Glaze is a system designed to protect human artists by disrupting style mimicry. At a high level, Glaze works by understanding the AI models that are training on human art, and using machine learning algorithms, computing a set of minimal changes to artworks, such that it appears unchanged to human eyes, but appears to AI models like a dramatically different art style.
Midjourney neural network produces images from descriptions by learning from a variety of high-resolution images and transforming them into works of art. It creates a realistic image of a given description, and can be used to generate images for specific needs.
The rapid development of artificial-intelligence technology has brought to us promising image-generation models that can produce realistic fake images. Here, we show that such advanced generative models threaten the publishing system in academia as they may be used to generate fake scientific images that cannot be effectively identified
It is now possible to create detailed realistic images by typing in some text on a computer. These images can reflect gender and cultural biases of the thousands of images that the AI machine was trained on.
Images showing people of color in German military uniforms from World War II that were created with Google’s Gemini chatbot have amplified concerns that artificial intelligence could add to the internet’s already vast pools of misinformation as the technology struggles with issues around race.
As part of Intel's Responsible AI work, the company has productized FakeCatcher, a technology that can detect fake videos with a 96% accuracy rate. Intel’s deepfake detection platform is the world’s first real-time deepfake detector that returns results in milliseconds.
Deepfake technology is AI software that has the ability to create fictitious people that are difficult to distinguish from actual VIPs or celebrities and make them say or do things that are fabricated.
Current studies focus primarily on the detection and dangers of deepfakes. In contrast, less attention is paid to the potential of this technology for substantive research - particularly as an approach for controlled experimental manipulations in the social sciences. This paper aims to fill this research gap and argue that deepfakes can be a valuable tool for conducting social science experiments.