Taylor & Francis announces innovative multimedia resources to support readers of Developing Little Minds books
Book Announcement
This month, we’re focusing on artificial intelligence (AI), a topic that continues to capture attention everywhere. Here, you’ll find the latest research news, insights, and discoveries shaping how AI is being developed and used across the world.
Updates every hour. Last Updated: 3-Nov-2026 02:17 ET (3-Nov-2026 07:17 GMT/UTC)
New research from University of Limerick has found gender bias in the workplace could be replicated in interactions with artificial intelligence.
The study, co-authored by Dr Mary Hausfeld of UL's Kemmy Business School, examined whether the way Artificial intelligence (AI) assistants are presented influences how people treat them in a workplace setting.
Researchers placed 189 workers in a virtual reality office and asked them to complete work-related tasks with different AI assistants, including human-like agents presented with either male or female appearance.
Participants were then given real money to divide between themselves and the AI assistant for completing the tasks, allowing the researchers to recreate a real-world transaction and examine how much people were willing to pay AI for its work.
AI agents with a female appearance were paid less than their male-presenting counterparts, despite using the same underlying technology, according to the research.
A new review in National Science Review unveils anti-visual perception as a cross-disciplinary arms race spanning biomimetics, spectral physics, and AI. From snow leopards and dazzle camouflage to UV-to-microwave signature control and adversarial attacks on machine vision, it reveals how every advance in seeing drives new ways of hiding—offering a roadmap for next-generation camouflage, stealth, robust sensing, and trustworthy AI.
Artificial Intelligence (AI) can predict judicial decisions, but can it explain how they are legally jusitified, and can judges trust it? A Perspective in National Science Review argues that legal computing requires higher interpretability and reliability, and judicial values should be embedded into model and algorithm design. It outlines a value-guided framework within a “society–law–ethics–algorithms–data” system and identifies three scenario-specific applications: legislation, feedback-validated enforcement and trustworthy, human-centered adjudication. The Perspective further suggests that combining empirical learning with formal reasoning may offer a particularly promising path forward.
The American Academy of Pediatrics has published guidance for pediatricians on the safe, equitable, and effective use of generative artificial intelligence (AI), acknowledging that the rapidly emerging tools offer both promise and risk.