ABSTRACTAdvertising and public relations executives claim the rules for ethical practices are changing. On the basis of 29 in-depth interviews with advertising and public relations executives, and an analysis guided by identity theories and moral justifications, new insights address the most pressing issues faced today, greater opportunities to behave unethically, and the lack of ethics training received. Some of the executives perceive a personal responsibility to be ethical, whereas others adopted a self-interested attitude by suggesting it’s the publishers’ or consumers’ (...) responsibility to make ethical decisions. Emerging marketing practices have increased the need for more ethics training and more sophisticated perspectives on professionalism and virtuous behavior that are also flexible enough to apply to envelope-pushing strategies. (shrink)

Using a Rawlsian approach to analyze the ethical implications of data mining within three major codes of ethics used by American marketing firms, the author argues that marketers should re-conceptualize their business conduct, as defined in their individual codes of ethics, to incorporate a Rawlsian concern for society's least advantaged members. Rawls's concept of primary goods provides the framework for the argument that anonymity, a component of privacy, is vital for consumers whose autonomy is affected by data mining. A combination (...) of practical measures, ethical guidelines, and legislative protections are recommended for minimizing concerns about data mining, while still allowing for commercial advantages provided by the practice. (shrink)

This article focuses on the issue of data mining as it relates to the consumer and to the issue of whether the consumer's private information has any proprietary status. A brief review of data mining is provided as a background for a better understanding of the purposes and uses of data mining. Also examined are several issues of the ethics of data mining, including a review of stakeholders, who they are and which may be most seriously affected by unethical data (...) mining practices. Several suggestions for the improvement of data mining as it relates to the consumer are further presented: suggestions that would allow for data mining that would be beneficial to both the business community and the consumer. (shrink)

This article focuses on the issue of data mining as it relates to the consumer and to the issue of whether the consumer's private information has any proprietary status. A brief review of data mining is provided as a background for a better understanding of the purposes and uses of data mining. Also examined are several issues of the ethics of data mining, including a review of stakeholders, who they are and which may be most seriously affected by unethical data (...) mining practices. Several suggestions for the improvement of data mining as it relates to the consumer are further presented: suggestions that would allow for data mining that would be beneficial to both the business community and the consumer. (shrink)

This study analyzes the increasing presence and capabilities of wearable computing devices in the cornucopia of personalized digital data. We argue that the institutional data practices typical of Google Glass will pose policy challenges and herald yet another dramatic shift to personalized data marketing. We also highlight the characteristics of Google’s existing synergetic data practices that will shape the development of not only Google Glass, but also all subsequent wearable mobile devices in light of 360-degree data collection. The key organizing (...) concept of our study is the disjuncture between institutional and policy forces in harnessing dual market mechanism, which frames how the new communication industry operates in the marketplace of ubiquitous personal advertising. We conclude by summarizing the three key areas of political-policy concern and suggest future solutions, with the discussion on the future of wearable computing practices related to the freedom of the human body. (shrink)

Mature information societies are characterised by mass production of data that provide insight into human behaviour. Analytics has arisen as a practice to make sense of the data trails generated through interactions with networked devices, platforms and organisations. Persistent knowledge describing the behaviours and characteristics of people can be constructed over time, linking individuals into groups or classes of interest to the platform. Analytics allows for a new type of algorithmically assembled group to be formed that does not necessarily align (...) with classes or attributes already protected by privacy and anti-discrimination law or addressed in fairness- and discrimination-aware analytics. Individuals are linked according to offline identifiers and shared behavioural identity tokens, allowing for predictions and decisions to be taken at a group rather than individual level. This article examines the ethical significance of such ad hoc groups in analytics and argues that the privacy interests of algorithmically assembled groups in inviolate personality must be recognised alongside individual privacy rights. Algorithmically grouped individuals have a collective interest in the creation of information about the group, and actions taken on its behalf. Group privacy is proposed as a third interest to balance alongside individual privacy and social, commercial and epistemic benefits when assessing the ethical acceptability of analytics platforms. (shrink)

