Digital Image

This paper considers the ontological significance of invisibility in relation to the question ‘what is a digital image?’ Its argument in a nutshell is that the emphasis on visibility comes at the expense of latency and is symptomatic of the style of thinking that dominated Western philosophy since Plato. This privileging of visible content necessarily binds images to linguistic (semiotic and structuralist) paradigms of interpretation which promote representation, subjectivity, identity and negation over multiplicity, indeterminacy and affect. Photography is the case in point because until recently critical approaches to photography had one thing in common: they all shared in the implicit and incontrovertible understanding that photographs are a medium that must be approached visually; they took it as a given that photographs are there to be looked at and they all agreed that it is only through the practices of spectatorship that the secrets of the image can be unlocked. Whatever subsequent interpretations followed, the priori- ty of vision in relation to the image remained unperturbed. This undisputed belief in the visibility of the image has such a strong grasp on theory that it imperceptibly bonded together otherwise dissimilar and sometimes contradictory methodol- ogies, preventing them from noticing that which is the most unexplained about images: the precedence of looking itself. This self-evident truth of visibility casts a long shadow on im- age theory because it blocks the possibility of inquiring after everything that is invisible, latent and hidden

Do we really care about artificial intelligence? A review on social transformations and ethical challenges of AI for the 21st century

Although Artificial Intelligence (AI) is based on research from the 20th century, computation and new algorithms have only recently allowed AI to gain momentum and practical applications in society. Examples of such uses include self-driving cars and autonomous robots that are changing society and how we interact. Despite these advances, the discussion about the social transformations and ethical implications of this new reality remains scarce. This chapter reviews the current stance of ethical and social transformation discussions on AI and presents a framework for future developments. The main contributions of the chapter allow researchers to understand the major gaps in research that may be explored further in this topic and allow practitioners to gain a better picture of how AI may change society in the near future and how society should prepare for those changes.info:eu-repo/semantics/acceptedVersio

Comparing Grounded Theory and Topic Modeling: Extreme Divergence or Unlikely Convergence?

Researchers in information science and related areas have developed various methods for analyzing textual data, such as survey responses. This article describes the application of analysis methods from two distinct fields, one method from interpretive social science and one method from statistical machine learning, to the same survey data. The results show that the two analyses produce some similar and some complementary insights about the phenomenon of interest, in this case, nonuse of social media. We compare both the processes of conducting these analyses and the results they produce to derive insights about each method\u27s unique advantages and drawbacks, as well as the broader roles that these methods play in the respective fields where they are often used. These insights allow us to make more informed decisions about the tradeoffs in choosing different methods for analyzing textual data. Furthermore, this comparison suggests ways that such methods might be combined in novel and compelling ways

The Perceived Ethics of Artificial Intelligence

Artificial Intelligence (AI) is being used by millions of consumers in their daily lives. Although this technology is providing convenience, information, and instant gratification the underlying moral framework that AI uses remains largely unknown to the consumers of the technology. Two of the mostly widely used moral approaches (deontology and teleology), and their implications for AI, are discussed. The context of chatbots that use AI is examined, specifically exploring Amazon’s Alexa. The context illustrates the issue of the latent moral frameworks that AI technologies use when interacting with consumers or the environment. Although AI holds the promise of many potential benefits, they may come at a cost currently unknown to consumers. Globalization concerns and potential solutions are discussed

Docility and “through doing” morality: An alternative approach to ethics

In this paper, we aim at presenting the distributed morality approach as it can be described by the docility model of social interactions. The proposition “morality is a matter of social interaction” constitutes our starting point. We aim at pointing out the ways through which individuals create moral alternatives to a given situation. The paper is dedicated to presenting morality as something connected to human cognition. We introduce a “manipulative” way of thinking about morality, and we argue that it is “distributed” through things, animals, computers, and other human beings (section I); furthermore, the idea of a type of “through doing” morality comes up. Then, we find that this model supports an alternative view of the socio-economic system and, therefore, we suggest that the docility model (section II, as amended from Simon’s original model 1990; 1993), fits the case. The field of business ethics exempts useful insights from research on this issue. Recent studies on moral thinking and moral imagination seem to support this research project.cognition, distributed morality, docility, social interactions, socioeconomic system