ACCEPTED OPEN PANELS–Big Data

3. AI through an education perspective: concerns, potentials, and trade-offs

Rodrigo Barbosa e Silva, Stanford University; Ana Carolina Goes Machado, Stanford University

Educators, policymakers, and civil society have attempted to address the complex phenomena behind the continuous advancement of artificial intelligence. Several educational systems currently use AI to promote personalization, adapt content to different learning styles, and to understand student characteristics. These AI applications have raised ethical concerns, such as data protection, fairness, and equity. Should we allow data processing on learner behavior, history, and actions? What biases does AI mirror, and how do these biases affect students?

We are interested in ways that Science, Technology, and Society practitioners can interpret and act on AI developments for  improving student educational achievement when considering the risks and social concerns. Paraphrasing Paulo Freire, how can we have an educational system as a practice of freedom, when taking into account the latest (ab)uses of AI in education and society at large?

National strategic plans, universities, social movements, and organizations around the world have begun to create specific programs to take steps towards an understanding of AI as a matter of public concern. Historically, STS scholars have warned of potential benefits, trade-offs, and risks of technologies. We invite submissions on AI as it applies to education and policy including but not limited to:

Emerging issues

Data fairness and equity

Ethical aspects of commercial platforms in Education

Power relations, control, and agency

International trends: how different countries address freedom, control, classification, and critical thinking

Public policy on AI and Education

Engagement in civil society and policymaking at large amidst the dynamics of “alternative facts” in AI?

Contact: rodrigo7@stanford.edu

Keywords: education, artificial intelligence, public policy, critical pedagogy

Categories: Big Data

Information, Computing and Media Technology

Governance and Public Policy

8. Approaching the Digital Anthropocene

James Maguire, IT University Copenhagen; Rachel Douglas Jones, IT University Copenhagen; Astrid Andersen, Aalborg University

It is becoming increasingly more difficult to address digital questions without considering how they overlap and intersect with environmental concerns. We make the digital from the natural world, crafting metals and plastics into sleek handheld forms, while powering our data through vast quantities of energy consumption. We observe and make our understandings of environments through digital devices, spreadsheet accounting and carbon calculations. We have brought epochal shifts into being through rhetoric, disciplines, and geological measures. The Anthropocene is a digitally mediated and produced time.

Yet the ‘we’ of these statements is an unevenly distributed set of actors, and the politics of producing (knowledge of) the Digital Anthropocene are pressing. From planetary observation and oceanic measurement to marine tailings, the appropriation of precious metals and labors of pollution, anthropogenic knowledge is deeply woven in with computation, tools, media and devices. It is also constituted through histories of colonialism, political economy, and ways of being in and knowing the world.

This panel invites scholars with an interest in the manifold interfaces and overlaps between and within the environmental and the digital. Our aspiration is to begin a conversation on how researchers can approach what we are provocatively calling the Digital Anthropocene. We invite papers from those who are already conducting research at this interface, as well as those who are interested in contributing to the generation of an ambitious and newly emerging field within STS.

Contact: jmag@itu.dk

Keywords: digitalization, anthropocene, temporality, politics, environmental knowledge making

Categories: Environmental/Multispecies Studies

Big Data

Information, Computing and Media Technology

15. Broken and livable futures with automated decision-making

Tuukka Lehtiniemi, University of Helsinki; Minna Ruckenstein, University of Helsinki

The growing use of automated decision-making (ADM) makes automation increasingly relevant to the lived experience of people, with examples ranging from credit scoring and predictive policing to self-care within health services and automated content moderation. A technological imaginary favours the strengthening of existing infrastructures with ADM: it is characterized by political-economic aims of efficiency and optimization. A critical imaginary, in contrast, questions technological developments: recent research details problematic aspects of ADM systems, for instance, their connections to discrimination and inequalities, and their lack of transparency and accountability.

Our panel concentrates on re-articulating ways in which ADM systems are currently described and debated. To make possible a creative move beyond the dominant logics of automation driven by the technological imaginary, scholars themselves should bypass their critical imaginary and explore alternative conceptualizations and frameworks. Therefore, we seek to open a practical and analytical space for the re-articulation of ADM systems and their effects. We expect papers to demonstrate that new socio-technical directions are possible, bringing into being ADM futures that we would rather live in. Various theoretical or methodological approaches might be employed, including broken world thinking to highlight breakdown, dissolution and change as starting points in discussing ADM (Jackson, 2014); situated interventions that experimentally engage with ADM practices to produce new normative directions (Zuiderent-Jerak, 2015); or feminist approaches offering alternative ways to care for socio-technical arrangements (Puig de la Bellacasa, 2012). Together, the papers can reinvigorate research on ADM systems and identify harms and benefits that are currently not addressed.

Contact: tuukka.lehtiniemi@iki.fi

Keywords: Automation, decision-making systems, technological imaginary, critical imaginary, socio-technical futures

Categories: Information, Computing and Media Technology

Big Data

16. Building digital bioethics: Transformations in theory and applied practice

Mustafa Ibraheem Hussain, University of California Irvine; Victoria Neumann, Lancaster University; Stephen Molldrem, University of California, Irvine

Technologies that facilitate the collection and use of electronic health data have increasingly become the tools used to diagnose conditions and administer services. Digital transformations are at the centre of scholarly critiques of power imbalances in healthcare, partly because developments in digital biomedicine have been accompanied by data misuse scandals and genuinely new bioethical problems. Just as scientific advancements and concomitant human rights violations in clinical research and practice led to the development of bioethics in the 20th century, the turn toward the digital in healthcare is giving rise to new transdisciplinary trends in the theory and practice of contemporary bioethics (e.g. Klugman et al., 2018).

