keynote session hosting the internationally renowned scholar Stefania Milan (https://www.stefaniamilan.net/about-me/). A maximum of 25 papers will be selected for presentation. Preference will be given to speakers who plan to attend the conference in person, but a small number of remote presentations (no more than one per panel) may be included in the programme. The organising committee is exploring options to publish a special issue in a peer review journal associated with this call for contributions.

Call for contributions

DEADLINE EXTENDED: the deadline for sending your contributions has been extended until 12 May 2023! We invite researchers who are active in the field of surveillance capitalism, data justice, algorithmic studies, data ethics, Science and Technology Studies (STS), digital and computational methods, digital labour, media consumption and attitudes, critical consumer studies, platform studies (and many more) to submit proposals for paper presentations. Please submit an abstract (max. 300 words) to the event organisers by sending it via email to vdataresearch@gmail.com by 12 May 2023.

The conference theme is The value of digital data: advancing empirical research on surveillance capitalism. We encourage proposals from researchers with a variety of backgrounds, including academic research, activism, marketing research, journalists, and government social research. The following are examples of topics that are of particular interest:

• Public opinion and awareness about processes of data extraction, appropriation, and valorisation.
• Emic conceptions of data value: surveillance capitalism imaginaries across socio-economic groups, cultures, ethnicities, age cohorts, and geographies.
• Consumer practices of resistance, compliance and negotiation towards vocal assistants, targeted advertising, algorithmic systems of recommendation, AI devices (etc.).
• The nexus between Covid-19 pandemic and surveillance capitalism.
• Digital labour exploitation in surveillance capitalism (or surreptitious strategies of data appropriation).
• Working in the data factory (e.g., data cleaning, moderation, data entry, etc.).
• Innovative methods for studying surveillance capitalism.
• Digital and computational methods for studying surveillance capitalism (or how to surveille the surveillants).
• Survey methods for studying surveillance capitalism.
• Making surveillance capitalism visible through data visualisation (and other visual aids).
• Arts and surveillance capitalism imaginaries.
• Utopian and dystopian imaginaries of surveillance capitalism.
• Data activism and surveillance capitalism.
• Surveillance capitalism in the Global South.
• Big data and finance.
• Discrimination, inequalities and injustice related to processes of surveillance capitalism.
• How does the concept of data value change according to different stakeholders (consumers, marketers, brands, analysts, etc.) as well as market segments (e.g. automotive, food, fashion, etc.)?
• Big data consumer profiling and implication on identity and subjectivity.
• How digital affordances shape imaginaries of and practices related to surveillance capitalism.
• The platformization of consumer imagination and practices (or how platforms standardise consumer behaviours to make them more predictable and data-ready).
• Living with the hyper-nudging.

Conference venue

The conference will take place at the University of Pavia (https://web-en.unipv.it/about-us/), Department of Political and Social Sciences, Italy. Pavia is located 30 km south of Milan, to which is connected by trains every 30 minutes.

Important dates

Abstracts are due by 12 May 2023. These should include the author(s) name and position, a short title, and a clear indication of whether they plan to attend the conference in person or remotely. Acceptance notices will be given by 31 May 2023.

Fees and Accommodation

The event fee is 80 Euros. Fee includes: a) welcome package; b) daily lunches and coffee break; c) social dinner. The fee does not include accommodation. Anyway, for those interested the Department provides up to 15 single rooms at a convenient rate of euros 49 by the University dorms. Participants who are interested in staying at the University dorms must mention it in their submission. Priority in the allocation of rooms will be given to early-career scholars and according to submission date.

Organising committee

Alessandro Caliandro, Flavio Ceravolo, Guido Legnante, Samantha Conte, Antonella Orologiaio, Susanna Sassi (Università di Pavia), Emma Garavaglia (Politecnico di Milano), Alessandra Gaia (Università degli Studi di Milano-Bicocca), Dario Pizzul (Università Cattolica del Sacro Cuore).

