This book unravels implications for society and security of a seismic shift in science, engineering, and computing. Driving the shift is ‘Big Data’, a term that loosely refers to remarkable advances in computational processing power, information storage, and clever software programmes. Whilst there is no universal definition of Big Data, it can be understood as referring to vast digital data sets that often capture very personal information of citizens and consumers. Examples would include Google searches, WhatsApp messages, or financial transaction flows by Walmart’s clientele. These data sets are increasingly recognised as a source to be harvested, aggregated, and analysed by, first and foremost, the private sector—corporate powerhouses have emerged in recent years that have adopted a business model largely on the promise of Big Data. Big Data’s significance may lie not only in the tsunami of information and the insights it is helping to gather, but in how it transforms the essence of decision-making and enables organisations to adapt to a radically altered landscape.
The public sector, academia, and non-governmental organisations (NGOs) are increasingly recognising Big Data’s potential as well. The challenges that Big Data poses for these sectors are perhaps more complex and less well researched than developments in the corporate world. Innovation, after all, is part of the DNA of capitalism, but is less well embedded within government agencies. The age of Big Data, however, presents an opportunity to these actors to embrace data-driven innovation and utilise the banks of information that are available to them to make better sense of the world around them. But how can and should governments, academics, and NGOs adopt Big Data in a sustainable manner?
This volume emerged as a response to these timely issues and has a strong focus on the interplay between society and security and between ethics and innovation. It will operate from the perspective that Big Data prompts manifold opportunities for innovation and risk-management. Practically, Big Data opens up scarcely imagined challenges for practitioners working in security, intelligence, and law enforcement. Simultaneously, it promises game-changing progress in cost-effective technologies and processes to enable agencies to operate with unprecedented efficiency and productivity. In relation to society and security, Big Data will be unpacked as a triptych of scientific, corporate, and societal concern, albeit one in which the parts are currently dangerously disconnected from the whole.
Advances in private and public laboratories are taking place largely removed from the scrutiny of the societal communities (artistic, political, and legal) that traditionally interpret the implications of radical turns in technology for humanity. Indeed, the news media, it will be argued, has shown scarce capacity to interrogate Big Data developments on behalf of the citizens who depend upon it for translation of important events. Where it has—as in the recent revelations in the Edward Snowden affair—the unintended cost in terms of blowback on states can be measured by compromised life-saving intelligence as well as jobs lost.
This book will, therefore, argue that the disconnection is both a hindrance to innovation for the many and a seam through which ethically dubious and practically dangerous developments can take place. The text will conclude by calling for a new methodological approach amongst scholars and ‘real world’ practitioners alike: the moment has arrived for a previously unimagined blurring of hard and social sciences to effect sustainable innovation that is ethically informed. This development can be achieved only by weaving together, in imaginative ways, knowledge and understanding from the sciences, humanities, and arts.
More broadly, security and law enforcement organisations internationally have reported to us serious concerns for corporate risk management arising from mining and analysing data. One aspect of this problem is how the traditional ‘signals to noise’ issue of useless/crucial information is reaching an unprecedented scale. Such organisations are hungry for solutions to help them to carry emerging data risk. In these communities, we are seeing a real interest in smart technological solutions but equally in realistic policy limitations for information operations and the management of political and media expectations, especially when things go wrong.
Bibliometric data gathered by the authors suggests that limited ethical discussions have taken place around the security threats posed by Big Data and communication aggregation. The result may be unwanted consequences for the state, business, and individual human rights. Our research also indicates weak journalistic interrogation of Big-Data-based evidence linked to negative consequences for national economic security. Whilst a plurality of legal approaches have been reported from around the world, the one point of consensus appears to be that legislation is structurally unable to keep pace with rapid advances in technology. Experimental work carried out by colleagues in collaboration with Cornell University suggests that privacy disclosure decisions have a highly unstable value at a personal level, meaning that users’ decisions are heavily influenced by emotion, calling into question the role of rational consent, at the core of much privacy-related legislation to date.
In these and many other ways, governments are lagging behind the corporate sector in their consideration of the uses, analyses, and ethics of aggregating large data-sets to create an increasingly fine-grained picture of individual and group activities. The limited contact among the technical, entrepreneurial, legislative, and academic weakens the societal scope to regulate and interpret the developments associated with Big Data. This volume serves as much as an academic interdisciplinary response to a pressing real-world problem as it is a call to action to those working to keep us safe and secure.
Organisation of the Book
The book is divided into two parts. Part I consists of conceptual explorations of Big Data through various mathematic and/or philosophical lenses. These chapters approach the topic with specific reference to the domains of computer science, philosophy of information, ethics, and media studies. These particular prisms were carefully selected to provide a deeper understanding of the radical change presented through Big Data. Part II takes a more empirical turn, and deals with Big Data’s ramifications on security, intelligence, and law enforcement in particular. How are these communities looking to embed Big Data in their organisations and practices? And does it indeed provide the innovation that they seek so as to respond to the contemporary threats of an increasingly digital and global world?
Part I: Between Mathematics and Philosophy
Chapter 2 traces the origins of Big Data by providing a brief history of data science and the ‘civil war’ between statisticians and machine learners. David Reid argues here that the impact of data now signifies a paradigm shift in the history of humanity as a machine rather than humankind’s being able to classify the world around us—a development often understood as machine learning. The reader is also treated to a discussion of the N = all debate, deep learning, and what this all means for society.