In this open panel, we aspire to deepen conversations between theoretical and applied approaches in bioethics, and call for contributions aimed at “building digital bioethics.” Inspired by the work of critical bioethicists (see “bioethics of the oppressed” by Guta et al., 2018 and Benjamin, 2016), we solicit contributions in keeping with the STS commitment to centering  subaltern perspectives, and to bioethics’ grounding principles of respect for persons, beneficence, and justice (Belmont Report, 1976). How can emancipation and self-determination become possible in an area in which individual control is often reduced to check-box “consent”? Who is the digital bioethicist? What are digital bioethics? We welcome submissions including, but not limited to, the following:

Digital bioethical imaginaries and controversies

Feminist, decolonial, anti-racist, and queer positions in bioethics

The ethics of consent and data (re-use)

Governing digital biomedicine

Counter-hegemonic practices

Organizational transformation

The assetization of health data

Contact: mihussai@uci.edu

Keywords: Bioethics, Data, Governance, Health, Biomedicine

Categories: Medicine and Healthcare

Big Data

Governance and Public Policy

17. Building Digital Public Sector

Marta Choroszewicz, University of Eastern Finland; Marja Alastalo, University of Eastern Finland

Public institutions across Europe and beyond are investing effort and money to intensify data collection and the use of data-analytics across various welfare domains for reasons of efficiency and cost-effectiveness. New data-driven technologies transform public services in many ways and at many levels, from transactional situations to management and knowledge production practices. Public sector has countless experiments under way with its business partners to forge and deploy data processing infrastructures and technologies to enable data-driven decision and policy making. The shift toward automated decision-making challenges the traditional relationship between the state and its citizens, and possibly leads to a variety of tensions and inequalities. Nonetheless, we still know little as far as how new data-driven future of public services aligns with the mission of public sector based on democratic values and provision of social security to citizens.

This panel will focus on how data-analytics and AI systems are changing the existing welfare institutions and reshaping of welfare provision. The panel welcomes empirical, theoretical and methodological papers, though we are particularly keen to see ethnographic contributions that include, but are not limited to: 1) particular examples of use and implementation of data-analytics in public sector; 2) the activities and reasoning related to translation of social practices, public services and existing infrastructures into a data-driven mode, 3) collaboration between different groups of professionals across sectors involved in creating of data-drivenness, and 4) the power of data-analytics to allocate resources and thus enable or hinder citizens’ social participation.

Contact: marta.choroszewicz@uef.fi

Keywords: digital public sector, data-analytics, data-driven technologies, automated decision-making, inequalities

Categories: Governance and Public Policy

Big Data

35. Decentring datacentres: their politics, energy, waste and epistemics

Stefan Laser, Ruhr University Bochum; Estrid Sørensen, Ruhr University Bochum; Laura Kocksch, Ruhr University Bochum

Data centres have gained attention in STS for their politics of territoriality and geographic location (Vonderau 2016 & 2019, Maguire & Winthereik 2019). We seek to extend the focus to the material configurations of data centres by discussing them as situated spaces of high resource consumption and excessive waste production, of contested politics and of knowledge production.

Half of the information and communication industries’ greenhouse gas emissions comes from data centres (Belkhir/Elmeligi); roughly 1,5% of global greenhouse gas emissions. Millions of gallons of water are used to keep data cool (Hogan 2015). Energy Humanities (Szeman &Boyer 2017) and Discard Studies (Lepawsky 2018) urge us to reflect on how such excesses are formed and maintained, by which actors and through which practices.

Data centres are important actors in configuring common resources: electricity, water, heat and knowledge. Nonetheless, they are hidden away and hardly accessible (Hogan &Shepard 2015). How are the politics of data centres made visible, and how can data centres be turned into a matter of democratic debate and regulation? This question is relevant both on state and industry level, as it is in workplaces where practices are increasingly shaped by the configurations of data centres.

Even though knowledge production of both corporate ‘data scientists’ as well as university scientists and researchers increasingly depend on data centres for both storage and data processing, little literature exists on the epistemic effects of data centre configurations.

We invite papers submissions addressing the political, ecological and epistemic entanglements of data centres.

Contact: laura.kocksch@rub.de

Keywords: data centres, data practices, ecologies, waste, infrastructure

Categories: Energy

Big Data

Governance and Public Policy

39. Digital Phenotyping –  Unpacking Intelligent Machines For Deep Medicine And A New Public Health

Lukas Engelmann, University of Edinburgh; Ger Wackers, UiT The Arctic University of Norway

Digital phenotyping has become a popular practice in the world of data-driven health research. It has developed into a tool to syphon structured health data from online populations. As a practice, it is hailed to refine the classification and understanding of psychiatric, infectious and chronic conditions. A new phenomics is developed to match the genomics of previous years and close the gap between the genotype and phenotype. In the widest sense, digital phenotyping has become identified with a medical knowledge production entirely based on the analysis of digital borne data, providing new ways of knowing disease with more granular insights from digital data. Digital phenotyping schizophrenia, dementia, the flu or Parkinson’s disease is supposed to overcome vague and unstructured clinical observations and to offer new, highly standardised pathways towards a complete symptomatology. Conceptually, the digital phenotype has been shaped with reference to Dawkins’ elaborations on the ‘extended phenotype’ while its practices are strongly aligned with the ‘deep medicine’ movement, which seeks to build and to exploit vast datasets of different kinds to achieve novel insight into drivers of disease.