Conference theme

The value of digital data: advancing empirical research on surveillance capitalism In 2022 the 67.1% of the World population is connected to the Internet (WeAreSocial, 2022), through a multiplicity of devices. Being constantly online, people generate enormous quantities of data on basically everything: shopping behaviours, political orientations, health status, etc. (boyd & Crawford, 2012). This huge amount of data is the ‘fuel’ of the contemporary digital economy (The Economist, 2017). The leaders of the digital economy are companies structured as platforms (e.g. Google, Apple, Amazon, Meta, etc.), which, on the one hand, intermediate relations among different groups of actors (consumers, advertisers, developers, etc.) (Gillespie, 2010), while, on the other hand, extract data from these very users, as well as their interactions (Srnicek, 2017). Platforms control over data goes well beyond the digital boundaries of the corporate platform, extending to the open Web (Helmond, 2015), mobile phones (Nieborg et al., 2020), households (Pridmore & Mols, 2020) and public institutions (Van Dijck et al., 2018). These massive and systematic processes of data extraction are at the base of the business model of digital platforms, which use data for: a) internal marketing purposes (Beer, 2018); b) selling them to third parties (for their own scopes of advertising and marketing) (van der Vlist & Helmond, 2021); c) developing new products and/or markets (vocal assistants, self-driving cars, etc.) (Hind et al., 2022)

Zuboff (2019) calls this emerging form of economic and socio-technical organisation surveillance capitalism. The term does not refer specifically to digital technologies of social monitoring, rather to an economic logic based on a unilateral extraction and accumulation of digital data from citizens, which are used to predict, personalise, customise and ultimately constrain their behaviours for business purposes (Mackenzie, 2019; Mühlhoff, 2020). In fact, Wood and Monahan (2019) frame this phenomenon as ‘platform surveillance’, meaning that it would not be possible outside the complex array of tracking devices, digital interfaces, algorithmic systems, and data analytics deployed (and owned) by corporate digital platforms. Despite the pervasiveness and currency of the phenomenon as well as its huge socio-economic impact (Beer, 2017; Arvidsson, 2019), empirical research in this field is still in its infancy (Ball & Webster 2020; Pizzul & Caliandro, 2022). Whereas platforms have a granular knowledge on social life, social actors seem to know very little about them - it is not easy to understand how they function, what kind of data they harvest, for which purpose etc; in other words, they are ‘opaque’ by design (Pasquale, 2015; Yeung, 2017). Curiously enough, such lack of empirical knowledge and data seems to reflect the asymmetries of power and information/knowledge typical of surveillance capitalism (Fuchs, 2021).

Currently, the scientific debate on datafication, dataveillance and data exploitation (Dijck, 2014) tend to focus mostly on privacy (Lutz et al., 2020). Questions of data protection are indubitably of great concern, since privacy is a human right connected to human dignity. Nevertheless, issues related to value appropriation are equally important, since digital data generated by citizens through their online activities produce a conspicuous economic value that is extracted from the social but not redistributed within the social.

In this regard, several key questions remain still unanswered, such as: do people perceive the economical value of their data? If so, to what extent? If not, why? What is really valuable for them? How does the concept of data value change according to different stakeholders (consumers, marketers, brands, analysts, etc.) as well as market segments (e.g. automotive, food, fashion, etc.)? How does the concept of data value change across different socio-economic groups? How does the concept of data value change across different cultures and geographies (West vs East, North vs South)? How do people protect their data in everyday life? Do they develop practices of resistance individually or collectively? Why do people give up their data? For which economical bargain? How do platforms themselves shape forms of resistance, negotiation, and compliance towards surveillance capitalism? Which (new) forms of inequality and discrimination are favoured by surveillance capitalism? Can citizens participate in a more open and transparent way in the processes of management and valorisation of their own digital data?

Exploring more closely citizens’ understanding of and awareness about the processes of value creation that are fuelled by their data, their cultural imaginaries (Bucher, 2017; Lyon, 2018; Sörum & Fuentes 2022) and everyday life practices of resistance, negotiation and compliance (Velkova & Kaun, 2021; Ruckenstein & Granroth, 2020) might orient the development of a much needed participated and positive critique to surveillance capitalism, stemming from an increased public awareness (Hong, 2017; Hinz et al., 2018).

Building on the understanding of these challenges, the present Special Issue seeks for contributors (from a multiplicity of disciplines and backgrounds) aiming to advance the state of the art of empirical research on surveillance capitalism, and, ultimately, increase the visibility, comprehension and accountability of the processes and logics of data extraction, appropriation and valorisation.

####### References Arvidsson, A (2019). Changemakers: The Industrious Future of the Digital Economy. Cambridge: Polity Press.

