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.

Teenagers' language might make online bullying hard to detect Generation Alpha's internet lingo is mutating faster than teachers, parents and AI models can keep up – potentially exposing youngsters to bullying and grooming that trusted adults and AI-based safety systems simply can't see. Manisha Mehta, a 14-year-old student at Warren E Hyde Middle School in Cupertino, California, and Fausto Giunchiglia at the University of Trento, Italy, collated 100 expressions and phrases popular with Generation Alpha – those born between 2010 and 2025 – from popular gaming, social media and video platforms. The pair then asked 24 volunteers aged between 11 and 14, who were Mehta's classmates, to analyse the phrases alongside context-specific screenshots. The volunteers explained whether they understood the phrases, in what context they were being used and if that use carried any potential safety concerns or harmful interpretations. They also asked parents, professional moderators and four AI models – GPT-4, Claude, Gemini and Llama 3 – to do the same.

The first generation to grow up entirely in the 21st century will never remember a time before smartphones or smart assistants. They will likely be the first children to ride in self-driving cars, as well as the first whose healthcare and education could be increasingly turned over to artificially intelligent machines. Futurists, demographers, and marketers have yet to agree on the specifics of what defines the next wave of humanity to follow Generation Z. That hasn't stopped some, like Australian futurist Mark McCrindle, from coining the term Generation Alpha, denoting a sort of reboot of society in a fully-realized digital age. "In the past, the individual had no power, really," McCrindle told Business Insider.

As artificial intelligence capabilities expand in the future, Millennial parents may be open to using it in their children's lives. The study, comprising a survey of 600 parents between 20 and 36 years old who have at least one child younger than eight, was designed to gauge parents' sentiment toward using AI in the lives of so-called'Generation Alpha' children. IEEE defines Generation Alpha as children born between 2010 and 2025 and expects artificial intelligence to be present in'nearly every aspect of their lives.' When it comes to teaching their children, almost three quarters (74%) of Millennial parents said they would consider using an AI tutor. Fewer than a quarter (10%) said they would not consider it at all, according to the study.