Underlying this new conceptual tool are a series of imaginaries that we like to unpack in this panel. We invite contributions that engage the impact of digital phenotyping in mental health research, that reconstruct historical genealogies of such infrastructures and which engage the phantasies of total insight, vast understanding and deep comprehension build into this budding tool at the bleeding edge of digital medical research.

Contact: ger.wackers@uit.no

Keywords: Digital phenotyping, deep medicine, public health, digital epidemiology

Categories: Medicine and Healthcare

Genetics, Genomics, Biotechnology

Big Data

65. Filling the Gaps Between Observations with Data: Nature, Models and Human Agency

Catharina Landström, Chalmers University of Technology; Dick Kasperowski, University of Gothenburg

STS case studies have shown how observations and measurements of phenomena in nature are transformed into scientific data in different practices. In light of the rapid digitalisation and a growing interest in ‘big data’ it is important to continue investigating the ways in which environmental science produce scientific data for use in research and policy. This panel invites papers that discuss how environmental data generation and processing is mediated by models.

There is a wide range of data collection practices in environmental science, ranging from remote sensing, to scientific field work, to citizen science observations. Data generation can also involve new mobile applications, or DIY counter monitoring, or computer model simulations. Papers analysing the many ways in which environmental data is collected by humans and non-humans are welcome.

Regardless of the starting point, data must be processed to become useable in scientific analysis. As the increasing digitalisation produces a deluge of data to order in scientific classification schemes, the human ability to discern and judge is delegated to models. Modelling of environmental data also enacts human agency when filling the gaps between empirical measurements or observations. Data processing algorithms perform imagined epistemic subjects. The consequences of the merging of numbers representing nature, machine calculations and scientific skills in the generation of environmental data are important issues for STS investigation and we invite presentations of ongoing research into the relations between nature, models and human agency.

Contact: catharina.landstrom@chalmers.se

Keywords: big data, environment, computer modelling

Categories: Big Data

Knowledge, Theory and Method

Environmental/Multispecies Studies

66. Flows and overflows of personal health data

Mary Ebeling, Drexel University; Tamar Sharon, iHub, Radboud University Nijmegen; Niccolò Tempini, University of Exeter, Egenis

With the explosion of digital technologies that generate massive sets of personal data, from internet networks and big data infrastructures, to wearable devices and sensors, many actors see the analytical potentials of these collections for healthcare and medical research and knowledge production. These data circulate across domains, amongst different types of actors – e.g. academic scientists, corporations, non-profit organizations, individual data subjects, and patient groups – and according to different logics of exchange – e.g. donation, sharing, commodification, and appropriation (Ebeling 2016; Sharon 2018; Tempini and Teira 2019). The promises for the increased circulation of health data are many, including: greater patient empowerment, better population health, and improved interoperability ensuring continuity of care, as well as less health-specific outcomes such as national economic growth. But so are its potential harms, including risks (e.g. privacy breaches), epistemic uncertainties (e.g. questions of data quality and algorithmic transparency), disruptions to existing research standards and protocols (e.g. the conduct of clinical trials), as well as wider concerns regarding the generation of profit based on donated or otherwise publicly available personal health data, and the emergence of new power asymmetries and conflicts of interest between data subjects, data users, and new data intermediaries.

This track invites papers that explore the complex dynamics of the increasing circulation of health data. In particular we seek analyses asking not only how benefits are construed and by whom, and what harms may result, but also what frameworks currently exist for governing flows and what alternative frameworks might be imagined.

Contact: n.tempini@exeter.ac.uk

Keywords: Personal health data, circulation, value, data practices, governance

Categories: Big Data

Medicine and Healthcare

Economics, Markets, Value/Valuation

69. Global Imaginaries of Precision Science: Diversity, Inclusion and Justice

Sandra Soo-Jin Lee, Columbia University; Janet K. Shim, University Of California, San Francisco

Precision science targets individual and group differences as a path towards greater accuracy, efficiency and efficacy by using techniques of big data analytics, algorithmic prediction, and large-scale data sharing and applying them in a growing number of domains.  This panel focuses on the sociotechnical imaginaries of the promise of precision that fuel the increasingly global infrastructure for collecting personal data and biospecimens in many different domains. For example, the promise of precision has been motivated by and operationalized in the quest for greater inclusion and diversity of historically underrepresented groups in precision medicine research as evidenced in initiatives such as the US All of Us Research Program and the Global Alliance for Genomics and Health. Extending beyond biomedicine, these processes are being taken up in studies of genetic associations of socio-behavioral traits such as criminality and educational attainment that are leading to new fields of “precision forensics” and “precision education.” This panel calls for papers that interrogate the constituent concepts, practices, and discourses of precision science – its actors, institutions, networks, values and cultures – and its applications and uptake in a wide range of domains, including medicine, criminal justice, and social policy. We are interested in examining forms of knowledge and practices in precision science, their impacts on emerging subjectivities and data-driven publics, and the development of frameworks on justice, ethics and inclusion. We aim to use this panel to build a global collaboratory of scholars who will use this opportunity to share their work and build future collaborations.

