What is morally at stake when using algorithms to make medical diagnoses? Expanding the discussion beyond risks and harms

In this paper, we examine the qualitative moral impact of machine learning-based clinical decision support systems in the process of medical diagnosis. To date, discussions about machine learning in this context have focused on problems that can be measured and assessed quantitatively, such as by estimating the extent of potential harm or calculating incurred risks. We maintain that such discussions neglect the qualitative moral impact of these technologies. Drawing on the philosophical approaches of technomoral change and technological mediation theory, which explore the interplay between technologies and morality, we present an analysis of concerns related to the adoption of machine learning-aided medical diagnosis. We analyze anticipated moral issues that machine learning systems pose for different stakeholders, such as bias and opacity in the way that models are trained to produce diagnoses, changes to how health care providers, patients, and developers understand their roles and professions, and challenges to existing forms of medical legislation. Albeit preliminary in nature, the insights offered by the technomoral change and the technological mediation approaches expand and enrich the current discussion about machine learning in diagnostic practices, bringing distinct and currently underexplored areas of concern to the forefront. These insights can contribute to a more encompassing and better informed decision-making process when adapting machine learning techniques to medical diagnosis, while acknowledging the interests of multiple stakeholders and the active role that technologies play in generating, perpetuating, and modifying ethical concerns in health care.

Timbre, Rhythm, and Texture within Music Theory’s White Racial Frame

This chapter discusses music theory’s neglect of EDM as it relates to the dominant methodologies of the field and Philip Ewell’s concept of the white racial frame, arguing that EDM is overlooked due to implicit biases against racial Otherness and against technological mediation, biases that runs deep enough in US culture to have impacted the trajectory of music theory as an academic field. The chapter examines unpitched percussion through analysis of performance, timbre, and texture in a Roland TR-909 drum machine “workout” performed by Jeff Mills. This analysis models one way that music theory might learn to take EDM seriously. By broadening the methodological toolbox, music theory can begin to course-correct and become more inclusive of music that challenges certain principles of Western music.

Postphenomenological Method and Technological Things Themselves

We live in a world where it is impossible to exist without, and beyond, technologies. Despite this omnipresence, we tend to overlook their influence on us. The vigorously developing approach of postphenomenology, combining insights from phenomenology and pragmatism, focuses on the so-called technological mediation, i.e., on how technologies as mediators of human-world relations influence the appearing of both the world and the human beings in it. My analysis aims at demonstrating both the methodological weaknesses and open possibilities of postphenomenology. After summarizing its essentials, I will scrutinize, first, its ability to turn to the technological things themselves and, second, the so-called empirical turn as realized by postphenomenology. By assessing its conceptual framework from the phenomenological perspective, I hope to demonstrate that postphenomenology needs philosophical clarification and strengthening. In short, it needs a more phenomenological, and less pragmatic, approach to technology in its influence on human experience.

Aligning artificial intelligence with human values: reflections from a phenomenological perspective

Artificial Intelligence (AI) must be directed at humane ends. The development of AI has produced great uncertainties of ensuring AI alignment with human values (AI value alignment) through AI operations from design to use. For the purposes of addressing this problem, we adopt the phenomenological theories of material values and technological mediation to be that beginning step. In this paper, we first discuss the AI value alignment from the relevant AI studies. Second, we briefly present what are material values and technological mediation and reflect on the AI value alignment through the lenses of these theories. We conclude that a set of finite human values can be defined and adapted to the stable life tasks that AI systems will be called upon to accomplish. The AI value alignment can also be fostered between designers and users through technological mediation. Upon that foundation, we propose a set of common principles to understand the AI value alignment through phenomenological theories. This paper contributes the unique knowledge of phenomenological theories to the discourse on AI alignment with human values.

Using game theory to support the audience participation in digital performances

Public participation in art performances has been leveraged by the use of technology as a mediating element between the public and artists. However, technological mediation alone may not be enough to ensure effective auditory participation. In this article, we present the performance “ O Chaos das 5 ”, an audiovisual digital performance with a strong technological support that had the support of game theory to achieve a more effective participation of the audience in their presentations.

Airplanes, cameras, computers, wildebeests: The technological mediation of spaces for humans and wildlife in the Serengeti since 1950

Drawing on the concept of technological mediation, this article examines the spatial politics of observation technologies and associated practices that have been used to monitor the movement of migratory wildebeests in the Serengeti from the 1950s until the 2000s. It shows that key technologies, and the types of research collaborations they sustained, mediated notably different normative ideas about human–wildlife interaction and the sharing of space in and around protected areas. During the 1950s and 1960s, observations of animal migration were conducted by airplane. Direct observation was characterized by the study of movement of migratory ungulates, such as the wildebeest, and humans across space in real time. Aerial observations depended on a close cooperation between scientists and park authorities, and on the knowledge and observational skills of game wardens. The experience of the movement of animals and people in real time allowed, to some degree, for experimentation with forms of human land-use. During the 1970s, many small-scale and short-term projects shifted the research focus toward data recording by camera. Aerial photographs created supposedly complete spatial overviews of inhabitation, which supported interpretations of spatial conflicts between humans occupying the park’s surrounding areas and animal populations inside the park. From the 1980s onward, computer technology allowed for long-term calculations of past and future trends in population densities of individual species. The understanding of the wildebeest as a keystone species and the Serengeti as a baseline ecosystem turned communities of local pastoralists and agriculturalists into a future threat. As observation technologies are here to stay, it remains important to pay attention to technologies’ potential roles in creating additional distances between researchers and research subjects. Historical insights, such as the ones presented in this article, can help reflect on how various forms of remote sensing may mediate normative views on human–wildlife interactions and consequentially affect local livelihoods.