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This review analyzes the most influential artificial intelligence (AI) studies in health and life sciences from the past three years, delineating the evolving role of AI in these fields. We identified and analyzed the top 50 cited articles on AI in biomedicine, revealing significant trends and thematic categorizations, including Drug Development, Real-World Clinical Implementation, and Ethical and Regulatory Aspects, among others. Our findings highlight a predominant focus on AIs application in clinical settings, particularly in diagnostics, telemedicine, and medical education, accelerated by the COVID-19 pandemic. The emergence of AlphaFold marked a pivotal moment in protein structure prediction, catalyzing a cascade of related research and signifying a broader shift towards AI-driven approaches in biological research. The review underscores AIs pivotal role in disease subtyping and patient stratification, facilitating a transition towards more personalized medicine strategies. Furthermore, it illustrates AIs impact on biology, particularly in parsing complex genomic and proteomic data, enhancing our capabilities to disentangle complex, interconnected molecular processes. As AI continues to permeate the health and life sciences, balancing its rapid technological advancements with ethical stewardship and regulatory vigilance will be crucial for its sustainable and effective integration into healthcare and research. [ABSTRACT FROM AUTHOR]

Artificial intelligence is more present than ever, both in our society in general and in science. At the center of this development has been the concept of deep learning, the use of artificial neural networks that are many layers deep and can often reproduce human‐like behavior much better than other machine‐learning techniques. The articles in this collection are some recent examples of its application for X‐ray photon science and crystallography that have been published in Journal of Applied Crystallography. [ABSTRACT FROM AUTHOR]

In recent decades, artificial intelligence has undergone transformative advancements, reshaping diverse sectors such as healthcare, transport, agriculture, energy, and the media. Despite the enthusiasm surrounding AI's potential, concerns persist about its potential negative impacts, including substantial energy consumption and ethical challenges. This paper critically reviews the evolving landscape of AI sustainability, addressing economic, social, and environmental dimensions. The literature is systematically categorized into "Sustainability of AI" and "AI for Sustainability", revealing a balanced perspective between the two. The study also identifies a notable trend towards holistic approaches, with a surge in publications and empirical studies since 2019, signaling the field's maturity. Future research directions emphasize delving into the relatively under-explored economic dimension, aligning with the United Nations' Sustainable Development Goals (SDGs), and addressing stakeholders' influence. [ABSTRACT FROM AUTHOR]

This paper investigates the complex interplay between generative artificial intelligence (AI) and human intellect in academic writing and publishing. It examines the 'organic versus synthetic' paradox, emphasizing the implications of using generative AI tools in educational and academic integrity contexts. The paper critiques the prevalent 'publish or perish' culture in academia, highlighting the need for systemic reevaluation due to generative AI's emerging role in academic writing and reporting. It delves into the legal and ethical challenges of authorship and ownership, especially in relation to copyright laws and AI-generated content. The paper discusses generative AI's diverse roles and advocates for transparent reporting to uphold academic integrity. Additionally, it calls for a broader examination of generative AI tools and stresses the need for new mechanisms to identify generative AI use and ensure adherence to academic integrity and ethics. The implications of generative AI are also explored, suggesting the need for innovative AI-inclusive strategies in academia. The paper concludes by emphasizing the significance of generative AI in various information-processing domains, highlighting the urgency to adapt and transform academic practices in an era of rapid generative AI-driven change. [ABSTRACT FROM AUTHOR]

This paper explores a paradigm shift in work culture in the contemporary art sector due to digital transition and the introduction of AI. New ways of working with AI and digital software are embedded and normalized in everyday Chinese artistic practices. This work includes new forms of creativity and efficiency, yet, simultaneously includes new types of digital labour. This paper conceptualizes this as "digital art work," which draws attention to the often-overlooked aspects of artists' work, particularly their everyday artistic practices that increasingly include digital software and AI. What is the role and position of the artist in an environment where digital software and AI are becoming more central in artistic creation? How do artists creatively (mis)use AI? What does this paradigm shift in work culture mean for the future of the artist's role and the future of the contemporary art sector? This paper draws on 48 semi-structured interviews with visual artists and arts professionals, including painters, sculptors, mixedmedia, and internet artists as well as contemporary art gallery owners, museum project directors, curators, and culture policymakers living and working in China during 2023. The findings show how Chinese artists are mastering AI and opening up new spaces for creativity and how the contemporary art sector in China has already transitioned to a new "digital way" in artistic creation. These findings can help to create policy around AI globally and provide solutions for the sustainability of the artist profession and the future of the contemporary art sector. [ABSTRACT FROM AUTHOR]

In recent years, the fusion of Artificial Intelligence (AI) with traditional sectors has catalyzed a paradigm shift that extends beyond technological advancements and reaches into the core of human learning and development. One such domain undergoing significant transformation is mental health education. This short conceptual paper seeks to examine the intricate relationship between AI and education in the context of mental health studies, shedding light on the challenges, opportunities, and ethical considerations that arise as teaching evolves in the Age of AI. This paper is not intended to serve as THE definitive solution to inquiries regarding the integration of AI/ChatGPT in mental health education. Rather, its purpose is to provide AN approach to contemplating this matter and to initiate further discussions within mental health-related fields about the utilization of AI and ChatGPT in education, given the persistent prominence of AI. [ABSTRACT FROM AUTHOR]