• Ball, K., & Webster, W. (2020). Big Data and surveillance: Hype, commercial logics and new intimate spheres. Big Data & Society, 7(1), 2053951720925853.
• Beer, D. (2017). The social power of algorithms. Information, Communication & Society, 20(1), 1-13.
• Beer, D. (2018). Envisioning the power of data analytics. Information, Communication & Society, 21(3), 465-479.
• Boyd, D., & Crawford, K. (2012). Critical questions for big data: Provocations for a cultural, technological, and scholarly phenomenon. Information, communication & society, 15(5), 662-679.
• Bucher, T. (2017). The algorithmic imaginary: Exploring the ordinary affects of Facebook algorithms. Information, Communication & Society, 20(1), 30-44.
• Fuchs, C. (2021). History and Class Consciousness 2.0: Georg Lukács in the age of digital capitalism and big data. Information, Communication & Society, 24(15), 2258-2276.
• Gillespie, T. (2010). The politics of ‘platforms’. New Media & Society, 12(3), 347-364.
• Helmond, A. (2015). The platformization of the web: Making web data platform ready. Social Media+ Society, 1(2), 2056305115603080.
• Hind, S., Kanderske, M., & van der Vlist, F. (2022). Making the Car “Platform Ready”: How Big Tech Is Driving the Platformization of Automobility. Social Media+ Society, 8(2), 20563051221098697.
• Hintz, A., Dencik, L. and Wahl-Jorgensen, K. (2018). Digital citizenship in a datafied society. Hoboken: John Wiley & Sons.
• Hong, S. (2017). Criticising Surveillance and Surveillance Critique: Why privacy and humanism are necessary but insufficient. Surveillance & Society, 15(2), 187-203.
• Lutz, C., Hoffmann, C. P., & Ranzini, G. (2020). Data capitalism and the user: An exploration of privacy cynicism in Germany. New Media & Society, 22(7), 1168-1187.
• Lyon, D. (2018). The culture of surveillance: Watching as a way of life. John Wiley & Sons.
• Mackenzie, A. (2019). From API to AI: platforms and their opacities. Information, Communication & Society, 22(13), 1989-2006.
• Milan, S., & Treré, E. (2019). Big data from the South (s): Beyond data universalism. Television & New Media, 20(4), 319-335.
• Mühlhoff, R. (2020). Human-aided artificial intelligence: Or, how to run large computations in human brains? Toward a media sociology of machine learning. New Media & Society, 22(10), 1868-1884.
• Nieborg, D. B., Young, C. J., & Joseph, D. (2020). App imperialism: The political economy of the Canadian app store. Social Media+ Society, 6(2), 2056305120933293.
• Pasquale, F. (2015). The black box society. Harvard University Press.
• Pizzul, D., & Caliandro, A. (2022). A systematic literature review on surveillance capitalism. Proceedings of The 9th biennial Surveillance & Society conference of the Surveillance Studies Network (SSN), Erasmus University Rotterdam on 1-3 June 2022 in Rotterdam, The Netherlands. https://www.eur.nl/en/eshcc/media/2022-05-timetable-abstractsdocx.
• Pridmore, J., & Mols, A. (2020). Personal choices and situated data: Privacy negotiations and the acceptance of household Intelligent Personal Assistants. Big Data & Society, 7(1), 2053951719891748.
• Sörum, N., & Fuentes, C. (2022). How sociotechnical imaginaries shape consumers’ experiences of and responses to commercial data collection practices. Consumption Markets & Culture, 1-23.
• Srnicek, N. (2017). Platform capitalism. Cambridge: Polity Press
• The Economist (2017) The world’s most valuable resource is no longer oil, but data. The Economist, 6 May. Available at: https://www.economist.com/leaders/2017/05/06/the-worlds-most-valuable-resource-is-no-longer-oil-but-data.
• Turow, J., McGuigan, L., & Maris, E. R. (2015). Making data mining a natural part of life: Physical retailing, customer surveillance and the 21st century social imaginary. European Journal of Cultural Studies, 18(4-5), 464-478.
• Van Dijck, J. (2014). Datafication, dataism and dataveillance: Big Data between scientific paradigm and ideology. Surveillance & society, 12(2), 197-208.
• Van Dijck, J., Poell, T., & De Waal, M. (2018). The platform society: Public values in a connective world. Oxford: Oxford University Press.
• Van der Vlist, F. N., & Helmond, A. (2021). How partners mediate platform power: Mapping business and data partnerships in the social media ecosystem. Big Data & Society, 8(1), 20539517211025061.
• Velkova, J., & Kaun, A. (2021). Algorithmic resistance: Media practices and the politics of repair. Information, Communication & Society, 24(4), 523-540.
• Wood, D. M., & Monahan, T. (2019). Platform surveillance. Surveillance & Society, 17(1/2), 1-6
• Yeung, K. (2017). ‘Hypernudge’: Big Data as a mode of regulation by design. Information, Communication & Society, 20(1), 118-136.
• Yeung, K. (2017). ‘Hypernudge’: Big Data as a mode of regulation by design. Information, Communication & Society, 20(1), 118-136.
• Zuboff, S. (2019). The age of surveillance capitalism: The fight for a human future at the new frontier of power. London: Profile Books.

