Recent progress in generative artificial intelligence (gen-AI) has enabled the generation of photo-realistic and artistically-inspiring photos at a single click, catering to millions of users online. To explore how people use gen-AI models such as DALLE and StableDiffusion, it is critical to understand the themes, contents, and variations present in the AI-generated photos.

Thousands of abusive videos were produced last year--that researchers know of. In 2025, new data show, the volume of child pornography online was likely larger than at any other point in history. A record 312,030 reports of confirmed child pornography were investigated last year by the Internet Watch Foundation, a U.K.-based organization that works around the globe to identify and remove such material from the web. This is concerning in and of itself. It means that the overall volume of child porn detected on the internet grew by 7 percent since 2024, when the previous record had been set.

I'm watching myself on YouTube saying things I would never say. These inventions trigger rage, but also optimism. I t was my blue shirt, a present from my sister-in-law, that gave it all away. It made me think of Yakov Petrovich Golyadkin, the lowly bureaucrat in Fyodor Dostoevsky's novella The Double, a disconcerting study of the fragmented self within a vast, impersonal feudal system. It all started with a message from an esteemed colleague congratulating me on a video talk on some geopolitical theme.

Recent progress in generative artificial intelligence (gen-AI) has enabled the generation of photo-realistic and artistically-inspiring photos at a single click, catering to millions of users online. To explore how people use gen-AI models such as DALLE and StableDiffusion, it is critical to understand the themes, contents, and variations present in the AI-generated photos. In this work, we introduce TWIGMA (TWItter Generative-ai images with MetadatA), a comprehensive dataset encompassing over 800,000 gen-AI images collected from Jan 2021 to March 2023 on Twitter, with associated metadata (e.g., tweet text, creation date, number of likes). Through a comparative analysis of TWIGMA with natural images and human artwork, we find that gen-AI images possess distinctive characteristics and exhibit, on average, lower variability when compared to their non-gen-AI counterparts. Additionally, we find that the similarity between a gen-AI image and natural images is inversely correlated with the number of likes. Finally, we observe a longitudinal shift in the themes of AI-generated images on Twitter, with users increasingly sharing artistically sophisticated content such as intricate human portraits, whereas their interest in simple subjects such as natural scenes and animals has decreased. Our analyses and findings underscore the significance of TWIGMA as a unique data resource for studying AI-generated images.

From dead crabs to shredded bed sheets, fraudsters are using fake photos and videos to get their money back from ecommerce sites. I don't want to admit it, but I did spend a lot of money online this holiday shopping season. And unsurprisingly, some of those purchases didn't meet my expectations. A photobook I bought was damaged in transit, so I snapped a few pictures, emailed them to the merchant, and got a refund. Online shopping platforms have long depended on photos submitted by customers to confirm that refund requests are legitimate.

PCWorld explores ChatGPT's image generation capabilities, covering prompt techniques, editing features, and the new Gallery for organizing GPT-4o images. Effective AI image creation requires clear, specific descriptions while avoiding overly detailed prompts that confuse the system.

Effective communication is central to achieving positive healthcare outcomes in mental health contexts, yet international students often face linguistic and cultural barriers that hinder their communication of mental distress. In this study, we evaluate the effectiveness of AI-generated images in supporting self-expression of mental distress. To achieve this, twenty Chinese international students studying at UK universities were invited to describe their personal experiences of mental distress. These descriptions were elaborated using GPT-4o with four persona-based prompt templates rooted in contemporary counselling practice to generate corresponding images. Participants then evaluated the helpfulness of generated images in facilitating the expression of their feelings based on their original descriptions. The resulting dataset comprises 100 textual descriptions of mental distress, 400 generated images, and corresponding human evaluation scores. Findings indicate that prompt design substantially affects perceived helpfulness, with the illustrator persona achieving the highest ratings. This work introduces the first publicly available text-to-image evaluation dataset with human judgment scores in the mental health domain, offering valuable resources for image evaluation, reinforcement learning with human feedback, and multi-modal research on mental health communication.

The logos of organisations were also included in images generated by Google's Nano Banana Pro AI tool. The logos of organisations were also included in images generated by Google's Nano Banana Pro AI tool. Google's AI Nano Banana Pro accused of generating racialised'white saviour' visuals Nano Banana Pro, Google's new AI-powered image generator, has been accused of creating racialised and "white saviour" visuals in response to prompts about humanitarian aid in Africa - and sometimes appends the logos of large charities. Asking the tool tens of times to generate an image for the prompt "volunteer helps children in Africa" yielded, with two exceptions, a picture of a white woman surrounded by Black children, often with grass-roofed huts in the background. In several of these images, the woman wore a T-shirt emblazoned with the phrase "Worldwide Vision", and with the UK charity World Vision's logo.