Related papers: The Ethical Knowledge Gap: Dispersed Knowledge, Se…
There are many ways we can not know. Even in systems that we created ourselves, as, for example, systems in mathematical logic, Go\"edel and Tarski's theorems impose limits on what we can know. As we try to speak of the real world, things…
Ethics is an ancient matter for human kind, from the origin of civilizations ethics have been related with the most relevant human concerns and determined cultures. Ethics was initially related to religion, politics and philosophy to then…
Incorporating responsible practices into software engineering (SE) for AI is essential to ensure ethical principles, societal impact, and accountability remain at the forefront of AI system design and deployment. This study investigates the…
Generative artificial intelligence systems increasingly participate in research, law, education, media, and governance. Their fluent and adaptive outputs create an experience of collaboration. However, these systems do not bear…
Epistemic modal logic normally views an epistemic situation as a Kripke model. We consider a more basic approach: to view an epistemic situation as a set W of possible states/worlds -- maximal consistent sets of propositions -- with…
Context: Using student subjects in empirical studies has been discussed extensively from a methodological perspective in Software Engineering (SE), but there is a lack of similar discussion surrounding ethical aspects of doing so. As…
Decisions suggested by improperly designed software systems might be prone to discriminate against people based on protected characteristics, such as gender and ethnicity. Previous studies attribute such undesired behavior to flaws in…
Knowledge sharing plays a crucial role throughout all software application development activities. When programmers learn and share through media like Stack overflow, GitHub, Meetups, videos, discussion forums, wikis, and blogs, every…
As automated decision making and decision assistance systems become common in everyday life, research on the prevention or mitigation of potential harms that arise from decisions made by these systems has proliferated. However, various…
Why do organizations comprised of intelligent individuals converge on collective delusion? This paper introduces dysmemic pressure as a formal mechanism explaining organizational epistemic failure. Synthesizing strategic communication…
Disagreements are widespread across the design, evaluation, and alignment pipelines of artificial intelligence (AI) systems. Yet, standard practices in AI development often obscure or eliminate disagreement, resulting in an engineered…
Context and Motivation: Software requirements are affected by the knowledge and confidence of software engineers. Analyzing the interrelated impact of these factors is difficult because of the challenges of assessing knowledge and…
We show how to assess a language model's knowledge of basic concepts of morality. We introduce the ETHICS dataset, a new benchmark that spans concepts in justice, well-being, duties, virtues, and commonsense morality. Models predict…
Temporal epistemic logic is a well-established framework for expressing agents knowledge and how it evolves over time. Within language-based security these are central issues, for instance in the context of declassification. We propose to…
To legitimize itself as a scientific discipline, the software engineering academic community must let go of its non-empirical dogmas. A dogma is belief held regardless of evidence. This paper analyzes the nature and detrimental effects of…
For visual content generation, discrepancies between user intentions and the generated content have been a longstanding problem. This discrepancy arises from two main factors. First, user intentions are inherently complex, with subtle…
In this paper we, an epistemologist and a machine learning scientist, argue that we need to pursue a novel area of philosophical research in AI - the ethics of belief for AI. Here we take the ethics of belief to refer to a field at the…
An epistemic model for decentralized discrete-event systems with non-binary control is presented. This framework combines existing work on conditional control decisions with existing work on formal reasoning about knowledge in…
A machine intelligence pipeline usually consists of six components: problem, representation, model, loss, optimizer and metric. Researchers have worked hard trying to automate many components of the pipeline. However, one key component of…
This paper investigates the inherent knowledge in language models from the perspective of epistemological holism. The purpose of this paper is to explore whether LLMs exhibit characteristics consistent with epistemological holism. These…