Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
Quality follows upgrading
Tag: Artificial Intelligence in Healthcare and Education
This viewpoint article first explores the ethical challenges associated with the future application of large language models (LLMs) in the context of medical education. These …
The legal and ethical issues that confront society due to Artificial Intelligence (AI) include privacy and surveillance, bias or discrimination, and potentially the philosophical challenge …
We argue why interpretability should have primacy alongside empiricism for several reasons: first, if machine learning (ML) models are beginning to render some of the …
Abstract As the efficacy of artificial intelligence (AI) in improving aspects of healthcare delivery is increasingly becoming evident, it becomes likely that AI will be …
The utilization of artificial intelligence (AI) applications has experienced tremendous growth in recent years, bringing forth numerous benefits and conveniences. However, this expansion has also …
Abstract Artificial Intelligence (AI)‐based systems are widely employed nowadays to make decisions that have far‐reaching impact on individuals and society. Their decisions might affect everyone, …
The increasing role of Artificial Intelligence in the area of medical science, transportation, aviation, space, education, entertainment (music, art, games, and films), industry, and many …
In the global debate about the use of Natural Language Processing (NLP)-based tools such as ChatGPT in healthcare decisions, the question of their use as …
This article summarizes best practices by organizations to manage their data, which should encompass the full range of responsibilities borne by the use of data …
Abstract The purpose of this research is to identify and evaluate the technical, ethical and regulatory challenges related to the use of Artificial Intelligence (AI) …