Big Data Challenges: Society, Security, Innovation and Ethics

he Snowden revelations about National Security Agency surveillance, starting in 2013, along with the ambiguous complicity of internet companies and the international controversies that followed provide a perfect segue into con- temporary conundrums of surveillance and Big Data. Attention has shifted from late C20th information technologies and networks to a C21st focus on data, currently crystallized in ‘‘Big Data.’’ Big Data intensifies certain surveillance trends associated with information technology and networks, and is thus implicated in fresh but fluid configurations. This is considered in three main ways: One, the capacities of Big Data (including metadata) intensify surveillance by expanding interconnected datasets and analytical tools. Existing dynamics of influence, risk-management, and control increase their speed and scope through new techniques, especially predictive analytics. Two, while Big Data appears to be about size, qualitative change in surveillance practices is...

The speed of development in Big Data and associated phenomena, such as social media, has surpassed the capacity of the average consumer to understand his or her actions and their knock-on effects. We are moving towards changes in how ethics has to be perceived: away from individual decisions with specific and knowable outcomes, towards actions by many unaware that they may have taken actions with unintended consequences for anyone. Responses will require a rethinking of ethical choices, the lack thereof and how this will guide scientists, governments, and corporate agencies in handling Big Data. This essay elaborates on the ways Big Data impacts on ethical conceptions. Big Data & Society July-December 2014 1: 2053951714559253, first published on November 20, 2014 doi:10.1177/2053951714559253

This special issue offers a critical dialogue around the myriad political dimen-sions of Big Data. We begin by recognising that the technological objects of Big Data are unprecedented in the speed, scope and scale of their computation and knowledge production. This critical dialogue is grounded in an equal recogni-tion of continuities around Big Data’s social, cultural, and political economic dimensions. Big Data, then, is political in the same way in which identity, the body, gender, sexuality, race and ethnicity are political, that is, as sites of struggle over meaning, interpretations, and categorisations of lived experience. Big Data is political in the way circuits of production, distribution, and consumption are political; that is, as sites where access, control and agency are unequally distrib-uted through asymmetrical power relations, including relations of data produc-tion. Big Data is political in the way contemporary politics are being reshaped by data analysis in electoral campaign strategy, and through state surveillance as strikingly evidenced by the Snowden revelations on the NSA and GCHQ. Big Data is also political in the contestation of this advanced scientific practice, wherein the generation of data at unprecedented scale promises a precise and objective measure of everyday life. However, the computational dreams of an N = all verisimilitude – that is, of datasets providing a one-to-one correspon-dence to a given phenomenon – are haunted by the normative biases embedded in all data. This is not to suggest that Big Data – more specifically processes of datafication1 – are best or at all understood as socially constructed. Indeed, discursive analysis or unreconstructed social theory cannot fully grasp how data re-articulates the social, cultural, political and economic in a deeply recursive manner. Thus, any political reckoning must equally account for the materiality of data, alongside the logic guiding its processes and the practices that deploy its tools. In short, what are the power relations animating the knowledge generated by data analytics?

Social Media + Society

In recent years, we have witnessed several situations that raise new and old questions about ethics. Just as we wrap up this Special Issue, in fact, our news feeds unveil details of the latest case, where Cambridge Analytica, a large data mining and analysis firm, was able to access personal details of 50 million Facebook users without their direct permission or knowledge. This case is just the latest in a long list that illuminate the complications of ethics in social media practices (i.e., wide scale public shaming), data management (i.e., deliberate or accidental releases of private information), data slippage (i.e., moving from one context to another), technology design (i.e., search engine bias), and multiple other areas relevant for (social) life today. The locus of responsibility and accountability for ethical design, behavior, and outcomes is difficult to ascertain. Every social media situation involves multiple moments, decisions, actions, and operations that can result in outcomes that have potential harm for people. A complex ecology of simultaneously functioning systems and entities with a variety of interests, power, and self-awareness operates underneath the apparent seamlessness of our interfaces. The challenge of locating responsibility and accountability is exacerbated by the difficulty of determining with any clarity the relationship between action and consequence as well as between data and persons. This is not just a matter of finding the proverbial paper trail, as many of our ontological assumptions about the distinctions between data produced by people and people themselves are challenged. Indeed, one of the hallmarks of the era of "big data" is the abstraction and disarticulation of data about individuals whose activity in digital spaces is the source of the data. In other words, through the symbolic alchemy of algorithmic computation, there is a transmogrification of the 784502S MSXXX10.

Big Data & Society

In The Black Box Society, Frank Pasquale develops a critique of asymmetrical power: corporations’ secrecy is highly valued by legal orders, but persons’ privacy is continually invaded by these corporations. This response proceeds in three stages. I first highlight important contributions of The Black Box Society to our understanding of political and legal relationships between persons and corporations. I then critique a key metaphor in the book (the one-way mirror, Pasquale’s image of asymmetrical surveillance), and the role of transparency and ‘watchdogging’ in its primary policy prescriptions. I then propose ‘relational selfhood’ as an important new way of theorizing interdependence in an era of artificial intelligence and Big Data, and promoting optimal policies in these spheres.

International development and humanitarian organizations are increasingly calling for digital data to be treated as a public good because of its value in supplementing scarce national statistics and informing interventions, including in emergencies. In response to this claim, a ‘responsible data’ movement has evolved to discuss guidelines and frameworks that will establish ethical principles for data sharing. However, this movement is not gaining traction with those who hold the highest-value data, particularly mobile network operators who are proving reluctant to make data collected in low- and middle-income countries accessible through intermediaries. This paper evaluates how the argument for ‘data as a public good’ fits with the corporate reality of big data, exploring existing models for data sharing. I draw on the idea of corporate data as an ecosystem involving often conflicting rights, duties and claims, in comparison to the utilitarian claim that data’s humanitarian value makes it imperative to share them. I assess the power dynamics implied by the idea of data as a public good, and how differing incentives lead actors to adopt particular ethical positions with regard to the use of data.

Communications of the Association for Information Systems, 2021

Changes in technology that have allowed organizations to capture, transmit, store, and analyze data at unprecedented levels have created numerous opportunities for both the organizations themselves and society. However, in conjunction with the opportunities that big data analytics promises, some have expressed concerns about the ethics involved in using and applying big data. In this debate, we develop questions that researchers and practitioners should consider regarding privacy, accuracy, property, accessibility, and society via identifying big data analytics' inputs, processes, and outputs. We do so to begin a dialogue in the information systems discipline related to the ethical issues associated with big data analytics and how we as IS researchers, teachers, and practitioners can ensure we use, analyze, interpret, and apply data in a responsible and appropriate manner.

Transparency in Social Media, 2015

Emerald Open Research, 2022

The effects of big data in this present age are highly significant, and big data have become more applicable to society. Big data technology has been adopted by many, and its applications are utilized at national, organizational, and industry levels. This transformation of industries due to big data is changing working practice in academia, business, the humanitarian sector, and government, as they offer insights and positive effects across all sectors, making legal, economic, political, social, and ethical impacts on our world and producing innovation, efficiency, better decision-making, and a greater return on investments. This paper reviews the social implications, risks, challenges, and present and future opportunities of big data.