Climate change is an existential risk reinforced by ordinary actions in afuent societies—often silently present in comfortable and enjoyable habits. This silence is sometimes broken, presenting itself as a nagging reminder of how our habits fuel a catastrophe. As a case in point, global warming has created a state of urgency among wine makers in Spain, as the alcohol level has risen to a point where it jeopardises wine quality and thereby Spanish viticulture. Eforts are currently being made to solve (...) this problem technologically by developing (non-GMO) strains of yeast that produce less alcohol. If successful, this could help save Spanish viticulture. This kind of technological solution is routinely criticised for ofering simplistic “techno-fx” solutions to solve complex societal problems. However, it is not clear what features are criticised by the notion of techno-fx and hence how to avoid this criticism. In our interpretation, the techno-fx notion is not exclusively used as a dismissive term. The notion points to a general virtue of engineering: to create technological solutions that work silently in the background. This asset of technological solutions might sometimes be problematic and sometimes not. Hence, it needs to be analysed case-by-case by paying attention to the moral relevance of the hidden implications of the technology and of the unrefective actions and habits that they facilitate. Such moral analysis will in turn inform strategies for foregrounding this technology to counteract silencing. We discuss what this means in the case of modifying yeast as a viticultural climate resilience strategy. (shrink)

This paper investigates the relationships between organizational change and trust in management. It is argued that organizational change represents a critical episode for the production and destruction of trust in management. Although trust in management is seen as a semi stable psychological state, changes in organizations make trust issues salient and organizational members attend to and process trust relevant information resulting in a reassessment of their trust in management. The direction and magnitude of change in trust is dependent on a (...) set of change dimensions that reflect trust relevant experiences and information. We distinguish between dimensions related to trust relevant consequences of the change and trust relevant aspects of how the change process is performed. Empirical results indicate that increases in post change emotional stress and the use of referential accounts for justifying change are both negatively related to post change trust in management. The use of ideological accounts and participation were found to be positively related to post change trust in management, so was perceived decision quality. Findings also indicate that the effects of change on trust are negatively moderated by tenure. (shrink)

Trust has a great potential for furthering our understanding of organizational change and learning. This potential however remains largely untapped. It is argued that two reasons as for why this potential remains unrealized are: (i) A narrow conceptualization of change as implementation and (ii) an emphasis on direct and aggregated effects of individual trust to the exclusion of other effects. It is further suggested that our understanding of the effects of trust on organizational change, should benefit from including effects of (...) trust on the formulation stage. It should also benefit from exploring the structuring effects of trust in organizations. Throughout this chapter, ways to extend current research on trust in organizations are suggested. The chapter also provides examples of relevant contributions where available. In order to capture organizational effects of trust, it is suggested that trust should be studied over longer time intervals, and include several referents of trust, spanning both horizontal and vertical relationships in the organization. (shrink)

Many authors have proposed constraining the behaviour of intelligent systems with ‘machine ethics’ to ensure positive social outcomes from the development of such systems. This paper critically analyses the prospects for machine ethics, identifying several inherent limitations. While machine ethics may increase the probability of ethical behaviour in some situations, it cannot guarantee it due to the nature of ethics, the computational limitations of computational agents and the complexity of the world. In addition, machine ethics, even if it were to (...) be ‘solved’ at a technical level, would be insufficient to ensure positive social outcomes from intelligent systems. (shrink)

Concerns about threats to human autonomy feature prominently in the field of AI ethics. One aspect of this concern relates to the use of AI systems for problematically manipulative influence. In response to this, the European Union’s draft AI Act (AIA) includes a prohibition on AI systems deploying subliminal techniques that alter people’s behavior in ways that are reasonably likely to cause harm (Article 5(1)(a)). Critics have argued that the term ‘subliminal techniques’ is too narrow to capture the target cases (...) of AI-based manipulation. We propose a definition of ‘subliminal techniques’ that (a) is grounded on a plausible interpretation of the legal text; (b) addresses all or most of the underlying ethical concerns motivating the prohibition; (c) is defensible from a scientific and philosophical perspective; and (d) does not over-reach in ways that impose excessive administrative and regulatory burdens. The definition is meant to provide guidance for design teams seeking to pursue responsible and ethically aligned AI innovation. (shrink)

With increasing publication and data production, scientific knowledge presents not simply an achievement but also a challenge. Scientific publications and data are increasingly treated as resources that need to be digitally ‘managed.’ This gives rise to scientific Knowledge Management : second-order scientific work aiming to systematically collect, take care of and mobilise first-hand disciplinary knowledge and data in order to provide new first-order scientific knowledge. We follow the work of Leonelli, Efstathiou and Hislop in our analysis of the use of (...) KM in semantic systems biology. Through an empirical philosophical account of KM-enabled biological research, we argue that KM helps produce new first-order biological knowledge that did not exist before, and which could not have been produced by traditional means. KM work is enabled by conceiving of ‘knowledge’ as an object for computational science: as explicated in the text of biological articles and computable via appropriate data and metadata. However, these founded knowledge concepts enabling computational KM risk focusing on only computationally tractable data as knowledge, underestimating practice-based knowing and its significance in ensuring the validity of ‘manageable’ knowledge as knowledge. (shrink)