Large language models (LLMs) are widely applied across diverse domains, raising concerns about their limitations and potential risks. In this study, we investigate two types of bias that LLMs may display: stereotype bias and deviation bias. Stereotype bias refers to when LLMs consistently associate specific traits with a particular demographic group. Deviation bias reflects the disparity between the demographic distributions extracted from LLM-generated content and real-world demographic distributions. By asking four advanced LLMs to generate profiles of individuals, we examine the associations between each demographic group and attributes such as political affiliation, religion, and sexual orientation. Our experimental results show that all examined LLMs exhibit both significant stereotype bias and deviation bias towards multiple groups. Our findings uncover the biases that occur when LLMs infer user attributes and shed light on the potential harms of LLM-generated outputs.

Artificial Intelligence or AI is the latest technological trend that will make life easier. The main goal of AI is not to steal people's jobs, but to automate some of the manual tasks they have. Technology has grown tremendously in the last years and every device or product that is invented relies heavily on technology. Even though many people associate AI with robots, it is useful not only for them. Cars use AI, smartphones use AI, and even marketing specialists.

Over time, the technological pipeline has made some content marketers remain in chaos. With AI as the fast-evolving approach, the SEO pillars are however expected to become vital for future trades. The developing systems are expected to make work easier and reliable. So far, SEO has been taking considerable attention by marketers as it has become one of the primary tools for boosting sales. However, considerable attention should be given also to the integration of AI into SEO and how will it impact its functionality.

"AI will be as central to the white-collar office environment as robotics has been to the production economy," said Mark Muro, senior fellow and policy director of the Metropolitan Policy Program at the Brookings Institution. "They'll fundamentally change what work is and what humans do. And no one gets a free pass." What's happening: A new analysis released Wednesday by Brookings overlaid the keywords in AI-related patents with job descriptions to get a more detailed understanding of which jobs are most likely to be affected by AI -- and where they are. The big picture: Much of the research assessing the workforce impact of these new technologies -- robotics, AI, and machine learning -- lumps them all together under the bucket of automation.

In today's day and age, everything is going digital. Nearly everything is becoming automated or streamlined, and businesses are increasingly looking for new ways to implement cutting-edge and innovative technology like artificial intelligence, virtual reality, and augmented reality. For instance, in recent years, AI-equipped chatbots have become the talk of the town when it comes to modern business. Not only do these bots allow businesses to connect with their customers in new exciting, engaging, and interactive ways, it also helps them streamline some of their customer service processes. Furthermore, chatbots have become so popular among businesses, that they have even made their way into the marketer's arsenal of marketing strategies.