GENERATIVE AI CHALLENGES While generative artificial intelligence models such as ChatGPT, DALL-E 2, and Stable Diffusion are rapidly advancing, this has both excited people and brought up urgent concerns. As it becomes more widely used, this potent technology—which can produce text, images, and other media on demand that resemble human content—may have many advantages, but it still faces serious obstacles related to prejudice, false information, and hazardous content. Download PDF: https://www.marketsandmarkets.com/industry-practice/RequestForm.asp?page=Generative%20AI. Although these systems exhibit seemingly magical abilities at times, their internal mechanisms are still unclear and susceptible to biases ingrained in their training data. Research has previously discovered problems with the stereotyping of marginalized groups, the creation of harmful, toxic outputs when prompted, and the assertion of falsehoods in an authoritative manner. Critics contend that much greater transparency and oversight are necessary, particularly for public deployment, despite the fact that tech companies are racing to use AI safety research and moderation to curb these issues. Dr. Rebecca Richards, an Oxford University AI ethics expert, stated,
