New Lines of (In)Sight? Big Data Surveillance & the Analytically-Driven Organization

4 - 5 June, 2018

A Research Workshop of the Big Data Surveillance partnership project funded by the Social Sciences and Humanities Research Council of Canada

Location: University of Stirling, Scotland

See the final report arising from the workshop, from July 2018.

This research workshop brings together research undertaken across the social sciences which concerns how big data analytics produce and construct surveillance within and around public and private sector organizations. 

Framed in the world of practice as the creation of new insight, this workshop will examine big data analytical activities critically, as they attempt to produce new surveillant lines of sight. The workshop will question how resources are brought together to create insight through analytics. It will seek to capture the legal, ethical, social and political consequences of big data analytical activities and their implications for trust, discrimination, accountability and transparency.  How, for instance, does analytics impact employees, professional practices, skills and domains? What new forms of thinking emerge about consumers, their profiles, and the prediction and pre-emption of their behaviour? What are the challenges for information flows and infrastructures, on networks, partnerships and collaboration? How are power relations reconfigured and how does conflict and resistance emerge? When analytics are applied to improve efficiency, how does the organization itself adapt to becoming a surveillance target?

Proposed topics:

•History, lock in and legacy in systems and practice transformations
•Data ethics and discriminatory consequences
•Sociotechnical alignment and data flow
•Analytics and the transformation of organizational and professional practices
•Inter-organizational data collaboration 
•Data donation
•Social sorting and its consequences
•Consumer perspectives
•Privacy and data protection
•Political economy and the labours of big data analytics
•Data scandal
•Enablement and empowerment through analytics 
•Protest and activism counter BD organizations
•The organization as surveilled subject

Further information:

Research currently underway in the Big Data Surveillance project  is starting to reveal how, in business settings, big data analytics are used to exploit IT innovations so that operational efficiency, strategic advantage and commercial value may be created. We would like to explore these issues further in this workshop using a critical, surveillance studies lens. Business organizations develop their analytical capabilities by streamlining internal systems, collaborating with analytics providers and by integrating internal data with those of external collaborators. Data analytics are as important in the production of those who consume as is it in the consumption of what is produced.  Businesses of all shapes and sizes are currently pursuing analytical solutions.  The original analytical competitors – Facebook, Uber or AirBnB, for example - enjoy powerful market positions but attract controversy because of the ethical, legal, political and social consequences of their activities.

Big Data Analytics are surveillant and ramp up previous iterations of consumer and worker surveillance.  In comparison with its predecessors, analytically intensive business operations feature pre-emptive impulses and the use of huge volumes of data.  A more penetrating gaze into the lives of consumers, into worker activities as well as into the organization itself is promised and pursued. Due to the availability of fine-grained qualitative and quantitative data about consumers, big data analytics allows individual consumer behaviours to be seen in their social, economic, and cognitive contexts and therefore understood in greater depth. The organization and its members also become a surveillance target, with socio-technical complexities being realigned to yield insight into operational processes.  

We are starting to understand that transforming an organization into one which is analytically capable is not a simple matter.  An enduring analytical connection with the consumer, the worker and other organizational elements is hard won. Legacy systems, incompatible infrastructures and the availability of skills to complete the analysis are common barriers.  The mesh of organizational subdivisions, personnel, systems and practices which mediate between the end consumer and the marketer of products reveals how the influence and power of Big Data analytics is far from a done deal.  Big data analytics also has its labours, its contested professional terrains, boundaries and practices. 

Several questions thus emerge as to the dominance of analytical logic in contemporary organizations across different sectors of the economy. Those who advocate for the uptake of Big Data analytics argue that existing organizational cultures and practices are the biggest barriers to its success. Concern has also been expressed about the ability of non-technical organizational members to make the most of analytical results and interpret them in a way which enables business value to be generated. Ethical questions concerning data protection, privacy and social sorting are reduced to questions of compliance with data protection legislation, despite fundamental issues over the transparency and accountability of the algorithms which drive analytics. 

This two-day event seeks to attract contributions which interrogate, from a critical perspective, the pragmatic issues and the ethical, discriminatory and social justice dangers associated with advanced analytical practice in business settings. 

The workshop is organized by Kirstie Ball (University of St. Andrews, Scotland), William Webster (University of Stirling, Scotland), and Colin Bennett (University of Victoria, Canada). Send all inquiries to surveill@queensu.ca.

Fees and Other Information:

The workshop will take place at the University of Stirling. Further details will be provided when invited participants have been confirmed. Although there are no registration fees, all attendees must pre-register. Space is limited. Some funds may be made available through the Big Data Surveillance project for participants who otherwise cannot obtain support for economy travel and accommodation through their universities or other employers. Priority will be given to paper presenters. Please note that if your paper is co-authored, only one author will be eligible for Big Data Surveillance funds. Details on how to apply for Big Data Surveillance funding is provided at the registration stage.

All enquiries should be sent to: surveill@queensu.ca