Contact: sandra.lee@columbia.edu

Keywords: Precision medicine, sociogenomics, ethics and justice, knowledge production, Diversity

Categories: Big Data

Genetics, Genomics, Biotechnology

Race/Racialization/Indigeneity

74. Hacker Cultures: Understanding the actors behind our software

Paula Bialski, Leuphana University Luneburg; Mace Ojala, IT University of Copenhagen

The spiraling changes around how we experience our social and physical world have stemmed from the massive amount of digital technologies that are ubiquitously used in all parts of our society today. Big data, offshore data centres, universities, grocery stores run by software companies of all shapes and sizes, are often hard to grasp and black-boxed, deeming the user unable to participate. These infrastructures are constructed by a wide range of “hackers” – a slippery term generally applied to anybody building or maintaining software or hardware. They (or we?) go by a wide range of labels such as programmers, developers (or “devs”), designers, analysts, data scientists, coders, sysadmins, dev/ops, or sometimes simply tech. They build, break, fix, and secure our navigation system, our banking database, our doctor’s healthcare software, our games, our phones, our word processors, our fridges and toasters. They work in massive software corporations, in teeny startups, or in something in-between. They volunteer for, or are employed by, free and open-source projects. While their work is ubiquitous, hackers can hold a lot of power but also none at all – as the software they are building oftentimes overpowers their capabilities of understanding and managing it. Inspired by research around hacker cultures, such as Chris Kelty’s work among free software communities, Biella Coleman’s work on the Debian communities (2012) and the politically-motivated hacker collective Anonymous (2014), or Stuart Geiger’s embedded ethnography in Wikipedia (2017 with Halfaker) – this panel shines a light on the people who build our opaque and oftentimes confusing technical worlds. In doing so, we wish to challenge the role of the STS scholar in describing the powers and agencies, and the practices and struggles of hacker cultures – a challenge that, in our increasingly complex, commodified technical worlds might never be fulfilled.

Contact: bialski@leuphana.de

Keywords: software, hackers, culture, agency, data collection, ethnography, computing

Categories: Information, Computing and Media Technology

Big Data

Engineering and Infrastructure

79. Holding It Together?  Data And Disasters

Louise Elstow, Lancaster University; Ben Epstein, UCL

We propose to convene a panel on the theme of data in disasters which includes the audience as active participants on a moving stage, engaging them in moving data collection. In this time of seemingly constant crisis and increasing numbers of disasters, people and things move around. Data gathering is often only a snapshot in time and location, accurate only in specific situated instances; an attempt to pin down a moveable feast.  A myriad of types of data is collected and deployed by different actors seeking to find their new normal, respond to the needs of the community, demonstrate that the incident is under control.  We’d like to explore some of the ways in which it is held together by the practices, politics and policies involved in data construction and use. 

Panel members might want to discuss topics such as: the performativity, commensur-ation/ability or [re]inscription of disaster research data, translation and interpretation of data into representations of disaster, and disaster data ontologies and epistemologies. We welcome presentations based on: the politics and ethics of data collection and management (e.g disaster data in a post GDPR, big data world), or how the quantitative and qualitative approaches to disaster data gathering might affect framings of these events.

This is important because researching the social life of data and how it lives in disasters, should move us towards reflecting on our own data choices.

We encourage panel members who will to incorporate ‘active’ data gathering in their presentations in unusual or engaging ways.

Contact: l.elstow@lancaster.ac.uk

Keywords: Disasters, data, crisis, performativity, movement

Categories: Science Communication/Public Engagement

Big Data

Knowledge, Theory and Method

83. Identification, Datafication, Citizenship

Richard Rottenburg, University of the Witwatersrand; Alena Thiel, Martin Luther University Halle-Wittenberg

The proliferation of (biometric) identification technologies across the globe – especially in Africa, South Asia and Latin America – is nested in profoundly new aspirations for the rationalization and even automation of political decision making in public-private governance. Building on interoperability-based data infrastructures, states and financial institutions, among many other organisations concerned with the surveillance of individual behaviour, subscribe to the idea that digital “data doubles” (Bouk 2017) circulate between previously disconnected registers, allowing thus the “datafication” (von Oertzen 2017) of new, previously unobserved areas of life, and thus ultimately the creation of new “human kinds” (Hacking 1995). The panel explores continuities and discontinuities of socio-technical configurations that have led to connecting recent innovations in identification technologies with the production of quantitative knowledge for decision making. While this happens in conventional state administrations and “global administrative apparatuses” (Eriksen 2012), the panel pays particular attention to the merging and blurring of these realms in largely privatized epistemic centres where tech giants radically transform quantitative data collection and the production of statistics through the development of learning algorithms. The by now classical analysis of statistical knowledge production as in “governance by numbers” (Rottenburg 2015) and the implications for “digital citizenship” (Isin and Ruppert 2015) needs to be revisited in the light this transformations. The panel seeks empirical contributions that examine how these developments play out in concrete settings in the Global South.

Contact: alena.thiel@ethnologie.uni-halle.de

Keywords: Biometrics, identification, quantification, digital citizenship

Categories: Governance and Public Policy

Information, Computing and Media Technology

Big Data

112. Moralizing the data economy

Thomas Beauvisage, Orange Labs; Mary Ebeling, Drexel University; Marion Fourcade, University of California, Berkeley Dept. of Sociology; Kevin Mellet, Orange Labs

The new economy of data operates digital traces and tracking tools at scale, combined with the use of big data and AI technologies. Data are turned into valuable assets and tradable products, and injected into market and organizational infrastructures and practices in various industries, such as marketing, health, finance or transportation.