In Chap. 3, Andrej Zwitter emphasises the radical departure that the Big Data age signifies for researchers, corporates, and public bodies alike. The argument is presented that the nature of Big Data and the means of analysis raise their own specific ethical problems that nowadays go beyond the privacy consideration of the individual. Instead, these changes raise questions about the privacy of communities against the collecting and tracking of group and network data, the security from manipulation, and education for appropriate internet use. Do our ethical frameworks still fit the Big Data age? The author concludes that we might need to redevelop individualistic ethical norms to match a network logic of power and responsibility.
Following from computer science and ethics, the Chap. 4 builds on some of the topics and questions raised earlier through the philosophical assumptions that have governed the evolution of online networks. These assumptions, drawn from the philosophy of mathematics, carry with them their own definitions of knowledge, intelligence, and security, which are not always compatible with the working definitions in either the intelligence community or the wider human domain. Drawing on a few practical examples, David Lundie examines some of the critical incidents that can result from this mismatch of design and purpose, and proposes an approach to values in design that can mitigate these concerns.
Chapter 5 of Part I deals with the role of news media in the age of Big Data and how this role relates to some of the ontological debates in this field: What is the core purpose of news and should news be classed primarily as a public good or a product? Anthony Cawley explains how Big Data underpins the emergence of data journalism, and he argues that an increasingly data-driven world is amongst the expanding list of social and technological complexities that the news media is expected to explain to the public. A case study of innovation in news media in Ireland considers some of these questions in more detail.
Part II: Implications for Security
Part II deals with the wider ramifications of Big Data for security and society. The concept of security here has a focus on the state, but goes beyond the realm of national security. Law enforcement, counter-terrorism, and food security are equally affected by Big Data and have, therefore, been addressed in this book. How are the agencies mandated with these tasks adapting their strategies, tactics, and operations to make full use of the innovation that Big Data presents? And what are the core challenges that need to be overcome to ensure these changes will prove to be effective as well as legitimate and sustainable?
Chapter 6, by Michael Mulqueen, opens this section on the security implications of Big Data. To what extent should state agencies make decisions on the basis of no other evidence than algorithmic sorting of messy, raw data? And how do these agencies marry innovation with ethics in order to prevent blowback from the media and public? This chapter raises pertinent ethical problems and addresses the need for professional ethics in organisations working on security. It is argued that decisions to deploy Big Data are being made in the absence of any systematic epistemology or methodology to track and manage the influences of human intuition and social processes on that action.
In Chap. 7, Julian Richards argues that Edward Snowden’s revelations about the nature and scale of data collection by American and British intelligence agencies added a new dimension to a debate already underway about the transformation of intelligence-gathering in an age of Big Data. Snowden’s revelations provided the bow-wave of a fundamentally critical and anti-state stance on the intelligence questions in hand. Such a critical stance is reflected in much of the academic literature about Big Data. In this chapter, such concerns are critically appraised. It is concluded that the slippery and sometimes deliberate mutation in public discourse of large-scale collection of data into ‘mass surveillance’ is misleading and unhelpful.
Chapter 8 explores the ramifications of Big Data for the contemporary challenges of countering terrorism, extremism, and radicalisation. Given the recent rise of jihadists and other extremists in the Middle East and Europe, how do state agencies respond to this challenge through Big Data? This chapter critically engages with questions such as the extent to which Big Data can inform us of future terrorist attacks, the prevention of radicalisation, and the role of the private sector and NGOs. The author, Anno Bunnik, argues here that academics and subject matter experts need to be involved in this process to better understand the relationship between extremism, radicalisation, and terrorism.
Chapter 9 offers an overview of primary Big Data sets that are ‘owned’ by or formally accessible to UK law enforcement. It examines, through the lens of practitioners, how Big Data is utilised in mitigating identified or anticipated harm to individuals and communities. It outlines accompanying oversight and governance arrangements that provide scrutiny, enhanced public accountability, and legitimacy, and guards the legality of data management. Ian Stanier explores the key organisational, technological, ethical, and cultural challenges faced by law enforcement as it seeks to exploit Big Data when discharging its legal responsibilities in safeguarding communities, reducing crime, and addressing anti-social behaviour.
Chapter 10 takes a closer look at the millions of square kilometres of high-resolution satellite imagery produced daily and which pose novel opportunities and challenges for state as well as non-state actors. It addresses the techno-political development of Earth observation, the changing ways of knowledge production, and the policy impact and governance of geospatial Big Data. Following this trichotomy, Philipp Olbrich and Nina Witjes outline how the satellite imagery community contributes to the formation of a specific sociotechnical imaginary of geospatial Big Data. The two notions most prevalent in the accounts of satellite imagery providers, government officials, and imagery analysts are a sense of condensed temporality and increasing transparency.
Chapter 11, by Bryce Evans, focuses on advancement of food security through better knowledge of novel ecosystem data. It is argued that leveraging Big Data can improve food security by reducing delays in the gathering, processing, and diffusion of information, allowing for more efficient, analytically-informed decision-making. In these ways, Big Data would form an essential part of the toolkit of established assessments used to identify food insecure populations, such as the World Food Programme’s Vulnerability Analysis and Mapping. The use of Big Data, therefore, has the potential to bolster food security and, in some contexts, to take its place as the centrepiece of new initiatives to combat hunger.