The potential for biases being built into algorithms has been known for some time, yet literature has only recently demonstrated the ways algorithmic profiling can result in social sorting and harm marginalised groups. We contend that with increased algorithmic complexity, biases will become more sophisticated and difficult to identify, control for, or contest. Our argument has four steps: first, we show how harnessing algorithms means that data gathered at a particular place and time relating to specific persons, can be used (...) to build group models applied in different contexts to different persons. Thus, privacy and data protection rights, with their focus on individuals, do not protect from the discriminatory potential of algorithmic profiling. Second, we explore the idea that anti-discrimination regulation may be more promising, but acknowledge limitations. Third, we argue that in order to harness anti-discrimination regulation, it needs to confront emergent forms of discrimination or risk creating new invisibilities, including invisibility from existing safeguards. Finally, we outline suggestions to address emergent forms of discrimination and exclusionary invisibilities via intersectional and post-colonial analysis. (shrink)

In this paper, it is argued that although data mining (DM) is being touted as a solution to many business problems and is basking in the glory of electronic business environments of today, as practiced currently, it reflects a preoccupation with short-run commercial applications and a neglect of the underlying theoretical issues. Although an argument can be made that theoretical precedence is not a necessary prerequisite for practical application or for commercial success, it can also be argued that an exclusive (...) reliance on data-driven and exploratory components of pattern recognition without a corresponding attention to the causal schemas underlying patterns is destined to limit the potential for DM to evolve into a long-term solution to business problems or into an intellectual discipline in its own right. This paper presents an overview of key features and assumptions in DM and examines some of the key practical, philosophical, and foundational issues in DM. (shrink)

Research is subject to more stringent ethical requirements than most other human activities, and a procedure that is otherwise allowed may be forbidden in research. Hence, risk-taking is more restricted in scientific research than in most non-research contexts, and privacy is better protected in scientific questionnaires than in marketing surveys. Potential arguments for this difference are scrutinized. The case in its favour appears to be weak. A stronger case can be made in favour of a difference in the opposite direction: (...) If perilous or otherwise problematic activities have to be performed it is usually better to perform them in a research context where they are properly evaluated so that guidance is obtained for the future. However, retreating from current ethical demands on research is not a desirable direction to go. Instead, research ethics can serve to inspire the introduction of more stringent ethical principles in other social sectors. (shrink)

This article proposes a new bi-directional way of understanding the convergence of biology and computing. It argues for a reciprocal interaction in which biology and computing have shaped and are currently reshaping each other. In so doing, we qualify both the view of a natural marriage and of a digital shaping of biology, which are common in the literature written by scientists, STS, and communication scholars. The DNA database is at the center of this interaction. We argue that DNA databases (...) are spaces of convergence for computing and biology that change in form, meaning, and function from the 1960s to the 2000s. The first part of the article shows how, in the 1980s, DNA sequencing shifted from passively incorporating computers to be increasingly modeled in digital coding and decoding. Information retrieval algorithms, reciprocally, were altered according to the peculiarities of DNA in the first sequence-storage databases. The second part of the article investigates the impact of these reciprocal interactions and globalization on the organization of research centers, ways of conducting big science, and scientific values. Through convergence and new technologies such as data mining, biology and computing were transformed technologically, institutionally, and culturally into a new bio-data enterprise called genomics. (shrink)

The accuracy principle is one of the key standards of informational privacy. It epitomises the obligation for those processing personal data to keep their records accurate and up-to-date, with the aim of protecting individuals from unfair decisions. Currently, however, different practices being put in place in order to enhance the protection of individuals appear to deliberately rely on the use of ‘inaccurate’ personal information. This article explores such practices and tries to assess their potential for privacy protection, giving particular attention (...) to their legal implications and to related ethical issues. Ultimately, it suggests that the use of ‘inaccurate’ data can potentially play a useful role to preserve the informational autonomy of the individual, and that any understandings of privacy or personal data protection that would tend to unduly limit such potential should be critically questioned. (shrink)