The industrialization of data has raised a series of concerns about its legitimacy or its morality. Data practices are disputed from a wide variety of grounds: privacy concerns; the emergence of a surveillance society; discrimination and filter bubbles; consumer manipulation; rise of new monopolies. As a reaction to these critics, new regulations (such as the GDPR in Europe) are put in place, and the players of the data economy themselves have come to incorporate moral considerations and discourses in their practices. All these views on how data should or should not be used for business and market purposes draw the boundaries of a new moral economy of data.

This panel aims to bring together empirical or theoretical contributions that explore the various facets of the moral economy of data. We particularly – though not exclusively – welcome contributions on the following topics: protest movements and civil resistance to the emerging data economy; new regulatory regimes around personal data that are held by public administrations or by corporations; the rise of market intermediaries dedicated to the moralization of the data economy; changes inside organizations and justifications surrounding the economization of data.

Contact: kevin.mellet@orange.com

Keywords: data, privacy, assetization, economization, moral economy

Categories: Economics, Markets, Value/Valuation

Big Data

127. Online Campaigns and Digital Personhood in the Age of Datafication

Christian Ritter, Tallinn University; Rajesh Sharma, Senior Researcher, Institute of Computer Science, University of Tartu

This panel examines how influencers construct their identities on digital platforms. By posting selfies, memes, vlogs, emojis, and textual messages on Twitter, Instagram, Facebook, and YouTube, influencers create complex online personas. For instance, diaspora activists, gamers, lifestyle vloggers, gender activists, leaders of religious communities, minority representatives, and political populists engage in large-scale campaigns on platforms to grow their following. Such campaign strategies are increasingly based on comprehensive expertise in platform metrics and exploit data analytics. Drawing on recent STS scholarship on technologies of the self, new materialist approaches, and intersectionality theory, this panel reassesses the rise of datafication in contemporary society. In the wake of the Facebook-Cambridge Analytica data scandal, access to the APIs of popular platforms has been increasingly restricted for academic researchers, requiring new research methodologies.

The overall aim of the panel is to bring together STS scholars who explore the multiple entanglements of influencers with big data in their everyday lives. The panel thus invites papers assessing the datafication of online activities through the lenses of data ethnography or data analytics solutions, such as social network analysis and natural language processing (text analytics, sentiment analysis, topic modeling). Contributions to this panel could address the following questions: What strategies do influencers pursue for platform campaigns? How is agency distributed in the platform worlds of influencers? What understandings of algorithmic mediation do influencers cultivate? What epistemological practices do influencers develop to understand platform metrics?

Contact: christian.ritter@tlu.ee

Keywords: big data, campaign, identity, influencer, platform

Categories: Big Data

Information, Computing and Media Technology

Knowledge, Theory and Method

131. Other Indigenous “Knowledge Engineering” Systems: Designing and operating knowledge technologies at scale in emerging worlds

Yoehan Oh, Rensselaer Polytechnic Institute

Some scholars in digital humanities and critical internet and digital technologies studies have asked for bringing critical concerns about race, gender, postcoloniality, and other inequal power structures to their field (Nakamura 2013; Noble et al. 2016; McPherson 2013; Posner 2016; Risam 2018; Benjamin 2019). One way to address those concerns is illuminating technically-inventive subjectivities, by appreciating and thus empowering them through conceptualizations they deserve. STSers have conceptualized them and their artifacts as “Black vernacular technological creativity,” “techno-vernacular creativity,” (Fouché 2006; Gaskins 2019), “innovation from below” (Williams 2018), “ethnocomputing,” (Petrillo 1994; Tedre et-al. 2006; Eglash 1999), “postcolonial computing,” (Irani et-al. 2010; cf. Burrell 2012), and “black software” (McIlwain 2019); historians of computing have studied information architectures, hardware, and software in the Middle East, Latin America, East Asia, Midwestern U.S., and (post-)communist contexts (Bowker 1994; Medina 2011; Tinn 2018; Rankin 2018; Švelch 2018; Biagioli et-al. 2019). To further these conceptualizations, this panel will focus on less resourceful worlds’ captures of knowledge technologies, predominated by a few resourceful countries’ R&D communities like U.S., Canada, some Western Europe countries, China, and Japan: Knowledge discovery by data, Data engineering, Semantic technologies, and Search engines, etc (Collins 1987; Forsythe 1993). Questions to be addressed are: How indigenous, aboriginal, vernacular, decolonial, de-ColdWar, or less capitalistically/settler-colonially exploitative the knowledge engineering practices at scales by technical actors in the underrecognized/emerging worlds can be? Which speculative, experimental, or empirical cases can we dig into as the Indigenous “Knowledge engineering” Systems (Watson-Verran et al. 1995; Brereton et-al. 2015; Chamunorwa et-al. 2018)?

REFERENCES

* Acker, Amelia, and Joan Donovan. 2019. “Data craft: a theory/methods package for critical internet studies.” Information, Communication & Society 22(11): 1590-1609.

* Aouragh, Miriyam, and Paula Chakravartty. 2016. “Infrastructures of empire: towards a critical geopolitics of media and information studies.” Media, Culture & Society 38(4): 559-575.

* Benjamin, Ruha. 2019. Race after technology: Abolitionist tools for the new Jim Code. John Wiley & Sons.

* Biagioli, Mario, and Vincent Antonin Lépinay, eds. 2019. From Russia with Code: Programming Migrations in Post-Soviet Times. Durham, N.C.: Duke University Press.

* Bowker, Geoffrey C. 1994. Science on the Run: Information management and industrial geophysics at Schlumberger, 1920-1940. MIT press.

