Introduction to ‘Making the most of AI’s potential: cross-disciplinary perspectives on the role of AI in science and society’
Year: 2024
Type: article
Abstract: We are pleased to introduce a special cross-disciplinary collection of manuscripts in Royal Society Open Science entitled 'Making the most of AI's potential: cross-disciplinary perspectives on the role of AI in science and society'.This collection of papers explores the use of machine learning, artificial intelligence (AI) and Big Data within science and society.These evolving fields will play an increasingly prominent part in not only the daily lives of individuals and societies, but also in how science is conducted, reported and applied.The papers bring together expert views on the applications and implications of these computational and statistical techniques.They also explore how science and societies will respond to these developments, alongside some of the ethical considerations the new technologies will bring to the fore.We, the Editors of the Computer Science & Artificial Intelligence, Mathematics, and Psychology & Cognitive Neuroscience sections of Royal Society Open Science, commissioned this collection back in early 2020 to mark 10 years since the rise of the new era of AI.Unfortunately, the COVID-19 pandemic and subsequent lockdown caused an unprecedented delay, and the collection was temporarily halted.After 4 years, we are delighted to finally showcase the extraordinary depth and breadth of the research community within the field.The papers initially published in this collection were invited by the Editors.However, no one could have predicted the tremendous developments in AI that occurred in the last couple of years and, to account for this, we would welcome future submissions.Subsequently, our long-term aim is to make this a 'living collection'.We, therefore, anticipate seeing a constant
Source: Royal Society Open Science
DOI: 10.1098/rsos.241306
Authors: Marta Kwiatkowska, Mark Chaplain, Essi Viding
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,471
OpenAlex ID: W4402461875