David Renton  (Barrister, Garden Court Chambers)
 

What are the implications for relations between employers and workers of living in a society where passive and active forms of data collection, near-ubiquitous connectivity and proliferating use of digital devices create highly detailed personal ‘data footprints’ combining everything from location data to shopping habits, political opinions and religious beliefs? Recent high-profile court cases have highlighted the ‘blacklisting’ of trade union activists by major construction companies, based the illegal collection of data about their presumed political opinions and personal lives. In an era when billions of people use social media to share information about themselves and their beliefs online, what considerations will shape future battles over the balance between rights to privacy and freedom of expression in the context of employment relations?

David Renton specialises in employment law and has worked a number of high-profile cases relating to blacklisting of trade union activists by employers. Before being called to the bar, David was an academic and then a trade union official specialising in discrimination law.

Ethics of Big Data - 17 October 2016 - Surveillance and Employment Relations in a Data-Saturated Society

Dr Phoebe Moore (University of Middlesex)

Technologies to track work and productivity have a long history, starting with Frederick Taylor's scientific management and Frank and Lilian Gilbreths' fatigue and motion studies. While their research took place in industrial conditions, new technologies have emerged that allow for ever more intimate levels of analysis that go into the realm of the body and physiology as well as emotions and even 'gut reactions' to situations. This session looks at the new world of work, where surveillance and electronic performance monitoring overlap with health and fitness schemes at work, moving beyond psychometrics and gamification. We will ask what the implications are with the newest technologies of the senses and how data produced are increasingly becoming ways to know the self both by the self and to others. How will we be judged as workers and citizens? Who is this new big brother of performance, wellness and self tracking, and should we be afraid of him?

Dr Phoebe Moore writes about production, technology, and governance.  She is a Senior Lecturer at Middlesex University in the Law and Politics department and her current research analyses tensions between materiality and quantification as people are being tracked and monitored at work from arthouses to warehouses. Dr Moore’s work looks at new performance enhancement techniques beyond the track, asking to what extent wellness and productivity monitoring with wearable sensory technologies could be used for surveillance over micro-conduct? Are new forms of work monitoring part of the trend toward the gig economy where precarious working life has become the norm?

Ethics of Big Data - 14 November 2016 - The Quantified Self at Work

Dr Ala'a Shehabi (The Work Foundation)
Valerio de Stefano (Bocconi University, Milan. International Labour Organisation)

Abstracts

Big Data underpins the operation of digital platforms which are playing an increasingly important role in managing the supply of labour and setting terms of employment in some sectors of the economy, from transport, to food delivery, to domestic repairs and cleaning. Via smartphone apps, companies such as Uber and Taskrabbit, can relay instructions, allocate tasks and monitor performance of a distributed and apparently disposable workforce. Meanwhile, online 'crowdworking' facilitated by platforms such as Amazon's Mechanical Turk or data enrichment company CrowdFlower, breaks work down into 'microtasks' which can be remunerated by the minute, rather than the hour. This seminar will examine the implications of digitally-enabled "on-demand working" for labour rights and social policy.

V De Stefano. The so-called "gig-economy" has been growing exponentially in numbers and importance in recent years but its impact on labour rights has been largely overlooked. Forms of work in the "gig-economy" include "crowd work", and "work-on-demand via apps", under which the demand and supply of working activities is matched online or via mobile apps. The presentation discusses the implications of this commodification and advocates the full recognition of activities in the gig-economy as "work". It shows how the gig-economy is not a separate silo of the economy and that is part of broader phenomena such as casualization and informalisation of work and the spread of non-standard forms of employment. It then analyses the risks associated to these activities with regard to Fundamental Principles and Rights at Work, as they are defined by the International Labour Organisation (ILO), and addresses the issue of misclassification of the employment status of workers in the gig-economy. Current relevant trends are thus examined, such as the emergence of forms of self-organisation of workers. Finally, some policy proposals are critically analysed, such as the possibility of creating an intermediate category of worker between "employee" and "independent contractor" to classify work in the gig-economy, and other tentative proposals are put forward such extension of fundamental labour rights to all workers irrespective of employment status, and recognition of the role of social partners in this respect, whilst avoiding temptations of hastened deregulation.

Biographies

Dr Ala'a Shehabi is a senior researcher at The Work Foundation having previously been an analyst at RAND Europe. She has also worked as a researcher and lecturer in the Middle-East and as an analyst in a hedge fund. She has been a visiting fellow at the Arab Council for Social Sciences (2013), Lund University (2014), Stanford University (2015) and has been an independent research consultant for the American University of Beirut and Amnesty International.  Her research interests are in development, technology and the future of work. And has worked on projects for the European Commission, the British Academy, AT&T, Department for Culture, Media and Sport amongst others.

She has a PhD in econometrics from Imperial College London, an MSc in economics and finance from Warwick University and a BSc in economics and statistics from University College London.

Valerio De Stefano holds a Ph.D. in Law of Business and Commerce from Bocconi University in Milan. He joined the International Labour Organisation (ILO) in 2014 and currently works in the Labour Law Reform Unit of the ILO. At the ILO, he has been conducting research on non-standard forms of employment, such as temporary and casual work, temporary agency work, dependent self-employment and on forms of casual labour driven by digitalisation, such as crowdwork. On this topic, he edited a special issue of the Compa

Ethics of Big Data - 31 October 2016 - Managed by an Algorithm? The rise of ‘on-demand working’ and the ‘Gig Economy’

The parsimonious anthropologist OR How string figures and a friar from the 14th Century might inform the preservation of digital research data

Victoria Tsoukala, PhD (National Documentation Centre/National Hellenic Research Foundation)

Policy Responses to Research Data Preservation Challenges

Data preservation Policies: from creation to exploitation

CRUK and Big Data – past, present and future

Professor Carole Goble, University of Manchester

Method Preservation: workflows and models matter

ELIXIR: Enabling European-wide sharing of data in the life sciences

Data Preservation for Re-Use: from tens of TB to tens of EB

Big Data is everywhere, no matter what you do – from humanities to natural sciences, from social sciences to engineering to medicine. Yet, data on its own, no matter how “Big”, is of little use. Distilling Big Data into actionable, useful information requires a range of tools from mathematics, statistics and computer science, which might appear intimidating when approached for the first time.

In these talks, we will introduce the key concepts and ideas which underlie modern analysis of large and complex data sets, in a maths-free manner. 

Image courtesy of François Quévillon from Flickr Creative Commons

Professor Jane Winters, Institute for Historical Research

Making sense of the archived web

William Kilbride, Executive Director, Digital Preservation Coalition

Past performance is no guide to the future value: remembering and forgetting in the digital age.

Adam Farquhar, Head of Digital Scholarshop, British Library

Diamonds are forever. What about research data?

The blessing and the curse of the big image

Eiko Yoneki, Systems Research Group University of Cambridge Computer Laboratory

Large-Scale Data Processing

Anders C. Hansen, Applied Functional and Harmonic Analysis (AFHA)

Big data and compressed sensing: How to sample your data in a clever way

Anuj Dawar, University of Cambridge Computer Laboratory

Algorithms

Statistical aspects of Big Data

Zoubin Ghahramani, Machine Learning Group, Department of Engineering University of Cambridge

Machine Learning

Richard Gibbens, Computer Laboratory, University of Cambridge

Data sources for road transport modelling

The Vocabulary of Big Data

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