* Brereton, Margot, Paul Roe, Ronald Schroeter, and A. Lee Hong. 2015. “Indigenous knowledge technologies: Moving from knowledge capture to engagement, reciprocity and use.” In At the Intersection of Indigenous and Traditional Knowledge and Technology Design, edited by Nicola Bidwell and Heike Winschiers-Theophilus, 239-258. Informing Science.

* Burrell, Jenna. 2012. Invisible Users: Youth in the Internet cafés of urban Ghana. MIT Press.

* Chamunorwa, Michael Bosomefi, Heike Winschiers-Theophilus, and Tariq Zaman. 2018. “An Intermediary Database Node in the Namibian Communities Indigenous Knowledge Management System.” In Digitisation of Culture: Namibian and International Perspectives, edited by Dharm Singh Jat, Jürgen Sieck, Hippolyte N’Sung-Nza Muyingi, Heike Winschiers-Theophilus, Anicia Peters, and Shawulu Nggada, 99-117. Singapore: Springer,

* Collins, Harry M. 1987. “Expert systems and the science of knowledge.” In The social construction of technological systems: New directions in the sociology and history of technology, edited by Wiebe E. Bijker, Thomas P. Hughes, Trevor Pinch, 329-348. MIT Press.

* Ebner, Susanne. 2019. “Hierarchies of Knowledge: Usage of a Chinese Media App in Rural Tamil Nadu” presented at the 2019 Annual Meeting of the Society for Social Studies of Science, New Orleans, U.S.

* Eglash, Ron. 1999. African fractals: Modern computing and indigenous design. Rutgers University Press.

* Forsythe, Diana E. 1993. “Engineering knowledge: The construction of knowledge in artificial intelligence.” Social studies of science 23(3): 445-477.

* Fouché, Rayvon. 2006. “Say it loud, I’m black and I’m proud: African Americans, American artifactual culture, and black vernacular technological creativity.” American Quarterly 58(3): 639-661.

* Gaskins, Nettrice R. 2019. “Techno-Vernacular Creativity and Innovation across the African Diaspora and Global South.” In Captivating Technology: Race, Carceral Technoscience, and Liberatory Imagination in Everyday Life, edited by Ruha Benjamin, 252-274. Durham, N.C.: Duke University Press.

* Irani, Lilly, Janet Vertesi, Paul Dourish, Kavita Philip, and Rebecca E. Grinter. 2010. “Postcolonial computing: a lens on design and development.” In Proceedings of the SIGCHI conference on human factors in computing systems, ACM. 1311-1320.

* Kita, Chigusa, and Hyungsub Choi. 2016. “History of computing in East Asia.” IEEE Annals of the History of Computing 38(2): 8-10.

* McIlwain, Charlton. 2019. Black Software: The Internet and Racial Justice, from the AfroNet to Black Lives Matter. Oxford University Press, USA.

* McPherson, Tara. 2013. “US operating systems at mid-century: The intertwining of race and UNIX.” In Race after the Internet, edited by Lisa Nakamura and Peter Chow-White, 27-43. Routledge.

* Medina, Eden. 2011. Cybernetic revolutionaries: Technology and politics in Allende’s Chile. MIT Press.

* Nakamura, Lisa, and Peter Chow-White, eds. 2013. Race after the Internet. Routledge.

* Noble, Safiya Umoja. 2018. Algorithms of Oppression: How search engines reinforce racism. NYU Press.

* Noble, Safiya Umoja, and Brendesha M. Tynes. 2016. The intersectional internet: Race, sex, class, and culture online. Peter Lang International Academic Publishers.

* Petrillo, Anthony. 1994. “Ethnocomputers in Nigerian Computer Education.” Paper presented at the 31st Annual Conference of the Mathematical Association of Nigeria (March 1994).

* Philip, Kavita, Lilly Irani, and Paul Dourish. 2012. “Postcolonial computing: A tactical survey.” Science, Technology, & Human Values 37(1): 3-29.

* Posner, Miriam. 2016. “What’s Next: The Radical Unrealised Potential of Digital Humanities.” In Debates in the digital humanities 2016, edited by Matthew K. Gold and Lauren F. Klein, 32-41. University of Minnesota Press.

* Risam, Roopika. 2018. New Digital Worlds: Postcolonial Digital Humanities in Theory, Praxis, and Pedagogy. Evanston, IL: Northwestern University Press.

* Snow, Jackie. 2018. “We’re in a diversity crisis”: Cofounder of Black in AI on what’s poisoning algorithms in our lives.” MIT Technology Review (Feb 14, 2018).

* Stöckelová, Tereza, and Jaroslav Klepal. 2018. “Chinese Medicine on the Move into Central Europe: A Contribution to the Debate on Correlativity and Decentering STS.” East Asian Science, Technology and Society. 12(1): 57-79.

* Rankin, Joy Lisi. 2018. A People’s History of Computing in the United States. Harvard University Press.

* Stevens, Hallam. 2019. “Digital Infrastructure in the Chinese Register.” Made in China Journal. 4(2):  84-89.

* Švelch, Jaroslav. 2018. Gaming the Iron Curtain: How Teenagers and Amateurs in Communist Czechoslovakia Claimed the Medium of Computer Games. MIT Press.

* Tedre, Matti, Erkki Sutinen, Esko Kähkönen, and Piet Kommers. 2006. “Ethnocomputing: ICT in cultural and social context.” Communications of the ACM 49(1): 126-130.

