Lessons learned from assessing trustworthy AI in practice
Building artificial intelligence (AI) systems that adhere to ethical standards is a complex
problem. Even though a multitude of guidelines for the design and development of such …
problem. Even though a multitude of guidelines for the design and development of such …
[HTML][HTML] Co-designing opportunities for Human-Centred Machine Learning in supporting Type 1 diabetes decision-making
Abstract Type 1 Diabetes (T1D) self-management requires hundreds of daily decisions.
Diabetes technologies that use machine learning have significant potential to simplify this …
Diabetes technologies that use machine learning have significant potential to simplify this …
Using sentence embeddings and semantic similarity for seeking consensus when assessing trustworthy ai
Assessing the trustworthiness of artificial intelligence systems requires knowledge from
many different disciplines. These disciplines do not necessarily share concepts between …
many different disciplines. These disciplines do not necessarily share concepts between …
From the ground truth up: doing AI ethics from practice to principles
J Brusseau - AI & SOCIETY, 2023 - Springer
Recent AI ethics has focused on applying abstract principles downward to practice. This
paper moves in the other direction. Ethical insights are generated from the lived experiences …
paper moves in the other direction. Ethical insights are generated from the lived experiences …
From Principles to Practice: Comparative Analysis of European and United States Ethical AI Frameworks for Assessment and Methodological Application
CM Pierson, E Hildt - … of the Association for Information Science …, 2023 - Wiley Online Library
ABSTRACT The Z‐Inspection® Process is a form of applied research for the ethical
assessment of AI systems. It is quickly establishing itself as a robust method to ethically …
assessment of AI systems. It is quickly establishing itself as a robust method to ethically …