Ethical decision-making frameworks assist in identifying the issues at stake in a particular setting and thinking through, in a methodical manner, the ethical issues that require consideration as well as the values that need to be considered and promoted. Decisions made about the use, sharing, and re-use of big data are complex and laden with values. This paper sets out an Ethics Framework for Big Data in Health and Research developed by a working group convened by the Science, Health and (...) Policy-relevant Ethics in Singapore Initiative. It presents the aim and rationale for this framework supported by the underlying ethical concerns that relate to all health and research contexts. It also describes a set of substantive and procedural values that can be weighed up in addressing these concerns, and a step-by-step process for identifying, considering, and resolving the ethical issues arising from big data uses in health and research. This Framework is subsequently applied in the papers published in this Special Issue. These papers each address one of six domains where big data is currently employed: openness in big data and data repositories, precision medicine and big data, real-world data to generate evidence about healthcare interventions, AI-assisted decision-making in healthcare, public-private partnerships in healthcare and research, and cross-sectoral big data. (shrink)

In the context of climate change, this study uncovers the role of green airlines’ social responsibility in conjunction with the consumers’ switching behavior while considering the effects of latent variables, including green psychology, airline corporate image, green experimental behavior, green service fairness, green alternative attractiveness and switching intention, were examined in the study.

Cognitive scaffolding refers to external structures that change the cognitive demands of tasks. This dissertation begins by reviewing the literature around scaffolding—discussing key thinkers such as Hutchins (1995a), Clark (1997) and Sterelny (2003, 2010). I then develop the above scaffolding characterisation by drawing a distinction between shallow and deep scaffolding. Shallow scaffolding primarily involves cues, whereas deep scaffolding involves the significant offloading of cognitive work. By appealing to the complementarity thesis, I show that deep scaffolds can be explained through a (...) model of cognitive extension (Menary, 2006; Sutton, 2010). Most crucially, despite the abundance of benign/ neutral examples in the literature, I argue that scaffolding can also be ‘hostile’ to agents’ interests—benefitting one agent while undermining another. I draw on Sterelny (2003) to clarify my use of the word ‘hostile’ and also specify what I mean by ‘interests’. I then review authors with similar concerns to my own—i.e., the lack of discussion around external structures that negatively impact agents (Aagaard, 2020; Liao & Huebner, 2020; Slaby, 2016). Despite these authors’ concerns, the idea of ‘hostile scaffolding’ is not quite reached. I then present examples of shallow hostile scaffolding by reviewing how sunglasses (Viola, 2022) and casino interior design and ambience (Friedman, 2000; Schüll, 2012) can be hostile. Most importantly, I show that deep hostile scaffolding is a genuine concern (and not only a theoretical one) by reviewing gambling machines that use player tracking systems and virtual reel mapping (Schüll, 2012), as well as Twitter’s use of gamification (Nguyen, 2021). I close the dissertation by discussing avenues for future hostile scaffolding research. This includes the ethical implications deep hostile scaffolding, scaffolding’s role in forming addictive behavior, other instance of gamification, ‘racist scaffolding’, and hostile scaffolding in developing technologies (such as VR, dark patterns and AI). (shrink)