* Tinn, Honghong. 2018. “Modeling Computers and Computer Models: Manufacturing Economic-Planning Projects in Cold War Taiwan, 1959–1968.” Technology and culture 59(5): S66-S99.

* Watson-Verran, Helen, and David Turnbull. 1995. “Science and other indigenous knowledge systems.” In Handbook of Science and Technology Studies, 2nd edition, edited by Jasanoff, S., G. E. Markle, J. Peterson, and T. Pinch, 115-139. Sage.

* Williams, Logan D. A. 2018. Eradicating Blindness: Global Health Innovation from South Asia. Palgrave Macmillan.

Contact: ohy@rpi.edu

Keywords: knowledge engineering, knowledge technologies, technological agency, indigenous knowledge systems, emerging worlds

Categories: Big Data

Information, Computing and Media Technology

Postcolonial/Decolonial STS

133. Peripheral States: Public Uses and Misuses of Big Data Technologies

María Belén Albornoz, FLACSO Latin American Social Studies Faculty; Henry Chavez, Pontificia Universidad Católica del Ecuador

In September 2019, an 18-gigabit database was found stored in an unsecured server in Miami containing about fifty data points of private and some very sensitive information on every Ecuadorian citizen. As the growing list of private data leaks (Facebook, Cambridge Analytica, etc.), the Ecuadorian episode launch the alarms, but nothing indicates real changes in the near future.

Though, there is a feature in the Ecuadorian case that opens a new range of questions on the problems and risk of the rise of the big data technologies. Unlike other similar massive leaks of information, the data exposed in this case was collected by different public agencies whose objectives and technological capacities are now in doubt.

For the last ten years, governments, especially in peripheral states have followed the technological path imposed by the giants of the new digital economy without having the time of reflecting and regulate the side effects of the production and accumulation of such amount of private and sensitive information. Moreover, many of them has fallen in the temptation of building (buying) mass surveillance systems to better control their citizens without having a real control over the technology they are using.

This open panel aims to bring together scholars from different parts of the world to discuss the paths and approach governments from south and north are following in the adoption of big data technologies, their uses and misuses.

Contact: balbornoz@flacso.edu.ec

Keywords: big data, peripheral states, data leaks, surveillance systems, privacy

Categories: Big Data

Governance and Public Policy

Engineering and Infrastructure

139. Public data repositories in the global health data economy

Ilpo Helén, University of Eastern Finland; Aaro Tupasela, University of Helsinki

During the past decade, digital health data has been highlighted as an asset with multiple values. This is due to many developments that have facilitated the emergence of global health data economy. Biomedical research has been impregnated by datafication; precision medicine has engendered great expectations and widespread activities; and corporations dominating the cyberspace like Google, Apple, Facebook and IBM have become increasingly interested in health-related digital data. At the same time, masses of health-related personal and population data exist and are continuously sourced in data reservoirs maintained by public authorities in different countries, especially in Europe. Now, national governments have shown an increased interest for wider and more intense utilization of health data reservoirs to facilitate biomedical research and personalized medicine, to improve clinical practices, and to boost innovative business in biomedicine and ICT. In addition, a number of projects to improve cross-border interoperability of these databases are under way in the EU and elsewhere, and transnational pharmaceutical and ICT corporations appear eager to engage in ‘collaboration’ for sourcing public health data. Discussion of this track will concentrate on the prospects, roles, purposes, and actual management of data sourcing by public authorities in the context of evolving global health data economy. We call for papers, first, about policy and technical rationales and practices that attempt to integrate collection, storage, circulation and uses public data with global health data economy, and, second, about problems and contestations related with such efforts of integration and collaboration.

Contact: ilpo.helen@uef.fi

Keywords: Health data sourcing, public databases, health data economy, data-driven health care

Categories: Big Data

Medicine and Healthcare

Economics, Markets, Value/Valuation

153. Science, Technology and Sport

Jennifer Sterling, University of Iowa; Mary McDonald, Georgia Institute of Technology; Gian Marco Campagnolo, University of Edinburgh

While sport studies scholars have established sport as a key site of cultural meanings and social relations, fewer scholars have engaged these issues within technology and science studies frameworks. This intersection of critical sport, science, and technology studies is key to understanding current and future collisions and impacts, particularly in this moment of increasing technological proliferation. This panel invites papers broadly concerned with social and cultural inquiry into the intersection of science, technology and sport. Potential topics include, but are not limited to: sport analytics, data science, algorithmic culture and the quantified self; issues related to medicine, risk and sport; performance enhancement and bioethics; sporting labs and scientific practices; elite, professional and commercial sporting practices in relation to digital objectivity, player performance, injury prevention, player valuation, etc.; public understandings, consumption and perceptions of sport technology (e.g. decision-aids); professional gaming and eSports;(new) media and other representations of science, technology and sport; science, technology and sport in relation to (dis)ability, gender, race, class, and sexuality; infrastructure, sustainability and sport; and (digital) sporting futures.