Da qui è possibile accedere a due interessanti documenti, pensati per docenti e studenti, utili per saperne di più sulle leggi italiane che tutelano privacy e reputazione online.

Privacy per educatori

Una risorsa per insegnanti ed educatori che vogliano saperne di più sulle basi giuridiche della gestione della privacy e dei dati online, così da supportare le più giovani e i più giovani nell’utilizzo degli strumenti digitali.

Privacy per studenti

Una risorsa che aiuta le più giovani e i più giovani a comprendere le fondamenta ed il funzionamento delle leggi che proteggono la nostra privacy e reputazione online.

Hereby a useful directory of Initiatives and Research Centres working on several issues and topics related to surveillance capitalism (such as dataveillance, data activism, data ethics, data privacy & transparency, platform surveillance, etc.)

Open the spreadsheet and contact us if you want to contribute to the list.

Hereby the slides that we presented at the 2022 Surveillance & Society Rotterdam Conference. Each set of slides is accompanied by the related abstract.

A systematic literature review of surveillance capitalism towards a research agenda

Although surveillance capitalism - as intended by Shoshana Zuboff - is an emerging topic, it already attracted the attention of many scholars from different fields within social sciences. Therefore, in this contribution we propose a systematic literature review of the topic of surveillance capitalism. Specifically, we developed a systematic literature review on a pool of 161 academic articles automatically extracted (through a Python script) from ad hoc scientific sources (e.g., Scopus), which we processed with computational techniques of text analysis (e.g., co-word analysis, topic modelling, TF-IDF). Also, a close reading of a sample of 30 articles was conducted. Results show that the topic of surveillance capitalism is composed by six main sub-topics: marketing & social control, big data & datafication, platforms & platformization, data privacy & protection, culture of surveillance, AI. We argue that all these key sub-topics need to be addressed attentively (or at least taken into consideration) when dealing with academic research and/or writing on surveillance capitalism, also paying attention on how each dimension inform and co-construct each other.

Mapping the culture of surveillance capitalism on Twitter

Although surveillance capitalism is already well-established in advanced economies, we can argue that the current Covid-19 emergence has probably accelerate the diffusion of surveillance capitalism logics and infrastructures (e.g., platformization of higher education). Despite the pervasiveness and currency of this phenomenon, we still know very little about how the general public perceives and frames it. In particular, there is a shortage of empirical research on citizens’ opinions towards surveillance capitalism as well as their level of awareness about the processes of data exploitation and value extraction carried out by corporate platforms on the very data users produce through their everyday digital practices. To address this research gap, we developed an exploration (based on digital methods) on dataset of 302k Italian tweets (collected by following ad hoc keywords, such as ‘surveillance + Facebook’, ‘surveillance + iPhone’, etc). We analyzed this dataset combining computational and qualitative techniques – network analysis, topic modelling, ethnographic content analysis. Our preliminary results show that, on a general level, Twitter users seem unable to distinguish between processes of surveillance upon citizens and consumers (which they consider basically the same thing). Anyhow, on a micro level, specific communities of users tend to develop different narratives on surveillance capitalism, imagining different ‘models’ of it (such as, dystopian surveillance, benevolent surveillance, conspiracy surveillance, entertainment surveillance).

Algorithmic countersurveillance Immuni on Reddit

This research proposes a reflection on the implications of dataveillance (based on algorithms) and practices of countersurveillance in the healthcare field. Countersurveillance is the practice of making surveillance activities of institutions difficult or implementing technologies to evade surveillance altogether. Countersurveillance achieves its goal by subverting various components of the surveillance process and it has many applications. It can be used to protect privacy, civil liberties, and against abuses of surveillance. Additionally, it may be employed to push surveillance systems beyond their breaking point and in doing so it identifies potential vulnerabilities and points of error. Many countersurveillance techniques use human methods rather than electronic; these activities might include ‘evasion’ (e.g., avoiding risky locations, being discreet or using code words), ‘being situation-aware’; ‘hiding in secure locations’; and ‘concealing one’s identity’. Through this proposal we want to explore resistance practices and imaginaries applied to algorithmic surveillance in the health domain. Specifically, we explore the debate on the Immuni App on Reddit.