There is surprisingly little attention in Information Technology ethics to respect for persons, either as an ethical issue or as a core value of IT ethics or as a conceptual tool for discussing ethical issues of IT. In this, IT ethics is very different from another field of applied ethics, bioethics, where respect is a core value and conceptual tool. This paper argues that there is value in thinking about ethical issues related to information technologies, especially, though not exclusively, issues (...) concerning identity and identity management, explicitly in terms of respect for persons understood as a core value of IT ethics. After explicating respect for persons, the paper identifies a number of ways in which putting the concept of respect for persons explicitly at the center of both IT practice and IT ethics could be valuable, then examines some of the implicit and problematic assumptions about persons, their identities, and respect that are built into the design, implementation, and use of information technologies and are taken for granted in discussions in IT ethics. The discussion concludes by asking how better conceptions of respect for persons might be better employed in IT contexts or brought better to bear on specific issues concerning identity in IT contexts. (shrink)

This paper reviews and analyses the implications of citizenship thinking for building ethical institutional arrangements for business. The paper looks at various stakeholder groups whose relation with the company changes quite significantly when one starts to conceptualize it in terms of citizenship. Rather than being simply stakeholders, we could see those groups either as citizens, or as other constituencies participating in the administration of citizenship for others, or in societal governance more broadly. This raises crucial questions about accountability and democracy (...) in stakeholder relations with the corporation. We sketch out the main currents informing and emerging from the citizenship perspective on firm-stakeholder relations; analyze specific stakeholder groups and their particular relevance in the context of a citizenship perspective; and conclude with a discussion of the broader implications in terms of building ethical institutions. (shrink)

While organizations today make extensive use of complex algorithms, the notion of algorithmic accountability remains an elusive ideal due to the opacity and fluidity of algorithms. In this article, we develop a framework for managing algorithmic accountability that highlights three interrelated dimensions: reputational concerns, engagement strategies, and discourse principles. The framework clarifies that accountability processes for algorithms are driven by reputational concerns about the epistemic setup, opacity, and outcomes of algorithms; that the way in which organizations practically engage with emergent (...) expectations about algorithms may be manipulative, adaptive, or moral; and that when accountability relationships are heavily burdened by the opacity and fluidity of complex algorithmic systems, the emphasis of engagement should shift to a rational communication process through which a continuous and tentative assessment of the development, workings, and consequences of algorithms can be achieved over time. The degree to which such engagement is, in fact, rational can be assessed based on four discourse-ethical principles of participation, comprehension, multivocality, and responsiveness. We conclude that the framework may help organizations and their environments to jointly work toward greater accountability for complex algorithms. It may further help organizations in reputational positioning surrounding accountability issues. The discourse-ethical principles introduced in this article are meant to elevate these positioning contests to extend beyond mere adaption or compliance and help guide organizations to find moral and forward-looking solutions to accountability issues. (shrink)

:This article examines privacy threats arising from the use of data mining by private Australian health insurance companies. Qualitative interviews were conducted with key experts, and Australian governmental and nongovernmental websites relevant to private health insurance were searched. Using Rationale, a critical thinking tool, the themes and considerations elicited through this empirical approach were developed into an argument about the use of data mining by private health insurance companies. The argument is followed by an ethical analysis guided by classical philosophical (...) theories—utilitarianism, Mill’s harm principle, Kant’s deontological theory, and Helen Nissenbaum’s contextual integrity framework. Both the argument and the ethical analysis find the use of data mining by private health insurance companies in Australia to be unethical. Although private health insurance companies in Australia cannot use data mining for risk rating to cherry-pick customers and cannot use customers’ personal information for unintended purposes, this article nonetheless concludes that the secondary use of customers’ personal information and the absence of customers’ consent still suggest that the use of data mining by private health insurance companies is wrong. (shrink)

In information societies, operations, decisions and choices previously left to humans are increasingly delegated to algorithms, which may advise, if not decide, about how data should be interpreted and what actions should be taken as a result. More and more often, algorithms mediate social processes, business transactions, governmental decisions, and how we perceive, understand, and interact among ourselves and with the environment. Gaps between the design and operation of algorithms and our understanding of their ethical implications can have severe consequences (...) affecting individuals as well as groups and whole societies. This paper makes three contributions to clarify the ethical importance of algorithmic mediation. It provides a prescriptive map to organise the debate. It reviews the current discussion of ethical aspects of algorithms. And it assesses the available literature in order to identify areas requiring further work to develop the ethics of algorithms. (shrink)