Data Power Conference

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Panel Session 1b): Data, Markets, Finance, Profit (Chair: Alison Hearn)


Open weather data and the financialisation of climate change

Jo Bates and Paula Goodale, University of Sheffield

Meteorological data are ‘big’: vast, real-time, relational, extensible, scalable, fine grained, diverse and indexical (Kitchin 2014). Meteorological data are also valuable in the exercising of power. They provide an evidence base for global climate change. They increase our understanding of natural ecosystems, and they potentially have the power to convince publics to develop more sustainable modes of development. Yet, they are also used to exploit the ecological risks that they illuminate and empower established economic interests (Bates 2014).

Over the last two decades, weather index-based risk products such as weather derivatives have emerged as a multi-billion dollar industry. Products are priced based on vast indexes of historical and real-time observed meteorological data, and are dependent upon the data of national meteorological institutions such as the UK’s Met Office. Weather market advocates are keen for this data to be made more open and freely available in order to drive the development of global weather markets, yet data policies in many countries – including the UK – are perceived to be restrictive and creating a barrier to growth.

This paper will present an analysis of recent efforts to drive the growth of the UK’s weather risk market through ‘opening’ UK Met Office data. Drawing on interviews, policy documentation, and other literature, the paper will examine the aspirations, frustrations and ideological foundations of some key advocates of weather markets in UK government and industry, and their efforts to shape national data policy in favour of weather market growth.


Twitter, Financial Markets and Hack Crash

Tero Karppi, State University of New York at Buffalo and Kate Crawford, Microsoft Research

In this paper co-authored by Tero Karppi and Kate Crawford the focus is on the interrelation between financial markets and social media data. We examine the financial flash crash of April 23 2013, which began from a fake Associated Press tweet reporting a terrorist attack in the White House. Within minutes after the tweet $136.5bn of the Standard & Poor’s 500 index’s value was wiped out. By analyzing the commentaries around this event we map different human and non-human actors involved. These actors include automated systems that analyze Twitter data such as the Dataminr and computational algorithms that are involved in high-frequency trading. Using the works of sociology of finance and texts by Christian Marazzi, Gabriel Tarde and Tony Sampson we maintain that these computational systems are not neutral but capable of producing particular realities through processing data. We argue that Twitter and social media are becoming more powerful forces, not just because they connect people or generate new modes of participation, but because they are connecting human communicative spaces to automated computational spaces in ways that are affectively contagious and highly volatile.


On Digital Markets, Data, and Concentric Diversification

Bernhard Rieder, University of Amsterdam, and Gernot Rieder, IT University of Copenhagen

In recent debates around the potential social and political implications of large-scale data collection and analysis, scholars have mainly focussed on two interrelated sets of issues, namely privacy (related to practices like surveillance or profiling) and discrimination (in the form of differential access or treatment).

While these are certainly crucial issues, they are mostly concerned with the relationship between powerful organizations such as governments or companies on the one side and surveilled individuals or groups on the other. However, the capacity to accumulate and process data can play an important role in how these organizations relate to one another.

This paper will examine the advantages data and data handling capabilities can confer to companies competing in the marketplace. This concerns the struggle for dominance in particular sectors, but also the expansion into new markets, and, in particular, the concentric diversification big Internet companies have pursued relentlessly over the last decade.

We argue that the ongoing move towards integrated digital environments has exacerbated market concentration along at least three lines that are intrinsically tied to the handling of data:
the reformulation of a steadily growing set of tasks as algorithmic problems has allowed Internet companies to transfer their considerable technical capacities to sectors that previously would have appeared far removed;
the massive quantities of data concerning many different aspects of life gathered from popular general-purpose online platforms make for valuable market research;
since data can be used to enhance the salience and expressivity of other data, Internet companies are able to offer products in one economic sector that are based on connections or aggregations established in another sector, as seen in the case of Facebook’s recently unveiled Atlas ad serving platform.

While these elements may not seem to be directly related to immediate social or political concerns, a larger recognition of data handling capacities’ repercussions for market competition is a crucial step towards a political economy analysis of data and a more comprehensive understanding of the different facets of “data power”.


In the name of Development: Power, Profit and the Datafication of the Global South

Linnet Taylor and Dennis Broeders, University of Amsterdam

We examine the current ‘datafication’ process underway in low- and middle-income countries, and the power shifts it is creating in the field of international development. The use of new communications and database technologies in LMICs is generating ‘big data’ (for example from the use of mobile phones, mobile-based financial services and the internet) which is collected and processed primarily by corporations. When shared, these data are also becoming a potentially valuable resource for development research and policy. With these new sources of data, new power structures are emerging within the field of development. We identify two trends in particular, illustrating them with examples: first, the empowerment of public-private partnerships around datafication in LMICs and the consequently growing agency of corporations as development actors. Second, the way commercially generated big data is becoming the foundation for country-level ‘data doubles’, i.e. digital representations of social phenomena and/or territories that are created in parallel with, and sometimes in lieu of, national data and statistics. We outline the potential risks and repercussions of these shifts in power relations between donor countries, LMIC governments and corporate actors, working towards a framework for analysing and questioning these trends.