Our contemporary condition is deeply infused with scientific-technological rationales. These influence and shape our ethical reasoning on war, including the moral status of civilians and the moral choices available to us. In this article, I discuss how technology shapes and directs the moral choices available to us by setting parameters for moral deliberation. I argue that technology has moral significance for just war thinking, yet this is often overlooked in attempts to assess who is liable to harm in war and (...) to what extent. This omission produces an undue deference to technological authority, reducing combatants, civilians and scenarios to data points. If we are to develop a maximally restrictive framework for harming civilians in war, which in my view should be a goal of just war thinking, then it is imperative that the scientific-technological dimension of contemporary war is given due attention. (shrink)

Military drones combine surveillance technology with missile equipment in a far-reaching way. In this article, I argue that military drones could and should be object for a philosophical investigation, referring in particular on Chamayou’s theory of the drone, who also coined the term “an eye turned into a weapon.” Focusing on issues of human self-understanding, agency, and alterity, I examine the intricate human-technology relations in the context of designing and deploying military drones. For that purpose, I am drawing on the (...) postphenomenological approach developed by Don Ihde in order to systematize the manifold aspects of human-technology relations in a four-level model. This inquiry also includes a critical reflection on the normative implications of this technology. In doing so, I do not intent to offer an exhaustive relational ontology of military drones. I rather aim at providing a framework that is able to capture the core dimensions of this technology and their complex interrelations in a systematic way that has been missing in the philosophical debate so far. (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 use of cognitive systems like pattern recognition or video tracking technology in security applications is becoming ever more common. The paper considers cases in which the cognitive systems are meant to assist human tasks by providing information, but the final decision is left to the human. All these systems and their various applications have a common feature: an intrinsic difference in how a situation or an event is assessed by a human being and a cognitive system. This difference, which (...) here is named “the model gap,” is analyzed pertaining to its epistemic role and its ethical consequences. The main results are as follows: (1) The model gap is not a problem, which might be solved by future research, but the central feature of cognitive systems. (2) The model gap appears on two levels: the aspects of the world, which are evaluated, and the way they are processed. This leads to changes in central concepts. While differences on the first level often are the very reason for the deployment of cognitive systems, the latter is hard to notice and often goes unreflected. (3) Such a missing reflection is ethically problematic because the human is meant to give the final judgment. It is particularly problematic in security applications where it might lead to a conflation of descriptive and normative concepts. (4) The idea of the human operator having the last word is based on an assumption of independent judgment. This assumption is flawed for two reasons: The cognitive system and the human operators form a “hybrid system” the components of which cannot be assessed independently; and additional modes of judgment might pose new ethical problems. (shrink)

The combination of increased availability of large amounts of fine-grained human behavioral data and advances in machine learning is presiding over a growing reliance on algorithms to address complex societal problems. Algorithmic decision-making processes might lead to more objective and thus potentially fairer decisions than those made by humans who may be influenced by greed, prejudice, fatigue, or hunger. However, algorithmic decision-making has been criticized for its potential to enhance discrimination, information and power asymmetry, and opacity. In this paper, we (...) provide an overview of available technical solutions to enhance fairness, accountability, and transparency in algorithmic decision-making. We also highlight the criticality and urgency to engage multi-disciplinary teams of researchers, practitioners, policy-makers, and citizens to co-develop, deploy, and evaluate in the real-world algorithmic decision-making processes designed to maximize fairness and transparency. In doing so, we describe the Open Algortihms project as a step towards realizing the vision of a world where data and algorithms are used as lenses and levers in support of democracy and development. (shrink)

