AI ethics on Thursday, 1 January 2026

Background: Automated brain tumor segmentation on multi-parametric magnetic resonance imaging (mpMRI) is crucial in assessing patient outcomes and remains a challenge across Sub-Saharan Africa (SSA). Since 2012, the Brain Tumor Segmentation (BraTS) Challenge has evaluated state-of-the-art artificial intelligence (AI) methods to detect, characterize, and classify tumors. However, it is unclear if these methods can generalize, and hence be widely implemented, in SSA populations. To address this, t

With the advent of Large Language Models (LLMs), medical artificial intelligence (AI) has experienced substantial technological progress and paradigm shifts, highlighting the potential of LLMs to streamline healthcare delivery and improve patient outcomes. Considering this rapid technical progress, in this survey, we trace the recent advances of Medical Large Language Models (Med-LLMs), including the background, key findings, and mainstream techniques, especially for the evolution from general-p

Quantum computing is considered to have tremendous potential to help take the emerging field of "Computational Law" to the next level of growth in terms of the expression and implementation of legal principles. With the promise of quantum technology's increasing influence on the legal industry in mind, this essay utilizes the emerging field of Computational Complexity Theory to explore the types of problems that quantum computing is capable of solving more efficiently than classical computing, w

Artificial intelligence (AI) is increasingly embedded in education through adaptive platforms, intelligent tutoring systems, and generative tools. While these technologies promise efficiency and personalization, they also raise concerns about pedagogical deskilling, reduced teacher autonomy, and ethical risks. This paper conceptualizes the potential impacts of AI on teaching expertise and instructional design through the lens of Cognitive Load Theory (CLT). The aim is to conceptualize how AI may

As an important development in CALL, artificial intelligence (AI)-assisted foreign language teaching not only offers unique advantages in leveled reading, vocabulary, pronunciation, self-assessment, personalized testing, and information retrieval but also effectively enhances learner interaction and emotional regulation in reading. Despite these advancements, research on learner emotional engagement in AI-augmented EFL reading instruction remains limited, and there is a lack of sufficient empiri

BACKGROUND: With the continuous advancement of cancer treatment technology, the proportion of cancer survivors is gradually increasing, but they also face many psychological challenges. These challenges can seriously affect their quality of life. Telemedicine, as an innovative medical service model, can be combined with psychosocial intervention to provide cancer survivors with convenient, economical and accessible services to assist them in more effectively managing the difficulties posed by ca

Unified Natural Ethics Theory (UNET) offers a trace-sourced account of why ethical and unethical behavior occur, not merely how such behavior should be judged after the fact. UNET argues that ethics is not fundamentally an externally imposed, mind-dependent, doctrine-dependent, or deity-dependent phenomenon, but a trace-sourced emergent coherence dynamic inherent to informational propagation itself. It frames ethics as an informational, emergent, evolutive, and propagative modulation regime: a c

Detection, classification, and localisation of animal sounds are essential in many ecological studies, including density estimation and behavioural studies. Real-time acoustic processing can also be used in mitigation exercises, with the possibility of curtailing harmful human activities when animals are present. Animal vocalisations vary widely, and there is no single detection algorithm that can robustly detect all sound types. Human-in-the loop analysis is often required to validate algorithm

Integrating artificial intelligence (AI) into higher education can revolutionise traditional learning paradigms by enhancing self-directed learning and fostering student autonomy. This systematic research paper examines the role of AI in supporting these educational shifts, analysing its impact on student engagement, personalised learning experiences and academic performance. Through a comprehensive review of existing literature, this study explores various AI-driven tools and applications that

Abstract As Artificial Intelligence (AI) continues to transform the public sector, particularly in the domain of public deliberation and democratic governance, it also presents distinct challenges. This chapter explores the insights from the ORBIS project, which is situated at the intersection of AI technology and democratic processes. The chapter will critically present and discuss how the project is contributing to advance AI-enhanced democratic and inclusive deliberations by developing AI too