Contact: jennifer-sterling@uiowa.edu

Keywords: sport, science, technology, data, interdisciplinary

Categories: Big Data

Gender/Sexuality/Feminist STS

Knowledge, Theory and Method

172. Taking Data Into Account

Burcu Baykurt, University Of Massachusetts Amherst

As ubiquitous data technologies seep into public services, news feeds, schools, workplaces, political campaigns, and urban living around the world, the effort to hold them accountable has become a topic of public concern. From computational audits to citizen activism, from public shaming of companies to policy proposals, activists, academics, journalists, technologists, and lawmakers have been trying to account for these emergent systems that appear to be inscrutable. Using the analytical tools of STS, this panel seeks to unpack how these automated, data-driven technologies become “accountabilia – objects mobilized to enact relations of accountability” (Sugden 2010; Ziewitz 2011). How does computational legibility inform the politics of government accountability? What work does the concept of accountability perform in popular and expert conversations? What are the new devices that mobilize, shift, and maintain existing processes of accounting and accountability? What would creative methods of mapping the distribution of accountability look like in emergent data-driven organizations? This panel invites both theoretical and empirical papers that examine the ways in which accountability is forged and put in practice through automated, data-driven systems. Of particular interest are practices and perceptions from the global south; those that attend to the racialized, gendered, and socioeconomic consequences of accountability regimes; and explorations of new possibilities that are invested in critical race theory, queer-feminist, postcolonial and social-justice based perspectives.

Contact: bbaykurt@umass.edu

Keywords: accountability, governance, algorithms, big data, policy

Categories: Information, Computing and Media Technology

Governance and Public Policy

Big Data

182. The Future of Quantifying Humanity: Reflections on Artificial Intelligence

Yu-cheng Liu, Nanhua University

The idea of algorithm constitutes almost every aspect of AI technology. Likewise, the development of AI technology and what goals AI can accomplish also depend on the advancement of algorithm. There are at least two implications when applying algorithm, one is simplification, and the other is quantification. Neither are the two concepts, simplification and quantification, completely equal to each other, nor are they contradictory with each other. As a function of algorithm, the aim of simplification is to know what it simplifies. In doing so, it applies various methods of quantification to assist and to accomplish its function of simplification. Furthermore, the two implications and their related technologies attempt at fixing, enhancing, improving or even replacing some – almost every – aspects of humanity. For example, the feeling of love can be generated through algorithms simulating the operational mechanisms of neocortex of human brain. Other qualities of humanity such like creativity, compassion, or rationality may also be quantified with AI-featured algorithms in the near future. It is possible to think that the boundary between humans and non-humans, or between nature and culture, may have a dramatic change or even will be completely canceled. What if those aspects of humanity, to some extent making humans a unique species, can be quantified, how do we think of ourselves what makes us human? The panel welcomes manuscripts that focus on reflection of quantifying humanity and related researches. It will be a platform for participants to discuss the near future of quantifying humanity.

Contact: ycliu15@gmail.com

Keywords: Artificial Intelligence, quantification, humanity, algorithm, simplification

Categories: Big Data

Information, Computing and Media Technology

Knowledge, Theory and Method

190. The regimes of biomedical knowledge production: the changing face of clinical trials

Olga Zvonareva, Maastricht University, Netherlands; Anna Geltzer, University of Notre Dame

The randomized controlled trial (RCT) has long been considered the gold standard for clinical research; carried out to ascertain the safety and efficacy of health interventions. Recently, however, the authority of the RCT has become increasingly contested and is beginning to be substituted by alternative research designs. Concurrently, we can observe the emergence of new, apparently more flexible and pluralistic, standards and regulatory forms and an increasing fascination in biomedical research with the promises of personalized medicine and Big Data. This panel invites papers that explore how STS can interpret these developments and evaluate their implications. How is acceptance of different approaches to medical intervention testing as scientifically reliable and ethically sound enabled? What kinds of technological innovations facilitate new types of clinical trials and to what effect?

We are especially interested in comparative and historical perspectives on the rise and fate of RCTs. The panel speaks directly to the conference’s interest in the fate of “alternative” approaches and futures, and encourages submissions exploring how novel clinical research formats can offer insights on transformations in the culture and the politics of biomedicine.

Contact: o.zvonareva@maastrichtuniversity.nl

Keywords: clinical trials, biomedical knowledge production, evidence, medical research, regulation

Categories: Medicine and Healthcare

Big Data

205. Unpacking the Foundations of the Current Biometric Moment

Michelle Spektor, Massachusetts Institute of Technology; Ranjit Pal Singh, Cornell University

From unlocking smartphones to verifying financial transactions, from boarding airplanes to clocking in at work, and from issuing national IDs and passports as tools of data-driven governance, the use of digital biometric technologies that rely on fingerprints, facial recognition, iris scans, and other metrics have increasingly become part of everyday life in the 21st century. While the proliferation of biometrics-based digital identities might be new, the use of biometrics – techniques of measuring the human body – to identify and/or classify individuals and groups has a much longer history.

This open track panel explores how individuals, states, and institutions have used biometrics to define individual and collective identities transnationally, and how those subjected to biometric identification experience it, accept it, or resist it. By bringing together papers that address how biometric identification encapsulates politics of identity in both the past and present, the panel aims to illuminate how past biometric systems inform the technological and socio-cultural features of the current biometric moment. Broadly, it inquires into how biometric identification (re)configures relationships among and across citizenship, migration, borders, and national belonging; race, gender, class, and disability; policing, surveillance, and criminality; labor, bureaucracy, and imaginaries of technological progress; power, subjectivity, and the body; social security, national security, and global development. It welcomes papers that address how STS tools and concepts can be leveraged to unpack the ways conceptions of identity shape and are shaped by biometric identification infrastructures in the past, present, and future.

Contact: spektor@mit.edu

Keywords: biometrics, identity/identification, governance, citizenship, surveillance

Categories: Governance and Public Policy

Big Data

Technologies of Militarism/(In)Security