Artificial Intelligence (AI) is increasingly adopted in society, creating numerous opportunities but at the same time posing ethical challenges. Many of these are familiar, such as issues of fairness, responsibility and privacy, but are presented in a new and challenging guise due to our limited ability to steer and predict the outputs of AI systems. This chapter first introduces these ethical challenges, stressing that overviews of values are a good starting point but frequently fail to suffice due to the context (...) sensitivity of ethical challenges. Frequently, additional (ethical) values emerge for specific applications, as e.g. challenges with fraud detection are very different from those around language technologies. Second, methods to tackle these challenges are discussed. Main ethical theories (virtue ethics, consequentialism, and deontology) are shown to provide a starting point, but often lack the details needed for actionable AI Ethics. Instead, mid-level philosophical theories coupled to design-approaches such as Design for Values, together with interdisciplinary working methods, offer the best way forwards. The chapter aims to show how these approaches can lead to an ethics of AI that is actionable and that can be proactively integrated in the design of AI systems. (shrink)

Conceptual Engineering (CE) is thought to be generally aimed at ameliorating deficient concepts. In this paper, we challenge this assumption: we argue that CE is frequently undertaken with the orthogonal aim of _conceptual adaptation_. We develop this thesis with reference to the interplay between technology and concepts. Emerging technologies can exert significant pressure on conceptual systems and spark ‘conceptual disruption’. For example, advances in Artificial Intelligence raise the question of whether AIs are agents or mere objects, which can be construed (...) as a CE question regarding the concepts AGENT and OBJECT. We distinguish between three types of conceptual disruption (conceptual gaps, conceptual overlaps, and conceptual misalignments) and argue that when CE occurs to address these disruptions, its primary aim is not to improve concepts, but to retain their functional quality, or to prevent them from degrading. This is the characteristic aim of CE when undertaken in philosophy of technology: to _preserve_ the functional role of a concept or conceptual scheme, rather than _improving_ how a concept fulfills its respective function. (shrink)

Should we be worried that the concept of trust is increasingly used when we assess non-human agents and artefacts, say robots and AI systems? Whilst some authors have developed explanations of the concept of trust with a view to accounting for trust in AI systems and other non-agents, others have rejected the idea that we should extend trust in this way. The article advances this debate by bringing insights from conceptual engineering to bear on this issue. After setting up a (...) target concept of trust in terms of four functional desiderata (trust-reliance distinction, explanatory strength, tracking affective responses, and accounting for distrust), I analyze how agential vs. non-agential accounts can satisfy these. A final section investigates how ‘non-ideal’ circumstances—that is, circumstances where the manifest and operative concept use diverge amongst concept users—affect our choice about which rendering of trust is to be preferred. I suggest that some prominent arguments against extending the language of trust to non-agents are not decisive and reflect on an important oversight in the current debate, namely a failure to address how narrower, agent-centred accounts curtail our ability to distrust non-agents. (shrink)

Online social networks can bridge the gap between distant individuals by simulating online experiences that closely resemble physical interactions. While people have positive experiences, such as joy, in a physical relationship and would like to enjoy those experiences online, they also have negative experiences, such as being subject to a lie. An online social network may allow users to lie to simulate a real-world social group better. However, lying must be prevented on social networks as unethical behavior. Thus, this study (...) aims to investigate an ethical dilemma raised due to the two abovementioned perspectives.,This paper examines different aspects of lying in social networks, using a comprehensive descriptive literature review approach and a classification scheme.,Contrary to their initial intent, social networks are disrupting the traditional notion of human interaction, either by disregarding the presence of dishonesty or by attempting to regulate relationships. In this research, the authors examine the challenges of these two perspectives by identifying enablers, consequences and control measures of lying on social networks at the individual, social and technological levels. The authors also develop a framework to facilitate investigating this dilemma.,This paper examines a controversial topic. Although lying is unethical, allowing users to lie may be considered an appealing feature of social network platforms. This paper offers a framework to propose several research directions for future studies. This study’s examination focuses on the challenges associated with deception on social networks, prompting the formulation of three crucial questions regarding the potential impact of technology on such behavior. (shrink)

In this special issue, we focus on the connection between conceptual engineering and the philosophy of technology. Conceptual engineering is the enterprise of introducing, eliminating, or revising words and concepts. The philosophy of technology examines the nature and significance of technology. We investigate how technologies such as AI and genetic engineering (so-called “socially disruptive technologies”) disrupt our practices and concepts, and how conceptual engineering can address these disruptions. We also consider how conceptual engineering can enhance the practice of ethical design. (...) The issue features seven articles that discuss a range of topics, including trust in blockchain applications and the evolving concept of nature. These articles highlight that as technology changes the world and our concepts, conceptual engineering provides invaluable tools and frameworks to reflect on these changes and adapt accordingly. (shrink)

Conceptual engineering is the design, evaluation and implementation of concepts. Despite its popularity, some have argued that the methodology is not worthwhile, because the implementation of new concepts is both inscrutable and beyond our control. In the recent literature we see different responses to this worry. Some have argued that it is for political reasons just as well that implementation is such a difficult task, while others have challenged the metasemantic and social assumptions that underlie this skepticism about implementation. In (...) this paper, I argue that even if implementation is as difficult as critics maintain, there is at least one context in which conceptual engineering is extremely impactful and demonstrably so: the design of new technology. Different conceptions of control, freedom, trust, etc. lead to different designs and implementations of systems that are built to embed those concepts. This means that if we want to design for control, freedom, trust, etc., we have to decide which conception we ought to use. When we determine what the appropriate conception of a concept is in a technological context and use this conception to operationalize a norm or value, we generate requirements which have real-world effects. This not only shows that conceptual engineering can be extremely impactful, the fact that it leads to different design requirements means that we have a way to evaluate our conceptual choices and that we can use this feedback loop to improve upon our conceptual work By illustrating the direct impacts of different conceptions on technology design, this paper underscores the practical applicability and value of conceptual engineering, demonstrating how it serves as a crucial bridge between abstract philosophical analysis and concrete technological innovation. (shrink)