This paper intends to contribute to the emerging literature on the ethical problems posed by quantum computing and quantum technologies in general. The key ethical questions are as follows: Does quantum computing pose new ethical problems, or are those raised by quantum computing just a different version of the same ethical problems raised by other technologies, such as nanotechnologies, nuclear plants, or cloud computing? In other words, what is new in quantum computing from an ethical point of view? The paper (...) aims to answer these two questions by (a) developing an analysis of the existing literature on the ethical and social aspects of quantum computing and (b) identifying and analyzing the main ethical problems posed by quantum computing. The conclusion is that quantum computing poses completely new ethical issues that require new conceptual tools and methods. (shrink)

Epidemiological models directly shape policy responses to public health crises. We argue that they also play a less obvious but important role in solving certain coordination problems and social dilemmas that arise during pandemics. This role is both ethically and epistemically valuable. However, it also gives rise to an underappreciated dilemma, as the features that make models good at solving coordination problems are often at odds with the features that make for a good scientific model. We examine and develop this (...) dilemma in the context of the COVID-19 pandemic, and suggest extensions to other domains. (shrink)

Several science studies scholars report instances of scientific “hype,” or sensationalized exaggeration, in journal articles, institutional press releases, and science journalism in a variety of fields (e.g., Caulfield and Condit 2012). Yet, how “hype” is being conceived varies. I will argue that hype is best understood as a particular kind of exaggeration, one that explicitly or implicitly exaggerates various positive aspects of science in ways that undermine the goals of science communication in a particular context. This account also makes clear (...) the ways that value judgments play a role in judgments of “hype,” which has implications for detecting and addressing this problem. (shrink)

Despite facing significant criticism for assigning human-like characteristics to artificial intelligence, phrases like “trustworthy AI” are still commonly used in official documents and ethical guidelines. It is essential to consider why institutions continue to use these phrases, even though they are controversial. This article critically evaluates various reasons for using these terms, including ontological, legal, communicative, and psychological arguments. All these justifications share the common feature of trying to justify the official use of terms like “trustworthy AI” by appealing to (...) the need to reflect pre-existing facts, be it the ontological status, ways of representing AI or legal categories. The article challenges the justifications for these linguistic practices observed in the field of AI ethics and AI science communication. In particular, it takes aim at two main arguments. The first is the notion that ethical discourse can move forward without the need for philosophical clarification, bypassing existing debates. The second justification argues that it’s acceptable to use anthropomorphic terms because they are consistent with the common concepts of AI held by non-experts—exaggerating this time the existing evidence and ignoring the possibility that folk beliefs about AI are not consistent and come closer to semi-propositional beliefs. The article sounds a strong warning against the use of human-centric language when discussing AI, both in terms of principle and the potential consequences. It argues that the use of such terminology risks shaping public opinion in ways that could have negative outcomes. (shrink)