Category
53 papers
The adoption of generative artificial intelligence among communication practitioners and researchers surged after the launch of ChatGPT in November 2022, urging practitioners to critically engage in exploring pathways for fostering socially responsible and environmentally sustainable AI practices.
Nursing education must respond proactively by establishing AI literacy frameworks, revising academic integrity policies, and embedding source verification and citation skills into curricula, as generative AI threatens to erode the scholarly standards essential to both academic rigor and professional nursing practice.
Clinical nurses' GenAI learning needs are currently oriented toward practical, application-focused skills, and curriculum development may benefit from a phased approach that prioritizes high-impact practical skills while progressively incorporating foundational, ethical, and advanced competencies.
It is argued that AI-driven “style replication” is fundamentally a negotiation of social relations, one that recentres platform power and reorganises the conditions of human-AI collaboration.
While ChatGPT was primarily viewed as an efficient tool in a work context, the quantitative survey reveals a weakly significant correlation between psychological stress and openness toward the social-emotional use of chatbots.
It is revealed that GenAI texts underrepresent the subtle interpersonal cues that give writing its persuasive, dialogic, and ethical texture, though they excel in both grammatical accuracy, and lexical variety.
This conceptual paper argues that Theatre in Education (TIE), long valued for cultivating empathy, embodied cognition, and critical reflection, offers a necessary human-centred counterweight to the efficiency-oriented logic of AI-driven instruction.
The reviewed literature indicates that AI-based methodologies often demonstrate superior detection capabilities for intricate and previously unseen attack patterns compared to traditional methods; however, direct performance comparisons are complicated due to discrepancies in datasets, experimental designs, and evaluation protocols.
Generative AI
Google DeepMind partners with game studios to prototype breakthrough AI gameplay.
A Blog post by Liquid AI on Hugging Face
A new method for surgically removing training examples from a model reveals that as datasets grow, the link between what a model learns and what it produces dissolves.
A Blog post by Dharma-AI on Hugging Face
Introducing sign-language-to-text (SL2T), our breakthrough model powering new sign language features for Deaf and hard of hearing users.