Information communication technology is spreading fast and wide. Driven by convenience, it enables people to undertake personal tasks and make decisions more easily and efficiently. Convenience enjoys an air of liberation as well as self-expression affecting all areas of life. The industry for children's toys is a major economic market becoming ever more tech-related and drawn into the battle for convenience. Like any other tech-related industry, this battle is about industry dominance and, currently, that involves networked toys. Networked toys aim (...) to enhance convenience for children and parents alike. Increasingly difficult to resist, these convenient networked devices are also a societal game changer. Neatly nestled in a lacuna juris and surrounded by a lack of clinical evidence, networked toys raise complex ethical issues concerning human development. This article lays bare the regulatory nexus for networked toys and invites ethical thinking to fill the gap to ensure sufficient protection for all human developmental stages. Networked toys not only affect but also might interfere with child development. Therefore, the article initially summarises the four key psychological stages through which the neurological development of the human brain processes. Each of these stages involves vital windows for human development in cognitive, emotional and social dimensions. Missing any of these developmental windows changes an individual human for life. The article then takes a look at the two main legal frameworks protecting the stages of human development which are applicable to networked toys: First, the examination of the human rights framework with its major segments emanating from the fundamental rights to privacy for family and home, to a child's education as well as to personal data reveals the use of current networked toys as a shielded part of parenting which tends to be at odds with privacy and data protection requirements. Second, the product liability framework for toy manufacturers requires evidence-based causality for putting a child's safety at risk. Unfortunately, these legal frameworks fail to offer sufficient protection of the human developmental stages. There is a lacuna juris. Although networked toys involve the risk of negatively impacting human development in every dimension, clinical psychological studies are impossible to acquire as court evidence for product liability because they take too long to provide reliable data while exposing several generations of children to the examined risk in the process. Meanwhile the temptation of convenience continues to drive the industry and consumers of networked toys and devices, which are already impacting children of all age groups. Accepting this phenomenon as an element of cognitive dissonance in society and in science falls far short of an appropriate ethical balance. The need for creating such an ethical balance concerning networked toys is all the more imperative because even if the networked toy industry managed to eliminate all psychological risks for human development and every legal conflict with privacy and security, significant ethical and societal risks of networked toys remain due to inevitable technological bias. Against these mounting changes, it is suggested that only an ethical approach of interdisciplinary research and learning seems most promising to develop an appropriate equilibrium between the complex challenges posed by networked toys and the societal values at stake. (shrink)

Decision-making assisted by algorithms developed by machine learning is increasingly determining our lives. Unfortunately, full opacity about the process is the norm. Would transparency contribute to restoring accountability for such systems as is often maintained? Several objections to full transparency are examined: the loss of privacy when datasets become public, the perverse effects of disclosure of the very algorithms themselves, the potential loss of companies’ competitive edge, and the limited gains in answerability to be expected since sophisticated algorithms usually are (...) inherently opaque. It is concluded that, at least presently, full transparency for oversight bodies alone is the only feasible option; extending it to the public at large is normally not advisable. Moreover, it is argued that algorithmic decisions preferably should become more understandable; to that effect, the models of machine learning to be employed should either be interpreted ex post or be interpretable by design ex ante. (shrink)

Decision-making assisted by algorithms developed by machine learning is increasingly determining our lives. Unfortunately, full opacity about the process is the norm. Would transparency contribute to restoring accountability for such systems as is often maintained? Several objections to full transparency are examined: the loss of privacy when datasets become public, the perverse effects of disclosure of the very algorithms themselves, the potential loss of companies’ competitive edge, and the limited gains in answerability to be expected since sophisticated algorithms usually are (...) inherently opaque. It is concluded that, at least presently, full transparency for oversight bodies alone is the only feasible option; extending it to the public at large is normally not advisable. Moreover, it is argued that algorithmic decisions preferably should become more understandable; to that effect, the models of machine learning to be employed should either be interpreted ex post or be interpretable by design ex ante. (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)

Debates about terrorism and technology often focus on the potential uses of technology by non-state terrorist actors and by states as forms of counterterrorism. Yet, little has been written about how technology shapes how we think about terrorism. In this chapter I argue that technology, and the language we use to talk about technology, constrains and shapes our understanding of the nature, scope, and impact of terrorism, particularly in relation to state terrorism. After exploring the ways in which technology shapes (...) moral thinking, I use two case studies to demonstrate how technology simultaneously hides and enables terroristic forms of state violence: police control technologies and Unmanned Aerial Vehicles (UAVs), or drones. In both these cases, I argue that features of these technologies, combined with a narrative of precision and efficiency, serves to mask the terroristic nature of the violence that these practices inflict and reinforces the moral exclusion of those against whom these technologies are deployed. In conclusion, I propose that identifying acts of terrorism requires a focus on the impact of technologies of violence (whether they are “high tech” or not) on those most affected, regardless of whether users of these technologies conceive of their actions as terroristic. (shrink)